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Wang ZZ, Yuan YF, Zhang Y, Chen YG. [Applications of anterior segment optical coherence tomography in corneal refractive surgery]. Zhonghua Yan Ke Za Zhi 2023; 59:851-857. [PMID: 37805419 DOI: 10.3760/cma.j.cn112142-20221129-00608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
Anterior segment optical coherence tomography (AS-OCT) has the characteristics of non-contact, noninvasive, high sensitivity, and repeatability, and offers high-resolution in vivo imaging of the structures of the anterior eye segment. It can be used in the diagnosis and assistance of conditions related to the anterior eye segment. This review provides an update on the research and clinical applications of AS-OCT in corneal refractive surgery, including preoperative keratoconus screening, intraoperative real-time visualization of corneal structures, postoperative corneal evaluation, and management of postoperative complications. We also explore the potential application of AS-OCT in combination with corneal biomechanical detection for corneal refractive surgery.
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Affiliation(s)
- Z Z Wang
- Department of Ophthalmology, Peking University Third Hospital, Beijing Key Laboratory of Restoration of Damaged Ocular Nerve, Beijing 100191, China
| | - Y F Yuan
- Department of Ophthalmology, Peking University Third Hospital, Beijing Key Laboratory of Restoration of Damaged Ocular Nerve, Beijing 100191, China
| | - Y Zhang
- Department of Ophthalmology, Peking University Third Hospital, Beijing Key Laboratory of Restoration of Damaged Ocular Nerve, Beijing 100191, China
| | - Y G Chen
- Department of Ophthalmology, Peking University Third Hospital, Beijing Key Laboratory of Restoration of Damaged Ocular Nerve, Beijing 100191, China
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202
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Jiang JN, Zhang Y, Chen L, Liu JY, Cai S, Chen ZY, Wang RL, Zhang YH, Song Y, Ma J, Dong YH. [Research on the association between unhealthy lifestyle and psychological distress among Chinese children and adolescents aged 9-18 years]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1567-1574. [PMID: 37875443 DOI: 10.3760/cma.j.cn112338-20230508-00286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To evaluate the level of psychological distress among Chinese children and adolescents and analyze its lifestyle influencing factors. Methods: Data were obtained from the 2019 Chinese National Survey on Students' Constitution and Health. A lotal of 120 285 Han Chinese children and adolescents aged 9-18 years with complete information on the psychological distress scale and lifestyle factors were selected, including 58 432 boys and 61 853 girls. The Kessler Psychological Distress Scale (K10) measured psychological distress, and lifestyles such as physical activity, sedentary behavior, diet, and sleep were also investigated. K10 scores of different genders were compared using the t-test, and the levels of psychological distress were compared using the χ2 test. Logistic regression was used to analyze lifestyle risk factors associated with high psychological distress, and multiple linear regression was used to find the relationship between K10 scores and lifestyle scores. Results: The average K10 score for Han Chinese children and adolescents aged 9-18 years was 21.25±7.35, with girls (21.43±7.35) scoring higher than boys (21.06±7.36), the difference was statistically significant (t=8.72, P<0.001). The rate of high psychological distress was 29.81%, with girls (31.08%) reporting higher rates than boys (28.46%), the difference was statistically significant (χ2=98.54,P<0.001). 56.10% of children and adolescents have unhealthy lifestyles, with girls (58.77%) reporting higher rates than boys (53.27%), the difference was statistically significant (χ2=368.53,P<0.001). Except for insufficient outdoor activities for girls (P=0.128), lifestyles such as insufficient physical activity, insufficient muscle-and-bone exercises, long screen time, not eating breakfast, eggs and dairy products every day, drinking sugary beverages once or more per day, and not having enough sleep are all risk factors for high psychological distress (all P<0.001). For every additional healthy lifestyle score, the K10 score decreased by 0.98 [β=-0.98 (95%CI: -1.01- -0.95)] points (P<0.001). K10 scores in each region negatively correlate with lifestyle scores (all P<0.001). Among them, the K10 score in the eastern region showed the slightest decrease as the lifestyle score increased, while the western region showed the most decrease. Conclusions: The prevalence of psychological distress and unhealthy lifestyle in Chinese children and adolescents are high and interrelated. Compared those with healthy lifestyles, children and adolescents with unhealthy lifestyles are at greater risk of high psychological distress. Therefore, promoting healthy lifestyles for children and adolescents may be one of the important ways to improve their mental health.
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Affiliation(s)
- J N Jiang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - L Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Y Liu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - S Cai
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Z Y Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - R L Wang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Song
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Dong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
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203
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Zhang YH, Cai S, Chen ZY, Zhang Y, Jiang JN, Liu YF, Dang JJ, Zhong PL, Shi D, Dong YH, Hu PJ, Zhu GR, Ma J, Song Y. [Research on the association between the occurrence of spermarche and menarche and psychological distress among Chinese children and adolescents aged 9-18 years]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1545-1551. [PMID: 37875440 DOI: 10.3760/cma.j.cn112338-20230514-00298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To analyze the association between the occurrence of spermarche and menarche and psychological distress among Chinese Han children and adolescents aged 9 to 18 years. Methods: Data were drawn from the 2019 Chinese National Survey on Students' Constitution and Health, and a total of 54 438 boys aged 11 to 18 years and 76 376 girls aged 9 to 18 years with psychological distress, spermarche/menarche records were included in the final analysis. The occurrence of spermarche/menarche was recorded by physicians, and psychological distress was classified according to the Kessler Psychological Distress Scale scores. The chi-square test was used to compare the difference between groups in the occurrence of spermarche/menarche, and the multinomial logistic regression model and stratification analysis was established to analyze the association between psychological distress and spermarche/menarche. Results: The incidence of spermarche/menarche in 2019 ranged from 6.3% to 96.5% for eight age groups of Chinese boys and 2.8% to 99.0% for ten age groups of girls. The rates of high psychological distress among boys and girls were 32.5% and 32.7%. Among boys aged 11 to 18 years, the rate of high psychological distress increased with age, with a trend test P<0.001, and the difference in the rate of high psychological distress between those who had and had not had their spermarche was not statistically significant in all age groups. Among girls aged 9 to 18 years, the rate of high psychological distress increased with age, with a trend P<0.001; the rate of high psychological distress was higher in the group with menarche at age 10 and 12 than in the group without menarche (all P<0.05). High psychological distress was positively correlated with spermarche among boys aged 13-15 years living in urban areas and hight level economic development areas (OR=1.11, 95%CI: 1.02-1.21;OR=1.18, 95%CI: 1.06-1.32). Overall, high psychological distress was positively correlated with menarche in girls aged 9-12 and 13-15 years (OR=1.33, 95%CI: 1.25-1.42; OR=1.22, 95%CI: 1.07-1.39). High psychological distress was positively correlated with menarche among girls aged 9-12 years living in different regions except for the Northeast region, in areas with different levels of economic development, and in urban and rural areas, in girls aged 13-15 years living in urban, central, and western regions, and in girls aged 16-18 years residing in the central region. Conclusions: This study found an association between the occurrence of spermarche/menarche and psychological distress among Chinese Han children and adolescents aged 9 to 18 years in 2019, which was particularly significant among girls aged 9 to 12 years and boys aged 13 to 15 years living in areas with higher levels of socioeconomic development.
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Affiliation(s)
- Y H Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - S Cai
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Z Y Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J N Jiang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y F Liu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J J Dang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - P L Zhong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - D Shi
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Dong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - P J Hu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - G R Zhu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Song
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
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204
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Zhang Y, Xu RT, Bai JA, Hu P, Li XY, Tian Y, Tang QY. [Efficacy, prognosis and influencing factors of transcatheter arterial embolization in the treatment of neuroendocrine neoplasm liver metastases]. Zhonghua Yi Xue Za Zhi 2023; 103:2952-2958. [PMID: 37752055 DOI: 10.3760/cma.j.cn112137-20230512-00776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Objective: To evaluate the efficacy of transcatheter arterial embolization (TAE) in the treatment of neuroendocrine neoplasm liver metastases (NENLM), analyze the prognosis and related factors. Methods: Clinical data of NENLM patients treated with TAE in the First Affiliated Hospital of Nanjing Medical University from January 2018 to March 2022 were retrospectively analyzed. Objective response rate (ORR), disease control rate (DCR), and adverse event rate after TAE were evaluated according to the Response Evaluation Criteria In Solid Tumors and the Common Terminology Criteria for Adverse Events. The prognosis was evaluated by median overall survival (mOS) and median progression-free survival (mPFS). The survival curve was plotted by Kaplan-Meier method. Multivariate Cox regression was used to analyze prognostic factors. Results: A total of 39 NENLM patients were included in this study, aged (53.3±10.3) (23-74) years old, including 23 males and 16 females. Among them, 9 cases had functional neuroendocrine neoplasms. There were 31 cases with primary sites locating in the digestive system, 32 cases with WHO G1 and G2 primary sites, 27 cases with abundant blood supply for liver metastases and 13 cases with liver tumor load >50%. Thirty patients received treatment of long-acting somatostatin analogue(SSA). A total of 123 TAE were performed in 39 cases, with an ORR of 38.5% (15/39) and a DCR of 76.9% (30/39). There were no serious adverse events of level 4-5 during the perioperative period. The median follow-up was 38.7 (95%CI: 31.3-46.1) months, with mOS of 37.3(95%CI: 27.0-47.5) months and mPFS of 12.6 (95%CI: 7.1-18.1) months. Multivariate Cox regression analysis found that the combination of long-term SSA treatment was an influencing factor for overall survival of patients (HR=0.207, 95%CI: 0.076-0.567, P=0.002). Conclusions: TAE can effectively reduce the load of liver metastases in patients with NENLM, and the combination of long-term SSA treatment can improve the ovreall survival of patients.
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Affiliation(s)
- Y Zhang
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
| | - R T Xu
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
| | - J A Bai
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
| | - P Hu
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
| | - X Y Li
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
| | - Y Tian
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
| | - Q Y Tang
- Department of Geriatric Gastroenterology, the First Affiliated Hospital of Naijing Medical University, Nanjing 210029, China
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205
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Cai S, Chen ZY, Zhang YH, Zhang Y, Jiang JN, Liu YF, Dang JJ, Zhong PL, Shi D, Dong YH, Hu PJ, Zhu GR, Ma J, Song Y. [Research on the association between the status of physical fitness and psychological distress among Chinese children and adolescents aged 13-18 years]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1552-1557. [PMID: 37875441 DOI: 10.3760/cma.j.cn112338-20230408-00222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To describe the status of physical fitness of children and adolescents aged 13-18 years in China in 2019 and analyze its association with psychological distress. Methods: Data were drawn from the 2019 Chinese National Survey on Students' Constitution and Health, and 90 633 Han children and adolescents aged 13-18 years were included. Physical fitness was evaluated by "National Students Constitutional Health Standards" (2014 revised edition). Psychological distress was classified according to the scores of the Kessler Psychological Distress Scale: ≤19, 20-24, 25-29, and ≥30 scores indicated no, mild, moderate, and severe psychological distress, respectively, with moderate and severe psychological distress collectively referred to as high psychological distress. The χ2 test was used to compare the distribution differences between boys and girls, the Cochran-Armitage test was used to analyze the trend, and the multinomial logistic regression in the mixed effect model was established to analyze the association between physical fitness and psychological distress. Results: In 2019, the unqualified rate of physical fitness among children and adolescents aged 13-18 years in China was 17.2%, and the prevalence of excellent and good physical fitness was 18.2%, which was lower among boys (15.9%) than girls (20.5%) with a statistically significant difference (P<0.05). The excellent and good physical fitness rate showed a significantly decreasing trend with age (trend test P<0.05). The rate of high psychological distress among children and adolescents aged 13-18 years in China in 2019 was 39.3%, with boys (37.0%) having a lower prevalence than girls (41.6%), supported by a statistically significant difference (P<0.05), and a decreasing trend with the degree of physical fitness was observed both in boys and girls (trend test P<0.05). The multinomial logistic regression model showed that the prevalence of moderate (OR=0.83, 95%CI: 0.79-0.88, P<0.001) and severe (OR=0.81, 95%CI: 0.77-0.86, P<0.001) psychological distress were both lower in children and adolescents with excellent and good physical fitness. Conclusion: The status of physical fitness and psychological distress of Chinese children and adolescents aged 13-18 in 2019 was not optimistic, with physical fitness showing a significantly negative association with psychological distress.
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Affiliation(s)
- S Cai
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Z Y Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J N Jiang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y F Liu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J J Dang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - P L Zhong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - D Shi
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Dong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - P J Hu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - G R Zhu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Song
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
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206
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Chen ZY, Cai S, Ma N, Zhang YH, Zhang Y, Jiang JN, Liu YF, Dang JJ, Zhong PL, Shi D, Dong YH, Zhu GR, Ma J, Song Y. [Prevalence of psychological distress among Chinese children and adolescents aged 9-18 years]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1537-1544. [PMID: 37875439 DOI: 10.3760/cma.j.cn112338-20230517-00304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To describe the prevalence of psychological distress and to analyze its influencing factors among Chinese children and adolescents aged 9-18 years in 2019. Methods: Data was from the 2019 Chinese National Survey on Students' Constitution and Health, and 148 892 children and adolescents were included. Psychological distress was measured using the Kessler Psychological Distress Scale (K10): scores ≤19 were defined as no psychological distress, scores between 20-24 were defined as mild psychological distress, scores between 25-29 were defined as moderate psychological distress, and scores ≥30 were defined as severe psychological distress (moderate to severe psychological distress were defined as high psychological distress). The ANOVA, t test, and χ2 test were used to compare the differences in K10 scores and high psychological distress rates among children and adolescents with different characteristics. The ANOVA and trend χ2 test were used to analyze the trends. Modified-Poisson regression models were used to determine influencing factors of high psychological distress. Results: The K10 scores for Chinese children and adolescents aged 9-18 years in 2019 was 21.5±9.2, and their rate of high psychological distress was 31.6%. The rates of high psychological distress among children and adolescents aged 9-12, 13-15, and 16-18 years were 22.3%, 35.9%, and 38.8%. K10 scores and rates of high psychological distress showed an increasing trend as age increased (trends test all P<0.001). K10 scores and rates of high psychological distress were higher among children and adolescents who were older, female, rural, in areas with medium to low GDP per capita level, and with lower parental education (all P<0.001). Multifactorial modified-Poisson regression analysis showed that children and adolescents aged 13-15 years, 16-18 years, female, rural, and in areas with low to moderate GDP per capita level were at higher risk of high psychological distress (all P<0.05), with aOR (95%CI) of 1.55 (1.52-1.58), 1.66 (1.63-1.69), 1.07 (1.05-1.09), 1.02 (1.01-1.04), 1.10 (1.07-1.12). Children and adolescents in areas with medium to high GDP per capita level, whose father had a secondary or high school degree, whose father had a college degree or above, whose mother had a secondary or high school degree, and whose mother had a college degree or above were at lower risk of high psychological distress (all P<0.05), with aOR (95%CI) of 0.96 (0.94-0.98), 0.92 (0.90-0.93), 0.84 (0.82-0.86), 0.95 (0.93-0.97), 0.86 (0.83-0.88). Conclusions: The prevalence of psychological distress was high among Chinese children and adolescents aged 9-18 years in 2019, which is a vital problem. Mental health interventions need to be implemented among children and adolescents that were older, girls, rural, live in areas with lower economic levels, and whose parents have a lower education level.
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Affiliation(s)
- Z Y Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - S Cai
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - N Ma
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Y H Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J N Jiang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y F Liu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J J Dang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - P L Zhong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - D Shi
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Dong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - G R Zhu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Song
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
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207
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Zhang Y, Chen L, Jiang JN, Ma T, Liu JY, Yuan W, Guo TJ, Chen MM, Wang RL, Dong YH, Song Y, Ma J. [Research on the association between ambient PM 2.5 and its components and psychological distress among Chinese children and adolescents aged 9-18 years]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1575-1582. [PMID: 37875444 DOI: 10.3760/cma.j.cn112338-20230504-00276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To analyze the association between exposure to ambient PM2.5 and its components [sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM), and black carbon (BC)] and psychological distress among school children and adolescents aged 9 to 18 years in China. Methods: Based on data from the 2019 Chinese National Survey on Students' Constitution and Health, 130 808 children and adolescents aged 9 to 18 years were included. Scoring and determination of higher psychological distress were based on the Kessler Psychological Distress Scale (K10), and annual average exposure data for air pollution were matched by survey location and time. We used a restricted cubic spline approach based on logistic regression to fit the associations between PM2.5, SO42-, NO3-, NH4+, organic matter, black carbon concentrations, and psychological distress. Logistic regression models were used to analyse different age, gender, BMI and physical activity subgroups to estimate the association between exposure to high levels of pollution and high levels of psychological distress in different subgroups. Results: The proportion of children and adolescents with high levels of psychological distress in China was 30.4%, with girls being higher than boys at 31.6% and 29.1%, respectively (P<0.05). A non-linear positive association existed between exposure to PM2.5, SO42-, NO3- and organic matter concentrations and higher psychological distress. As PM2.5, NO3-, NH4+, organic matter, and black carbon concentrations continued to rise, the increase in the risk of higher psychological distress slowed, while SO42- showed little change in the OR of psychological distress at lower concentrations but continued to rise at higher concentrations. PM2.5 and its components were statistically associated with psychological distress in the physically inactive group but not in the physically active group. The association between high levels of pollutants and high psychological distress was stronger among students aged 9 to 12 years compared with students aged 13 to 15 years and 16 to 18 years. Conclusions: The ambient pollutant PM2.5 and its components are associated with psychological distress in children and adolescents aged 9 to 18 years in China. High pollutant exposure is a risk factor for high psychological distress among physically inactive children and adolescents, and there are age differences in the association between PM2.5 and components and psychological distress.
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Affiliation(s)
- Y Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - L Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J N Jiang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - T Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Y Liu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - W Yuan
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - T J Guo
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - M M Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - R L Wang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Dong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Song
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
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208
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Dong YH, Jiang JN, Chen L, Liu JY, Zhang Y, Cai S, Chen ZY, Wang RL, Zhang YH, Song Y, Ma J. [Research on the association between overweight and obesity mediated by Chinese children and adolescent aged 13-18 years physical exercise and psychological distress]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1558-1566. [PMID: 37875442 DOI: 10.3760/cma.j.cn112338-20230512-00295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To analyze the association between overweight and obesity, psychological distress, and the influence of physical exercise among Chinese children and adolescents. Methods: The study used data from the 2019 Chinese National Survey on Students' Constitution and Health. A total of 95 280 Han Chinese children and adolescents aged 13 to 18 years were included in the study based on complete information on overweight and obesity, psychological distress assessment, and physical exercise variables. The Kessler Psychological Distress Scale was used to measure their psychological distress, with scores above 25 indicating high psychological distress. The BMI group of the adolescents was evaluated according to the Chinese standard "WS/T 586-2018 Screening for Overweight and Obesity in School-age Children and Adolescents", including underweight, normal weight, overweight, and obesity. The individual's BMI Z-score (BMIZ) was evaluated using the WHO standard and divided into ten groups based on the population percentile distribution. The survey collected the subjects' average daily physical exercise time and divided them into two groups: less than 1 hour and greater than or equal to 1 hour. Logistic regression analysis was used to analyze the relationship between overweight and obesity and high psychological distress among children and adolescents and the differences in association between different physical exercise groups. Results: The detection rates of overweight and obesity among Han Chinese children and adolescents aged 13 to 18 years in 2019 were 14.5%, and 7.6%, respectively. The rate of high psychological distress was 37.6%, and the rate of average daily physical exercise time exceeding 1 hour was 17.1%. Using the population with a BMIZ P10 below as a reference, the association strength between high psychological distress and the population gradually increased, with an OR (95%CI) value of 1.08 (1.02-1.14), 1.09 (1.02-1.14), 1.10 (1.03-1.16), and 1.16 (1.09-1.23) for BMIZ in the P60-, P70-, P80-, >P90 groups. Compared to normal weight, both overweight and obesity were positively associated with high psychological distress in children and adolescents, with obesity showing a more significant correlation, while underweight was negatively associated with high psychological distress. The detection rates of high psychological distress in normal weight, underweight, overweight, and obese groups were 37.6%, 37.0%, 38.2%, and 38.7%, respectively, with an OR (95%CI) value of 0.93 (0.88-0.98) for the underweight group and 1.05 (1.01-1.10) and 1.13 (1.07-1.19) for the overweight and obese groups, respectively. The positive correlation between BMIZ, overweight, and obesity with high psychological distress was significant only in adolescents who exercised less than 1 hour per day on average. Conclusions: Chinese children and adolescents face the problem of obesity and high psychological distress, with a positive correlation between these two problems. Physical activity may moderate the association between obesity and psychological distress in children and adolescents. Adequate physical exercise may offset the potential high psychological distress caused by obesity in children and adolescents. Thus, strengthening physical exercise among children and adolescents reduces the risks of both obesity and psychological health problems effectively.
