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Chakrabarty N, Mahajan A, Basu S, D’Cruz AK. Comprehensive Review of the Imaging Recommendations for Diagnosis, Staging, and Management of Thyroid Carcinoma. J Clin Med 2024; 13:2904. [PMID: 38792444 PMCID: PMC11122658 DOI: 10.3390/jcm13102904] [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: 04/18/2024] [Revised: 05/01/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
Thyroid cancer is the most common head and neck cancer (HNC) in the world. In this article, we comprehensively cover baseline, posttreatment, and follow-up imaging recommendations for thyroid carcinomas along with the eighth edition of the tumor, node, metastasis (TNM) staging system proposed by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). We include characterization and risk stratification of thyroid nodules on ultrasound (US) proposed by various international bodies. Management guidelines (depending upon the type of thyroid carcinoma) based on the international consensus recommendations (mainly by the American Thyroid Association) are also extensively covered in this article, including the role of a radioiodine scan. The management of recurrent disease is also briefly elucidated in this article. In addition, we cover the risk factors and etiopathogenesis of thyroid carcinoma along with the non-imaging diagnostic workup essential for thyroid carcinoma management, including the significance of genetic mutations. US is the diagnostic imaging modality of choice, with US-guided fine needle aspiration (FNA) being the procedure of choice for tissue diagnosis. The roles of computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography/CT (FDG-PET/CT) in thyroid carcinoma staging are also specified. Through this article, we aim to provide a comprehensive reference guide for the radiologists and the clinicians in the pursuit of optimal care for patients with thyroid carcinoma.
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Affiliation(s)
- Nivedita Chakrabarty
- Department of Radiodiagnosis, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Homi Bhabha National Institute (HBNI), Parel, Mumbai 400012, Maharashtra, India;
| | - Abhishek Mahajan
- Department of Imaging, The Clatterbridge Cancer Centre NHS Foundation Trust, 65 Pembroke Place, Liverpool L7 8YA, UK
- Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 3BX, UK
| | - Sandip Basu
- Radiation Medicine Centre, Bhabha Atomic Research Centre, Tata Memorial Hospital Annexe, Homi Bhabha National Institute (HBNI), Parel, Mumbai 400012, Maharashtra, India;
| | - Anil K. D’Cruz
- Apollo Hospitals, Navi Mumbai 400614, Maharashtra, India;
- Foundation of Head Neck Oncology, Mumbai 400012, Maharashtra, India
- Union International Cancer Control (UICC), 1202 Geneva, Switzerland
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Bai G, Chen X, Peng Y, Ji Y, Bie F, Liu Y, Yang Z, Gao S. Surgery challenges and postoperative complications of lung cancer after neoadjuvant immunotherapy. Thorac Cancer 2024; 15:1138-1148. [PMID: 38572774 DOI: 10.1111/1759-7714.15297] [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: 02/16/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND In China, real-world data on surgical challenges and postoperative complications after neoadjuvant immunotherapy of lung cancer are limited. METHODS Patients were retrospectively enrolled from January 2018 to January 2023, and their clinical and pathological characters were subsequently analyzed. Surgical difficulty was categorized into a binary classification according to surgical duration: challenging or routine. Postoperative complications were graded using Clavien-Dindo grades. Logistic regression was used to identify risk factors affecting the duration of surgery and postoperative complications greater than Clavien-Dindo grade 2. RESULTS In total, 261 patients were included. Of these, stage III patients accounted for 62.5% (163/261) at initial diagnosis, with 25.3% (66/261) at stage IIIB. Central-type non-small-cell lung cancer accounted for 61.7% (161/261). One hundred and forty patients underwent video-assisted thoracoscopic surgery and lobectomy accounted for 53.3% (139/261) of patients. Surgical time over average duration was defined as challenging surgeries, accounting for 43.7%. The postoperative complications rate of 261 patients was only 22.2%. Smoking history (odds ratio [OR] = 9.96, 95% [CI] 1.15-86.01, p = 0.03), chemoimmunotherapy (OR = 2.89, 95% CI 1.22-6.86, p = 0.02), and conversion to open surgery (OR = 11.3, 95% CI 1.38-92.9, p = 0.02) were identified as independent risk factors for challenging surgeries, while pneumonectomy (OR = 0.36, 95% CI 0.15-0.86, p= 0.02) was a protective factor. Meanwhile, pneumonectomy (OR = 7.51, 95% CI 2.40-23.51, p < 0.01) and challenging surgeries (OR = 5.53, 95% CI 1.50-20.62, p = 0.01) were found to be risk factors for postoperative complications greater than Clavien-Dindo grade 2. CONCLUSIONS Compared to immunotherapy alone or in combination with apatinib, neoadjuvant chemoimmunotherapy could increase the difficulty of surgery while the incidence of postoperative complications remained acceptable. The conversion to open surgery and pneumonectomy after neoadjuvant immunotherapy should be reduced.
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Affiliation(s)
- Guangyu Bai
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaowei Chen
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yue Peng
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Ying Ji
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Fenglong Bie
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yang Liu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhenlin Yang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shugeng Gao
- Department of Thoracic Surgery, 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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Chen Z, Wang Z, Liu S, Zhang S, Zhou Y, Zhang R, Yang W. Nomograms based on multiparametric MRI radiomics integrated with clinical-radiological features for predicting the response to induction chemotherapy in nasopharyngeal carcinoma. Eur J Radiol 2024; 175:111438. [PMID: 38613869 DOI: 10.1016/j.ejrad.2024.111438] [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: 10/06/2023] [Revised: 01/27/2024] [Accepted: 03/20/2024] [Indexed: 04/15/2024]
Abstract
OBJECTIVE To establish nomograms integrating multiparametric MRI radiomics with clinical-radiological features to identify the responders and non-responders to induction chemotherapy (ICT) in nasopharyngeal carcinoma (NPC). METHODS We retrospectively analyzed the clinical and MRI data of 168 NPC patients between December 2015 and April 2022. We used 3D-Slicer to segment the regions of interest (ROIs) and the "Pyradiomic" package to extract radiomics features. We applied the least absolute shrinkage and selection operator regression to select radiomics features. We developed clinical-only, radiomics-only, and the combined clinical-radiomics nomograms using logistic regression analysis. The receiver operating characteristic curves, DeLong test, calibration, and decision curves were used to assess the discriminative performance of the models. The model was internally validated using 10-fold cross-validation. RESULTS A total of 14 optimal features were finally selected to develop a radiomic signature, with an AUC of 0.891 (95 % CI, 0.825-0.946) in the training cohort and 0.837 (95 % CI, 0.723-0.932) in the testing cohort. The nomogram based on the Rad-Score and clinical-radiological factors for evaluating tumor response to ICT yielded an AUC of 0.926 (95 % CI, 0.875-0.965) and 0.901 (95 % CI, 0.815-0.979) in the two cohorts, respectively. Decision curves demonstrated that the combined clinical-radiomics nomograms were clinically useful. CONCLUSION Nomograms integrating multiparametric MRI-based radiomics and clinical-radiological features could non-invasively discriminate ICT responders from non-responders in NPC patients.
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Affiliation(s)
- Zhiqiang Chen
- Department of Radiology, the First Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570102, China; Department of Radiology, the General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China.
| | - Zhuo Wang
- Department of Radiology, the General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China
| | - Shili Liu
- Department of Radiology, the General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China
| | - Shaoru Zhang
- Department of Radiology, the General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China
| | - Yunshu Zhou
- Department of Radiology, the General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China
| | - Ruodi Zhang
- Department of Radiology, the General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China
| | - Wenjun Yang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, School of Basic Medicine and Life Sciences, Hainan Medical University, Haikou, Hainan 571199, China.
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Gao D, Liu L, Liu J, Liu J. Predictive response and outcome of peripheral CD4 + T cell subpopulations to combined immunotherapy and chemotherapy in advanced gastric cancer patients. Int Immunopharmacol 2024; 129:111663. [PMID: 38364744 DOI: 10.1016/j.intimp.2024.111663] [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: 11/26/2023] [Revised: 01/26/2024] [Accepted: 02/05/2024] [Indexed: 02/18/2024]
Abstract
BACKGROUND The identification of predictive biomarkers for patient stratification in immunotherapy is of utmost importance, given the limited benefit observed in certain populations. However, only limited information is so far available on the association between peripheral CD4+ T cell subpopulations and immunotherapy for advanced gastric cancer. Our current report aimed to investigate the predictive value of peripheral CD4+ T cell subpopulations in advanced gastric cancer patients treated with immunotherapy. METHODS A retrospective cohort analysis of 169 advanced gastric cancer patients treated with sintilimab combined with capecitabine and oxaliplatin in The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University (Xinghua, China) between June 2019 and October 2022 was conducted. Clinical outcomes of peripheral CD4+ T cell subpopulations were analyzed by receiver operating characteristic (ROC) curve, chi-square test, Kaplan-Meier method and the univariate and multivariate Cox proportional hazards regression models. RESULTS The optimal cutoff values for percentages of CD4+ T cells, naive CD4+ T cells (CD4+ Tn), memory CD4+ T cells (CD4+ Tm), central memory CD4+ T cells (CD4+ Tcm) and effector memory CD4+ T cells (CD4+ Tem) expressing PD-1 were 30.16 %, 17.79 %, 42.49 %, 31.54 % and 74.64 %, respectively. It was found that the percentages of CD4+ T, CD4+ Tn, CD4+ Tm, CD4+ Tcm and CD4+ Tem expressing PD-1 were significantly higher in responder (R) than non-responder (NonR) advanced gastric cancer patients associated with a longer progression free survival (PFS) and overall survival (OS). This correlation was also observed in the PD-L1 combined positive score (CPS) ≥ 5 populations. Univariate and multivariate Cox regression analyses indicated that lower CD4+ T, CD4+ Tn, CD4+ Tm, CD4+ Tcm and CD4+ Tem expressing PD-1 were independent risk factors of PFS and OS in advanced gastric cancer patients treated with combined immunotherapy and chemotherapy. CONCLUSION The peripheral CD4+ T cell subpopulations demonstrated the high predictive value for therapeutic response and prolonged survival outcomes in advanced gastric cancer patients. CD4+ T cell subpopulations have the potential in predicting and screening benefit populations in advanced gastric cancer patients.
