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Xu HF, Wang H, Liu Y, Wang XY, Guo XL, Liu HW, Kang RH, Chen Q, Liu SZ, Guo LW, Zheng LY, Qiao YL, Zhang SK. Baseline Performance of Ultrasound-Based Strategies in Breast Cancer Screening Among Chinese Women. Acad Radiol 2024:S1076-6332(24)00461-6. [PMID: 39174359 DOI: 10.1016/j.acra.2024.07.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 06/26/2024] [Accepted: 07/16/2024] [Indexed: 08/24/2024]
Abstract
RATIONALE AND OBJECTIVE There is a notable absence of robust evidence on the efficacy of ultrasound-based breast cancer screening strategies, particularly in populations with a high prevalence of dense breasts. Our study addresses this gap by evaluating the effectiveness of such strategies in Chinese women, thereby enriching the evidence base for identifying the most efficacious screening approaches for women with dense breast tissue. METHODS Conducted from October 2018 to August 2022 in Central China, this prospective cohort study enrolled 8996 women aged 35-64 years, divided into two age groups (35-44 and 45-64 years). Participants were screened for breast cancer using hand-held ultrasound (HHUS) and automated breast ultrasound system (ABUS), with the older age group also receiving full-field digital mammography (FFDM). The Breast Imaging Reporting and Data System (BI-RADS) was employed for image interpretation, with abnormal results indicated by BI-RADS 4/5, necessitating a biopsy; BI-RADS 3 required follow-up within 6-12 months by primary screening strategies; and BI-RADS 1/2 were classified as negative. RESULTS Among the screened women, 29 cases of breast cancer were identified, with 4 (1.3‰) in the 35-44 years age group and 25 (4.2‰) in the 45-64 years age group. In the younger age group, HHUS and ABUS performed equally well, with no significant difference in their AUC values (0.8678 vs. 0.8679, P > 0.05). For the older age group, ABUS as a standalone strategy (AUC 0.9935) and both supplemental screening methods (HHUS with FFDM, AUC 0.9920; ABUS with FFDM, AUC 0.9928) outperformed FFDM alone (AUC 0.8983, P < 0.05). However, there was no significant difference between HHUS alone and FFDM alone (AUC 0.9529 vs. 0.8983, P > 0.05). CONCLUSION The findings indicate that both HHUS and ABUS exhibit strong performance as independent breast cancer screening strategies, with ABUS demonstrating superior potential. However, the integration of FFDM with these ultrasound techniques did not confer a substantial improvement in the overall effectiveness of the screening process.
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Affiliation(s)
- Hui-Fang Xu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Hong Wang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Yin Liu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Xiao-Yang Wang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Xiao-Li Guo
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Hong-Wei Liu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Rui-Hua Kang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Qiong Chen
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Shu-Zheng Liu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Lan-Wei Guo
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - Li-Yang Zheng
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.)
| | - You-Lin Qiao
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.); Center for Global Health, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China (Y.L.Q.)
| | - Shao-Kai Zhang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China (H.F.X., H.W., Y.L., X.Y.W., X.L.G., H.W.L., R.H.K., Q.C., S.Z.L., L.W.G., L.Y.Z., Y.L.Q., S.K.Z.).
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Song X, Xu H, Wang X, Liu W, Leng X, Hu Y, Luo Z, Chen Y, Dong C, Ma B. Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk of postoperative recurrence in breast cancer. BMC Womens Health 2024; 24:380. [PMID: 38956552 PMCID: PMC11218367 DOI: 10.1186/s12905-024-03231-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 06/25/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer. METHODS A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves. RESULTS In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability. CONCLUSION The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.