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Affiliation(s)
- Y H Dong
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J N Jiang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - L Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Y Liu
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - S Cai
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Z Y Chen
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - R L Wang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y H Zhang
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - Y Song
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University/School of Public Health, Peking University, Beijing 100191, China
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209
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Zhang Y, He Y. [Management of traumatic temporomandibular joint ankylosis: a perspective]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:985-990. [PMID: 37818532 DOI: 10.3760/cma.j.cn112144-20230905-00141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/12/2023]
Abstract
Traumatic injury to the temporomandibular joint (TMJ) was the most common cause of TMJ ankylosis (85%), while sagittal fracture of the mandibular condyle was identified as the high risk fracture pattern. TMJ disc displacement is one of the prerequisite factors of TMJ ankylosis. The severe damage and close contacts of both the articular surface of glenoid fossa and condyle were also crucial pathogenic factors in the development of TMJ ankylosis. The mechanism and development of TMJ ankylosis may be similar to hypertrophic non-union, and the persistence of radiolucent zone within the ankylotic callus governs the clinical and pathological process of TMJ ankylosis. In type Ⅰ traumatic TMJ ankylosis, repositioning of the displaced disk is required, while the preservation of pseudo-joint is essential in the management of the type Ⅱ traumatic TMJ ankylosis. Nevertheless, the rate of TMJ reankylosis still remains high. Higher rate of TMJ reankylosis was observed in paediatric population, bilateral involvement of TMJ ankylosis, and in cases with reconstruction of mandibular condyle with coronoid process.
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Affiliation(s)
- Y Zhang
- Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - Y He
- Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
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210
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Wang LY, Liu ZY, Yin JJ, Yan LW, Wang PP, Shi YS, Zhang Y, Zhao HM. [Analysis of the common respiratory viruses in children with acute respiratory infection in a hospital in Lanzhou City from 2021 to 2022]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1635-1639. [PMID: 37859383 DOI: 10.3760/cma.j.cn112150-20230518-00391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
To explore the situation of 8 common respiratory pathogens in children with acute respiratory infection (ARI) from 2021 to 2022.The retrospective study selected 8 710 ARI patients from September 2021 to August 2022 in the Maternal and Child Health Hospital of Gansu Province as the study object, patients aged 0 to 17 years old, including 5 048 male children and 3 662 female children. Indirect immunofluorescence was used to detect 8 common respiratory pathogens, including influenza virus A (FluA), influenza virus B (FluB), parainfluenza virus (PIV), respiratory syncytial virus (RSV), adenovirus (ADV), Mycoplasma pneumoniae (MP), Chlamydia pneumoniae (CP), and Coxsackie virus group B (CoxB) IgM antibodies. χ2 test was used to analyze the results. The results showed that 1 497 of 8 710 children with ARI were positive, with a positive rate of 17.19%. The detection rate of MP among 8 common respiratory pathogens was 11.34%, accounting for 66.0%, followed by FluB, CoxB, PIV, RSV, ADV, FluA and CP, accounting for 13.83%, 9.55%, 6.01%, 2.61%, 1.47%, 0.40% and 0.13%, respectively. Respiratory tract viruses (FluA, FluB, RSV, ADV, PIV, CoxB) accounted for 33.86%.There were significant differences in the detection rates of PIV, ADV and MP among children of different genders (χ2=6.814, 5.154 and 17.784, P<0.05). The detection rate of school-age children (6-17 years old) was the highest, accounting for 33.27% (184/553). The detection rates of 8 common respiratory pathogens in patients with ARI were higher in spring and winter and lower in summer and autumn. To sum up, from 2021 to 2022, MP and FluB infection were dominant in ARI patients in our hospital. The peak period of 8 common respiratory pathogens was in spring and winter. The physical examination rate of 8 common respiratory pathogens in ARI patients aged 6-17 years old was the highest.
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Affiliation(s)
- L Y Wang
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - Z Y Liu
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - J J Yin
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - L W Yan
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - P P Wang
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - Y S Shi
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - Y Zhang
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
| | - H M Zhao
- Department of Clinical Laboratory, Gansu Provincial Maternal and Child Health Care Hospital, Lanzhou 730050, China
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211
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Hou XT, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. First Experimental Study of the Purely Leptonic Decay D_{s}^{*+}→e^{+}ν_{e}. Phys Rev Lett 2023; 131:141802. [PMID: 37862669 DOI: 10.1103/physrevlett.131.141802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/25/2023] [Accepted: 09/05/2023] [Indexed: 10/22/2023]
Abstract
Using 7.33 fb^{-1} of e^{+}e^{-} collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay D_{s}^{*+}→e^{+}ν_{e}. Our data contain a signal of this decay with a statistical significance of 2.9σ. The branching fraction of D_{s}^{*+}→e^{+}ν_{e} is measured to be (2.1_{-0.9_{stat}}^{+1.2}±0.2_{syst})×10^{-5}, corresponding to an upper limit of 4.0×10^{-5} at the 90% confidence level. Taking the total width of the D_{s}^{*+} [(0.070±0.028) keV] predicted with the radiative D_{s}^{*+} decay from the lattice QCD calculation as input, the decay constant of the D_{s}^{*+} is determined to be f_{D_{s}^{*+}}=(214_{-46_{stat}}^{+61}±44_{syst}) MeV, corresponding to an upper limit of 354 MeV at the 90% confidence level.
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Affiliation(s)
- M Ablikim
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - M N Achasov
- G.I. Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
| | - P Adlarson
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - R Aliberti
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - A Amoroso
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - M R An
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Q An
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y Bai
- Southeast University, Nanjing 211100, People's Republic of China
| | - O Bakina
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - I Balossino
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
| | - Y Ban
- Peking University, Beijing 100871, People's Republic of China
| | - V Batozskaya
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- National Centre for Nuclear Research, Warsaw 02-093, Poland
| | - K Begzsuren
- Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
| | - N Berger
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - M Berlowski
- National Centre for Nuclear Research, Warsaw 02-093, Poland
| | - M Bertani
- INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
| | - D Bettoni
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
| | - F Bianchi
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - E Bianco
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - J Bloms
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - A Bortone
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - I Boyko
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - R A Briere
- Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - A Brueggemann
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - H Cai
- Wuhan University, Wuhan 430072, People's Republic of China
| | - X Cai
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - A Calcaterra
- INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
| | - G F Cao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - N Cao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S A Cetin
- Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
| | - J F Chang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - T T Chang
- Xinyang Normal University, Xinyang 464000, People's Republic of China
| | - W L Chang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - G R Che
- Nankai University, Tianjin 300071, People's Republic of China
| | - G Chelkov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - C Chen
- Nankai University, Tianjin 300071, People's Republic of China
| | - Chao Chen
- Soochow University, Suzhou 215006, People's Republic of China
| | - G Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H S Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - M L Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S J Chen
- Nanjing University, Nanjing 210093, People's Republic of China
| | - S M Chen
- Tsinghua University, Beijing 100084, People's Republic of China
| | - T Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X R Chen
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X T Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y B Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y Q Chen
- Jilin University, Changchun 130012, People's Republic of China
| | - Z J Chen
- Hunan University, Changsha 410082, People's Republic of China
| | | | - S K Choi
- Chung-Ang University, Seoul 06974, Republic of Korea
| | - X Chu
- Nankai University, Tianjin 300071, People's Republic of China
| | - G Cibinetto
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
| | - S C Coen
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | | | - J J Cui
- Shandong University, Jinan 250100, People's Republic of China
| | - H L Dai
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J P Dai
- Yunnan University, Kunming 650500, People's Republic of China
| | - A Dbeyssi
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - R E de Boer
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - D Dedovich
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - Z Y Deng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - A Denig
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - I Denysenko
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - M Destefanis
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - F De Mori
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - B Ding
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Jinan, Jinan 250022, People's Republic of China
| | - X X Ding
- Peking University, Beijing 100871, People's Republic of China
| | - Y Ding
- Liaoning University, Shenyang 110036, People's Republic of China
| | - Y Ding
- Jilin University, Changchun 130012, People's Republic of China
| | - J Dong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - L Y Dong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - M Y Dong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Dong
- Wuhan University, Wuhan 430072, People's Republic of China
| | - S X Du
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Z H Duan
- Nanjing University, Nanjing 210093, People's Republic of China
| | - P Egorov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - Y L Fan
- Wuhan University, Wuhan 430072, People's Republic of China
| | - J Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - S S Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W X Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - R Farinelli
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
| | - L Fava
- University of Eastern Piedmont, I-15121 Alessandria, Italy
- INFN, I-10125 Turin, Italy
| | - F Feldbauer
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - G Felici
- INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
| | - C Q Feng
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - J H Feng
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - K Fischer
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - M Fritsch
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - C Fritzsch
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - C D Fu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J L Fu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y W Fu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H Gao
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y N Gao
- Peking University, Beijing 100871, People's Republic of China
| | - Yang Gao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | | | - I Garzia
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
- University of Ferrara, I-44122 Ferrara, Italy
| | - P T Ge
- Wuhan University, Wuhan 430072, People's Republic of China
| | - Z W Ge
- Nanjing University, Nanjing 210093, People's Republic of China
| | - C Geng
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - E M Gersabeck
- University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - A Gilman
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - K Goetzen
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - L Gong
- Liaoning University, Shenyang 110036, People's Republic of China
| | - W X Gong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - W Gradl
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - S Gramigna
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
- University of Ferrara, I-44122 Ferrara, Italy
| | - M Greco
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - M H Gu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y T Gu
- Guangxi University, Nanning 530004, People's Republic of China
| | - C Y Guan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z L Guan
- Henan University of Technology, Zhengzhou 450001, People's Republic of China
| | - A Q Guo
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L B Guo
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - R P Guo
- Shandong Normal University, Jinan 250014, People's Republic of China
| | - Y P Guo
- Fudan University, Shanghai 200433, People's Republic of China
| | - A Guskov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - X T Hou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T T Han
- Shandong University, Jinan 250100, People's Republic of China
| | - W Y Han
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - X Q Hao
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - F A Harris
- University of Hawaii, Honolulu, Hawaii 96822, USA
| | - K K He
- Soochow University, Suzhou 215006, People's Republic of China
| | - K L He
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | | | - C H Heinz
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - Y K Heng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C Herold
- Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
| | - T Holtmann
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - P C Hong
- Fudan University, Shanghai 200433, People's Republic of China
| | - G Y Hou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y R Hou
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z L Hou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H M Hu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J F Hu
- South China Normal University, Guangzhou 510006, People's Republic of China
| | - T Hu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y Hu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - G S Huang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - K X Huang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - L Q Huang
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X T Huang
- Shandong University, Jinan 250100, People's Republic of China
| | - Y P Huang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - T Hussain
- University of the Punjab, Lahore-54590, Pakistan
| | - N Hüsken
- Indiana University, Bloomington, Indiana 47405, USA
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - W Imoehl
- Indiana University, Bloomington, Indiana 47405, USA
| | - M Irshad
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - J Jackson
- Indiana University, Bloomington, Indiana 47405, USA
| | - S Jaeger
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - S Janchiv
- Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
| | - J H Jeong
- Chung-Ang University, Seoul 06974, Republic of Korea
| | - Q Ji
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Q P Ji
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - X B Ji
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X L Ji
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y Y Ji
- Shandong University, Jinan 250100, People's Republic of China
| | - Z K Jia
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - P C Jiang
- Peking University, Beijing 100871, People's Republic of China
| | - S S Jiang
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - T J Jiang
- Hangzhou Normal University, Hangzhou 310036, People's Republic of China
| | - X S Jiang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y Jiang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J B Jiao
- Shandong University, Jinan 250100, People's Republic of China
| | - Z Jiao
- Huangshan College, Huangshan 245000, People's Republic of China
| | - S Jin
- Nanjing University, Nanjing 210093, People's Republic of China
| | - Y Jin
- University of Jinan, Jinan 250022, People's Republic of China
| | - M Q Jing
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T Johansson
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - X Kui
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - S Kabana
- Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica, Chile
| | | | - X L Kang
- China University of Geosciences, Wuhan 430074, People's Republic of China
| | - X S Kang
- Liaoning University, Shenyang 110036, People's Republic of China
| | - R Kappert
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - M Kavatsyuk
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - B C Ke
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - A Khoukaz
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - R Kiuchi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - R Kliemt
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - L Koch
- Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
| | - O B Kolcu
- Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
| | - B Kopf
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | | | - A Kupsc
- National Centre for Nuclear Research, Warsaw 02-093, Poland
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - W Kühn
- Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
| | - J J Lane
- University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - J S Lange
- Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
| | - P Larin
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - A Lavania
- Indian Institute of Technology Madras, Chennai 600036, India
| | - L Lavezzi
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - T T Lei
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Z H Lei
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H Leithoff
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - M Lellmann
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - T Lenz
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - C Li
- Qufu Normal University, Qufu 273165, People's Republic of China
| | - C Li
- Nankai University, Tianjin 300071, People's Republic of China
| | - C H Li
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Cheng Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - D M Li
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - F Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - G Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H B Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H J Li
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - H N Li
- South China Normal University, Guangzhou 510006, People's Republic of China
| | - Hui Li
- Nankai University, Tianjin 300071, People's Republic of China
| | - J R Li
- Tsinghua University, Beijing 100084, People's Republic of China
| | - J S Li
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - J W Li
- Shandong University, Jinan 250100, People's Republic of China
| | - Ke Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - L J Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L K Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Lei Li
- Beijing Institute of Petrochemical Technology, Beijing 102617, People's Republic of China
| | - M H Li
- Nankai University, Tianjin 300071, People's Republic of China
| | - P R Li
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - S X Li
- Fudan University, Shanghai 200433, People's Republic of China
| | - T Li
- Shandong University, Jinan 250100, People's Republic of China
| | - W D Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W G Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - X H Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X L Li
- Shandong University, Jinan 250100, People's Republic of China
| | - Xiaoyu Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y G Li
- Peking University, Beijing 100871, People's Republic of China
| | - Z J Li
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - Z X Li
- Guangxi University, Nanning 530004, People's Republic of China
| | - Z Y Li
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - C Liang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - H Liang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H Liang
- Jilin University, Changchun 130012, People's Republic of China
| | - H Liang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y F Liang
- Sichuan University, Chengdu 610064, People's Republic of China
| | - Y T Liang
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - G R Liao
- Guangxi Normal University, Guilin 541004, People's Republic of China
| | - L Z Liao
- Shandong University, Jinan 250100, People's Republic of China
| | - J Libby
- Indian Institute of Technology Madras, Chennai 600036, India
| | - A Limphirat
- Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
| | - D X Lin
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T Lin
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - B J Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - B X Liu
- Wuhan University, Wuhan 430072, People's Republic of China
| | - C Liu
- Jilin University, Changchun 130012, People's Republic of China
| | - C X Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - D Liu
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - F H Liu
- Shanxi University, Taiyuan 030006, People's Republic of China
| | - Fang Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Feng Liu
- Central China Normal University, Wuhan 430079, People's Republic of China
| | - G M Liu
- South China Normal University, Guangzhou 510006, People's Republic of China
| | - H Liu
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - H B Liu
- Guangxi University, Nanning 530004, People's Republic of China
| | - H M Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Huanhuan Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Huihui Liu
- Henan University of Science and Technology, Luoyang 471003, People's Republic of China
| | - J B Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - J L Liu
- University of South China, Hengyang 421001, People's Republic of China
| | - J Y Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - K Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - K Y Liu
- Liaoning University, Shenyang 110036, People's Republic of China
| | - Ke Liu
- Henan University of Technology, Zhengzhou 450001, People's Republic of China
| | - L Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - L C Liu
- Nankai University, Tianjin 300071, People's Republic of China
| | - Lu Liu
- Nankai University, Tianjin 300071, People's Republic of China
| | - M H Liu
- Fudan University, Shanghai 200433, People's Republic of China
| | - P L Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Q Liu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S B Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - T Liu
- Fudan University, Shanghai 200433, People's Republic of China
| | - W K Liu
- Nankai University, Tianjin 300071, People's Republic of China
| | - W M Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X Liu
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Y Liu
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Y B Liu
- Nankai University, Tianjin 300071, People's Republic of China
| | - Z A Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z Q Liu
- Shandong University, Jinan 250100, People's Republic of China
| | - X C Lou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - F X Lu
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - H J Lu
- Huangshan College, Huangshan 245000, People's Republic of China
| | - J G Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - X L Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y Lu
- Central South University, Changsha 410083, People's Republic of China
| | - Y P Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Z H Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C L Luo
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - M X Luo
- Zhejiang University, Hangzhou 310027, People's Republic of China
| | - T Luo
- Fudan University, Shanghai 200433, People's Republic of China
| | - X L Luo
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - X R Lyu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y F Lyu
- Nankai University, Tianjin 300071, People's Republic of China
| | - F C Ma
- Liaoning University, Shenyang 110036, People's Republic of China
| | - H L Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J L Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L L Ma
- Shandong University, Jinan 250100, People's Republic of China
| | - M M Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Q M Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - R Q Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - R T Ma
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Y Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y Ma
- Peking University, Beijing 100871, People's Republic of China
| | - F E Maas
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - M Maggiora
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - S Maldaner
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - S Malde
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - A Mangoni
- INFN Sezione di Perugia, I-06100 Perugia, Italy
| | - Y J Mao
- Peking University, Beijing 100871, People's Republic of China
| | - Z P Mao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - S Marcello