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Affiliation(s)
- Deyu Gao
- Department of Laboratory Medicine, Hefei BOE Hospital, Hefei, People's Republic of China
| | - Liqiong Liu
- Department of Oncology and Endocrinology, Xiangcheng Hospital of Traditional Chinese Medicine, Suzhou, People's Republic of China
| | - Jianhua Liu
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, Xinghua, Jiangsu, People's Republic of China
| | - Jiang Liu
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, Xinghua, Jiangsu, People's Republic of China.
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Liu J, Liu D, Hu G, Wang J, Chen D, Song C, Cai Y, Zhai C, Xu W. Circulating memory PD-1 +CD8 + T cells and PD-1 +CD8 +T/PD-1 +CD4 +T cell ratio predict response and outcome to immunotherapy in advanced gastric cancer patients. Cancer Cell Int 2023; 23:274. [PMID: 37974194 PMCID: PMC10655311 DOI: 10.1186/s12935-023-03137-9] [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: 06/15/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND Limited benefit population of immunotherapy makes it urgent to select effective biomarkers for screening appropriate treatment population. Herein, we have investigated the predictive values of circulating CD8+ T cells and CD8+T/CD4+T cell ratio in advanced gastric cancer patients receiving immunotherapy. METHODS A retrospective cohort analysis of 187 advanced gastric cancer patients receiving sintilimab combined with oxaliplatin and capecitabine therapy in The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University between December 2019 and February 2023 was conducted. The corresponding clinical outcomes of the variables were analyzed by receiver operating characteristic (ROC) curve, chi-square test, Kaplan-Meier methods and Cox proportional hazards regression models. RESULTS The optimal cutoff values for percentages of CD8+ T cells, naive CD8+ T cells (CD8+ Tn) and memory CD8+ T cells (CD8+ Tm) expressing programmed cell death -1(PD-1) as well as PD-1+CD8+T/PD-1+CD4+T cell ratio were 21.0, 21.5, 64.3 and 0.669, respectively. It was found that the mean percentages of CD8+ T and CD8+ Tm expressing PD-1 as well as PD-1+CD8+T/PD-1+CD4+T cell ratio were significantly higher in responder (R) than non-responder (NonR) advanced gastric cancer patients associated with a longer progression free survival (PFS) and overall survival (OS). We also observed this correlation in programmed cell death-ligand 1(PD-L1) combined positive score (CPS) ≥ 5 subgroups. Univariate and multivariate Cox regression analyses demonstrated that lower CD8+ T and CD8+ Tm expressing PD-1 as well as PD-1+CD8+T/PD-1+CD4+T cell ratio were independent risk factors in advanced gastric cancer patients receiving immunotherapy plus chemotherapy. CONCLUSION The circulating memory PD-1+CD8+ T cells and PD-1+CD8+T/PD-1+CD4+T cell ratio revealed high predictive values for response and prolonged survival outcomes in advanced gastric cancer patients receiving immunotherapy. Memory PD-1+CD8+ T cells and PD-1+CD8+T/PD-1+CD4+T cell ratio might be effective for screening benefit population of immunotherapy in advanced gastric cancer patients based on this preliminary evidence.
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Affiliation(s)
- Jiang Liu
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China.
| | - Degan Liu
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Guangyin Hu
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Jingjing Wang
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Dadong Chen
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Chuanjun Song
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Yin Cai
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Chentong Zhai
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China
| | - Wenjing Xu
- Department of Oncology, The Affiliated Xinghua People's Hospital, Medical School of Yangzhou University, 419 Ying Wu Nan Road, Xinghua, 225700, Jiangsu, People's Republic of China.
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Zhou J, Sun H, Wang Z, Cong W, Zeng M, Zhou W, Bie P, Liu L, Wen T, Kuang M, Han G, Yan Z, Wang M, Liu R, Lu L, Ren Z, Zeng Z, Liang P, Liang C, Chen M, Yan F, Wang W, Hou J, Ji Y, Yun J, Bai X, Cai D, Chen W, Chen Y, Cheng W, Cheng S, Dai C, Guo W, Guo Y, Hua B, Huang X, Jia W, Li Q, Li T, Li X, Li Y, Li Y, Liang J, Ling C, Liu T, Liu X, Lu S, Lv G, Mao Y, Meng Z, Peng T, Ren W, Shi H, Shi G, Shi M, Song T, Tao K, Wang J, Wang K, Wang L, Wang W, Wang X, Wang Z, Xiang B, Xing B, Xu J, Yang J, Yang J, Yang Y, Yang Y, Ye S, Yin Z, Zeng Y, Zhang B, Zhang B, Zhang L, Zhang S, Zhang T, Zhang Y, Zhao M, Zhao Y, Zheng H, Zhou L, Zhu J, Zhu K, Liu R, Shi Y, Xiao Y, Zhang L, Yang C, Wu Z, Dai Z, Chen M, Cai J, Wang W, Cai X, Li Q, Shen F, Qin S, Teng G, Dong J, Fan J. Guidelines for the Diagnosis and Treatment of Primary Liver Cancer (2022 Edition). Liver Cancer 2023; 12:405-444. [PMID: 37901768 PMCID: PMC10601883 DOI: 10.1159/000530495] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/24/2023] [Indexed: 10/31/2023] Open
Abstract
Background Primary liver cancer, of which around 75-85% is hepatocellular carcinoma in China, is the fourth most common malignancy and the second leading cause of tumor-related death, thereby posing a significant threat to the life and health of the Chinese people. Summary Since the publication of Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China in June 2017, which were updated by the National Health Commission in December 2019, additional high-quality evidence has emerged from researchers worldwide regarding the diagnosis, staging, and treatment of liver cancer, that requires the guidelines to be updated again. The new edition (2022 Edition) was written by more than 100 experts in the field of liver cancer in China, which not only reflects the real-world situation in China but also may reshape the nationwide diagnosis and treatment of liver cancer. Key Messages The new guideline aims to encourage the implementation of evidence-based practice and improve the national average 5-year survival rate for patients with liver cancer, as proposed in the "Health China 2030 Blueprint."