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Affiliation(s)
- Xinyu Song
- Department of Breast and Thyroid Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, No. 789 of Suzhou Street, Xinshi District, Urumqi, 830000, China
| | - Haoyi Xu
- Department of Breast and Thyroid Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, No. 789 of Suzhou Street, Xinshi District, Urumqi, 830000, China
| | - Xiaoli Wang
- Department of Breast and Thyroid Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, No. 789 of Suzhou Street, Xinshi District, Urumqi, 830000, China
| | - Wen Liu
- Department of Artificial Intelligence and Smart Mining Engineering Technology Center, Xinjiang Institute of Engineering, Urumqi, 830023, China
| | - Xiaoling Leng
- Department of Ultrasound, The Tenth Affiliated Hospital of Southern Medical University, Dongguan, 523000, China
| | - Yue Hu
- Department of Breast Cancer Center Diagnosis Specialist, Sun Yat-sen Memorial Hospital, Guangzhou, 510120, China
| | - Zhimin Luo
- Department of General Surgery, Tori County People's Hospital, Tuoli, 834500, China
| | - Yanyan Chen
- Department of Breast and Thyroid Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, No. 789 of Suzhou Street, Xinshi District, Urumqi, 830000, China
| | - Chao Dong
- Department of Breast and Thyroid Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, No. 789 of Suzhou Street, Xinshi District, Urumqi, 830000, China.
| | - Binlin Ma
- Department of Breast and Thyroid Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, No. 789 of Suzhou Street, Xinshi District, Urumqi, 830000, China.
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Bai S, Song D, Chen M, Lai X, Xu J, Dong F. The association between mammographic density and breast cancer risk in Chinese women: a systematic review and meta-analysis. BMC Womens Health 2024; 24:131. [PMID: 38378562 PMCID: PMC10877813 DOI: 10.1186/s12905-024-02960-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 02/08/2024] [Indexed: 02/22/2024] Open
Abstract
PURPOSE Breast density has consistently been shown to be an independent risk factor for breast cancer in Western populations; however, few studies have evaluated this topic in Chinese women and there is not yet a unified view. This study investigated the association between mammographic density (MD) and breast cancer risk in Chinese women. METHODS The PubMed, Cochrane Library, Embase, and Wanfang databases were systematically searched in June 2023 to include all studies on the association between MD and breast cancer risk in Chinese women. A total of 13,977 breast cancer cases from 14 studies were chosen, including 10 case-control/cross-sectional studies, and 4 case-only studies. For case-control/cross-sectional studies, the odds ratios (ORs) of MD were combined using random effects models, and for case-only studies, relative odds ratios (RORs) were combinations of premenopausal versus postmenopausal breast cancer cases. RESULTS Women with BI-RADS density category II-IV in case-control/cross-sectional studies had a 0.93-fold (95% confidence interval [CI] 0.55, 1.57), 1.08-fold (95% CI 0.40, 2.94), and 1.24-fold (95% CI 0.42, 3.69) higher risk compared to women with the lowest density category. Combined RORs for premenopausal versus postmenopausal women in case-only studies were 3.84 (95% CI 2.92, 5.05), 22.65 (95% CI 7.21, 71.13), and 42.06 (95% CI 4.22, 419.52), respectively, for BI-RADS density category II-IV versus I. CONCLUSIONS For Chinese women, breast cancer risk is weakly associated with MD; however, breast cancer risk is more strongly correlated with mammographic density in premenopausal women than postmenopausal women. Further research on the factors influencing MD in premenopausal women may provide meaningful insights into breast cancer prevention in China.
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Affiliation(s)
- Song Bai
- Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, 518020, China
| | - Di Song
- Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, 518020, China
| | - Ming Chen
- Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, 518020, China
| | - Xiaoshu Lai
- Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, 518020, China
| | - Jinfeng Xu
- Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, 518020, China.
| | - Fajin Dong
- Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, 518020, China.