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - Z X Meng
- University of Jinan, Jinan 250022, People's Republic of China
| | - J G Messchendorp
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - G Mezzadri
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
| | - H Miao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T J Min
- Nanjing University, Nanjing 210093, People's Republic of China
| | - R E Mitchell
- Indiana University, Bloomington, Indiana 47405, USA
| | - X H Mo
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - N Yu Muchnoi
- G.I. Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
| | - Y Nefedov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - F Nerling
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - I B Nikolaev
- G.I. Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
| | - Z Ning
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - S Nisar
- COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
| | - Y Niu
- Shandong University, Jinan 250100, People's Republic of China
| | - S L Olsen
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Q Ouyang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S Pacetti
- INFN Sezione di Perugia, I-06100 Perugia, Italy
- University of Perugia, I-06100 Perugia, Italy
| | - X Pan
- Soochow University, Suzhou 215006, People's Republic of China
| | - Y Pan
- Southeast University, Nanjing 211100, People's Republic of China
| | - A Pathak
- Jilin University, Changchun 130012, People's Republic of China
| | - P Patteri
- INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
| | - Y P Pei
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - M Pelizaeus
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - H P Peng
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - K Peters
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - J L Ping
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - R G Ping
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S Plura
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - S Pogodin
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - V Prasad
- Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica, Chile
| | - F Z Qi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H Qi
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H R Qi
- Tsinghua University, Beijing 100084, People's Republic of China
| | - M Qi
- Nanjing University, Nanjing 210093, People's Republic of China
| | - T Y Qi
- Fudan University, Shanghai 200433, People's Republic of China
| | - S Qian
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - W B Qian
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C F Qiao
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J J Qin
- University of South China, Hengyang 421001, People's Republic of China
| | - L Q Qin
- Guangxi Normal University, Guilin 541004, People's Republic of China
| | - X P Qin
- Fudan University, Shanghai 200433, People's Republic of China
| | - X S Qin
- Shandong University, Jinan 250100, People's Republic of China
| | - Z H Qin
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J F Qiu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - S Q Qu
- Tsinghua University, Beijing 100084, People's Republic of China
| | - C F Redmer
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - K J Ren
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | | | - V Rodin
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - M Rolo
- INFN, I-10125 Turin, Italy
| | - G Rong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Ch Rosner
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - S N Ruan
- Nankai University, Tianjin 300071, People's Republic of China
| | - N Salone
- National Centre for Nuclear Research, Warsaw 02-093, Poland
| | - A Sarantsev
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - Y Schelhaas
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - K Schoenning
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - M Scodeggio
- INFN Sezione di Ferrara, I-44122 Ferrara, Italy
- University of Ferrara, I-44122 Ferrara, Italy
| | - K Y Shan
- Fudan University, Shanghai 200433, People's Republic of China
| | - W Shan
- Hunan Normal University, Changsha 410081, People's Republic of China
| | - X Y Shan
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - J F Shangguan
- Soochow University, Suzhou 215006, People's Republic of China
| | - L G Shao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - M Shao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - C P Shen
- Fudan University, Shanghai 200433, People's Republic of China
| | - H F Shen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W H Shen
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Y Shen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - B A Shi
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H C Shi
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - J L Shi
- Fudan University, Shanghai 200433, People's Republic of China
| | - J Y Shi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Q Q Shi
- Soochow University, Suzhou 215006, People's Republic of China
| | - R S Shi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Shi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J J Song
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - T Z Song
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - W M Song
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- Jilin University, Changchun 130012, People's Republic of China
| | - Y J Song
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y X Song
- Peking University, Beijing 100871, People's Republic of China
| | - S Sosio
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - S Spataro
- University of Turin and INFN, University of Turin, I-10125 Turin, Italy
- INFN, I-10125 Turin, Italy
| | - F Stieler
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - Y J Su
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - G B Sun
- Wuhan University, Wuhan 430072, People's Republic of China
| | - G X Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H Sun
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H K Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J F Sun
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - K Sun
- Tsinghua University, Beijing 100084, People's Republic of China
| | - L Sun
- Wuhan University, Wuhan 430072, People's Republic of China
| | - S S Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W Y Sun
- Jilin University, Changchun 130012, People's Republic of China
| | - Y Sun
- China University of Geosciences, Wuhan 430074, People's Republic of China
| | - Y J Sun
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y Z Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z T Sun
- Shandong University, Jinan 250100, People's Republic of China
| | - Y X Tan
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - C J Tang
- Sichuan University, Chengdu 610064, People's Republic of China
| | - G Y Tang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Tang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - Y A Tang
- Wuhan University, Wuhan 430072, People's Republic of China
| | - L Y Tao
- University of South China, Hengyang 421001, People's Republic of China
| | - Q T Tao
- Hunan University, Changsha 410082, People's Republic of China
| | - M Tat
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - J X Teng
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - V Thoren
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - W H Tian
- Shanxi Normal University, Linfen 041004, People's Republic of China
| | - W H Tian
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - Z F Tian
- Wuhan University, Wuhan 430072, People's Republic of China
| | - I Uman
- Turkish Accelerator Center Particle Factory Group, Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
| | - B Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - B L Wang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Bo Wang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - C W Wang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - D Y Wang
- Peking University, Beijing 100871, People's Republic of China
| | - F Wang
- University of South China, Hengyang 421001, People's Republic of China
| | - H J Wang
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - H P Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - K Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - L L Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - M Wang
- Shandong University, Jinan 250100, People's Republic of China
| | - Meng Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S Wang
- Fudan University, Shanghai 200433, People's Republic of China
| | - S Wang
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - T Wang
- Fudan University, Shanghai 200433, People's Republic of China
| | - T J Wang
- Nankai University, Tianjin 300071, People's Republic of China
| | - W Wang
- University of South China, Hengyang 421001, People's Republic of China
| | - W Wang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - W H Wang
- Wuhan University, Wuhan 430072, People's Republic of China
| | - W P Wang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X Wang
- Peking University, Beijing 100871, People's Republic of China
| | - X F Wang
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - X J Wang
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - X L Wang
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y Wang
- Tsinghua University, Beijing 100084, People's Republic of China
| | - Y D Wang
- North China Electric Power University, Beijing 102206, People's Republic of China
| | - Y F Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y H Wang
- Qufu Normal University, Qufu 273165, People's Republic of China
| | - Y N Wang
- North China Electric Power University, Beijing 102206, People's Republic of China
| | - Y Q Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Yaqian Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- Hebei University, Baoding 071002, People's Republic of China
| | - Yi Wang
- Tsinghua University, Beijing 100084, People's Republic of China
| | - Z Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Z L Wang
- University of South China, Hengyang 421001, People's Republic of China
| | - Z Y Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Ziyi Wang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - D Wei
- University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
| | - D H Wei
- Guangxi Normal University, Guilin 541004, People's Republic of China
| | - F Weidner
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - S P Wen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - C W Wenzel
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - U W Wiedner
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - G Wilkinson
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - M Wolke
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | | | - C Wu
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - J F Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L H Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - L J Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Wu
- Fudan University, Shanghai 200433, People's Republic of China
| | - X H Wu
- Jilin University, Changchun 130012, People's Republic of China
| | - Y Wu
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y J Wu
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
| | - Z Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - L Xia
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X M Xian
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - T Xiang
- Peking University, Beijing 100871, People's Republic of China
| | - D Xiao
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - G Y Xiao
- Nanjing University, Nanjing 210093, People's Republic of China
| | - H Xiao
- Fudan University, Shanghai 200433, People's Republic of China
| | - S Y Xiao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y L Xiao
- Fudan University, Shanghai 200433, People's Republic of China
| | - Z J Xiao
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - C Xie
- Nanjing University, Nanjing 210093, People's Republic of China
| | - X H Xie
- Peking University, Beijing 100871, People's Republic of China
| | - Y Xie
- Shandong University, Jinan 250100, People's Republic of China
| | - Y G Xie
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y H Xie
- Central China Normal University, Wuhan 430079, People's Republic of China
| | - Z P Xie
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - T Y Xing
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C F Xu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C J Xu
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - G F Xu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H Y Xu
- University of Jinan, Jinan 250022, People's Republic of China
| | - Q J Xu
- Hangzhou Normal University, Hangzhou 310036, People's Republic of China
| | - Q N Xu
- Inner Mongolia University, Hohhot 010021, People's Republic of China
| | - W Xu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W L Xu
- University of Jinan, Jinan 250022, People's Republic of China
| | - X P Xu
- Soochow University, Suzhou 215006, People's Republic of China
| | - Y C Xu
- Yantai University, Yantai 264005, People's Republic of China
| | - Z P Xu
- Nanjing University, Nanjing 210093, People's Republic of China
| | - Z S Xu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - F Yan
- Fudan University, Shanghai 200433, People's Republic of China
| | - L Yan
- Fudan University, Shanghai 200433, People's Republic of China
| | - W B Yan
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - W C Yan
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - X Q Yan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H J Yang
- Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
| | - H L Yang
- Jilin University, Changchun 130012, People's Republic of China
| | - H X Yang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Tao Yang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y Yang
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y F Yang
- Nankai University, Tianjin 300071, People's Republic of China
| | - Y X Yang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Yifan Yang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z W Yang
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - M Ye
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - M H Ye
- China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
| | - J H Yin
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z Y You
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - B X Yu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C X Yu
- Nankai University, Tianjin 300071, People's Republic of China
| | - G Yu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T Yu
- University of South China, Hengyang 421001, People's Republic of China
| | - X D Yu
- Peking University, Beijing 100871, People's Republic of China
| | - C Z Yuan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L Yuan
- Beihang University, Beijing 100191, People's Republic of China
| | - S C Yuan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - X Q Yuan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y Yuan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z Y Yuan
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - C X Yue
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - A A Zafar
- University of the Punjab, Lahore-54590, Pakistan
| | - F R Zeng
- Shandong University, Jinan 250100, People's Republic of China
| | - X Zeng
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y Zeng
- Hunan University, Changsha 410082, People's Republic of China
| | - Y J Zeng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Y Zhai
- Jilin University, Changchun 130012, People's Republic of China
| | - Y H Zhan
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - A Q Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - B L Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - B X Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - D H Zhang
- Nankai University, Tianjin 300071, People's Republic of China
| | - G Y Zhang
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - H Zhang
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H H Zhang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - H H Zhang
- Jilin University, Changchun 130012, People's Republic of China
| | - H Q Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H Y Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J J Zhang
- Shanxi Normal University, Linfen 041004, People's Republic of China
| | - J L Zhang
- Henan University, Kaifeng 475004, People's Republic of China
| | - J Q Zhang
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - J W Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J X Zhang
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - J Y Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Z Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Jianyu Zhang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Jiawei Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L M Zhang
- Tsinghua University, Beijing 100084, People's Republic of China
| | - L Q Zhang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - Lei Zhang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - P Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Q Y Zhang
- Liaoning Normal University, Dalian 116029, People's Republic of China
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Shuihan Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Shulei Zhang
- Hunan University, Changsha 410082, People's Republic of China
| | - X D Zhang
- North China Electric Power University, Beijing 102206, People's Republic of China
| | - X M Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - X Y Zhang
- Soochow University, Suzhou 215006, People's Republic of China
| | - X Y Zhang
- Shandong University, Jinan 250100, People's Republic of China
| | - Y Zhang
- University of South China, Hengyang 421001, People's Republic of China
| | - Y Zhang
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - Y T Zhang
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Y H Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Yan Zhang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Yao Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z H Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z L Zhang
- Jilin University, Changchun 130012, People's Republic of China
| | - Z Y Zhang
- Nankai University, Tianjin 300071, People's Republic of China
| | - Z Y Zhang
- Wuhan University, Wuhan 430072, People's Republic of China
| | - G Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Zhao
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - J Y Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J Z Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Lei Zhao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Ling Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - M G Zhao
- Nankai University, Tianjin 300071, People's Republic of China
| | - S J Zhao
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Y B Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y X Zhao
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z G Zhao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - A Zhemchugov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - B Zheng
- University of South China, Hengyang 421001, People's Republic of China
| | - J P Zheng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - W J Zheng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y H Zheng
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - B Zhong
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - X Zhong
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - H Zhou
- Shandong University, Jinan 250100, People's Republic of China
| | - L P Zhou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Zhou
- Wuhan University, Wuhan 430072, People's Republic of China
| | - X K Zhou
- Central China Normal University, Wuhan 430079, People's Republic of China
| | - X R Zhou
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X Y Zhou
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Y Z Zhou
- Fudan University, Shanghai 200433, People's Republic of China
| | - J Zhu
- Nankai University, Tianjin 300071, People's Republic of China
| | - K Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - K J Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L Zhu
- Jilin University, Changchun 130012, People's Republic of China
| | - L X Zhu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S H Zhu
- University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
| | - S Q Zhu
- Nanjing University, Nanjing 210093, People's Republic of China
| | - T J Zhu
- Fudan University, Shanghai 200433, People's Republic of China
| | - W J Zhu
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y C Zhu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Z A Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J H Zou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Zu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
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212
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Li BH, Zhang Y, Tao S, Guo YN, Liu Q, Sun QQ. [A dry-reagent assay to rapidly detect Mycobacterium tuberculosis using loop-mediated isothermal amplification]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1625-1629. [PMID: 37859381 DOI: 10.3760/cma.j.cn112150-20230623-00488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
A molecular diagnostic assay which could be stored at room temperature was developed to rapidly detect Mycobacterium tuberculosis (MTB) based on loop-mediated isothermal amplification (LAMP) technology and dry-reagent process. LAMP uses 4 or 6 primers and Bst DNA polymerase to amplify DNA at a constant temperature. The results showed that the LAMP assay could detect the amplification of IS6110 target gene within 20 min using real-time fluorescence signal detection. The sensitive of LAMP assay was similar to the PCR technology while the precision of PCR was better than LAMP (coefficient of variation, LAMP 18.9%, PCR 3.4%), meaning LAMP was more suitable for qualitative detection. The LAMP assay did not amplify DNA of other 10 types of pathogens, including Neisseria meningitidis, Haemophilus influenzae, Staphylococcus aureus, Streptococcus pneumoniae, Rubivirus, mumps virus, adenovirus (type 3), adenovirus (type 7), respiratory syncytial virus B and parainfluenza virus type 2, indicating a good specificity. Furthermore, a dry-reagent assay was developed using air-drying and freeze-drying process. The performance of dried reagents did not change after 10 days storage at 50 ℃, meaning the dried reagents could be stored at room temperature (25 ℃) for more than six months. The dry-reagent LAMP assay also successfully amplified MTB DNA from several clinical samples within 20 min. In conclusion, the developed LAMP assay together with isothermal amplifier could rapidly detection MTB.
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Affiliation(s)
- B H Li
- Clinical Laboratory, University of Chinese Academy of Sciences Shenzhen Hospital, Shenzhen 518107, China
| | - Y Zhang
- EDAN Instruments Inc., Shenzhen 518122, China
| | - S Tao
- EDAN Instruments Inc., Shenzhen 518122, China
| | - Y N Guo
- Clinical Laboratory, University of Chinese Academy of Sciences Shenzhen Hospital, Shenzhen 518107, China
| | - Q Liu
- Clinical Laboratory, University of Chinese Academy of Sciences Shenzhen Hospital, Shenzhen 518107, China
| | - Q Q Sun
- EDAN Instruments Inc., Shenzhen 518122, China
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213
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Tian Y, Shi Z, Wang C, Ke S, Qiu H, Zhao W, Chen J, Gong Y, Wu Y, Zhang W, Xia L, Zhang Y, Chen Y. A Comparison of Clinicopathologic Outcomes and Patterns of Lymphatic Spread across Neoadjuvant Chemotherapy, Neoadjuvant Chemoradiotherapy and Neoadjuvant Immunochemotherapy in Locally Advanced Esophageal Squamous Cell Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:e345. [PMID: 37785201 DOI: 10.1016/j.ijrobp.2023.06.2412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To evaluate the differences in pathologic complete response (pCR) rates, TRG score, pathologic T stage and the pattern of lymphatic spread among patients receiving neoadjuvant chemotherapy (NCT) or neoadjuvant chemoradiotherapy (NCRT) or neoadjuvant immunochemotherapy (NICT) prior to esophagectomy for locally advanced esophageal squamous cell carcinoma (ESCC). MATERIALS/METHODS A total of 702 patients with ESCC who completed transthoracic esophagectomy followed neoadjuvant therapy at three cancer centers from January 2017 to December 2022 were enrolled. Among the included patients, 382 patients were treated with NCR, 172 with NCRT, and 148 with NICT. Inverse probability of treatment weighting (IPTW) was performed to control potential confounding factors. Pathological response of primary tumor was evaluated using the Chirieac modified tumor regression grade (TRG) system. The complete regression of primary lesion and nodal metastases were considered pCR. Lymph node classification system used the 8th edition of AJCC. Specimens were assessed for pattern of lymphatic spread. RESULTS After adjusting for baseline characteristics, the R0 resection rate did not significantly differ between the patients receiving NCT or NCRT or NICT (99.48% vs.100% vs.98.65%, P = 0.273). Compared with the NCT group, the NCRT group and NICT group had an advantage in pathological response (P<0.05). The pCR rate was 7.07% in the NCT group, 30.23% in the NCRT group, and 22.30% in the NICT group. Compared to the other two groups, the TRG score (P<0.05) and pathologic T stage (P<0.05) in the NCT group were significantly higher. In the NCT group, 9.97% had ypT0 disease, compared with 35.76% in the NCRT group and 25.68% in the NICT group. And in the NCT group, 9.71% had TRG1 disease, compared with 32.76% in the NCRT group and 25% in the NICT group. Compared with NICT, NCRT can significantly reduce the rate of LNM in station 1R (0 vs 3.38%, P<0.05) and 2R (1.15% vs 6.76%, P<0.05). Subgroup analysis according to the tumor location distribution showed that in upper thoracic cases, there was no statistical difference in LNM rates among stations no matter whether patients received NCT or NCRT or NICT. NICT group had higher LNM rates in station 2R (9.1%) in middle thoracic cases (P<0.05) and in station 18 (7.5%) (P<0.05) in lower thoracic cases, compared with the NCRT group and NCT group. CONCLUSION NCRT or NICT followed by surgery may result in a promising pCR rate and show a better performance in therapeutic response of primary lesion. No matter whether patients received NCT or NCRT or NICT, multiple level and skip node metastases are common, and adequate lymphadenectomy should be achieved to ensure the complete removal of metastatic lymph nodes.