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Affiliation(s)
- Jian Zhou
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Huichuan Sun
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zheng Wang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wenming Cong
- Department of Pathology, The Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiping Zhou
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Ping Bie
- Institute of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Lianxin Liu
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tianfu Wen
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Ming Kuang
- Department of Hepatobiliary Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Guohong Han
- Department of Liver Diseases and Digestive Interventional Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Zhiping Yan
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Maoqiang Wang
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing, China
| | - Ruibao Liu
- Department of Interventional Radiology, The Tumor Hospital of Harbin Medical University, Harbin, China
| | - Ligong Lu
- Department of Interventional Oncology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhenggang Ren
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhaochong Zeng
- Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ping Liang
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Changhong Liang
- Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Min Chen
- Editorial Department of Chinese Journal of Digestive Surgery, Chongqing, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wenping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jinlin Hou
- Department of Infectious Diseases, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jingping Yun
- Department of Pathology, Tumor Prevention and Treatment Center, Sun Yat-sen University, Guangzhou, China
| | - Xueli Bai
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Dingfang Cai
- Department of Integrative Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weixia Chen
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yongjun Chen
- Department of Hematology, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenwu Cheng
- Department of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Shuqun Cheng
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Chaoliu Dai
- Department of Hepatobiliary and Spleenary Surgery, The Affiliated Shengjing Hospital, China Medical University, Shenyang, China
| | - Wengzhi Guo
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yabing Guo
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Baojin Hua
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xiaowu Huang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weidong Jia
- Department of Hepatic Surgery, Affiliated Provincial Hospital, Anhui Medical University, Hefei, China
| | - Qiu Li
- Department of Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Tao Li
- Department of General Surgery, Qilu Hospital, Shandong University, Jinan, China
| | - Xun Li
- The First Hospital of Lanzhou University, Lanzhou, China
| | - Yaming Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yexiong Li
- Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jun Liang
- Department of Oncology, Peking University International Hospital, Beijing, China
| | - Changquan Ling
- Changhai Hospital of Traditional Chinese Medicine, Second Military Medical University, Shanghai, China
| | - Tianshu Liu
- Department of Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xiufeng Liu
- Department of Medical Oncology, PLA Cancer Center, Nanjing Bayi Hospital, Nanjing, China
| | - Shichun Lu
- Institute and Hospital of Hepatobiliary Surgery of Chinese PLA, Chinese PLA Medical School, Chinese PLA General Hospital, Beijing, China
| | - Guoyue Lv
- Department of General Surgery, The First Hospital of Jilin University, Jilin, China
| | - Yilei Mao
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC and Chinese Academy of Medical Sciences, Beijing, China
| | - Zhiqiang Meng
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tao Peng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Weixin Ren
- Department of Interventional Radiology the First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Hongcheng Shi
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guoming Shi
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ming Shi
- Department of Hepatobiliary Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Tianqiang Song
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Kaishan Tao
- Department of Hepatobiliary Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Jianhua Wang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kui Wang
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Lu Wang
- Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Wentao Wang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaoying Wang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhiming Wang
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Bangde Xiang
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China
| | - Baocai Xing
- Department of Hepato-Pancreato-Biliary Surgery, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jianming Xu
- Department of Gastrointestinal Oncology, Affiliated Hospital Cancer Center, Academy of Military Medical Sciences, Beijing, China
| | - Jiamei Yang
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Jianyong Yang
- Department of Interventional Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yefa Yang
- Department of Hepatic Surgery and Interventional Radiology, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Yunke Yang
- Department of Integrative Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shenglong Ye
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhenyu Yin
- Department of Hepatobiliary Surgery, Zhongshan Hospital of Xiamen University, Xiamen, China
| | - Yong Zeng
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Bixiang Zhang
- Department of Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Boheng Zhang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Leida Zhang
- Department of Hepatobiliary Surgery Institute, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Shuijun Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, ZhengZhou, China
| | - Ti Zhang
- Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yanqiao Zhang
- Department of Gastrointestinal Medical Oncology, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China
| | - Ming Zhao
- Minimally Invasive Interventional Division, Liver Cancer Group, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Yongfu Zhao
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, ZhengZhou, China
| | - Honggang Zheng
- Department of Oncology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ledu Zhou
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Jiye Zhu
- Department of Hepatobiliary Surgery, Peking University People’s Hospital, Beijing, China
| | - Kangshun Zhu
- Department of Minimally Invasive Interventional Radiology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Rong Liu
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yinghong Shi
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yongsheng Xiao
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lan Zhang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhifeng Wu
- Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhi Dai
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Minshan Chen
- Department of Hepatobiliary Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jianqiang Cai
- Department of Abdominal Surgical Oncology, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Weilin Wang
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiujun Cai
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Qiang Li
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Feng Shen
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Shukui Qin
- Department of Medical Oncology, PLA Cancer Center, Nanjing Bayi Hospital, Nanjing, China
| | - Gaojun Teng
- Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Jiahong Dong
- Department of Hepatobiliary and Pancreas Surgery, Beijing Tsinghua Changgung Hospital (BTCH), School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Jia Fan
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
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Chen Z, Huang M, Lyu J, Qi X, He F, Li X. Machine learning for predicting breast-conserving surgery candidates after neoadjuvant chemotherapy based on DCE-MRI. Front Oncol 2023; 13:1174843. [PMID: 37621690 PMCID: PMC10446166 DOI: 10.3389/fonc.2023.1174843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 07/20/2023] [Indexed: 08/26/2023] Open
Abstract
Purpose This study aimed to investigate a machine learning method for predicting breast-conserving surgery (BCS) candidates, from patients who received neoadjuvant chemotherapy (NAC) by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) obtained before and after NAC. Materials and methods This retrospective study included 75 patients who underwent NAC and breast surgery. First, 3,390 features were comprehensively extracted from pre- and post-NAC DCE-MRIs. Then patients were then divided into two groups: type 1, patients with pathologic complete response (pCR) and single lesion shrinkage; type 2, major residual lesion with satellite foci, multifocal residual, stable disease (SD), and progressive disease (PD). The logistic regression (LR) was used to build prediction models to identify the two groups. Prediction performance was assessed using the area under the curve (AUC), accuracy, sensitivity, and specificity. Results Radiomics features were significantly related to breast cancer shrinkage after NAC. The combination model achieved an AUC of 0.82, and the pre-NAC model was 0.64, the post-NAC model was 0.70, and the pre-post-NAC model was 0.80. In the combination model, 15 features, including nine wavelet-based features, four Laplacian-of-Gauss (LoG) features, and two original features, were filtered. Among these selected were four features from pre-NAC DCE-MRI, six were from post-NAC DCE-MRI, and five were from pre-post-NAC features. Conclusion The model combined with pre- and post-NAC DCE-MRI can effectively predict candidates to undergo BCS and provide AI-based decision support for clinicians with ensured safety. High-order (LoG- and wavelet-based) features play an important role in our machine learning model. The features from pre-post-NAC DCE-MRI had better predictive performance.
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Affiliation(s)
| | | | | | | | | | - Xiang Li
- Department of Radiology, the Second Hospital of Dalian Medical University, Dalian, China
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Rossini D, Germani MM, Lonardi S, Pietrantonio F, Dell'Aquila E, Borelli B, Allegrini G, Maddalena G, Randon G, Marmorino F, Zaniboni A, Buonadonna A, Boccaccino A, Conca V, Antoniotti C, Passardi A, Masi G, Cremolini C. Treatments after second progression in metastatic colorectal cancer: A pooled analysis of the TRIBE and TRIBE2 studies. Eur J Cancer 2022; 170:64-72. [PMID: 35594613 DOI: 10.1016/j.ejca.2022.04.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/11/2022] [Accepted: 04/16/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND The availability of new drugs in the chemo-refractory setting opened the way to the concepts of treatment sequencing in mCRC. However, the impact of later line options in the therapeutic route of metastatic colorectal cancer (mCRC) patients and the attrition rate across subsequent lines of therapy are not well established. METHODS We performed a pooled analysis of treatments administered after the 2nd disease progression in 1187 mCRC patients enrolled in the randomized phase III TRIBE and TRIBE2 studies, where upfront FOLFOXIRI/bev was compared with FOLFOX or FOLFIRI/bev. Per each line, we assessed the attrition rate, treatment choices and clinical outcomes. RESULTS 625 (53%), 326 (27%) and 136 (11%) patients received a systemic treatment after the 2nd, 3rd and 4th disease progression, respectively. PFS and objective response rate decreased along each line. RAS/BRAF wild-type patients received more likely a 3rd line (75%) compared with RAS (66%, p = 0.005) and BRAF (66%, p = 0.11) mutants. In 3rd line, 67% of RAS/BRAF wild-type patients received anti-EGFRs, achieving longer PFS with respect to other therapies (6.4 vs 3.9 months, p = 0.02). A trend towards longer 3rd line OS was observed in TRIBE patients (9.9 vs 7.2 months, p = 0.05). CONCLUSIONS A relevant attrition rate across subsequent lines of therapy is evident, and more pronounced in RAS and BRAF mutated patients, thus highlighting the relevance of the choice of the upfront treatment. The efficacy of anti-EGFR agents among RAS/BRAF wild-type patients unexposed to anti-EGFRs is higher than other options. The reintroduction of chemotherapy remains frequent in clinical practice. TRIAL REGISTRATION Clinicaltrials. gov Identifiers NCT00719797, NCT02339116.
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Affiliation(s)
- Daniele Rossini
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Marco M Germani
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Sara Lonardi
- Medical Oncology Unit 3, Veneto Institute of Oncology IOV - IRCCS, Via Gattamelata, 64, 35128, Padua, Italy
| | - Filippo Pietrantonio
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Via Giacomo Venezian, 1, 20133, Milan, Italy
| | - Emanuela Dell'Aquila
- Department of Medical Oncology, University Campus Biomedico, Via Álvaro Del Portillo, 21, 00128, Rome, Italy; Medical Oncology 1, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi, 53, 0144, Rome, Italy
| | - Beatrice Borelli
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Giacomo Allegrini
- Department of Oncology, Division of Medical Oncology, Azienda Toscana Nord Ovest, Viale Vittorio Alfieri, 36, 57124, Livorno, Italy
| | - Giulia Maddalena
- Medical Oncology Unit 3, Veneto Institute of Oncology IOV - IRCCS, Via Gattamelata, 64, 35128, Padua, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - Giovanni Randon
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Via Giacomo Venezian, 1, 20133, Milan, Italy
| | - Federica Marmorino
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Alberto Zaniboni
- Medical Oncology Unit, Poliambulanza Foundation, Via Bissolati, 57, 25124, Brescia, Italy
| | - Angela Buonadonna
- Medical Oncology Unit, Centro di Riferimento Oncologico di Aviano, Istituto di Ricovero e Cura a Carattere Scientifico, Via Franco Gallini, 2, 33081, Aviano, Italy
| | - Alessandra Boccaccino
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Veronica Conca
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Carlotta Antoniotti
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Alessandro Passardi
- Department of Medical Oncology, IRCCS Istituto Romagnolo per Lo Studio Dei Tumori (IRST) "Dino Amadori", Via Piero Maroncelli, 40, 47014, Meldola, Italy
| | - Gianluca Masi
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy
| | - Chiara Cremolini
- Department of Translational Research and New Technologies in Medicine, University of Pisa, Via Roma 67, 56127, Pisa, Italy; Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, 56127, Pisa, Italy.