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Getz KR, Adedokun B, Xu S, Toriola AT. Breastfeeding and Mammographic Breast Density: A Cross-sectional Study. Cancer Prev Res (Phila) 2023; 16:353-361. [PMID: 36930943 PMCID: PMC10239347 DOI: 10.1158/1940-6207.capr-22-0482] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/23/2023] [Accepted: 03/14/2023] [Indexed: 03/19/2023]
Abstract
Breastfeeding is inversely associated with breast cancer risk but the associations of breastfeeding with mammographic breast density (MBD) are not clear. We investigated the association between breastfeeding and volumetric measures of MBD [volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV)] and evaluated whether it differs by race, menopausal status, and body mass index (BMI). The study population was comprised of 964 women (67% non-Hispanic White, 29% non-Hispanic Black) who had screening mammography at Washington University School of Medicine, St. Louis, MO. VPD, DV and NDV were log10 transformed. We performed multivariable linear regression models adjusted for age, BMI, family history of breast cancer, race, and age at menarche among all participants and exclusively in parous women. Mean age was 50.7 years. VPD was 12% lower among women who breastfed 0-6 months, [10β = 0.88, 95% confidence interval (CI; 0.79-0.98)] compared with nulliparous women. Breastfeeding was not associated with VPD among women who breastfed >7 months. Breastfeeding was inversely associated with DV [parous never breastfed: 10β = 0.93; 95% CI (0.83-1.04), breastfed 0-6 months: 10β = 0.91, 95% CI (0.79-1.05), breastfed 7-12 months: 10β = 0.94; 95% CI (0.81-1.10), breastfed >12 months: 10β = 0.87, 95% CI (0.78-0.98), Ptrend = 0.03]. BMI modified the association between breastfeeding and VPD. Women who breastfed for 0-6 months and had a BMI < 25 kg/m2 had lower VPD compared with nulliparous women, but among women with a BMI ≥ 25 kg/m2 there was no association (Pinteraction = 0.04). In this diverse study population, the association of breastfeeding with VPD appears to be modified by BMI, but not by race or menopausal status. Future research exploring the associations of breastfeeding with other mammographic features are needed. PREVENTION RELEVANCE Breastfeeding for up to 6 months may be associated with lower VPD among women with a BMI < 25 kg/m2. The potential role of MBD in mediating the associations of breastfeeding with breast cancer risk in a select group of women deserves further evaluation. See related Spotlight, p. 309.
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Affiliation(s)
- Kayla R. Getz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Babatunde Adedokun
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Shuai Xu
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Adetunji T. Toriola
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
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Trieu PD(Y, Mello-Thoms CR, Barron ML, Lewis SJ. Look how far we have come: BREAST cancer detection education on the international stage. Front Oncol 2023; 12:1023714. [PMID: 36686760 PMCID: PMC9846523 DOI: 10.3389/fonc.2022.1023714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 12/05/2022] [Indexed: 01/06/2023] Open
Abstract
The development of screening mammography over 30 years has remarkedly reduced breast cancer-associated mortality by 20%-30% through detection of small cancer lesions at early stages. Yet breast screening programmes may function differently in each nation depending on the incidence rate, national legislation, local health infrastructure and training opportunities including feedback on performance. Mammography has been the frontline breast cancer screening tool for several decades; however, it is estimated that there are 15% to 35% of cancers missed on screening which are owing to perceptual and decision-making errors by radiologists and other readers. Furthermore, mammography screening is not available in all countries and the increased speed in the number of new breast cancer cases among less developed countries exceeds that of the developed world in recent decades. Studies conducted through the BreastScreen Reader Assessment Strategy (BREAST) training tools for breast screening readers have documented benchmarking and significant variation in diagnostic performances in screening mammogram test sets in different countries. The performance of the radiologists from less well-established breast screening countries such as China, Mongolia and Vietnam were significant lower in detecting early-stage cancers than radiologists from developed countries such as Australia, USA, Singapore, Italy. Differences in breast features and cancer presentations, discrepancies in the level of experiences in reading screening mammograms, the availability of high-quality national breast screening program and breast image interpretation training courses between developed and less developed countries are likely to have impact on the variation of readers' performances. Hence dedicated education training programs with the ability to tailor to different reader cohorts and different population presentations are suggested to ameliorate challenges in exposure to a range of cancer cases and improve the interpretation skills of local radiologists. Findings from this review provide a good understanding of the radiologist' performances and their improvement using the education interventions, primarily the BREAST program, which has been deployed in a large range of developing and developed countries in the last decade. Self-testing and immediate feedback loops have been shown to have important implications for benchmarking and improving the diagnostic accuracy in radiology worldwide for better breast cancer control.
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Affiliation(s)
- Phuong Dung (Yun) Trieu
- Discipline of Medical Imaging Sciences, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Claudia R. Mello-Thoms
- Discipline of Medical Imaging Sciences, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - Melissa L. Barron
- Discipline of Medical Imaging Sciences, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Sarah J. Lewis
- Discipline of Medical Imaging Sciences, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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