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Affiliation(s)
- Y Tian
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Z Shi
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - C Wang
- Department of Thoracic Oncology, Anyang Tumor Hospital, The Affiliated Anyang Tumor Hospital of Henan University of Science and Technology, Henan Medical key Laboratory of Precise Prevention and Treatment of Esophageal Cancer, Anyang, China
| | - S Ke
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - H Qiu
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - W Zhao
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - J Chen
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Y Gong
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Y Wu
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - W Zhang
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - L Xia
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Y Zhang
- Department of Thoracic Oncology, Anyang Tumor Hospital, The Affiliated Anyang Tumor Hospital of Henan University of Science and Technology, Henan Medical key Laboratory of Precise Prevention and Treatment of Esophageal Cancer, Anyang, China
| | - Y Chen
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
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214
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Montalvo SK, Arbab M, Gonzalez Y, Lin MH, Parsons DDM, Zhuang T, Cai B, Pompos A, Hannan R, Westover KD, Zhang Y, Timmerman RD, Iyengar P. Predictive Factors for Response to Adaptive Therapy in Thoracic Stereotactic Ablative Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e43. [PMID: 37785405 DOI: 10.1016/j.ijrobp.2023.06.742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Online adaptive radiotherapy (ART) has been increasingly adopted for clinical use. However, ART for thoracic malignancies has lagged beyond its implementation for other primary cancers. Efforts are needed to identify optimal patients for ART by finding trends for changes in tumor position, shape, or proximity to OARs are needed. We hypothesized tumor size, histology, pre-RT SUV value, and intrathoracic location could influence how tumors change during cone beam computed tomography (CBCT)-based ART Stereotactic Ablative Radiotherapy (SAbR) for thoracic disease. MATERIALS/METHODS Data was collected from a prospective registry of patients who received CBCT-ART and SAbR for primary and secondary lung tumors. Dosimetry data was obtained from the simulation planning and the daily adaptive workflow. Central lung tumors were defined as those located within 2 cm of the bronchial tree. Plans were either delivered as per simulation or through the online adaptive workflow delivery (AD). Change in planning tumor volumes (PTV) were calculated between initial and final fractions (ΔPTV). RESULTS A total of 42 patients with a median age of 67 (range 17-90) and median 8.3 months follow up, treated between June 2021 and December 2022 were included. Most patients had NSCLC or presumed NSCLC (73.85%, 31/42), and most lesions were peripheral (61.9%, 26/42) versus central (31%, 13/42) or apical (7.1%, 3/42). Mean dose and median fractions were 52.5 Gy (SD 8.07) and 5 (range 3-5) while median initial (i) PTV was 31.75 cm3 (IQR 42.3 cm3). On average, ΔPTV decreased by 4.9% (SD 21) and volume shrunk by 5 cm3 (SD 14.5). AD improved per fraction PTV coverage and conformality while esophageal, cardiac, and spinal cord dose were significantly decreased (all p < 0.05), and most fractions were delivered with AD (73.4%, 138/188). AD was aborted most often for small iPTVs. ΔPTV grew >10% for two lesions though their iPTV were < 10 cm3. 12/42 ΔPTV were >10% smaller by the end of RT and corresponded to larger iPTVs. Age, lung primary, metastatic disease, smoking status, and tumor location were not predictive for >10% decrease in ΔPTV. Among 24 biopsy-proven NSCLC ΔPTV was >10% smaller in 6/12 patients (50%) with adenocarcinoma and only in 2/12 (16.7%) with SCC, although this was not significant on χ2 testing (p = 0.08). There were no differences in local, regional, distant failure or death comparing those with a ΔPTV of >10% vs <10% (all p > 0.1). Comparing pre-treatment PET SUV and tumor response, lower SUVs appear to be associated with more PTV shrinkage, with no significant PTV change plateauing at SUV 20. However, this analysis was limited by the number of patients with high SUV values. CONCLUSION CBCT-ART SAbR is associated with improved PTV coverage, target conformality, and reduced OAR dose. Large iPTV and adenocarcinomas were more likely to decrease >10%. High metabolic activity appeared predictive for a lack of significant ΔPTV. Further clinical and radiographic features should be explored to predict response to ART.
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Affiliation(s)
- S K Montalvo
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M Arbab
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - Y Gonzalez
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Pompos
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R Hannan
- University of Texas Southwestern Medical Center, Dallas, TX
| | - K D Westover
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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215
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Hu D, Zhang Y, Li W, Zhang W, Reddy K, Chen Y, Gao H. SEA-Net: Structure-Enhanced Attention Network for Limited-Angle CBCT Reconstruction of Clinical Projection Data. Int J Radiat Oncol Biol Phys 2023; 117:S178-S179. [PMID: 37784443 DOI: 10.1016/j.ijrobp.2023.06.2523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Limited-angle CBCT (LA-CBCT) is of great clinical interest, because the scanning time and the patient dose are proportional to the scanning range of gantry rotation angles of CBCT. However, the image reconstruction for LA-CBCT remains technically challenging, which suffers from severe wedge artifacts and image distortions. This work aims to improve LA-CBCT by developing deep learning (DL) methods for real clinical CBCT projection data, which is the first feasibility study of clinical-projection-data-based LA-CBCT, to the best of our knowledge. MATERIALS/METHODS Targeting at real clinical projection data, we have explored various DL methods such as image/data/hybrid-domain methods and finally developed a so-called Structure-Enhanced Attention Network (SEA-Net) method that has the best image quality from clinical projection data among the DL methods we have implemented. Specifically, the proposed SEA-Net employs a specialized structure enhancement sub-network to promote texture preservation. Based on the observation that the distribution of wedge artifacts in reconstruction images is non-uniform, the spatial attention module is utilized to emphasize the relevant regions while ignores the irrelevant ones, which leads to more accurate texture restoration. RESULTS SEA-Net was validated in comparison with analytic (FDK), iterative (TV), image-domain DL (DDNet and FED-INet, data-domain DL (DCAR), dual-domain DL (Sam'Net), and various unrolling DL (hdNet, CTNet, FSR-Net, CasRedSCAN) methods. Among all methods, the SEA-Net had the best image reconstruction quality as quantified by root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM), for various LA-CBCT problems of 90°-180° projection data. In addition, LA-CBCT via SEA-Net provided comparable accuracy for both patient setup (quantified by image registration accuracy from planning CT (pCT) to CBCT) and dose calculation (see the table), with full-view CBCT. CONCLUSION We explored various DL methods and developed an image-domain-based method termed SEA-Net that provided the best image quality for clinical projection data. To the best of our knowledge, this is the first feasibility study of the real clinical-projection-data-based LA-CBCT. Moreover, LA-CBCT via SEA-Net can potentially provide comparable accuracy for patient setup and dose calculation, with full-view CBCT.
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Affiliation(s)
- D Hu
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - Y Zhang
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - W Li
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - W Zhang
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - K Reddy
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - Y Chen
- School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - H Gao
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
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216
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Zarenia M, Zhang Y, Ding J, Sarosiek C, Amjad A, Dang NP, Conlin R, Li A. Auto-Correction for Inaccurate Auto-Segmentation of Abdominal MRI by Combining Deep Learning and Active Contour Method. Int J Radiat Oncol Biol Phys 2023; 117:S33. [PMID: 37784478 DOI: 10.1016/j.ijrobp.2023.06.298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Fast and accurate auto-segmentation is crucial during the magnetic resonance-guided adaptive radiation therapy (MRgART). Deep learning auto-segmentation (DLAS) approaches do not always result in clinically acceptable contours, especially for complex abdominal organs. We have previously reported that the inaccurate DLAS for bowels can be refined using deep learning (DL) and/or active contour method (ACM). This study aims to develop an automatic contour correction (ACC) tool by combining DL and ACM techniques to correct for inaccurate DLAS of pancreas and stomach on MRI. MATERIALS/METHODS The ACC technique consisted of ACM and DL based on UNet system. The ACM utilizes the probability maps generated from DLAS models to establish 2D parameter maps and to initialize contour evolution, thus not requiring initial parameter adjustments. The Organ specific DL-UNet models were trained for pancreas and stomach contours obtained from a research DLAS tool on abdominal MRIs acquired during routine MRgART from a 1.5T MR-Linac using either turbo field-echo or balanced turbo field-echo sequences. The training dataset contained MR slices along with DLAS and ground truth contours from 54 abdominal MRL sets, and 540 additional augmented sets created by shifting and rotating. DLAS contours were classified based on the expected editing effort into the acceptable, minor edit, or major edit category using an in-house developed classification model. Performance of the obtained ACC models were tested on an independent dataset of 11 sets of abdominal MRIs. RESULTS For pancreas, the DL-UNet model improved 17% (26/153) and 2% (2/95) of the minor and major edits' slices of the testing dataset, respectively, to acceptable and 39% (37/95) of the major edit slices improved to minor edits. The ACM model improved 3% (4/153) of the minor edit slices to acceptable and the 36% (34/95) of the major slices to minor edits. Using the ACC technique with DL and ACM combined, the percentage of acceptable contours increased from 10% (29/277) to 24% (66/277), and minor edits from 55% (153/277) to 61% (170/277), while the percentage of the major edit slices reduced from 35% (95/277) to 15% (41/277). For stomach, the DL model improved 8% (29/366) of the minor edit slices to acceptable and 50% (16/32) of the major edit slices to minor edit slices. The ACM resulted in 2% (6/366) of minor edit slices to acceptable and 41% (13/32) of major edit slices to minor category. Combining both the DL and ACM, the overall percentage of acceptable stomach contours grew from 13% (58/456) to 22% (101/456) and the percentage of major edit slices reduced from 7% (32/456) to 2% (11/456). CONCLUSION The ACC method combining both DL and ACM models can substantially improve the quality of inaccurate DLAS contours of pancreas and stomach in a fully automated and fast manner, minimizing the subsequent manual editing time required for MRgART.
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Affiliation(s)
- M Zarenia
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - Y Zhang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - J Ding
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - C Sarosiek
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Amjad
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - N P Dang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - R Conlin
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
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217
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Zhang Y, Jiang S, Ji K, Dong Y, Tao Z. Targeting Immunosuppressive Myeloid Cells and Exhausted CD8 + T Cells Overcomes Radioresistance in NSCLC. Int J Radiat Oncol Biol Phys 2023; 117:e278-e279. [PMID: 37785042 DOI: 10.1016/j.ijrobp.2023.06.1258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Although stereotactic body radiation therapy (SBRT) has achieved great success in the treatment of non-small cell lung cancer (NSCLC), local relapses still occur and abscopal effects are rarely seen even when combined with immune checkpoint blockers (ICBs). Therefore, it is necessary to thoroughly understand the immune responses after SBRT. MATERIALS/METHODS We characterized the dynamic changes of tumor-infiltrating immune cells at early and late time points after SBRT in a therapy-resistant murine tumor model using single-cell transcriptomes and T-cell receptor sequencing. RESULTS At the early stage, the innate and adaptive immune systems were activated, including activation of NKs and NKTs, and infiltration of cytotoxic CD8+ T cells. At the late stage, however, the tumor immune microenvironment (TIME) shifted into immunosuppressive properties, containing enrichment of immunosuppressive tumor-associated neutrophils (TANs), M2-like tumor-associated macrophages (TAMs), and terminal exhausted CD8+ T cells. Furthermore, our study revealed that inhibition of CD39 combined with SBRT preferentially reinvigorated exhausted CD8+ T cells and promoted their proliferation, infiltration, and cytotoxicity. Meanwhile, it also promoted M1-like macrophage infiltration and DCs maturation. On the other hand, consequently increased infiltration of immunosuppressive myeloid cells after SBRT could be a potential mechanism mediating CD8+ T cell dysfunction. Moreover, we found that combination treatment with anti-VISTA and SBRT synergistically reduced immunosuppressive myeloid cells, containing TANs, M-MDSCs, and M2-like TAMs, and further activated CD8+ T cells. Clinically, high VISTA expression was associated with poor prognosis in NSCLC patients. CONCLUSION Altogether, our data provides deep insight into acquired resistance to SBRT from an immune perspective and presents rational combination strategies.
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Affiliation(s)
- Y Zhang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - S Jiang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - K Ji
- Department of Pain Relief, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Y Dong
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Z Tao
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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Wu F, Tang X, Zhang Y, Wei L, Wang T, Lu Z, Wei J, Ma S, Jiang L, Gao T, Huang Q. The Role of Radiation Therapy for Metastatic Cervical Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e555. [PMID: 37785704 DOI: 10.1016/j.ijrobp.2023.06.1865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Survival rates for women with metastatic cervical cancer (CC) are low, with limited management options. Radiation therapy (RT) for metastatic disease has led to prolonged survival in other malignancies, however, the data are scarce in CC. Herein, we evaluated the effect of RT for metastatic CC. MATERIALS/METHODS A total of 58 patients with metastatic CC between September 2019 and January 2023 were retrospectively analyzed. All the patients were treated with platinum-based chemotherapy combined with targeted therapy or immunotherapy followed with or without RT (NRT). The recent efficacy, survival status and prognostic factors were analyzed statistically. RESULTS Objective response rate (ORR) was 63.6% with one complete and twenty partial responses in RT group (n = 33) and 40.0% with two complete and eight partial responses in NRT group (n = 25), respectively (p = 0.074). Disease control rate (DCR) of the RT and NRT groups were 79.4% vs 80.0%, respectively (p = 0.861). Median follow-up time was 17 months (3-39months). In RT group, 11(33.3%) patients experienced local regional or distant failure and 9 (27.3%) patients were dead. In NRT group, 15(60%) patients had progression and 8 (32%) patients dead. There was no significant difference between the two groups in overall survival (OS); however, RT group displayed superior progression-free survival (PFS) (1-year OS: 72.7% vs. 68.0%, p = 0.460; 1-year PFS: 66.7% vs. 40.0%, p = 0.039). The multivariate analysis showed that RT, immunotherapy, lymph node metastasis only relevant predictor of superior PFS but not OS. In subgroup analysis, patients treated with RT appeared to have a better PFS in some specific cohorts, such as age>45 years (72.0% vs 36.4% P = 0.015), squamous carcinoma histology (71.0% vs 40.9% P = 0.017), metastatic at diagnosis (75.0% vs 47.6% P = 0.012), non-targeted therapy (72.4% vs 43.8% P = 0.040). No significant increase in treatment-related toxicity was observed in the RT group compared with the NRT group. CONCLUSION RT provided superior PFS in metastatic CC patients compared to NRT, and well tolerated. Moreover, RT, immunotherapy, lymph node metastasis only were independent significant prognostic factors for PFS. Subgroup analysis showed that combination of RT and chemotherapy obtained favorable PFS in metastatic CC patients with age>45 years, squamous carcinoma histology, metastatic at diagnosis, non-targeted therapy. Studies with a larger sample size and longer follow-up are warranted.
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Affiliation(s)
- F Wu
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - X Tang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China; Department of Radiation Oncology, Liuzhou People's Hospital, Liuzhou, Guangxi, China
| | - Y Zhang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - L Wei
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - T Wang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Z Lu
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - J Wei
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - S Ma
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - L Jiang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - T Gao
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Q Huang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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Xiang X, Chen P, Lan F, Ma L, Jin J, Zhang Y. The Short-Term Efficacy and Safety of Induction Chemotherapy Combined with PD-1 Inhibitor or Anti-EGFR in Locoregionally Advanced Nasopharyngeal Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:e635. [PMID: 37785894 DOI: 10.1016/j.ijrobp.2023.06.2036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) This study aimed to investigate the short-term efficacy and safety of induction chemotherapy (IC) combined with PD-1 inhibitor or anti-EGFR in the treatment of locoregionally advanced nasopharyngeal carcinoma (LA-NPC). MATERIALS/METHODS We retrospectively reviewed the clinical data of 206 patients with LA-NPC, including IC combined with anti-PD1 (57 patients), IC combined with anti-EGFR (28 patients), and IC alone (121 patients). The short-term efficacy was assessed at the end of IC and one month after overall treatment. According to the RECIST v1.1, the short-term efficacy of cervical lymph nodes and primary nasopharynx foci was divided into complete remission (CR), partial remission (PR), stable disease (SD), and progressive disease (PD). The overall response (ORR) was defined as the sum of CR and PR. Acute toxicities were graded according to the CTCAE v5.0. One-way analysis of variance (ANOVA) was used to compare differences in the numerical variables among groups. Fisher Freeman-Halton test or Pearson Chi-square test was used to compare classified variables. RESULTS The ORR rates of primary nasopharynx foci in IC, anti-EGFR, and anti-PD1 group were 68.60%, 67.9%, and 94.7%, respectively, and the corresponding rates of ORR in cervical lymph nodes were 78.5%, 71.4%, and 93.0%, respectively. There was a statistical difference in the ORR between the three groups. Further analysis showed that after IC or overall treatment, the CR rate of primary nasopharynx foci in the anti-PD1 group was significantly higher than the other two groups. The most common adverse effects were hematotoxicity, gastrointestinal toxicity, and transaminase elevation. However, there were no statistical differences in the frequency of any common adverse effects between the three groups. CONCLUSION The addition of anti-PD1 based on IC significantly improved the short-term efficacy of LA-NPC and toxicities were tolerable.
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Affiliation(s)
- X Xiang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China, Shenzhen, China
| | - P Chen
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - F Lan
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong, China
| | - L Ma
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Zhang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Ren H, Zhang Y, Duan H. Recent advances in the management of postmenopausal women with non-atypical endometrial hyperplasia. Climacteric 2023; 26:411-418. [PMID: 37577792 DOI: 10.1080/13697137.2023.2226316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 04/30/2023] [Accepted: 06/08/2023] [Indexed: 08/15/2023]
Abstract
Non-atypical endometrial hyperplasia is a benign disease without significant somatic genetic changes. Postmenopausal women with non-atypical endometrial hyperplasia have a significant risk of progression to endometrial cancer and persistent endometrial hyperplasia. Most cases of atypical endometrial hyperplasia in postmenopausal women are treated surgically, including hysterectomy. At present, the treatment of postmenopausal women with non-atypical endometrial hyperplasia is still controversial. Correct and timely diagnosis and treatment are of great significance to prevent progression of the lesion. This study mainly provides an updated synthesis of the literature that investigates the etiology, diagnosis and treatment of postmenopausal women with non-atypical endometrial hyperplasia. As of December 2022, a literature search related to postmenopausal non-atypical endometrial hyperplasia was conducted on the PubMed database. For most postmenopausal patients with non-atypical endometrial hyperplasia, regular re-examination should be performed during conservative treatment. For postmenopausal patients with endometrial cancer risk factors, persistent non-atypical endometrial hyperplasia or progesterone contraindications, hysterectomy and bilateral salpingo-oophorectomy should be the first choice.
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Affiliation(s)
- H Ren
- Department of Minimally Invasive Gynecologic Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Y Zhang
- Department of Minimally Invasive Gynecologic Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - H Duan
- Department of Minimally Invasive Gynecologic Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
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Zhang Y, Amjad A, Ding J, Sarosiek C, Zarenia M, Conlin R, Dang NP, Hall WA, Erickson BA, Paulson ES, Li A. Clinical Usability-Oriented Automatic Contour Quality Evaluation for Deep Learning Auto-Segmentation. Int J Radiat Oncol Biol Phys 2023; 117:S144-S145. [PMID: 37784368 DOI: 10.1016/j.ijrobp.2023.06.559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Various auto-segmentations, including deep learning auto-segmentation (DLAS), are being increasingly adopted in radiotherapy. A common method to evaluate quality of auto-segmented contours uses thresholds of various quantitative metrics (e.g., dice similarity coefficient (DSC), mean distance to agreement (MDA), etc.) that are often averaged over all contour slices. This method fails to detect contour errors on individual slices, thus, does not reflect the current clinical practice (slice-by-slice evaluation) and the clinical usability (e.g., expected contour editing time). In addition, the use of multi-metrics is generally not easy to interpret. This work aims to develop a novel contour quality classification (CQC) model to evaluate auto-segmented contours based on their clinical applicability. MATERIALS/METHODS The CQC method was designed to classify a contour on a slice into acceptable, minor edit or major edit category, based on the expected editing effort/time. Organ-specific supervised ensemble tree classification models were trained to relate the slice-based quality category with the combination of seven commonly used calculatable quantitative metrics (i.e., DSC, MDA, Hausdorff 95% distance, surface DSC, added path length (APL), slice area and relative APL). The proposed method was demonstrated by training CQC models using DLAS contours of five abdominal organs (i.e., pancreas, duodenum, stomach, and small and large bowels) from 50 MRI sets and evaluating on 20 MRI and 9 CT testing sets. These test datasets were labelled by six individual observers and the consensus labels were generated through majority vote method. The model performance was evaluated using accuracy (acc), and risk rate (RR, the percentage of unacceptable slices mislabeled as acceptable) and compared with inter-observer variation and baseline threshold-based method. RESULTS Compared to the majority vote labels, the obtained CQC models achieved a mean accuracy of 95.8% ([94.5%-99.1%]) and 94.3% ([90.6%-96.9%]), and the mean RR of 0.8% ([0.3%-1.3%]) and 0.7% ([0%-1.1%]) for the MRI and CT testing sets, respectively. The CQC performance was comparable to the inter-observer variation and significantly higher than those from the threshold-based method with single or multiple metrics. The execution time on a typical abdominal dataset (e.g., 70 slices) took less than 3 seconds. Table 1 CQC models performance for different organs CONCLUSION: The proposed CQC model can classify the quality of a contour slice with high accuracy. This slice-based single-output evaluation method better reflects the current clinical practice and may be used to evaluate/compare performance of DLAS on any image modality, facilitating its clinical implementation and quality assurance.