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Chakrabarty N, Mahajan A, Baheti AD, Choudhari A, Patil V, Popat P, Unde H. A Radiologist's Perspective on Treatment-Related Pseudoprogression: Clues and Hues. Indian J Med Paediatr Oncol 2022. [DOI: 10.1055/s-0042-1742609] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
AbstractPseudoprogression refers to the initial apparent increase in tumor burden observed on imaging after cancer therapy, with subsequent delayed response to the same treatment, thus giving a false initial appearance of disease progression. It is essential to differentiate pseudoprogression from true progression to prevent the patients from getting deprived of the benefits of their ongoing cancer therapy owing to their early withdrawal. It also affects their recruitment for clinical trials. Pseudoprogression, albeit uncommon, has been observed after various types of cancer therapy; however, this phenomenon has gained momentum of late due to the emergence of immunotherapy for the treatment of various malignancies. Besides immunotherapy, pseudoprogression has predominantly been of concern in a few patients after radiation therapy for brain tumors and metastasis, after molecular targeted therapy for a variety of tumors, and after chemotherapy in metastatic bone lesions. This article reviews the available data on imaging of pseudoprogression from various types of cancer therapies, highlighting ways to suspect or identify it on imaging.
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Affiliation(s)
- Nivedita Chakrabarty
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
| | - Abhishek Mahajan
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
| | - Akshay D. Baheti
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
| | - Amit Choudhari
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
| | - Vasundhara Patil
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
| | - Palak Popat
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
| | - Himangi Unde
- Department of Radiodiagnosis, Tata Memorial Centre, Tata Memorial Hospital, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
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I-124 PET/CT image-based dosimetry in patients with differentiated thyroid cancer treated with I-131: correlation of patient-specific lesional dosimetry to treatment response. Ann Nucl Med 2022; 36:213-223. [PMID: 35119623 DOI: 10.1007/s12149-021-01655-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 07/12/2021] [Indexed: 11/01/2022]
Abstract
PURPOSE The objective of this study is to evaluate the lesion absorbed dose (AD), biological effective dose (BED), and equivalent uniform dose (EUD) to clinical-response relationship in lesional dosimetry for 131I therapy. METHODS Nineteen lesions in four patients with metastatic differentiated thyroid cancer (DTC) were evaluated. The patients underwent PET/CT imaging at 2 h, 24 h, 48 h, 72 h, and 96 h post administration of ~ 33-65 MBq (0.89-1.76 mCi) of 124I before undergoing 131I therapy. The 124I PET/CT images were used to perform dosimetry calculations for 131I therapy. Lesion dose-rate values were calculated using the time-activity data and integrated over the measured time points to obtain AD and BED. The Geant4 toolkit was used to run Monte Carlo on spheres the same size as the lesions to estimate EUD. The lesion AD, BED, and EUD values were correlated with response data (i.e. change in lesion size pre- and post-therapy): complete response (CR, i.e. disappearance of the lesion), partial response (PR, i.e. any decrease in lesion length), stable disease (SD, i.e., no change in length), and progressive disease (PD, i.e., any increase in length). RESULTS The lesion responses were CR and PR (58%, 11/19 lesions), SD (21%, 4/19), and PD (21%, 4/19). For CR and PR lesions, the ADs, BEDs and EUDs were > 75 Gy for 82% (9/11) and < 75 Gy for 18% (2/11). The ADs and BEDs were < 75 Gy for SD and PD lesions. CONCLUSION By performing retrospective dosimetry calculations for 131I therapy based on 124I PET/CT imaging, we evaluated the correlation of three dosimetric quantities to lesional response. When lesion AD, BED, and EUD values were > 75 Gy, 47% (9/19) of the lesions had a CR or PR. The AD, BED, and EUD values for SD and PD lesions were < 75 Gy. The data presented herein suggest that the greater the lesion AD, BED, and/or EUD, the higher the probability of a therapeutic response to 131I therapy.
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Mahajan A, Chakrabarty N. Pre-treatment “Lung Cancer Imaging - Reporting and Data System” (LCI-RADS) and “Post-therapy Lung Cancer Imaging - Reporting and Data System” (pLCI-RADS): A narrative review of comprehensive synoptic reporting formats for lung cancer imaging. CANCER RESEARCH, STATISTICS, AND TREATMENT 2022. [DOI: 10.4103/crst.crst_192_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
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Chen C, Margolis DJ. Prostate-Specific Membrane Antigen (PSMA) PET: A Counterpart to Prostate MRI. Semin Roentgenol 2021; 56:376-383. [PMID: 34688340 DOI: 10.1053/j.ro.2021.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/11/2021] [Accepted: 08/16/2021] [Indexed: 11/11/2022]
Affiliation(s)
- Christine Chen
- Department of Radiology, Weill Cornell Medical College: Weill Cornell Medicine, 1300 York Ave, New York, NY 10065.
| | - Daniel J Margolis
- Department of Radiology, Weill Cornell Medical College: Weill Cornell Medicine, 1300 York Ave, New York, NY 10065
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Huang Y, Chen W, Zhang X, He S, Shao N, Shi H, Lin Z, Wu X, Li T, Lin H, Lin Y. Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast Cancer. Front Bioeng Biotechnol 2021; 9:662749. [PMID: 34295877 PMCID: PMC8291046 DOI: 10.3389/fbioe.2021.662749] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 06/07/2021] [Indexed: 01/01/2023] Open
Abstract
Aim: After neoadjuvant chemotherapy (NACT), tumor shrinkage pattern is a more reasonable outcome to decide a possible breast-conserving surgery (BCS) than pathological complete response (pCR). The aim of this article was to establish a machine learning model combining radiomics features from multiparametric MRI (mpMRI) and clinicopathologic characteristics, for early prediction of tumor shrinkage pattern prior to NACT in breast cancer. Materials and Methods: This study included 199 patients with breast cancer who successfully completed NACT and underwent following breast surgery. For each patient, 4,198 radiomics features were extracted from the segmented 3D regions of interest (ROI) in mpMRI sequences such as T1-weighted dynamic contrast-enhanced imaging (T1-DCE), fat-suppressed T2-weighted imaging (T2WI), and apparent diffusion coefficient (ADC) map. The feature selection and supervised machine learning algorithms were used to identify the predictors correlated with tumor shrinkage pattern as follows: (1) reducing the feature dimension by using ANOVA and the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation, (2) splitting the dataset into a training dataset and testing dataset, and constructing prediction models using 12 classification algorithms, and (3) assessing the model performance through an area under the curve (AUC), accuracy, sensitivity, and specificity. We also compared the most discriminative model in different molecular subtypes of breast cancer. Results: The Multilayer Perception (MLP) neural network achieved higher AUC and accuracy than other classifiers. The radiomics model achieved a mean AUC of 0.975 (accuracy = 0.912) on the training dataset and 0.900 (accuracy = 0.828) on the testing dataset with 30-round 6-fold cross-validation. When incorporating clinicopathologic characteristics, the mean AUC was 0.985 (accuracy = 0.930) on the training dataset and 0.939 (accuracy = 0.870) on the testing dataset. The model further achieved good AUC on the testing dataset with 30-round 5-fold cross-validation in three molecular subtypes of breast cancer as following: (1) HR+/HER2–: 0.901 (accuracy = 0.816), (2) HER2+: 0.940 (accuracy = 0.865), and (3) TN: 0.837 (accuracy = 0.811). Conclusions: It is feasible that our machine learning model combining radiomics features and clinical characteristics could provide a potential tool to predict tumor shrinkage patterns prior to NACT. Our prediction model will be valuable in guiding NACT and surgical treatment in breast cancer.