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Affiliation(s)
- Y Zhang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Amjad
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - J Ding
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - C Sarosiek
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - M Zarenia
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - R Conlin
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - N P Dang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - W A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - B A Erickson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - E S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
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Zhu J, Zhang W, Huang W, Zhang Y, Li T, Wang Q. Radical Chemoradiotherapy vs. Radical Surgery plus Adjuvant Chemotherapy or Chemoradiotherapy in Locally Advanced Primary Small Cell Carcinoma of the Esophagus: A Multicenter Retrospective Study in China. Int J Radiat Oncol Biol Phys 2023; 117:e359-e360. [PMID: 37785236 DOI: 10.1016/j.ijrobp.2023.06.2446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The purpose was to compare the treatment outcomes of radical chemoradiotherapy versus radical surgery plus adjuvant chemotherapy or chemoradiotherapy in locally advanced primary small cell carcinoma of the esophagus (LA-PSCCE). The hypothesis was that radical chemoradiotherapy had better overall survival (OS) than radical surgery plus adjuvant chemotherapy or chemoradiotherapy. MATERIALS/METHODS This large-scale multicenter retrospective study in China enrolled patients with newly diagnosed LA-PSCCE (T3-4N0M0 or TanyN+M0, AJCC 8th edition) from 2008 to 2021. According to different curative treatment approaches, patients were divided into two groups: radical chemoradiotherapy (group: CRT), and radical surgery following adjuvant chemotherapy or chemoradiotherapy (group: S + CT/CRT). The propensity score match (PSM) was applied to reduce the effect of confounding biases in clinicopathological characteristics (age, gender, KPS, tumor location, tumor length, and cTNM stage). Univariate Cox-regression analysis and Kaplan-Meier curve were calculated for OS. Statistical results were summarized as hazard ratio (HR), 95% confidence interval (CI) and P value. A two-sided P < 0.05 was regarded to be statistically significant. RESULTS A total of 291 patients with a median follow-up of 4.3 years were retrospectively enrolled. After PSM analysis, 94 and 94 patients were eventually included in group CRT and S + CT/CRT, respectively. Group CRT demonstrated a significantly superior survival than group S + CT/CRT (HR, 0.63; 95% CI, 0.43-0.91; P = 0.01), with a 3-year OS of 49.5% and 27.8% (P = 0.02), respectively. In secondary analysis, patients treated with radical chemoradiotherapy consistently showed significant survival benefit than those with radical surgery plus adjuvant chemoradiotherapy (HR, 0.4; 95% CI, 0.21-0.79; P = 0.008). CONCLUSION For patients with newly diagnosed LA-PSCCE, radical chemoradiotherapy should be a preferred recommendation in real-world clinical practice.
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Affiliation(s)
- J Zhu
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China
| | - W Zhang
- Department of Radiation oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention Therapy, Tianjin, China
| | - W Huang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Y Zhang
- Department of Thoracic Oncology, Anyang Tumor Hospital, The Affiliated Anyang Tumor Hospital of Henan University of Science and Technology, Henan Medical key Laboratory of Precise Prevention and Treatment of Esophageal Cancer, Anyang, China
| | - T Li
- Department of Radiation Oncology, Sichuan Cancer Hospital& Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Q Wang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Chengdu, China
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Li S, Zhu X, Song M, Xiang Y, Zhang Y, Wang HZ, Geng J, Liu Z, Teng H, Cai Y, Li Y, Wang W. Outcomes and Failure Patterns after Chemoradiotherapy for Locally Advanced Rectal Cancer with Positive Lateral Pelvic Lymph Nodes: A Propensity Score-Matched Analysis. Int J Radiat Oncol Biol Phys 2023; 117:e314. [PMID: 37785131 DOI: 10.1016/j.ijrobp.2023.06.2345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Locally advanced rectal cancer (LARC) combined with positive lateral pelvic lymph nodes (LPLN) tends to present worse prognosis. However, for those patients it remains unclear whether other combination high-risk factors affect the prognosis. This study aimed to use propensity score matching (PSM) to examine long-term outcomes and failure patterns in patients with positive vs. negative LPLN. MATERIALS/METHODS Patients with LARC were retrospectively divided into LPLN-positive and LPLN-negative groups. LPLN-positivity was defined as lymph node short diameter greater than or equal to 7 mm with specific morphological features. Clinical characteristics were compared between the groups using the chi-square test. PSM was applied to balance these differences. Progression-free survival (PFS) and overall survival (OS), and local-regional recurrence (LRR) and distant metastasis (DM) rates were compared between the groups using the Kaplan-Meier method and log-rank tests. RESULTS Prior to PSM, a total of 651 LARC patients were included. The LPLN-positive group had higher rates of lower location (53.1% vs. 43.0%, P = 0.025), mesorectal fascia (MRF)-positive (53.9% vs. 35.4%, P<0.001) and extramural venous invasion (EMVI)-positive (51.2% vs. 27.2%, P<0.001) disease than the LPLN-negative group. After PSM, there were 114 patients for each group along with the balanced clinical factors, and both groups had comparable surgery, pathologic complete response (pCR), and ypN stage rates. The median follow-up time was 45.9 months, 3-year OS (88.3% vs. 92.1%, P = 0.276) and LRR (5.7% vs. 2.8%, P = 0.172) rates were comparable between LPLN-positive and LPLN-negative groups. Meanwhile, despite no statistical difference, 3-year PFS (78.8% vs. 85.9%, P = 0.065) and DM (20.4% vs. 13.3%, P = 0.061) rates slightly differed between the groups. Among 10 patients with LRR, seven (70.0%) had lateral pelvic recurrence, among them, five patients were LPLN-positive, and four (80.0%) of these patients did not receive simultaneous integrated boost intensity-modulated radiotherapy (SIB- IMRT).45 patients were diagnosed with DM, 11 (40.7%) LPLN-positive and 3 (17.6%) LPLN-negative patients were diagnosed with oligometastases (P = 0.109). CONCLUSION Our study shows there is a tendency of worse PFS and DM in LPLN-positive than LPLN-negative patients, for LPLN-positive patients, oligometastases account for a large proportion of all distant metastases.
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Affiliation(s)
- S Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - X Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - M Song
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Xiang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - H Z Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - J Geng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Z Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - H Teng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Cai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - W Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
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Abstract
PURPOSE/OBJECTIVE(S) Radiation therapy (RT) is indispensable for managing thoracic carcinomas. However, its application is limited by radiation-induced lung injury (RILI), one of the most common and fatal complications of thoracic RT. Nonetheless, the exact molecular mechanisms of RILI remain poorly understood. MATERIALS/METHODS To elucidate the underlying mechanisms, various knockout (KO) mouse strains were subjected to 16 Gy whole-thoracic RT. RILI was assessed by qRT-PCR, ELISA, histology, western blot, immunohistochemistry, and CT examination. To perform further mechanistic studies on the signaling cascade during the RILI process, pulldown, CHIP, and rescue assays were conducted. RESULTS We found that the cGAS-STING pathway was significantly upregulated after irradiation exposure in both the mouse models and clinical lung tissues. Knocking down either cGAS or STING led to attenuated inflammation and fibrosis in mouse lung tissues. NLRP3 is hardwired to the upstream DNA-sensing cGAS-STING pathway to trigger of the inflammasome and amplification of the inflammatory response. STING deficiency suppressed the expressions of the NLRP3 inflammasome and pyroptosis-pertinent components containing IL-1β, IL-18, and cleaved caspase-1. Mechanistically, interferon regulatory factor 3, the essential transcription factor downstream of cGAS-STING, promoted the pyroptosis by transcriptionally activating NLRP3. Moreover, we found that RT triggered the release of self-dsDNA in the bronchoalveolar space, which is essential for the activation of cGAS-STING and the downstream NLRP3-mediated pyroptosis. Of note, Pulmozyme, an old drug for the management of cystic fibrosis, was revealed to have the potential to mitigate RILI by degrading extracellular dsDNA and then inhibiting the cGAS-STING-NLRP3 signaling pathway. CONCLUSION These results delineated the crucial function of cGAS-STING as a key mediator of RILI, and described a mechanism of pyroptosis linking cGAS-STING activation with the amplification of initial RILI. These findings indicate that the dsDNA-cGAS-STING-NLRP3 axis might be potentially amenable to therapeutic targeting for RILI.
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Affiliation(s)
- Y Zhang
- Zhongshan Hospital, Fudan University, Shanghai, China
| | - S Du
- Zhongshan Hospital, Fudan University, Shanghai, China
| | - Z Zeng
- Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
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Wang L, Zou B, Huang W, Shao Q, Meng X, Tang X, Zhang P, Hu X, Zhang Y, Guo J, Fu L, Zhao W, Zhao C, Yuan J, Yu J, Chen D. Safety and Efficacy Analysis of Patients with Extensive-Stage Small Cell Lung Cancer (ES-SCLC) Treated with SHR-1316 Plus Chemotherapy and Sequential Chest Radiotherapy as First-Line Therapy from a Phase II Trial. Int J Radiat Oncol Biol Phys 2023; 117:S58-S59. [PMID: 37784531 DOI: 10.1016/j.ijrobp.2023.06.354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) CAPSTONE-1, a phase 3 trial, showed that SHR-1316 (PD-L1 antibody) combined with standard first-line chemotherapy could prolong overall survival (OS) in patients (pts) with ES-SCLC. The CREST trial reported consolidative thoracic radiotherapy (TRT) of 30 Gy in 10 fractions provided a 10% 2-year OS benefit and more intensive TRT should be investigated in ES-SCLC. In the era of immunotherapy, the role of TRT also needs further exploration. Therefore, we designed this clinical trial to investigate the efficacy and safety of SHR-1316 plus first-line chemotherapy followed by TRT combined with SHR-1316. MATERIALS/METHODS Key inclusion criteria were pts aged 18-75 years, with previously untreated histologically or cytologically confirmed ES-SCLC, and an ECOG performance status of 0-1. Eligible pts would receive 4∼6 cycles of SHR-1316 (20mg/kg, D1, q3w) combined with EP/EC (etoposide, 100mg/m2, D1-5, q3w and cisplatin, 75mg/m², D1-3, q3w or carboplatin, AUC = 5, D1, q3w), followed by SHR-1316 combined with TRT (≥3 Gy*10 f or ≥2 Gy*25 f, involved-field irradiation), and then the maintenance therapy with SHR-1316 until disease progression or intolerable adverse events (AEs). The main endpoints included ORR, PFS and safety. RESULTS From October 2020 to January 2023, 33 pts received SHR-1316 and sequential consolidative TRT. Among them, 19 pts received high-dose TRT (>3 Gy*10 f or ≥2 Gy*25 f) and 14 pts received low-dose TRT (≤3 Gy*10 f or<2 Gy*25 f). The median age was 62 (range: 38-73). Most pts were male (28, 84.8%), former smokers (22, 66.7%) with an ECOG performance status 1 (32, 97%). Ten (30.3%) pts were diagnosed with brain metastasis and 10 (30.3%) pts had liver metastasis at baseline. At the data cutoff date, 9 pts remained on treatment, the average number of treatment cycles was 9.2. 33 pts had at least one 1 post-treatment tumor assessment. The confirmed ORR and DCR were 90.9% (30/33) and 100% (33/33) in all pts, were 89.5% (17/19) and 100% (19/19) in high-dose TRT group, and were 92.9% (13/14) and 100% (14/14) in low-dose TRT group. The median PFS was 10.2(CI: 5.8∼14.7) months in all pts, was 7 (CI: 3.8∼10.2) months in high-dose TRT group and 10.4 (CI: 8.4∼12.3) months in low-dose TRT group. AEs occurred in 27 (81.8%) pts and grade 3 or 4 AEs occurred in 20 (60.6%) pts. The most common grade 3 or 4 AEs included neutropenia (15, 45.5%), leukopenia (8, 24.2%), lymphocytopenia (5, 15.2%), pneumonia (3, 9.1%), anemia (3, 9.1%) and thrombocytopenia (2, 6.1%). CONCLUSION SHR-1316 plus chemotherapy and sequential TRT as first-line therapy for ES-SCLC showed promising efficacy and acceptable safety. There is no significant difference between high-dose and low-dose TRT groups in terms of safety and efficacy according to current data.
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Affiliation(s)
- L Wang
- Shandong Cancer Hospital, Shandong University, Jinan, China
| | - B Zou
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - W Huang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Shao
- Shandong Cancer Hospital and Institute, Jinan, China
| | - X Meng
- Shandong Cancer Hospital, Shandong University, Jinan, China
| | - X Tang
- Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan 250117, Shandong Province, China
| | - P Zhang
- Shandong Cancer Hospital, Shandong University, Jinan, China
| | - X Hu
- Shandong Cancer Hospital, Shandong University, Jinan, China
| | - Y Zhang
- Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan 250117, Shandong Province, China
| | - J Guo
- Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan 250117, Shandong Province, China
| | - L Fu
- Shandong Cancer Hospital, Shandong University, Jinan, China
| | - W Zhao
- Shandong Cancer Hospital, Shandong University, Jinan, China
| | - C Zhao
- Jiangsu Hengrui Pharmaceuticals Co. Ltd, Shanghai, China
| | - J Yuan
- Jiangsu Hengrui Pharmaceuticals Co. Ltd, Shanghai, China
| | - J Yu
- Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
| | - D Chen
- Shandong Cancer Hospital, Shandong University, Jinan, China
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Guo Q, Liu J, Dou X, Zhu K, Shi P, Zhang Y, Li S, Feng R, Yue J. Camrelizumab with Chemoradiotherapy for Locally Advanced Biliary Tract Cancer: Preliminary Results from A Phase II Study. Int J Radiat Oncol Biol Phys 2023; 117:e355. [PMID: 37785226 DOI: 10.1016/j.ijrobp.2023.06.2434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) For locally advanced biliary tract cancer (BTC), capecitabine-based chemoradiotherapy (CRT) is commonly used but has limited benefits. Immunotherapy is potentially effective for BTC and may be synergized with CRT. Followed by gemcitabine and cisplatin (GP) consolidation chemotherapy (CT), we evaluated the safety and efficacy of combined camrelizumab and capecitabine-based CRT for locally advanced BTC. MATERIALS/METHODS Patients had stage II-III (T4N0M0, T1-4N+M0) BTC (per the 7th [2010] edition of the American Joint Committee on Cancer staging system) were eligible for CRT (capecitabine plus [50-60 Gy] radiotherapy), to be followed by GP CT. Camrelizumab was given concurrently with CRT. Safety was defined as the incidence and severity of adverse events (AEs), while efficacy was defined as overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR). RESULTS Ten patients completed the planned treatment. None experienced grade ≥3 treatment-related AEs during CRT. Grade ≥3 immune-related AEs occurred in 2 of 10 patients (20%) only during GP CT. The mean OS time was 18.2 months (95% confidence interval [CI] 12.9m-23.5m) while the median OS time was 14.1 months (95% CI 10.1m-18.1m). OS rates were 100%, 59%, 44% at 6 months, 1 year and 2 years, respectively. The ORR was 30% while the DCR was 90%. Two patients (20%) obtained OS over 2 years with partial response (25.9m, 29.1m). Median PFS time was 14.1 months (95% CI 9.3m-18.9m). CONCLUSION Camrelizumab in combination with concurrent CRT was well tolerated and did not impair delivery of CRT in patients with locally advanced BTC.
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Affiliation(s)
- Q Guo
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - J Liu
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - X Dou
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - K Zhu
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - P Shi
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Y Zhang
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - S Li
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - R Feng
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - J Yue
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
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Zhang J, Wang F, Shang S, Yan W, Ma Y, Ren Z, Wu M, Ma J, Zhang Y, Yu J, Chen D. HPK1 Inhibition Enhancing HFRT Anti-Tumor Immune Response. Int J Radiat Oncol Biol Phys 2023; 117:S120-S121. [PMID: 37784312 DOI: 10.1016/j.ijrobp.2023.06.458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Radiation therapy, as one of the canonical treatments for classic tumors, results in impressive clinical responses. Stereotactic body radiotherapy (SBRT) has been increasingly used as one main therapy in early-stage non-small-cell lung cancer (NSCLC). SBRT affords good local tumor control, however, recurrence and metastasis are still the main causes of treatment failure. With the continuous deepening of the relationship between radiotherapy (RT) and immunity, reversing RT induced immunosuppression is considered to be a promising strategy to improve radiotherapy efficacy. Hematopoietic progenitor kinase 1 (HPK1) is mainly expressed in immune cells while rarely expressed in tumor cells. It has been proven to play a negative regulatory role in T cell receptor (TCR) signal. Therefore, we hypothesized that the combination of HPK1 inhibitor with SBRT would boost local and systemic anti-tumor immune responses by potentiating the anti-tumor effects of SBRT. MATERIALS/METHODS Using Digital Spatial Profiler (DSP), we analyzed HPK1 expression in the tumor specimens of 39 NSCLC patients treated with SBRT. By establishing mice subcutaneous tumor models, we assessed the combination of a HPK1 inhibitor and local hyper-fractionated radiotherapy (HFRT) on local and systemic tumor control and mouse survival. Using Single-cell RNA sequencing, Flow cytometry and pharmacological treatment, we analyzed and verified Tumor-infiltrating lymphocytes (TILs), and excavated the specific mechanism of the HPK1 inhibitor enhancing HFRT -induced anti -tumor immune response. RESULTS In the tumor specimens of NSCLC patients treated with SBRT, we found that high expression HPK1 in TILs predicted poor progression-free survival (PFS). Among the C57BL/6 mice model, HFRT combined with a HPK1 inhibitor promoted local response, and improved the survival rate of mice, showing better anti-tumor curative effects. We further showed that HFRT promoted CD8+ T cell cytotoxic activity, and also aggravated CD8+ T cell exhaustion. After the intervention of HPK1 small molecular inhibitors, the proportion of exhaustion CD8+T cells was significantly reduced, while CD8+T cell cytotoxic activity was further enhanced in the later period. Single-cell RNA sequencing and pharmacological inhibition of HPK1 revealed that HPK1 mediated the exhaustion of CD8+T cells by regulating RGS16. In abscopal effects preclinical models, BGB-15025 induced obvious abscopal effect. CONCLUSION Thus, we demonstrate that HPK1 mediates HFRT-induced CD8+T cell exhaustion by regulating RGS16, and HPK1 is an attractive drug target for enhancing local and systemic radiotherapy.