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Affiliation(s)
- Yuhong Huang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wenben Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Xiaoling Zhang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shaofu He
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Nan Shao
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huijuan Shi
- Department of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhenzhe Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Xueting Wu
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Tongkeng Li
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Haotian Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Ying Lin
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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The Importance of Accurate Tumor Measurements and Staging in Oncologic Imaging: Impact on Patients' Health. Acad Radiol 2021; 28:767-768. [PMID: 33468419 DOI: 10.1016/j.acra.2021.01.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 01/08/2021] [Indexed: 12/20/2022]
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Shafiei A, Bagheri M, Farhadi F, Apolo AB, Biassou NM, Folio LR, Jones EC, Summers RM. CT Evaluation of Lymph Nodes That Merge or Split during the Course of a Clinical Trial: Limitations of RECIST 1.1. Radiol Imaging Cancer 2021; 3:e200090. [PMID: 33874734 PMCID: PMC8189184 DOI: 10.1148/rycan.2021200090] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 02/11/2021] [Accepted: 02/16/2021] [Indexed: 06/12/2023]
Abstract
Purpose To compare Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 with volumetric measurement in the setting of target lymph nodes that split into two or more nodes or merge into one conglomerate node. Materials and Methods In this retrospective study, target lymph nodes were evaluated on CT scans from 166 patients with different types of cancer; 158 of the scans came from The Cancer Imaging Archive. Each target node was measured using RECIST 1.1 criteria before and after merging or splitting, followed by volumetric segmentation. To compare RECIST 1.1 with volume, a single-dimension hypothetical diameter (HD) was determined from the nodal volume. The nodes were divided into three groups: (a) one-target merged (one target node merged with other nodes); (b) two-target merged (two neighboring target nodes merged); and (c) split node (a conglomerate node cleaved into smaller fragments). Bland-Altman analysis and t test were applied to compare RECIST 1.1 with HD. On the basis of the RECIST 1.1 concept, we compared response category changes between RECIST 1.1 and HD. Results The data set consisted of 30 merged nodes (19 one-target merged and 11 two-target merged) and 20 split nodes (mean age for all 50 included patients, 50 years ± 7 [standard deviation]; 38 men). RECIST 1.1, volumetric, and HD measurements indicated an increase in size in all one-target merged nodes. While volume and HD indicated an increase in size for nodes in the two-target merged group, RECIST 1.1 showed a decrease in size in all two-target merged nodes. Although volume and HD demonstrated a decrease in size of all split nodes, RECIST 1.1 indicated an increase in size in 60% (12 of 20) of the nodes. Discrepancy of the response categories between RECIST 1.1 and HD was observed in 5% (one of 19) in one-target merged, 82% (nine of 11) in two-target merged, and 55% (11 of 20) in split nodes. Conclusion RECIST 1.1 does not optimally reflect size changes when lymph nodes merge or split. Keywords: CT, Lymphatic, Tumor Response Supplemental material is available for this article. © RSNA, 2021.
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Yirgin IK, Erturk SM, Dogan I, Vatansever S. Are radiologists ready to evaluate true response to immunotherapy? Insights Imaging 2021; 12:29. [PMID: 33625595 PMCID: PMC7905005 DOI: 10.1186/s13244-021-00968-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 01/12/2021] [Indexed: 12/14/2022] Open
Abstract
Background Standardized response criteria for evaluating patients radiological imaging have an essential role in oncological management. Immunotherapy, using immune checkpoint inhibitors (ICIs), including drugs targeting cytotoxic T-lymphocyte-associated antigen 4 and programmed cell death protein 1 or its ligand, promise a new role that has demonstrated improvement management in cancers resistant to chemotherapy. This article reviews the literature to understand the most useful response evaluation criteria for optimal patient management under immunotherapy treatment. Areas that warrant further research are described. Conclusion In conclusion, ICIs have become more widely accepted and used by medical oncologists. Radiologists face challenges in assessing tumor response and becoming more involved in the management of treatment. The latest published immune-RECIST criteria can be used in response assessment, but further prospective evaluation is needed with registration clinical trials to be definitively validated.
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Affiliation(s)
- Inci Kizildag Yirgin
- Department of Radiology, Oncology Institute, Istanbul University, Istanbul, 34390, Capa, Turkey.
| | - Sukru Mehmet Erturk
- Department of Radiology, Istanbul Medical Faculty, Istanbul University, Istanbul, 34390, Capa, Turkey
| | - Izzet Dogan
- Department of Medical Oncology, Oncology Institute, Istanbul University, Istanbul, 34390, Capa, Turkey
| | - Sezai Vatansever
- Department of Medical Oncology, Oncology Institute, Istanbul University, Istanbul, 34390, Capa, Turkey
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Alongi F, Nicosia L, Figlia V, Giaj-Levra N, Cuccia F, Mazzola R, Ricchetti F, Rigo M, Vitale C, De Simone A, Naccarato S, Sicignano G, Gurrera D, Corradini S, Ruggeri R. Long-term disease outcome and volume-based decision strategy in a large cohort of multiple brain metastases treated with a mono-isocentric linac-based Stereotactic Radiosurgery technique. Clin Transl Oncol 2021; 23:1561-1570. [PMID: 33570720 DOI: 10.1007/s12094-020-02550-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 12/28/2020] [Indexed: 10/22/2022]
Abstract
PURPOSE Radiosurgery (SRS) is an effective treatment option for brain metastases (BMs). Long-term results of the first worldwide experience with a mono-isocentric, non-coplanar, linac-based stereotactic technique in the treatment of multiple BMs are reported. METHODS patients with multiple BMs, life expectancy > 3 months, and good performance status (≤ 2) were treated with simultaneous SRS with volumetric modulated arc technique. Data were retrospectively evaluated. RESULTS 172 patients accounting for 1079 BMs were treated at our institution from 2017 to 2020. The median number of treated metastases was 4 (range 2-22). Primary tumor histology was: lung (44.8%), breast (32%), and melanoma (9.4%). The 2-year LPFS was 71.6%, respectively. A biological effective dose (BED) ≥ 51.3 Gy10 correlated with higher local control. Uncontrolled systemic disease and melanoma histology were independent prognostic factors correlated with decreased iPFS. Patients with > 10 BMs had a trend towards shorter iPFS (p = 0.055). 31 patients received multiple SRS courses (2-7) in case of intracranial progression. The median iOS was 22.4 months. Brainstem metastases and total PTV > 7.1 cc correlated with shorter iOS. The 1- and 2-year WBRT-free survival was 83.2% and 61.1%, respectively. CONCLUSION Long-term results in a large patient population treated with a mono-isocentric, dedicated technique demonstrated its effectiveness and safety also in the case of multiple courses. The shortened treatment time and the possibility to safely spare healthy brain tissue allows the safe treatment of patients with a large number of metastases and to deliver multiple courses of SRS. In selected cases, the administration of WBRT can be delayed.
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Affiliation(s)
- F Alongi
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy.,University of Brescia, Brescia, Italy
| | - L Nicosia
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy.
| | - V Figlia
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - N Giaj-Levra
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - F Cuccia
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - R Mazzola
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - F Ricchetti
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - M Rigo
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - C Vitale
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - A De Simone
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - S Naccarato
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - G Sicignano
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - D Gurrera
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
| | - S Corradini
- Radiation Oncology Department, University Hospital, LMU Munich, Munich, Germany
| | - R Ruggeri
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Cancer Care Center, via Don Sempreboni 5, 37034, Negrar, Verona, Italy
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Hidayat YM, Wagey F, Suardi D, Susanto H, Laihad BJ, Tobing MDL. Analysis of Curcumin as a Radiosensitizer in Cancer Therapy with Serum Survivin Examination: Randomised Control Trial. Asian Pac J Cancer Prev 2021; 22:139-143. [PMID: 33507691 PMCID: PMC8184198 DOI: 10.31557/apjcp.2021.22.1.139] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 01/15/2021] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE One of the important treatments for cervical cancer is radiation therapy. This study sought to determine the role of curcumin as a radio-sensitizing agent for use with radiation therapy for cervical cancer. To accomplish this, we assessed the levels of survivin, which is an anti-apoptotic protein that plays a role in cell division and apoptosis inhibition. METHOD This study used a quasi-experimental design, including a pretest-posttest control group design approach. The study subjects included cervical carcinoma stage IIB-IIIB patients who were scheduled to undergo surgery at the Hasan Sadikin Hospital Bandung during the research period. The advanced cervical cancer patients were assigned to two groups: i) those who received curcumin + radiation therapy and ii) those who received placebo + radiation therapy. RESULTS In the group treated with curcumin + radiation, 15 (75%) patients showed decreased survivin levels and 5 (25%) showed increased survivin levels. Whereas, in the placebo + radiation group, there were 8 (40%) patients who showed decreased survivin levels and 12 (60%) who showed increased survivin levels. CONCLUSION In conclusion, curcumin is an effective, alternative radiosensitizer agent for application in cervical cancer treatment. .
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Affiliation(s)
- Yudi Mulyana Hidayat
- Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia.
| | - Frank Wagey
- Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia.
| | - Dodi Suardi
- Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia.
| | - Herman Susanto
- Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia.
| | - Bismarck J Laihad
- Department of Obstetrics and Gynecology, School of Medicine, Universitas Sam Ratulangi, Manado, Indonesia.
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19
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Lee H, Eads JR, Pryma DA. 68 Ga-DOTATATE Positron Emission Tomography-Computed Tomography Quantification Predicts Response to Somatostatin Analog Therapy in Gastroenteropancreatic Neuroendocrine Tumors. Oncologist 2021; 26:21-29. [PMID: 32886441 PMCID: PMC7794177 DOI: 10.1634/theoncologist.2020-0165] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 08/04/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Somatostatin analogs (SSAs) are the frontline antitumor therapy in advanced well-differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs). A subset of patients demonstrate early disease progression on SSA therapy, yet the currently known predictors for treatment failure lack specificity to affect therapeutic decision. SSAs target tumor somatostatin receptors, the level of which can be quantitatively assessed with 68 Ga-DOTATATE positron emission tomography-computed tomography (PET/CT). We investigated the ability of 68 Ga-DOTATATE PET/CT to predict response to SSA therapy. MATERIALS AND METHODS The records of 108 consecutive patients with well-differentiated grade 1-2 GEP-NETs on SSA monotherapy who received 68 Ga-DOTATATE PET/CT scans were retrospectively reviewed to obtain baseline characteristics, 68 Ga-DOTATATE maximum standardized uptake value (SUVmax), and progression-free survival (PFS) data. The optimal SUVmax cutoff for patient stratification was obtained with receiver operating characteristic curve analysis. PFS in the high versus low SUVmax groups was compared with Kaplan-Meier survival analysis. The effects of baseline characteristics and SUVmax on PFS were examined with univariate and multivariate Cox regression. RESULTS 68 Ga-DOTATATE SUVmax predicted therapeutic failure with sensitivity and specificity of 39% and 98%, respectively. SUVmax of <18.35 was associated with shorter PFS, which was reproduced in the subgroup analysis of SSA-naïve patients. Low SUVmax was the only predictor of early treatment failure (hazard ratio, 6.85) in multivariate analysis, as well as in the subgroup analysis of grade 2 GEP-NETs. CONCLUSION Low SUVmax on 68 Ga-DOTATATE PET/CT independently predicts early failure on SSA monotherapy in patients with well-differentiated grade 1-2 GEP-NET. Patients with lack of expected benefit from SSA therapy can be readily identified using routine 68 Ga-DOTATATE PET/CT with very high specificity. IMPLICATIONS FOR PRACTICE Based on 68 Ga-DOTATATE positron emission tomography-computed tomography imaging, clinicians can better inform patients on the expected benefit of somatostatin analog therapy for gastroenteropancreatic neuroendocrine tumors, especially when access to the therapy is difficult, and offer proactive discussion on alternative management options.