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Affiliation(s)
- J Zhang
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - F Wang
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - S Shang
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - W Yan
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Y Ma
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Z Ren
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - M Wu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - J Ma
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China; Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Zhang
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - J Yu
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - D Chen
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
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Wang L, Zang J, Zhang Y, Yin Y, Wang P, Zhang J, Long X, Zhao LN. Investigating Incidence of Nausea and Vomiting in Patients Receiving Concurrent Chemoradiotherapy: A Real-World Cohort Study. Int J Radiat Oncol Biol Phys 2023; 117:e448-e449. [PMID: 37785445 DOI: 10.1016/j.ijrobp.2023.06.1632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Vomiting and nausea (VN) caused by anticancer agents and/or radiation therapy (RT) can significantly affect a patient's quality of life, leading to poor compliance with further anticancer agents and/or RT. Few studies pay attention to synergistic effect of RT and concurrent highly emetogenic chemotherapy for inducing vomiting and nausea. The aim of this real-world study is to investigate the incidence of VN in patients receiving concurrent chemoradiotherapy (CCRT). MATERIALS/METHODS From June 2022 to December 2022, patients receiving concurrent chemoradiotherapy in our center were consecutively enrolled in this study. Patients received moderate and low emetic agents were excluded. The antiemesis regimens were NK1 receptor antagonist plus 5-HT3 antagonist and dexamethasone (NHD) with or without olanzapine, which were recommended by guideline of National Comprehensive Cancer Network. Acute and delayed VN were analyzed in the following stratification factors: tumor site and antiemesis regimen. Acute VN usually occurred after administration of anticancer agents and commonly resolves within the first 24 hours. Delayed VN develops in patients more than 24 hours after anticancer agent administration. The grade of VN was evaluated according to Common Terminology Criteria for Adverse Events Criteria. RESULTS A total of 312 patients were enrolled for analysis. During the CCRT period, the incidence rate of acute VN in all patients was 28.2%, the delayed VN occurred in 139 of 312 patients (44.6%). The incidence rate of acute nausea in head and neck, thorax and abdomen were 33.8%, 28.9% and 25.2%, respectively. The incidence rate of acute vomiting in head and neck, thorax and abdomen were 7.0%, 3.9% and 5.2%, respectively. The incidence rate of delayed nausea in head and neck, thorax and abdomen were 51.1%, 35.5% and 45.9%, respectively. The incidence rate of delayed vomiting in head and neck, thorax and abdomen were 14.0%, 5.3% and 9.6%, respectively. There were not significant differences between NHD regimen and NHD plus olanzapine in VN (acute nausea, 25.5% vs. 30.3%, P = 0.356; acute vomiting, 4.4% vs. 6.8%, P = 0.352; delayed nausea, 40.1% vs. 48%, P = 0.166; delayed vomiting, 8.0% vs. 10.8%, P = 0.4). Multivariate logistic regression analysis showed age <50 years (P = 0.030. HR, 95% CI: 1.893, 1.062-3.374) and history of vomiting = 0.017, HR, 95% CI: 2.249, 1.154-4.384) were risk factor for acute nausea; female (P = 0.026, HR, 95% CI: 4.254, 1.192-15.186) and sleeping time <7 hours (p = 0.049, HR, 95% CI: 3.373, 1.003-11.344) were risk factors for acute vomiting; pregnancy (P = 0.011, HR, 95% CI: 2.424, 1.228-4.783) was risk factor for delayed nausea; pregnancy = 0.013, HR, 95% CI: 3.060, 1.269-7.380) and history of vomiting = 0.020, HR, 95% CI: 2.845, 1.182-6.844) were risk factors for delayed vomiting in patients receiving CCRT. CONCLUSION CCRT still contributed high incidence of delayed nausea in patients receiving standard antiemesis regimen.
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Affiliation(s)
- L Wang
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - J Zang
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Y Zhang
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Y Yin
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - P Wang
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - J Zhang
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - X Long
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - L N Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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229
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Li J, Zhang Y, Bai KX, Qi XJ, Zhao Y, Bu H. Bioinformatics screening of gene expression profile and diagnostic application of meningeal carcinoma. Eur Rev Med Pharmacol Sci 2023; 27:9601-9613. [PMID: 37916326 DOI: 10.26355/eurrev_202310_34132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/03/2023]
Abstract
OBJECTIVE The aim of this study was to research gene expression profiles and diagnostic applications of meningeal carcinoma based on bioinformatics. MATERIALS AND METHODS We used the Gene Expression Omnibus (GEO) database to obtain the GSE43290 dataset based on the expression data of normal meninges and meningiomas consisting of 51 samples divided into two groups (47 samples of meningioma tumors and four samples of normal meninges). We used the GEO2R tool to identify differentially expressed genes (DEGs) by setting the log2 fold change as greater than two and an adjusted p-value lower than 0.05. We used the database for annotation, visualization and integrated discovery (DAVID) to perform gene ontology, biological pathways and functional annotation of the DEGs. A search Tool for the Retrieval of Interacting Gene database (STRING) was used to obtain Protein-Protein Interaction (PPI) and modular networks based on the Markov clustering algorithm. RESULTS Our study identified 358 significant DEGs, of which 343 were downregulated genes while 15 were upregulated. Five significant hub genes (CXCL8, AGT, CXCR4, CXCL12 and CXCL2) were associated with various biological pathways, molecular functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The DEGs were enriched in biological pathways of chemokine-mediated signaling, positive regulation of leukocyte chemotaxis, second messenger-mediated signaling, induction of positive chemotaxis, CXCR chemokine receptor binding and activities of cytokines. CONCLUSIONS These hub genes and pathways could be targeted in clinical research to discover new treatments for meningeal carcinoma.
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Affiliation(s)
- J Li
- Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
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Qiao Y, Zhang C, Li A, Wang D, Luo Z, Ping Y, Zhou B, Liu S, Li H, Yue D, Zhang Z, Chen X, Shen Z, Lian J, Li Y, Wang S, Li F, Huang L, Wang L, Zhang B, Yu J, Qin Z, Zhang Y. Correction: IL6 derived from cancer-associated fibroblasts promotes chemoresistance via CXCR7 in esophageal squamous cell carcinoma. Oncogene 2023; 42:3287-3288. [PMID: 37723312 DOI: 10.1038/s41388-023-02822-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Affiliation(s)
- Y Qiao
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - C Zhang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - A Li
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - D Wang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Z Luo
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Y Ping
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - B Zhou
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, China
| | - S Liu
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, China
| | - H Li
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - D Yue
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Z Zhang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - X Chen
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Z Shen
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - J Lian
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, China
| | - Y Li
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, China
| | - S Wang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - F Li
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - L Huang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - L Wang
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - B Zhang
- Department of Hematology/Oncology, School of Medicine, Northwestern University, Chicago, IL, USA
| | - J Yu
- Department of Internal Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Z Qin
- Medical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Y Zhang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
- School of Life Sciences, Zhengzhou University, Zhengzhou, China.
- Key Laboratory for Tumor Immunology and Biotherapy of Henan Province, Zhengzhou, China.
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231
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Huh SN, Zhang Y, Park JY, Indelicato DJ. Development of a Filtimator for Pediatric Image-Guided Radiation Therapy with Low Imaging Dose. Int J Radiat Oncol Biol Phys 2023; 117:S178. [PMID: 37784441 DOI: 10.1016/j.ijrobp.2023.06.2521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) We propose to use the filtimator (a filter and a collimator) for CBCT-based image-guided radiation therapy (IGRT) optimized for pediatric patients to minimize the imaging dose but not to sacrifice the imaging quality required for bony-based image fusion. MATERIALS/METHODS The filtimator was made of Tin (0.6 - 1 mm) and Cu sheets (0.6 to 1.2mm) for filter and collimation with adjustable collimation with 4 to 6 cm fields at the isocenter. The thickness of the filter in the central and the peripheral regions were determined using vendor-provided image registration software and to ensure that the rigid image registration results from the CBCT were with and without the filtimator. The image quality of the filtered CBCT was compared with the regular CBCTs. Image registration accuracy was investigated by creating a < 2° shift in pitch, roll, and rotation and < 3 cm shifts in the lateral, vertical, and longitudinal directions, using commercial head and house-made phantoms. The imaging dose reduction factor of the filtimator was measured using a CT dose index phantom. RESULTS The contrast-to-noise ratio substantially improved in the opening region of the filter, which provided better visualization of normal anatomy and target volumes. The slim filter reduced the imaging dose by > 98% in the filtered region, and the visualization of bony structures was well preserved, allowing for accurate rigid image registration with the filter. The imaging registration difference was < 0.2° shift in pitch, roll, and rotation and < 0.5 mm shift in the lateral, vertical, and longitudinal directions compared to the regular CBCT. CONCLUSION The proposed dose reduction with the filtimator was demonstrated to be efficient and effective in considerably reducing the patient imaging dose while yielding accurate registration results. This novel technique can become a valuable tool for generating 3- and 4-dimensional images with a much-reduced dose to improve the precision of target localization in radiation therapy.
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Affiliation(s)
- S N Huh
- Department of Radiation Oncology, University of Florida College of Medicine, Gainesville, FL; University of Florida Health Proton Therapy Institute, Jacksonville, FL
| | - Y Zhang
- Department of Radiation Oncology, University of Florida College of Medicine, Gainesville, FL; University of Florida Health Proton Therapy Institute, Jacksonville, FL
| | - J Y Park
- Department of Radiation Oncology, University of Florida College of Medicine, Gainesville, FL; University of Florida Health Proton Therapy Institute, Jacksonville, FL
| | - D J Indelicato
- Department of Radiation Oncology, University of Florida College of Medicine, Gainesville, FL; University of Florida Health Proton Therapy Institute, Jacksonville, FL
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Zhang Y, Ye X, Ge J, Guo D, Zheng D, Yu H, Chen Y, Yao G, Lu Z, Yuille A, Lu L, Jin D, Yan S. Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:e498. [PMID: 37785566 DOI: 10.1016/j.ijrobp.2023.06.1739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model. MATERIALS/METHODS We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance. RESULTS The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality. CONCLUSION We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.
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Affiliation(s)
- Y Zhang
- Johns Hopkins University, Baltimore, MD
| | - X Ye
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - J Ge
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - D Guo
- Alibaba Group (US) Inc., New York, NY
| | - D Zheng
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - H Yu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Y Chen
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - G Yao
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Z Lu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - A Yuille
- Johns Hopkins University, Baltimore, MD
| | - L Lu
- Alibaba Group (US) Inc., New York, NY
| | - D Jin
- Alibaba Group (US) Inc., New York, NY
| | - S Yan
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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233
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Li R, Montalvo SK, Zhuang T, Parsons DDM, Zhong X, Chen L, Iqbal Z, Kim H, Hrycushko BA, Westover KD, Zhang Y, Cai B, Lin MH, Iyengar P. Dosimetric Analysis of CBCT-Based Weekly Online Adaptive Radiotherapy for Locally Advanced Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e36-e37. [PMID: 37785239 DOI: 10.1016/j.ijrobp.2023.06.728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Anatomic and geometric changes are common during a radiotherapy course amongst patients receiving conventional fractionated radiotherapy for locally advanced non-small cell lung cancer (LA-NSCLC). These changes may cause significant deviation from initial reference plan resulting in over-treatment of normal tissue or under-coverage of the target. Cone-beam computed tomography (CBCT)-based online adaptive radiotherapy (ART) platforms allow for response to these changes and is being increasingly used in the clinic though less so for intrathoracic disease. We hypothesized weekly CBCT-ART would improve target coverage and decrease dose to organs at risk (OAR) in patients with LA-NSCLC. MATERIALS/METHODS Data was collected from a prospective registry of 23 LA-NSCLC patients treated to 60 Gy in 30 fractions with CBCT-ART between June 2021 and December 2022. For weekly ART (Wk-ART), online plan adaptation started on week two. The adapted plan was then used to treat patients with image guidance until the next ART. For comparison, doses were recalculated with the initial reference plan on the SCT with updated contours to derive non-adapted (non-ART) dosimetry for each week. The final dosimetric parameters were obtained by averaging weekly coverage (ITV, PTV) and critical OAR (Lung, esophagus, heart, spinal cord) doses for non-ART and weekly ART treatments respectively for each patient. Paired student t-test was performed to compare the dosimetric parameters between non-ART and Wk-ART. RESULTS We observed an average 29% ± 19% (median: 26%) reduction in ITV volume through the radiotherapy course, with 48% (11/23) of patients showing >30% reduction. Most significant volume reductions (16%) were observed between the third and fourth adaptation. Weekly ART showed significant (p<1×10-3) improvements in ITV and PTV coverage, and showed improved clinically relevant lung, esophageal, cardiac, and lung dosimetry (Table 1), especially in the later stages of treatment when the tumor showed significant shrinkage. The average time from contour review to quality assurance completed is 8.5±1.2 min. CONCLUSION CBCT-ART provides robust ART plan quality and efficient workflow. There are significant improvements in target coverage and OAR sparing in LA-NSCLC treated with weekly CBCT-ART and these are driven by the significant volume reduction of the ITV throughout treatment course.
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Affiliation(s)
- R Li
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - S K Montalvo
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - X Zhong
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - L Chen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Z Iqbal
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Kim
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B A Hrycushko
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - K D Westover
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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Rahimi AS, Kim N, Leitch M, Gu X, Parsons DDM, Nwachukwu CR, Alluri PG, Lu W, Nichols EM, Becker SJ, Ahn C, Zhang Y, Spangler A, Farr D, Wooldridge R, Bahrami S, Stojadinovic S, Lieberman M, Neufeld S, Timmerman RD. Multi-Institutional Phase II Trial Using Dose Escalated Five Fraction Stereotactic Partial Breast Irradiation (S-PBI) with GammaPod TM for Early-Stage Breast Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e203. [PMID: 37784857 DOI: 10.1016/j.ijrobp.2023.06.1082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) We report on our early experience of a multi-institutional phase II study of dose escalated five fraction stereotactic partial breast irradiation (S-PBI) for early-stage breast cancer after partial mastectomy using the GammaPodTM stereotactic radiation system. MATERIALS/METHODS Patient eligibility included DCIS or invasive epithelial histologies, AJCC clinical stage 0, I, or II with tumor size < 3 cm, and negative margins. Prior safety of Phase I dose escalation has been reported. Dose was 40 Gy delivered in 5 fractions to the CTV, and minimum dose 30 Gy in 5 fractions to the PTV. CTV margin was 1 cm and PTV margin 3 mm. For PTV cavities larger than 100cc, dose was reduced to 35Gy in 5 fractions to the CTV and 30 Gy in 5 fractions to the PTV. Primary endpoint of the study is to determine the 3-year patient global cosmesis score (4-point scale excellent, good, fair, or poor) and adverse cosmesis using a dose escalated approach with smaller PTV margins than conventional methods. Both patients and physicians completed baseline and subsequent cosmesis outcome questionnaires. Treatment related toxicity was graded using the NCI version 4.0 and RTOG/EORTC late radiation scale. RESULTS From 3/2019-10/2021, 74 patients were treated respectively. Of these, 38 were treated to 40Gy and 36 were treated to 35 Gy. Median follow up (f/u) was 24 months (mo), range (r) 3-39mo. Median age was 63 years (r 43-77). Histology included 28 DCIS, and 46 invasive carcinomas. 45/46 invasive tumors were ER+. 60/74 (81%) patients received endocrine therapy, and 7/74 patient received chemotherapy. There were 221 acute grade 1 toxicities, and 28 Grade 2 toxicities. No grade 3 or higher acute toxicities were reported (< 90 days). The most common Grade 2 toxicities were radiation dermatitis (10), breast pain (8), blister (4), skin infection (2), nipple discharge (2), and fatigue (2). In the late period, there were 54 Grade 1 late toxicities, 4 Grade 2 late toxicities, and no Grade 3 or higher late toxicities. Grade 2 toxicities included fibrosis (2), and pain (2). Two patients developed grade 1 asymptomatic nonpalpable fat necrosis both diagnosed at 12 months after radiation treatments. The most common grade 1 late toxicities were breast pain (14), hyperpigmentation (8), fibrosis (10), and fatigue (5). Physicians scored cosmesis excellent or good 70/73 (95.8%), 58/60 (96.7%), 36/36 (100%),17/17(100%) respectively at baseline, 12 months, 24 months, and 36months post SBRT, while patients scored the same periods 62/71 (83.7%), 53/59 (89.8%), 33/36 (91.6%), 17/18 (94.4%). There have been no reports of disease recurrences. CONCLUSION Results at 24-month median follow-up, of our dose escalated stereotactic partial breast 5 fraction regimen, has low acute and late toxicity, while maintaining high proportion of excellent/good cosmetic outcomes. Continued analysis of all cohorts is in progress. CLINICAL TRIALS gov identifier is NCT03581136.
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Affiliation(s)
- A S Rahimi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - N Kim
- Vanderbilt University Department of Radiation Oncology, Nashville, TN
| | - M Leitch
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX
| | - X Gu
- Stanford University Department of Radiation Oncology, Palo Alto, CA
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - C R Nwachukwu
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - P G Alluri
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - W Lu
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - E M Nichols
- University of Maryland School of Medicine, Baltimore, MD
| | - S J Becker
- University of Maryland School of Medicine, Baltimore, MD
| | - C Ahn
- Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Zhang
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - A Spangler
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D Farr
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX
| | - R Wooldridge
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX
| | - S Bahrami
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - S Stojadinovic
- University of Texas Southwestern Medical Center, Dallas, TX
| | - M Lieberman
- University of Texas Southwestern Medical Center, Dallas, TX
| | - S Neufeld
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
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Kwon YS, Parsons DDM, Kim N, Lu W, Gu X, Stojadinovic S, Alluri PG, Arbab M, Lin MH, Chen L, Gonzalez Y, Chiu TD, Zhang Y, Timmerman RD, Rahimi AS. Assessment of Cardiac Radiation Dose in the Co-60 Prone Based Stereotactic Partial Breast Irradiation (CP-sPBI) Using the Distance from the Heart to the Planning Treatment Volume as a Surrogate Marker. Int J Radiat Oncol Biol Phys 2023; 117:e682. [PMID: 37786008 DOI: 10.1016/j.ijrobp.2023.06.2144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Irradiation of the breast has shown to provide sharp dose gradients using Co-60 prone based stereotactic partial breast irradiation (CP-sPBI), a contemporary device for stereotactic radiotherapy for breast cancer (BC) for accelerated partial breast irradiation (APBI). In addition, the precise setup of CP-sPBI permits a small planning treatment volume (PTV) margin of 3 mm creating a greater distance from PTV to organs at risk. However, to date the factors that influence dose gradients and subsequent cardiac doses of ionizing radiation using CP-sPBI have not been well-studied. Here we evaluate distance of the heart to the lumpectomy PTV cavity and how this effects cardiac dose. MATERIALS/METHODS A retrospective database of 113 consecutive patients treated by CP-sPBI for APBI from March 2019 to February 2023 who were treated with 30 Gy in 5 fractions were queried for analysis. The minimum distance from the heart to the PTV (hP) was measured in either the axial or sagittal view. A group of 28 patient cases were randomly selected to achieve an even distribution of 28 cases with hP < 2.75 cm and hP ≥ 2.75 cm to compare cardiac toxicities based on hP. Descriptive analyses were performed to evaluate various cardiac dosimetric parameters based on laterality of BC and hP, using the student's t test. RESULTS The mean (range) hP was 4.58 cm (0.80-12.23) for all cases. The subgroup analyses of 28 patient cases with cardiac parameters showed the heart mean (range) dose of 1.20 Gy (0.01-2.11). The mean and max heart dose to the left-sided BC were similar to those to the right-sided BC (mean dose: 1.20 vs. 1.19 Gy; P = 0.97 and max dose: 10.47 vs. 5.66 Gy; P = 0.06). An inverse correlation between hP and mean heart dose was shown with the correlation coefficient of -0.81. Using a cutoff of 2.75 cm hP, the differences between hP < 2.75 and hP ≥ 2.75 cm for all cardiac dosimetric evaluations were all statistically significant, including mean (1.67 vs. 0.79 Gy; p<0.01) and maximal heart dose (14.48 vs. 4.11 Gy; p<0.01) CONCLUSION: CP-sPBI treatment delivery system was able to achieve acceptable clinically relevant heart dosimetric parameters when delivering 5 fraction APBI with a mean heart dose of 1.20 Gy for all locations of PTV cavity volume in the breast. Due to CP-sPBIs excellent dose fall-off characteristics, APBI using CP-SPBI showed clinically acceptable cardiac dosimetric parameters, particularly for PTVs located > 2.75 cm from the heart.