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Affiliation(s)
- Hwan Lee
- Department of Radiology, University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Jennifer R. Eads
- Department of Medicine, University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Daniel A. Pryma
- Department of Radiology, University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
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20
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Costa LB, Queiroz MA, Barbosa FG, Nunes RF, Zaniboni EC, Ruiz MM, Jardim D, Gomes Marin JF, Cerri GG, Buchpiguel CA. Reassessing Patterns of Response to Immunotherapy with PET: From Morphology to Metabolism. Radiographics 2020; 41:120-143. [PMID: 33275541 DOI: 10.1148/rg.2021200093] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Cancer demands precise evaluation and accurate and timely assessment of response to treatment. Imaging must be performed early during therapy to allow adjustments to the course of treatment. For decades, cross-sectional imaging provided these answers, showing responses to the treatment through changes in tumor size. However, with the emergence of immune checkpoint inhibitors, complex immune response patterns were revealed that have quickly highlighted the limitations of this approach. Patterns of response beyond tumor size have been recognized and include cystic degeneration, necrosis, hemorrhage, and cavitation. Furthermore, new unique patterns of response have surfaced, like pseudoprogression and hyperprogression, while other patterns were shown to be deceptive, such as unconfirmed progressive disease. This evolution led to new therapeutic evaluation criteria adapted specifically for immunotherapy. Moreover, inflammatory adverse effects of the immune checkpoint blockade were identified, many of which were life threatening and requiring prompt intervention. Given complex concepts like tumor microenvironment and novel therapeutic modalities in the era of personalized medicine, increasingly sophisticated imaging techniques are required to address the intricate patterns of behavior of different neoplasms. Fluorine 18-fluorodeoxyglucose PET/CT has rapidly emerged as one such technique that spans both molecular biology and immunology. This imaging technique is potentially capable of identifying and tracking prognostic biomarkers owing to its combined use of anatomic and metabolic imaging, which enables it to characterize biologic processes in vivo. This tailored approach may provide whole-body quantification of the metabolic burden of disease, providing enhanced prediction of treatment response and improved detection of adverse events. ©RSNA, 2020.
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Affiliation(s)
- Larissa B Costa
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Marcelo A Queiroz
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Felipe G Barbosa
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Rafael F Nunes
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Elaine C Zaniboni
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Mariana Mazo Ruiz
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Denis Jardim
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Jose Flavio Gomes Marin
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Giovanni G Cerri
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
| | - Carlos A Buchpiguel
- From the Departments of Radiology (L.B.C., M.A.Q., F.G.B., R.F.N., E.C.Z., M.M.R., J.F.G.M., G.G.C., C.A.B.) and Oncology (D.J.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, 01308-060 São Paulo, SP, Brazil; and Department of Radiology and Oncology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., J.F.G.M., G.G.C., C.A.B.)
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Zhou J, Sun H, Wang Z, Cong W, Wang J, Zeng M, Zhou W, Bie P, Liu L, Wen T, Han G, Wang M, Liu R, Lu L, Ren Z, Chen M, Zeng Z, Liang P, Liang C, Chen M, Yan F, Wang W, Ji Y, Yun J, Cai D, Chen Y, Cheng W, Cheng S, Dai C, Guo W, Hua B, Huang X, Jia W, Li Y, Li Y, Liang J, Liu T, Lv G, Mao Y, Peng T, Ren W, Shi H, Shi G, Tao K, Wang W, Wang X, Wang Z, Xiang B, Xing B, Xu J, Yang J, Yang J, Yang Y, Yang Y, Ye S, Yin Z, Zhang B, Zhang B, Zhang L, Zhang S, Zhang T, Zhao Y, Zheng H, Zhu J, Zhu K, Liu R, Shi Y, Xiao Y, Dai Z, Teng G, Cai J, Wang W, Cai X, Li Q, Shen F, Qin S, Dong J, Fan J. Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2019 Edition). Liver Cancer 2020; 9:682-720. [PMID: 33442540 PMCID: PMC7768108 DOI: 10.1159/000509424] [Citation(s) in RCA: 435] [Impact Index Per Article: 108.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 06/12/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Primary liver cancer, around 90% are hepatocellular carcinoma in China, is the fourth most common malignancy and the second leading cause of tumor-related death, thereby posing a significant threat to the life and health of the Chinese people. SUMMARY Since the publication of Guidelines for Diagnosis and Treatment of Primary Liver Cancer (2017 Edition) in 2018, additional high-quality evidence has emerged with relevance to the diagnosis, staging, and treatment of liver cancer in and outside China that requires the guidelines to be updated. The new edition (2019 Edition) was written by more than 70 experts in the field of liver cancer in China. They reflect the real-world situation in China regarding diagnosing and treating liver cancer in recent years. KEY MESSAGES Most importantly, the new guidelines were endorsed and promulgated by the Bureau of Medical Administration of the National Health Commission of the People's Republic of China in December 2019.
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Affiliation(s)
- Jian Zhou
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Huichuan Sun
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zheng Wang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wenming Cong
- Department of Pathology, The Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Jianhua Wang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiping Zhou
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Ping Bie
- Institute of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Lianxin Liu
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tianfu Wen
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Guohong Han
- Department of Liver Diseases and Digestive Interventional Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Maoqiang Wang
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing, China
| | - Ruibao Liu
- Department of Interventional Radiology, The Tumor Hospital of Harbin Medical University, Harbin, China
| | - Ligong Lu
- Department of Interventional Oncology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhengang Ren
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Minshan Chen
- Department of Hepatobiliary Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhaochong Zeng
- Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ping Liang
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Changhong Liang
- Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Min Chen
- Editorial Department of Chinese Journal of Digestive Surgery, Chongqing, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wenping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jingping Yun
- Department of Pathology, Tumor Prevention and Treatment Center, Sun Yat-sen University, Guangzhou, China
| | - Dingfang Cai
- Department of Integrative Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yongjun Chen
- Department of Hematology, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenwu Cheng
- Department of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Shuqun Cheng
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Chaoliu Dai
- Department of Hepatobiliary and Spleenary Surgery, The Affiliated Shengjing Hospital, China Medical University, Shenyang, China
| | - Wenzhi Guo
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Baojin Hua
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xiaowu Huang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weidong Jia
- Department of Hepatic Surgery, Affiliated Provincial Hospital, Anhui Medical University, Hefei, China
| | - Yaming Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yexiong Li
- Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jun Liang
- Department of Oncology, Peking University International Hospital, Beijing, China
| | - Tianshu Liu
- Department of Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guoyue Lv
- Department of General Surgery, The First Hospital of Jilin University, Jilin, China
| | - Yilei Mao
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC and Chinese Academy of Medical Sciences, Beijing, China
| | - Tao Peng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Weixin Ren
- Department of Interventional Radiology The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Hongcheng Shi
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guoming Shi
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kaishan Tao
- Department of Hepatobiliary Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wentao Wang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaoying Wang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhiming Wang
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Bangde Xiang
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China
| | - Baocai Xing
- Department of Hepato-Pancreato-Biliary Surgery, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jianming Xu
- Department of Gastrointestinal Oncology, Affiliated Hospital Cancer Center, Academy of Military Medical Sciences, Beijing, China
| | - Jiamei Yang
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Jianyong Yang
- Department of Interventional Oncology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yefa Yang
- Department of Hepatic Surgery & Interventional Radiology, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Yunke Yang
- Department of Integrative Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shenglong Ye
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhengyu Yin
- Department of Hepatobiliary Surgery, Zhongshan Hospital of Xiamen University, Hubing South Road, Xiamen, China
| | - Bixiang Zhang
- Department of Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Boheng Zhang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Leida Zhang
- Department of Hepatobiliary Surgery Institute, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Shuijun Zhang
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Zhengzhou University, ZhengZhou, China
| | - Ti Zhang
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yongfu Zhao
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Zhengzhou University, ZhengZhou, China
| | - Honggang Zheng
- Department of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jiye Zhu