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Affiliation(s)
- Y S Kwon
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - N Kim
- Vanderbilt University Department of Radiation Oncology, Nashville, TN
| | - W Lu
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - X Gu
- Stanford University Department of Radiation Oncology, Palo Alto, CA
| | - S Stojadinovic
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P G Alluri
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - M Arbab
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - L Chen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Gonzalez
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T D Chiu
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - Y Zhang
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A S Rahimi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
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Wang HZ, Zheng X, Sun J, Zhu X, Dong D, Du Y, Feng Z, Gong J, Wu H, Geng J, Li S, Song M, Zhang Y, Liu Z, Cai Y, Li Y, Wang W. 4D-MRI Guided Stereotactic Body Radiation Therapy for Unresectable Colorectal Liver Metastases. Int J Radiat Oncol Biol Phys 2023; 117:e359. [PMID: 37785235 DOI: 10.1016/j.ijrobp.2023.06.2445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) This study evaluated the feasibilities and outcomes following four-dimensional magnetic resonance imaging (4D-MRI) guided stereotactic body radiation therapy (SBRT) for unresectable colorectal liver metastases (CRLM). MATERIALS/METHODS From March 2018 to January 2022, we identified 76 unresectable CRLM patients with 123 lesions who received 4D-MRI guided SBRT in our institution. 4D-MRI simulation with or without abdominal compression was conducted for all patients. The prescription dose was 50-65 Gy in 5-12 fractions. The image quality of computed tomography (CT) and MRI were compared using the Clarity Score. Clinical outcomes and toxicity profiles were evaluated. RESULTS The 4D-MRI significantly improved the image quality compared with CT images (mean Clarity Score: 1.67 vs 2.88, P < 0.001). The abdominal compression significantly reduced motions in cranial-caudal direction (P = 0.03) with 2 phase T2 weighted images assessing tumor motion. The median follow-up time was 12.5 months. For 98 lesions assessed for best response, the complete response, partial response and stable disease rate were 57.1 %, 30.6 % and 12.2 %, respectively. The local control (LC) rate at 2 year was 97.3%. 46.1% of patients experienced grade 1-2 toxicities and only 2.6% patients experienced grade 3 hematologic toxicities. CONCLUSION The 4D-MRI technique allowed precise target delineation and motion tracking in unresectable CRLM patients. High LC rate and mild toxicities were achieved. This study provided evidence for using 4D-MRI guided SBRT as an alternative treatment in unresectable CRLM.
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Affiliation(s)
- H Z Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - X Zheng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - J Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - X Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - D Dong
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - Y Du
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - Z Feng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - J Gong
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - H Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, Beijing, China
| | - J Geng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - S Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - M Song
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Z Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Cai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - W Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
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Sarosiek C, Zhang Y, Ding J, Amjad A, Dang NP, Zarenia M, Conlin R, Li A. Organ Specific Deep Learning-Based Correction of Inaccurate Auto-Segmentation on Abdominal MRI. Int J Radiat Oncol Biol Phys 2023; 117:S118-S119. [PMID: 37784307 DOI: 10.1016/j.ijrobp.2023.06.453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Deep learning-based automatic segmentation (DLAS) techniques offer limited success for abdominal organs on MRI, requiring substantial editing time. We have previously developed a deep learning based automatic contour correction (ACC) technique that can correct for inaccurate DLAS contours of bowels on MRI, reducing the manual editing time in MR-guided online adaptive radiation therapy (MRgART). This study aims to develop deep learning-based ACC models for pancreas and duodenum that are particularly difficult to contour either manually or with DLAS. MATERIALS/METHODS Dense UNet, a deep learning algorithm that combines UNet with dense blocks, was trained to create ACC models. Organ-specific models were trained for pancreas and duodenum contours obtained from a research DLAS tool on MRIs from a 1.5T MR-Linac. The training dataset contained MRI slices paired with DLAS contours from 54 abdominal MRL sets along with ground truth contours and 540 additional augmented sets created by shifting, rotating, and scaling each organ along with the contours and varying the noise and bias field for each patient set. Each DLAS contour was classified into the acceptable (no additional edits required), minor edit (only simple edits required), or major edit category based on the expected editing effort determined using a contour classification model developed in a separate study. The ACC models were trained for the slices requiring minor edit and major edit separately. Performance of the obtained models were tested using an independent 11 MRI sets in term of the change of contour category based on the contour classification model. RESULTS After applying the duodenum ACC model to the testing datasets, 16% (27/165) and 5% (8/178) of the minor and major edits' slices, respectively, improved to acceptable and 31% (54/178) of the major edit slices improved to minor edits. Furthermore, the total percentage of acceptable contours grew from 10% (36/378) to 19% (71/378) and the percentage of the major edit slices reduced from 47% (178/378) to 30% (115/378). After applying the pancreas ACC model to the testing datasets, 32% (47/143) and 1% (1/96) of the minor and major edits' slices, respectively, improved to acceptable and 49% (47/96) of the major edit slices improved to minor edit slices. Furthermore, the total percentage of acceptable contours grew from 14% (38/277) to 31% (86/277) and the percentage of major edit slices reduced from 35% (96/277) to 17% (48/277). CONCLUSION Deep learning based automatic contour corrections can substantially improve inaccurate DLAS contours of pancreas and duodenum on MRI that would otherwise require time-consuming edits, resulting in less manual intervention and increased efficiency during MRgART.
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Affiliation(s)
- C Sarosiek
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - Y Zhang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - J Ding
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Amjad
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - N P Dang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - M Zarenia
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - R Conlin
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
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Shen Z, Brand D, Zhang Y, Simard M, Lopes A, Miles E, Gilbert A, West N, Blake A, Royle G, Appelt A, Maughan TS, Sebag-Montefiore D, Collins-Fekete CA, Hawkins MA. Modeling Acute Chemoradiotherapy (CRT) Diarrhea Severity Using Automatically Contoured Small Bowel. Int J Radiat Oncol Biol Phys 2023; 117:e338. [PMID: 37785184 DOI: 10.1016/j.ijrobp.2023.06.2397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Acute severe diarrhea is a common toxicity in rectal cancer patients receiving CRT. A better understanding of the radiation tolerance of the small bowel is needed especially for novel radiation drug combinations. We investigate the dose impact by providing auto-contoured small bowel, using data from the ARISTOTLE phase III trial ISRCTN: 09351447. MATERIALS/METHODS A subset of participants (n = 93/564) with locally advanced rectal cancer in the ARISTOTLE trial testing the addition of concurrent irinotecan (n = 48) to neoadjuvant capecitabine (n = 45) CRT (45/25 Gy/fx), in an MRI defined high risk of loco-regional failure. CRT was delivered with conformal techniques. Diarrhea was measured using CTCAE v4.0 weekly. We applied an AI-based auto-contouring model to segment the small bowel on planning CT. The small-bowel DVH parameters were combined with the treatment arm, age, sex and MRI-defined tumor stage in a linear regression (LR) model to predict acute diarrhea severity. Explainable Shapley values (conditional marginalized expectation of a machine learning model per feature) were used to quantify the independent and normalized impact of radiation dose vs Irinotecan on the likelihood of severe diarrhea. RESULTS The auto-contouring model accuracy was consistent with clinical practice (mean dice coefficient = 0.739) and clinically acceptable when reviewed by clinicians. The treatment arm, MRI-defined T stage and small-bowel mean dose were found to be independently correlated to the diarrhea severity (p<0.001). V30Gy showed the strongest correlation to diarrhea severity in all the DVH parameters. The LR using the three variables yielded mean AUC scores of 0.898 (95% CI: [0.831,0.958]) on predicting Grade 2 and higher diarrhea, and 0.774 (95% CI: [0.678,0.869]) on predicting Grade 3 diarrhea based on 10-fold cross-validation. Shapley values showed that V30Gy>30.56 cm3 increases the likelihood of more severe diarrhea against the average (grade = 1.03) in the cohort. The impact of irradiation will be larger than the usage of Irinotecan within the patients with V30Gy >160.93 cm3. CONCLUSION We accurately modelled acute diarrhea (AUC = 0.90) for rectal cancer patients receiving CRT using AI-contoured small-bowel structures. The treatment arm and small-bowel dose were independently correlated to the diarrhea severity. The explainable model allowed us to quantify the impact of radiation dose, usage of irinotecan, and its combination, with a threshold of V30Gy = 160.93 cm3 yielding an equivalent impact. We will be extending the analysis to the whole trial cohort to improve the statistical power.
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Affiliation(s)
- Z Shen
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - D Brand
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom; Department of Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Y Zhang
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - M Simard
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - A Lopes
- University College London, London, United Kingdom
| | - E Miles
- National Radiotherapy Trials QA Group, Mount Vernon Hospital, Northwood, United Kingdom
| | - A Gilbert
- University of Leeds, Leeds, United Kingdom
| | - N West
- University of Leeds, Leeds, United Kingdom
| | - A Blake
- MRC Oxford institute for Radiation Biology, Department of Oncology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - G Royle
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - A Appelt
- St. James's University Hospital, Leeds, United Kingdom
| | - T S Maughan
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
| | | | - C A Collins-Fekete
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - M A Hawkins
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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Zhang J, Shang S, Wang F, Wang R, Shangguan J, Zhang Y, Wu M, Ma J, Yu J, Chen D. The Baseline Serum Lipid Levels and Outcomes of NSCLC Patients Receiving Immunotherapy Combined or Non-Combined with Radiotherapy: A Single Center Retrospective Study. Int J Radiat Oncol Biol Phys 2023; 117:e11. [PMID: 37784645 DOI: 10.1016/j.ijrobp.2023.06.670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) In recent years, many studies have shown that lipids and lipid-like substances are key regulatory factors in tumor development and play an important role in immune regulation. However, it remains unclear whether serum lipids influence the outcome of immunotherapy. Therefore, determining the serum lipid levels of the immune treatment-beneficiary population may be valuable. The aim of this study is to evaluate the prognostic value of baseline serum lipid levels in non-small cell lung cancer (NSCLC) patients receiving immunotherapy. MATERIALS/METHODS We retrospectively included 294 patients with stage III-IV NSCLC who received immunotherapy continuously from December 2018 to November 2021 at our hospital, collecting their pre-treatment lipid levels, such as total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Of these, 160 receiving immunotherapy without combined radiotherapy (ICIs-nRT) and 134 combined with radiotherapy (iRT). The endpoint was the correlation between pre-treatment serum lipid levels and overall survival (OS), as well as progression-free survival (PFS). The X-tile tool was used to determine the optimal cut-off value of the indicators. The Kaplan-Meier survival curves were used to calculate OS and PFS and log rank tests were used for comparison. And the Cox proportional hazard model were used for univariate and multivariate analysis. RESULTS In all 294 patients, low TG, low TC, and low HDL-C predicted poor OS (P<0.001) and poor PFS (P<0.05). Low LDL-C was associated with poor OS (P = 0.0001). Among 160 patients receiving ICIs-nRT and 134 iRT patients, low levels of TG (P = 0.0134, 0.0024), TC (P = 0.0003, 0.0023), HDL-C (P = 0.0004, 0.0043), and LDL-C (P = 0.0003, 0.0419) were associated with worse OS compared to high levels of them. In the ICIs-nRT patients, low HDL-C predicted poor PFS (P = 0.0011). In 134 iRT patients, low levels of TG (P = 0.0017), TC (P = 0.0028), and LDL-C (P = 0.0330) were poor prognostic factors for PFS. In the univariate and multivariate analysis with OS in all patients, TG and HDL-C were independent risk factors, while TG was an independent risk factor in the analysis with PFS. In ICIs-nRT patients, HDL-C was an independent prognostic factor for patients' OS and PFS. In iRT patients, both TG and HDL-C were prognostic risk factors for OS. CONCLUSION These data confirm that higher serum lipid levels are associated with better outcomes in patients with NSCLC undergoing immunotherapy. Serum lipids may identify tumors that are more likely to respond to immunotherapy. Radiation therapy may affect lipid metabolism within the body to enhance the efficacy of immunotherapy.
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Affiliation(s)
- J Zhang
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - S Shang
- Shandong University Cancer Center, Jinan, Shandong, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - F Wang
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - R Wang
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - J Shangguan
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Y Zhang
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - M Wu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - J Ma
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China; Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - J Yu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - D Chen
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
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Zhang Y, Hu D, Li W, Zhang W, Chen RC, Chen Y, Gao H. 2V-CBCT: Two-Orthogonal-Projection Based CBCT Reconstruction and Dose Calculation from Real CBCT Projection Data. Int J Radiat Oncol Biol Phys 2023; 117:e748. [PMID: 37786167 DOI: 10.1016/j.ijrobp.2023.06.2289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Not all radiation therapy (RT) treatments/fractions have CBCT acquired, but two orthogonal projections (i.e., KV radiography) are always available. This work demonstrates the feasibility of two-orthogonal-projection-based CBCT (2V-CBCT) reconstruction and dose calculation for RT from real CBCT projection data, which is the first 2V-CBCT feasibility study using real projection data, to the best of our knowledge. MATERIALS/METHODS 2V-CBCT is a severely ill-posed inverse problem for which we propose a coarse-to-fine learning strategy. First, a 3D deep neural network that can extract and exploit the inter-slice and intra-slice information is adopted to predict the initial 3D volumes. Then, a 2D deep neural network is utilized to fine-tune the initial 3D volumes slice-by-slice. During the fine-tuning stage, a perceptual loss based on multi-frequency features is employed to enhance the image reconstruction. Dose calculation results from both photon and proton RT demonstrate that 2V-CBCT provides comparable accuracy with full-view CBCT based on real projection data. RESULTS The proposed method was evaluated on real HN data acquired from on-board CBCT scanners rather than the low-resolution simulated data or down-sampled data. Both visual assessment and quantitative analysis demonstrate that the proposed coarse-to-fine learning strategy has the potential to produce satisfactory volumetric images from two orthogonal projections. Furthermore, we assessed the utility of 2V-CBCT in RT. The results show that the dose distribution maps, dose-volume histograms, and dose parameters calculated using 2V-CBCT have comparable accuracy with the counterparts calculated using the corresponding full-view CBCT for both photon and proton RT. In the table, the methods under comparison are pCT (planning CT), FV-CBCT (CBCT reconstructed with full-view projection data), and 2V-CBCT (CBCT reconstructed with two orthogonal projections). CONCLUSION A new effective 2V-CBCT reconstruction method is proposed and validated using real CBCT projection data, which can potentially provide comparable dose calculation accuracy for both photon and proton RT.
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Affiliation(s)
- Y Zhang
- School of Computer Science and Engineering, Southeast University, Nanjing, China; Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - D Hu
- School of Computer Science and Engineering, Southeast University, Nanjing, China; Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - W Li
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - W Zhang
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - R C Chen
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
| | - Y Chen
- School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - H Gao
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, KS
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Zheng L, Zhang Y, Zhang Q, Wu DR, Shi LX. [A case of acromegaly complicated with Graves' disease]. Zhonghua Nei Ke Za Zhi 2023; 62:1227-1229. [PMID: 37766444 DOI: 10.3760/cma.j.cn112138-20230202-00051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Affiliation(s)
- L Zheng
- Department of Endocrinology and Metabolism, Guiqian International General Hospital, Guiyang 550018, China
| | - Y Zhang
- Department of Endocrinology and Metabolism, Guiqian International General Hospital, Guiyang 550018, China
| | - Q Zhang
- Department of Endocrinology and Metabolism, Guiqian International General Hospital, Guiyang 550018, China
| | - D R Wu
- Department of Endocrinology and Metabolism, Guiqian International General Hospital, Guiyang 550018, China
| | - L X Shi
- Department of Endocrinology and Metabolism, Guiqian International General Hospital, Guiyang 550018, China
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Hoke JC, Ippoliti M, Rosenberg E, Abanin D, Acharya R, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Eppens D, Erickson C, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Miao KC, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Mi X, Khemani V, Roushan P. Measurement-induced entanglement and teleportation on a noisy quantum processor. Nature 2023; 622:481-486. [PMID: 37853150 PMCID: PMC10584681 DOI: 10.1038/s41586-023-06505-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/01/2023] [Indexed: 10/20/2023]
Abstract
Measurement has a special role in quantum theory1: by collapsing the wavefunction, it can enable phenomena such as teleportation2 and thereby alter the 'arrow of time' that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time3-10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium11-13. For present-day noisy intermediate-scale quantum (NISQ) processors14, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping9,15-17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling3,4 to measurement-induced teleportation18. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.
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Jia W, Li Q, Ni J, Zhang Y, Wu L, Xu L. Efficacy and safety of methylene blue injection for intractable idiopathic pruritus ani: a single-arm metaanalysis and systematic review. Tech Coloproctol 2023; 27:813-825. [PMID: 37306793 DOI: 10.1007/s10151-023-02825-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 05/15/2023] [Indexed: 06/13/2023]
Abstract
PURPOSE To evaluate how effective methylene blue injection was at treating intractable idiopathic pruritus ani. METHODS A comprehensive literature search of the PubMed, Embase, Cochrane library, and Web of Science databases was conducted. All clinical studies (prospective and retrospective) that evaluated the efficacy of methylene blue in treating intractable idiopathic pruritus ani were included. Studies that reported the resolution rate, after a single injection and after a second injection, the recurrence rate, symptom scores, and transient complications of methylene blue injections in treating intractable idiopathic pruritus ani were included. RESULTS The seven selected studies included 225 patients with idiopathic pruritus ani. The resolution rates after a single injection and after a second injection was 0.761 (0.649-0.873, P < 0.01, I2 = 69.06%) and 0.854 (0.752-0.955, P < 0.01, I2 = 77.391%), respectively, the remission rates at 1, 3, and 5 years were 0.753 (0.612-0.893, P < 0.001), 0.773 (0.675-0.871, P < 0.001) and 0.240 (0.033-0.447, P < 0.001), respectively, the effect value of the merger was 0.569 (0.367-0.772, P < 0.001, I2 = 79.199%), and the recurrence rates at 1, 2, 3, and < 1 year were 0.202 (0.083-0.322, P < 0.001), 0.533 (0.285-0.781, P < 0.001), 0.437 (-0.044, 0.917, P < 0.001) and 0.067 (0.023-0.111, P < 0.001), respectively. The effect value of the merger was 0.223 (0.126-0.319, P < 0.001, I2 = 75.840). CONCLUSION Using methylene blue injections to treat intractable idiopathic pruritus ani is relatively efficacious, resulting in a relatively low recurrence rate and no severe complications. However, the available literature was of poor quality. Therefore, higher quality studies are necessary to confirm that methylene blue injection is efficacious for pruritus ani, such as a randomized prospective multicenter studies.
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Affiliation(s)
- W Jia
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, 310006, Zhejiang Province, China
| | - Q Li
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou, 310053, Zhejiang Province, China
| | - J Ni
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, 310006, Zhejiang Province, China
| | - Y Zhang
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, 310006, Zhejiang Province, China
| | - L Wu
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, 310006, Zhejiang Province, China
| | - L Xu
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, 310006, Zhejiang Province, China.
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Aliru ML, Zhang Y, Westover KD, Timmerman RD, Iyengar P. Could Poor Outcomes for Patients with Limited Lung Function Treated with SAbR Necessitate PULSAR? Int J Radiat Oncol Biol Phys 2023; 117:e1-e2. [PMID: 37784622 DOI: 10.1016/j.ijrobp.2023.06.650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Stereotactic ablative radiotherapy (SAbR) employs precise targeting and delivery of ablative radiation doses in patients with medically inoperable early-stage non-small cell lung cancer, as well as patients with pulmonary metastases. SAbR is well tolerated with few studies reporting a minimal decline in pulmonary function tests (PFTs). However, poor pulmonary function is considered a risk factor for radiation induced lung toxicity. Personalized Ultrafractionated Stereotactic Adaptive Radiotherapy (PULSAR) is an adaptive radiation therapy regimen where radiation pulses are delivered over longer periods of time, thereby allowing for modification of the treatment based on the patient's response, as well as limiting toxicities. As such, we hypothesize that treating patients with poor pulmonary function using a PULSAR approach is better tolerated in when compared to patients treated with SAbR. MATERIALS/METHODS We performed a retrospective review of our institutional database of patients treated with SAbR to lung lesions from 2005 to 2022. We assessed the overall survival in stage-matched patients with normal vs poor lung function who received SAbR (40 patients in each cohort). Patients with decreased lung function included those with a diagnosis of moderate/severe COPD, restrictive lung disease, or patients needing home oxygen at the time of treatment. We then analyzed PFTs changes for patients receiving SAbR, and evaluated these changes relative to treatment delivery. RESULTS Stage-matched Kaplan-Meier analysis of patients with normal vs poor lung function receiving SAbR revealed a statistically significant difference in survival with Log-rank test p = 0.007. Of the patients with PFTs, 45 (90%) received SAbR with two to three treatments weekly, while 5 (10%) were treated on a PULSAR regimen with one fraction every week to three weeks. No trends or significant differences are observed in the changes of total lung capacity (TLC), the first second of exhalation (FEV1), forced vital capacity (FVC) or FEV1/FVC ratios. However, we did note variations in the diffusing capacity of the lung for carbon monoxide (DLCO). The mean difference in DLCO for the SAbR and PULSAR groups were -26.07% (95% CI: -31.28 to -20.87, p < 0.0001), and -10.52% (95% CI: -40.74 to 19.69, p = 0.388), respectively. CONCLUSION We observed a significant difference in overall survival between patients with normal vs poor lung function receiving SAbR. In a preliminary analysis, we discovered a small decline in DLCO for patients treated with regularly scheduled SAbR treatments. In the patients treated on the PULSAR regimen, however, this change in DLCO is not statistically significant. While this data suggests that increasing the time frame between individual doses of radiation may result in better toleration of radiotherapy in this patient population, the sample size of patients treated via PULSAR is limited, and longer follow-up is needed to further evaluate the potential benefits.
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Affiliation(s)
- M L Aliru
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - K D Westover
- University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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Guo Q, Song Y, Cheng K, Zhu Z, Zhang Y, Yue J. Impact of FAPI-PET/CT on Target Volume Definition in Radiation Therapy of Locally Advanced Biliary Tract Cancer: Compared with MRI/CT. Int J Radiat Oncol Biol Phys 2023; 117:e355. [PMID: 37785225 DOI: 10.1016/j.ijrobp.2023.06.2435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) A new radioactive positron emission tomography (PET) tracer uses inhibitors of fibroblast activation protein (FAPI) to visualize FAP-expressing cancer associated fibroblasts. Significant FAPI-uptake has recently been demonstrated in biliary tract cancer (BTC) patients. Target volume delineation for radiation therapy still relies on often less precise conventional magnetic resonance imaging (MRI) registered with computed tomography (CT) imaging, especially in locally advanced BTC patients. The need for improvement in precise tumor detection and delineation led us to innovatively use the novel FAPI-PET/CT for radiation treatment planning. MATERIALS/METHODS Gross tumor volumes (GTVs) of five locally advanced BTC cases were contoured under FAPI-PET/CT method. MRI/CT was used to delineate tumors additionally. The differentiation in target definition was analyzed between FAPI-PET/CT-based GTVs and the manually MRI/CT-based GTVs. RESULTS Target definition differed significantly between different imaging methods with mean dice similarity coefficients of 0.5527, mean Jaccard similarity coefficients of 0.4296 and mean volumetric overlap difference of 0.5704, while the mean volumes and standard deviations of GTVs were 18.12±15.10 cm3 and 38.44±24.72 cm3, based on FAPI-PET/CT and MRI/CT respectively (P = 0.102). There was a discordance and difference between the volumes of FAPI-GTVs-based GTVs and the manually contoured GTVs based on MRI/CT. CONCLUSION Due to its high tumor to background contrast, FAPI-PET/CT seems to be a superior imaging modality compared to the current gold standard MRI/CT in BTC. For the first time, we demonstrate how FAPI-PET/CT could facilitate target definition and increases accuracy in radiation oncology in BTC. Limited to the sample size, we still need more large-scale data to support this view.
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Affiliation(s)
- Q Guo
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Y Song
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China; Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - K Cheng
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China; Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Z Zhu
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China; Weifang Medical University, Weifang, Shandong, China
| | - Y Zhang
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - J Yue
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
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Parikh SB, Zhang Y, Vergalasova I, Jabbour SK, Ohri N, Sherwani Z, Jan I, Hathout L. Impact of the COVID-19 Pandemic on Brachytherapy and Cancer Patient Outcomes: A Systematic Review. Int J Radiat Oncol Biol Phys 2023; 117:e612. [PMID: 37785842 DOI: 10.1016/j.ijrobp.2023.06.1987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To assess the impact of the COVID-19 pandemic on the use of brachytherapy as a treatment modality in patients with gynecologic and prostate cancers including treatment delays, increased burden of mortality and associated clinical outcomes. MATERIALS/METHODS A comprehensive search of PubMed, Cochrane Library, CINAHL, Scopus, and Web of Science was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Databases were searched for studies published through January 2023 using MeSH terms and keywords related to "COVID and brachytherapy". Inclusion criteria included all studies reporting on the impact of COVID-19 on treatment delay, treatment omission, recurrence rates and clinical outcomes in patients requiring brachytherapy for prostate or gynecologic cancers. Data were extracted from two pairs of independent reviewers. RESULTS Of the 292 screened records, 8 retrospective studies met the eligibility criteria and were selected. A total of 15,879 patients were included, of which 829 brachytherapy patients were identified. An Italian study reported an increase in the use of adjuvant radiation therapy (RT) in patients with uterine cancers during the lockdown period while the use of vaginal cuff brachytherapy remained stable. Hypofractionated regimens were the preferred approach in RT centers worldwide. Intracavitary brachytherapy for cervical cancer was limited to 3-4 fractions to limit personnel and patient exposure. RT treatment delay was the most common COVID-related care change ranging between 19% and 53% followed by treatment omission (2-28%). Causes of treatment delays and omissions were multifactorial: patient fear, COVID-19 infection, barriers to accessing care and operating room closures. Two studies reported modified brachytherapy approaches using single-application (SA) rather than multiple applications (MA) approaches with excellent local control, shorter overall treatment time, but at the expense of increased grade ≥2 vaginal, genitourinary and gastrointestinal events. For cervical cancer patients, overall treatment time (OTT) was significantly impacted by COVID-19 as reported by 2 studies from India. OTT >60 days occurred in 40-53% of patients with COVID-19 infection being the main cause of treatment delays of up to 3 weeks. CONCLUSION This is the first systematic review to assess the impact of the COVID-19 pandemic on brachytherapy in patients with gynecologic and prostate cancers. Although many expert consensus recommendations have been published during the pandemic regarding radiation therapy, few studies evaluated its clinical impact on brachytherapy delivery and patient outcomes. The impact of the pandemic on gynecologic and prostate cancers is yet to be determined as well as the long-term outcomes on patients treated during the lockdown period.
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Affiliation(s)
- S B Parikh
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
| | - Y Zhang
- Rutgers, The State University of New Jersey, New Brunswick, NJ
| | - I Vergalasova
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
| | - S K Jabbour
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
| | - N Ohri
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
| | - Z Sherwani
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
| | - I Jan
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
| | - L Hathout
- Rutgers Cancer Institute of New Jersey, Department of Radiation Oncology, New Brunswick, NJ
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Clark CA, Zhang Z, Zhang Y, Xing C, Larimer B, Yang ES. Tumor Cell-Intrinsic PD-L1 Effects on Radiation-Induced Locoregional Antitumor Immunity. Int J Radiat Oncol Biol Phys 2023; 117:e224. [PMID: 37784910 DOI: 10.1016/j.ijrobp.2023.06.1130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Targeting PD-L1 is a beneficial strategy to reinvigorate antitumor immunity, however variable response and resistance are challenging and suggest the need for multimodality approaches. Tumor cell-intrinsic PD-L1 signals also regulate non-canonical pathogenic pathways that may impact treatment resistance. Ionizing radiation (IR) can induce antitumor immunity and has demonstrated therapeutic synergy with immunotherapy in some cases, however tumor-driven immunologic mechanisms affecting clinical outcomes remain incompletely understood. In this study, we investigated the impact of tumor cell-intrinsic PD-L1 signals on IR-induced locoregional immune response and tumor control. MATERIALS/METHODS We used orthotopic B16-F10 melanoma (WT-B16) and 4T1 triple negative breast cancer (WT-4T1) murine tumor models, as well as PD-L1 disabled variants (KO) generated by CRISPR/Cas9, implanted bilaterally. IR (10 Gy) was targeted at one tumor alone to evaluate both direct and indirect IR effects based on tumor PD-L1 status. We evaluated response by tumor volume (TV) measurements, flow cytometry of tumor-infiltrating lymphocytes (TILs) and tumor draining lymph nodes (TDLNs) in both irradiated and unirradiated compartments, and granzyme B (GZB) PET imaging to assess functional in vivo changes. Chemokine-based multiplex assays were used to assess cell lines receiving IR (4Gy) and ex vivo tumor lysates and serum. RESULTS IR-induced local tumor control was not significantly affected based on tumor PD-L1 status, however deactivation of tumor cell PD-L1 enhanced IR-induced regional tumor control. Unirradiated WT tumors in mice harboring irradiated KO but not irradiated WT tumors demonstrated a significant mean reduction in TV with instances of complete distant tumor regression. PET imaging demonstrated a nearly 2-fold higher concentration of GZB in KO versus WT tumors, in line with known locally immunosuppressive effects of tumor PD-L1. Remarkably, GZB levels were >1.5-fold higher in unirradiated WT tumors in mice harboring an irradiated KO versus WT tumor, which correlated with a 50% increase in PD-1+CD8+ T cells. Higher levels of CD62+CD44- naïve CD4+ (4-fold) and CD8+ (2-fold) memory T cells were seen in TDLNs of irradiated KO versus WT tumors. Cytokine levels positively correlated with immune recruitment and activation status, as CXCL10, CCL2 and CCL5 were significantly upregulated in PD-L1 KO versus WT tumors cells. CONCLUSION Results from this study demonstrate cell-intrinsic PD-L1 inhibits IR-induced locoregional immune activation and frequency of regional tumor control, with clinical implications including therapeutic targeting of tumor cell-intrinsic PD-L1 signals to enhance IR-induced immunogenicity, utility of IR based on tumor PD-L1 status particularly in the metastatic setting, and immunotherapy combinations. Future studies investigating mechanisms of resistance to IR-induced immune activation to enhance responsiveness are warranted.
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Affiliation(s)
- C A Clark
- UAB Hazelrig Salter Radiation Oncology Center, Birmingham, AL
| | | | - Y Zhang
- University of Alabama at Birmingham, Birmingham, AL
| | - C Xing
- University of Alabama at Birmingham, Birmingham, AL
| | - B Larimer
- University of Alabama at Birmingham, Birmingham, AL
| | - E S Yang
- University of Alabama at Birmingham, Birmingham, AL
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Liu Q, Lun L, Meng S, Wang Z, Qu Y, Huang X, Chen X, Wang J, Zhang J, Wang K, Wu R, Zhang Y, Yi J, Luo J. Feasibility of Omitting Contralateral Neck Irradiation in Patients with Node-Negative Sinonasal Squamous Cell Carcinoma Crossing the Midline. Int J Radiat Oncol Biol Phys 2023; 117:e600. [PMID: 37785813 DOI: 10.1016/j.ijrobp.2023.06.1961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) This study aims to analyze the nodal target volume in patients with node-negative SNSCC crossing the midline. MATERIALS/METHODS One hundred and four patients with node-negative advanced sinonasal squamous cell carcinoma (SNSCC) crossing the midline were included. Survival rates were estimated and compared between treatment groups. RESULTS Sixty-four patients received contralateral ENI (contralateral ENI group), while forty patients did not (non-contralateral ENI group). The median follow-up time was 89.99 and 95.01 months in the contralateral and non-contralateral ENI groups, respectively. At 5 years, the regional relapse-free survival and contralateral regional relapse-free survival were 57.68% vs. 55.83% (p = 0.372), and 57.68% vs. 61.62% (p = 0.541), in contralateral ENI group vs. non-contralateral ENI group, respectively. Five-year overall survival, local relapse-free survival, and distant metastasis-free survival were similar in the two groups (all p > 0.05). CONCLUSION In patients with node-negative SNSCC crossing the midline, omission of contralateral ENI did not affect regional control and survival outcomes on the premise of receiving ipsilateral ENI covering at least levels Ib and II.
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Affiliation(s)
- Q Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - L Lun
- Department of Head and Neck Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, China
| | - S Meng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Z Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Qu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Huang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Zhang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - K Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - R Wu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Zhang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Yi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Luo
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Yang X, An J, Zhang Y, Yang Y, Jia S, Li W, Huang M, Wu L. The Value of Progression-Free Survival at Three Years as a Primary Endpoint for Studies on Radiotherapy in Patients with Locally Advanced Cervical Cancer: Individual Patient Data and Validation From 27 Randomized Trials. Int J Radiat Oncol Biol Phys 2023; 117:e556-e557. [PMID: 37785708 DOI: 10.1016/j.ijrobp.2023.06.1869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) A traditional endpoint for locally advanced cervical cancer (LACC) clinical trials is overall survival (OS) with five years of follow-up. At present, many clinical trials evaluating concurrent chemoradiotherapy combined with immunotherapy for LACC are underway in worldwide. The use of a shorter-term endpoint could significantly speed the translation of research findings into practice. The primary hypothesis was that PFS with three years of follow-up (PFS36) is an appropriate primary endpoint to replace OS with five years of follow-up (5-year OS). MATERIALS/METHODS The primary hypothesis was developed from our individual data, was further investigated using phase III randomized controlled trials (RCTs), and then externally validated by phase II trials and retrospective studies up to 2022. Correlation analysis at the treatment-arm level was performed between 2-, 3-, 4-, and 5-year PFS rates and 5-year OS, using the Pearson correlation coefficient r in weighted linear regression, with weight equal to patient size. The MEDLINE, Embase, and PubMed databases, together with the Cochrane Central Register of Controlled Trials, were searched from January 1, 1999, to February 2, 2023. Articles eligible for inclusion contained complete survival data. RESULTS A total of 613 patients with histologically confirmed, FIGO 2009 stage IB-IVA cervical cancer who underwent radiotherapy at our institute from January 2010 to December 2013 were eligible. Individual patient data were pooled to explore the correlation between PFS and the OS trend. The recurrence rates for years 1 through 5 were 12.9%, 7.3%, 3%, 2.3%, and 1.8%, respectively. The median recurrence time was 13 months and the median time from recurrence to death was 12.2 months. Within all the recurrence, 47.3% of recurrences occurred during the first year, 71.4% in the first two years, and 85% in the first three years. Patients who did not achieve PFS36 had a 5-year OS rate of 30.3%. In contrast, a 5-year OS rate of 98.2% was observed in patients who achieved PFS36. Further data were extracted from 27 RCTs on locally advanced cervical cancer. The trials included 57 arms, with a pooled sample size of 7,692 patients. Formal measures of surrogacy were satisfied. Quality control was performed, where studies with a high risk of bias were excluded. In trial-level surrogacy, PFS36 (r2, 0.778) was associated with 5-year OS. The correlation between PFS36 and OS was externally validated using independent phase II trials and retrospective data. In total, 23 studies representing 5,174 patients were included. PFS36 (r2, 0.719) was found to be associated with OS. CONCLUSION The patients who achieved PFS36 had excellent outcomes, whereas patients that experienced earlier progression had poor survival. A significant correlation was found between PFS36 and 5-year OS in clinical trials on patients with locally advanced cervical cancer. These results suggest that PFS36 is an appropriate endpoint for LACC clinical trials of radiotherapy-based regimens.
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Affiliation(s)
- X Yang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J An
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Zhang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Yang
- Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors (Fujian Medical University), Fuzhou, China
| | - S Jia
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - W Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - M Huang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - L Wu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Zhu Z, Zhang X, Zhang Y, Hu X, Yue J. 18F-AlF-NOTA-FAPI-04 PET/CT can Predict Treatment Response and Survival in Patients with Inoperable Pancreatic Adenocarcinoma. Int J Radiat Oncol Biol Phys 2023; 117:e360. [PMID: 37785240 DOI: 10.1016/j.ijrobp.2023.06.2447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) We investigated whether uptake of 18F-AlF-NOTA-FAPI-04 on positron emission tomography/computed tomography (PET/CT) could predict treatment response and survival in patients with pancreatic adenocarcinoma (PAAD). MATERIALS/METHODS We prospectively evaluated 47 patients with histopathologically confirmed primary PAAD and pretreatment 18F-FAPI PET/CT scans to determine uptake of fibroblast activation protein (FAP) and compare the findings with those from blood tests and immunohistochemically stained tumor specimens. Cox regression and Kaplan-Meier methods were used to assess relationships between disease progression and potential predictors. Receiver operating characteristic (ROC) curve analysis was used to define the optimal cutoff points for distinguishing patients according to good response vs poor response per RECIST v. 1.1. RESULTS The FAPI PET variables maximum and mean standardized uptake values (SUVmax, SUVmean); metabolic tumor volume (MTV); and total lesion FAP expression (TLF) were positively correlated with cancer-associated fibroblast (CAF) markers (FAP, α-smooth muscle actin, vimentin, S100A4, and platelet-derived growth factor receptor α/β, all P<0.05). MTV and Log2TLF were associated with survival in patients with inoperable PAAD (all P<0.05). Analyses controlling for sex, age, cTNM, and performance status showed that MTV and Log2TLF were associated with overall survival (MTV hazard ratio [HR] = 1.016, P = 0.016 and Log2TLF HR = 4.093, P = 0.003). ROC cutoff analysis indicated that elevated MTV and TLF were associated with poorer survival. Greater changes from before to after chemotherapy in SUVmax, MTV, and TLF were associated with good treatment response (all P<0.05). ΔMTV, ΔTLF and ΔSUVmax had larger areas under the curve than ΔCA19-9 for predicting treatment response. Kaplan-Meier analysis showed that the extent of change in MTV and TLF from before to after treatment predicted progression-free survival, with cutoff values (based on medians) of -4.95 for ΔMTV (HR = 8.09, P = 0.013) and -77.83 for ΔTLF (HR = 4.62, P = 0.012). CONCLUSION Higher baseline MTV on 18F-FAPI-04 PET/CT scans was associated with poorer survival in patients with inoperable PAAD. ΔMTV was more sensitive for predicting response than ΔCA19-9. These results are clinically meaningful for identifying patients with PAAD who are at high risk of disease progression.
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Affiliation(s)
- Z Zhu
- Weifang Medical University, Weifang, Shandong, China
| | - X Zhang
- Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Y Zhang
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - X Hu
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - J Yue
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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