- Department of Hepatobiliary Surgery, Peking University People's Hospital, Beijing, China
| | - Kangshun Zhu
- Department of Minimally Invasive Interventional Radiology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Rong Liu
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yinghong Shi
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yongsheng Xiao
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhi Dai
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Gaojun Teng
- Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Jianqiang Cai
- Department of Abdominal Surgical Oncology, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Weilin Wang
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiujun Cai
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Qiang Li
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Feng Shen
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Shukui Qin
- Department of Medical Oncology, PLA Cancer Center, Nanjing Bayi Hospital, Nanjing, China
| | - Jiahong Dong
- Department of Hepatobiliary and Pancreas Surgery, Beijing Tsinghua Changgung Hospital (BTCH), School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Jia Fan
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
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Imaging in Therapy Response Assessment and Surveillance of Lung Cancer: Evidenced-based Review With Focus on the Utility of 18F-FDG PET/CT. Clin Lung Cancer 2020; 21:485-497. [DOI: 10.1016/j.cllc.2020.06.020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 06/18/2020] [Accepted: 06/28/2020] [Indexed: 12/11/2022]
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Barbosa FG, Queiroz MA, Ferraro DA, Nunes RF, Dreyer PR, Zaniboni EC, Costa LB, Bastos DA, Marin JFG, Buchpiguel CA. Prostate-specific Membrane Antigen PET: Therapy Response Assessment in Metastatic Prostate Cancer. Radiographics 2020; 40:1412-1430. [PMID: 32762625 DOI: 10.1148/rg.2020200058] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Therapy response assessment is a critical step in cancer management, leading clinicians to optimize the use of therapeutic options during the course of the disease. Imaging is a pivotal biomarker for therapy response evaluation in oncology and has gained wider use through the development of reproducible data-based guidelines, of which the Response Evaluation Criteria in Solid Tumors is the most successful example. Disease-specific criteria have also been proposed, and the Prostate Cancer Working Group 3 criteria are the mainstay for prostate cancer (PC). However, conventional imaging evaluation in metastatic PC has several limitations, including (a) the inability to detect small-volume disease, (b) the high prevalence of bone (nonmeasurable) lesions at imaging, and (c) the established role of serum prostate-specific antigen (PSA) levels as the biomarker of choice for response assessment and disease progression. In addition, there are an increasing number of newer treatment options with various effects on imaging features. Prostate-specific membrane antigen (PSMA) PET has improved patient selection for newer treatments, such as metastasis-directed therapy (MDT) or radionuclide therapy. The role of PSMA PET in response assessment for many metastatic PC therapeutic options (MDT, androgen deprivation therapy, chemotherapy, radionuclide therapy, and immunotherapy) is an evolving issue, with emerging data showing good correlation with PSA levels and clinical outcome. However, there are specific implications of each therapy (especially androgen deprivation therapy and immunotherapy) on PSMA expression by PC cells, leading to potential pitfalls and inaccuracies that must be known by radiologists. Despite some limitations, PSMA PET is addressing gaps left by conventional imaging methods (eg, CT and bone scanning) and nonimaging biomarkers (PSA levels) in metastatic PC therapy response assessment, a role that can be improved with advances like refinement of interpretation criteria and whole-body tumor burden quantification.© RSNA, 2020See discussion on this article by Barwick and Castellucci.
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Affiliation(s)
- Felipe G Barbosa
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Marcelo A Queiroz
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Daniela A Ferraro
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Rafael F Nunes
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Priscilla R Dreyer
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Elaine C Zaniboni
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Larissa B Costa
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Diogo A Bastos
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - José Flávio G Marin
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
| | - Carlos A Buchpiguel
- From the Departments of Radiology (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.) and Oncology (D.A.B.), Hospital Sírio-Libanês, Rua Dona Adma Jafet 115, São Paulo, SP, CEP 01308-060, Brazil (F.G.B., M.A.Q., R.F.N., P.R.D., E.C.Z., L.B.C., J.F.G.M., C.A.B.); Department of Radiology and Oncology, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil (M.A.Q., D.A.B., J.F.G.M., C.A.B.); and Department of Nuclear Medicine, University Hospital of Zurich, Zurich, Switzerland (D.A.F.)
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Park HY, Kim KW, Yoon MA, Lee MH, Chae EJ, Lee JH, Chung HW, Yoon DH. Role of whole-body MRI for treatment response assessment in multiple myeloma: comparison between clinical response and imaging response. Cancer Imaging 2020; 20:14. [PMID: 32000858 PMCID: PMC6993415 DOI: 10.1186/s40644-020-0293-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 01/20/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Whole-body MRI (WB-MRI) including diffusion-weighted image (DWI) have been widely used in patients with multiple myeloma. However, evidence for the value of WB-MRI in the evaluation of treatment response remains sparse. Therefore, we evaluated the role of WB-MRI in the response assessment. METHODS In our WB-MRI registry, we searched multiple myeloma patients treated with chemotherapy who underwent both baseline and follow-up WB-MRI scans. Clinical responses were categorized as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD), using IMWG criteria. Using RECIST 1.1, MD Anderson (MDA) criteria, and MDA-DWI criteria, imaging responses on WB-MRI were rated as CR, PR, SD, or PD by two radiologists independently. Then, discrepancy cases were resolved by consensus. Weighted Kappa analysis was performed to evaluate agreement between the imaging and clinical responses. The diagnostic accuracy of image responses in the evaluation of clinical CR, objective response (CR and PR), and PD was calculated. RESULTS Forty-two eligible patients were included. There was moderate agreement between imaging and clinical responses (κ = 0.54 for RECIST 1.1, κ = 0.58 for MDA criteria, κ = 0.69 for MDA-DWI criteria). WB-MRI showed excellent diagnostic accuracy in assessment of clinical PD (sensitivity 88.9%, specificity 94.7%, positive predictive value [PPV] 84.2%, negative predictive value [NPV] 96.4% in all three imaging criteria). By contrast, WB-MRI showed low accuracy in assessment of clinical CR (sensitivity 4.5%, specificity 98.1%, PPV 50.0%, NPV 71.2% in all three imaging criteria). As to the clinical objective response, the diagnostic accuracy was higher in MDA-DWI criteria than RECIST 1.1 and MDA criteria (sensitivity/specificity/PPV/NPV, 84.2%/94.4%/98.0%/65.4, 54.4%/100%/100%/40.9, and 61.4%/94.4%/97.2%/43.6%, respectively). CONCLUSIONS In the imaging response assessment of multiple myeloma, WB-MRI showed excellent performance in the evaluation of PD, but not in the assessment of CR or objective response. When adding DWI to imaging response criteria, diagnostic accuracy for objective response was improved and agreement between imaging and clinical responses was increased.
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Affiliation(s)
- Ho Young Park
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea
| | - Kyung Won Kim
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
| | - Min A Yoon
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea
| | - Min Hee Lee
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea
| | - Eun Jin Chae
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea
| | - Jeong Hyun Lee
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea
| | - Hye Won Chung
- Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Clinical Trial Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea
| | - Dok Hyun Yoon
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
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Do HM, Spear LG, Nikpanah M, Mirmomen SM, Machado LB, Toscano AP, Turkbey B, Bagheri MH, Gulley JL, Folio LR. Augmented Radiologist Workflow Improves Report Value and Saves Time: A Potential Model for Implementation of Artificial Intelligence. Acad Radiol 2020; 27:96-105. [PMID: 31818390 DOI: 10.1016/j.acra.2019.09.014] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 09/12/2019] [Accepted: 09/17/2019] [Indexed: 12/12/2022]
Abstract
RATIONALE AND OBJECTIVES Our primary aim was to improve radiology reports by increasing concordance of target lesion measurements with oncology records using radiology preprocessors (RP). Faster notification of incidental actionable findings to referring clinicians and clinical radiologist exam interpretation time savings with RPs quantifying tumor burden were also assessed. MATERIALS AND METHODS In this prospective quality improvement initiative, RPs annotated lesions before radiologist interpretation of CT exams. Clinical radiologists then hyperlinked approved measurements into interactive reports during interpretations. RPs evaluated concordance with our tumor measurement radiologist, the determinant of tumor burden. Actionable finding detection and notification times were also deduced. Clinical radiologist interpretation times were calculated from established average CT chest, abdomen, and pelvis interpretation times. RESULTS RPs assessed 1287 body CT exams with 812 follow-up CT chest, abdomen, and pelvis studies; 95 (11.7%) of which had 241 verified target lesions. There was improved concordance (67.8% vs. 22.5%) of target lesion measurements. RPs detected 93.1% incidental actionable findings with faster clinician notification by a median time of 1 hour (range: 15 minutes-16 hours). Radiologist exam interpretation times decreased by 37%. CONCLUSIONS This workflow resulted in three-fold improved target lesion measurement concordance with oncology records, earlier detection and faster notification of incidental actionable findings to referring clinicians, and decreased exam interpretation times for clinical radiologists. These findings demonstrate potential roles for automation (such as AI) to improve report value, worklist prioritization, and patient care.
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Peacock JG, Christensen CT, Banks KP. RESISTing the Need to Quantify: Putting Qualitative FDG-PET/CT Tumor Response Assessment Criteria into Daily Practice. AJNR Am J Neuroradiol 2019; 40:1978-1986. [PMID: 31780460 DOI: 10.3174/ajnr.a6294] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 09/11/2019] [Indexed: 12/20/2022]
Abstract
Tumor response assessments are essential to evaluate cancer treatment efficacy and prognosticate survival in patients with cancer. Response criteria have evolved over multiple decades, including many imaging modalities and measurement schema. Advances in FDG-PET/CT have led to tumor response criteria that harness the power of metabolic imaging. Qualitative PET/CT assessment schema are easy to apply clinically, are reproducible, and yield good prognostic results. We present 3 such criteria, namely, the Lugano classification for lymphoma, the Hopkins criteria, and the Neck Imaging Reporting and Data Systems criteria for head and neck cancers. When comparing baseline PET/CTs with interim or end-of-treatment PET/CTs, radiologists can classify the tumor response as complete metabolic response, partial metabolic response, no metabolic response, or progressive disease, which has important implications in directing further cancer management and long-term patient prognosis. The purpose of this article is to review the progression of tumor response assessments from CT- and PET/CT-based quantitative and semi-quantitative systems to PET/CT-based qualitative systems; introduce the classification schema for these systems; and describe how to use these rapid, powerful, and qualitative PET/CT-based systems in daily practice through illustrative cases.
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Affiliation(s)
- J G Peacock
- From the Department of Radiology (J.G.P., K.P.B.), Brooke Army Medical Center, San Antonio, Texas
| | - C T Christensen
- Department of Radiology (C.T.C.), Wilford Hall Ambulatory Surgical Center, San Antonio, Texas
| | - K P Banks
- From the Department of Radiology (J.G.P., K.P.B.), Brooke Army Medical Center, San Antonio, Texas
- Department of Radiology (K.P.B.), Uniformed Services University of the Health Sciences, Bethesda, Maryland
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ACR Practice Parameter for the Performance of Gallium-68 DOTATATE PET/CT for Neuroendocrine Tumors. Clin Nucl Med 2018; 43:899-908. [PMID: 30394933 DOI: 10.1097/rlu.0000000000002309] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Radiopharmaceuticals targeting cell surface expression of somatostatin receptors (SSTRs) are particularly useful in the evaluation of neuroendocrine tumors. Gallium-68 DOTA-Tyr-octreotatate (Ga-DOTATATE) primarily binds to SSTR type 2 receptors. Ga DOTATATE PET/CT is proven to have high impact on the management of neuroendocrine patients compared to traditional anatomical imaging as well as provides additional information over that of conventional nuclear medicine studies (indium-III DTPA-octreotide). It can result in change in management of approximately 75% of patients with neuroendocrine tumors. Ga DOTATATE and F FDG PET/CT imaging are complementary, with the degree of uptake varying depending on the degree of differentiation of the tumor. Well-differentiated tumors maintain their SSTRs and are positive on Ga DOTATATE PET/CT scan, while dedifferentiated tumors are less likely to demonstrate uptake of Ga DOTATATE but will demonstrate uptake with F FDG PET/CT. In addition, Ga DOTATATE PET/CT identifies patients with SSTR expression in their tumors, who have progressed on somatostatin analog therapy, for treatment with Lu DOTATATE.
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28
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Huh J, Park J, Kim KW, Kim HJ, Lee JS, Lee JH, Jeong YK, Shinagare AB, Ramaiya NH. Optimal Phase of Dynamic Computed Tomography for Reliable Size Measurement of Metastatic Neuroendocrine Tumors of the Liver: Comparison between Pre- and Post-Contrast Phases. Korean J Radiol 2018; 19:1066-1076. [PMID: 30386138 PMCID: PMC6201971 DOI: 10.3348/kjr.2018.19.6.1066] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 04/22/2018] [Indexed: 11/16/2022] Open
Abstract
Objective The reliability of size measurements of liver metastases from neuroendocrine tumors (NETs) on contrast-enhanced computed tomography (CT) phases made by different readers may be hampered due to transient, variable rim enhancement in arterial phase (AP) or portal venous phase (PVP) images. We aimed to assess the reliability of tumor size measurements in pre- and post-contrast scans. Materials and Methods The study coordinator selected target lesions according to Response Evaluation Criteria in Solid Tumors 1.1 guidelines in 44 consecutive patients with pathologically confirmed NET liver metastases. Two blinded readers measured the longest diameters of target lesions on pre-contrast, AP, and PVP images twice with a 4-week interval. Inter- and intra-observer agreements were evaluated using Bland-Altman plots and 95% limit of agreement (LOA) calculations. Results Of the 79 target lesions (approximate mean size of 3 cm), 45 showed rim enhancement. Inter-observer agreement assessed based on LOA was highest in pre-contrast CT images (−6.1–5.7 mm), followed by PVP (−7.9–7.1 mm) and AP (−8.5–7.4 mm) images. Intra-observer agreement showed the same trend: −2.8–2.9 mm and −2.9–2.9 mm for readers 1 and 2, respectively, on pre-contrast CT, −2.8–2.9 mm and −3.0–3.2 mm, respectively, on PVP, and −3.2–4.2 mm and −3.4–3.2 mm, respectively, on AP images. Mean tumor diameters differed significantly among the phases in the following increasing order: pre-contrast CT, PVP, and AP images. Conclusion There was better inter- and intra-observer agreement in size measurements of NET liver metastases on precontrast scans than on AP and PVP scans. Pre-contrast CT may be the optimal for measuring NET liver metastases if its accuracy is proven.
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Affiliation(s)
- Jimi Huh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.,Department of Radiology, Ajou University School of Medicine and Graduate School of Medicine, Ajou University Hospital, Suwon 16499, Korea
| | - Jisuk Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Kyung Won Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Hyoung Jung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Jong Seok Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Jong Hwa Lee
- Department of Radiology, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan 44033, Korea
| | - Yoong Ki Jeong
- Department of Radiology, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan 44033, Korea
| | - Atul B Shinagare
- Department of Imaging, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - Nikhil H Ramaiya
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH 44106, USA
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Zhou J, Sun HC, Wang Z, Cong WM, Wang JH, Zeng MS, Yang JM, Bie P, Liu LX, Wen TF, Han GH, Wang MQ, Liu RB, Lu LG, Ren ZG, Chen MS, Zeng ZC, Liang P, Liang CH, Chen M, Yan FH, Wang WP, Ji Y, Cheng WW, Dai CL, Jia WD, Li YM, Li YX, Liang J, Liu TS, Lv GY, Mao YL, Ren WX, Shi HC, Wang WT, Wang XY, Xing BC, Xu JM, Yang JY, Yang YF, Ye SL, Yin ZY, Zhang BH, Zhang SJ, Zhou WP, Zhu JY, Liu R, Shi YH, Xiao YS, Dai Z, Teng GJ, Cai JQ, Wang WL, Dong JH, Li Q, Shen F, Qin SK, Fan J. Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China (2017 Edition). Liver Cancer 2018; 7:235-260. [PMID: 30319983 PMCID: PMC6167671 DOI: 10.1159/000488035] [Citation(s) in RCA: 406] [Impact Index Per Article: 67.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 02/24/2018] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) (about 85-90% of primary liver cancer) is particularly prevalent in China because of the high prevalence of chronic hepatitis B infection. HCC is the fourth most common malignancy and the third leading cause of tumor-related deaths in China. It poses a significant threat to the life and health of Chinese people. SUMMARY This guideline presents official recommendations of the National Health and Family Planning Commission of the People's Republic of China on the surveillance, diagnosis, staging, and treatment of HCC occurring in China. The guideline was written by more than 50 experts in the field of HCC in China (including liver surgeons, medical oncologists, hepatologists, interventional radiologists, and diagnostic radiologists) on the basis of recent evidence and expert opinions, balance of benefits and harms, cost-benefit strategies, and other clinical considerations. KEY MESSAGES The guideline presents the Chinese staging system, and recommendations regarding patients with HCC in China to ensure optimum patient outcomes.
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Affiliation(s)
- Jian Zhou
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Hui-Chuan Sun
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Zheng Wang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Wen-Ming Cong
- Department of Pathology, the Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Jian-Hua Wang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Meng-Su Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jia-Mei Yang
- Department of Hepatic Surgery, the Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Ping Bie
- Institute of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Lian-Xin Liu
- Department of General Surgery, the First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tian-Fu Wen
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Guo-Hong Han
- Department of Liver Diseases and Digestive Interventional Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Mao-Qiang Wang
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing, China
| | - Rui-Bao Liu
- Department of Interventional Radiology, the Tumor Hospital of Harbin Medical University, Harbin, China
| | - Li-Gong Lu
- Department of Interventional Oncology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zheng-Gang Ren
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Min-Shan Chen
- Department of Hepatobiliary Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhao-Chong Zeng
- Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ping Liang
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Chang-Hong Liang
- Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Min Chen
- Editorial Department of Chinese Journal of Digestive Surgery, Chongqing, China
| | - Fu-Hua Yan
- Department of Radiology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wen-Ping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wen-Wu Cheng
- Department of integrated treatment, Tumor Hospital of Fudan University, Shanghai, China
| | - Chao-Liu Dai
- Department of Hepatobiliary and Spleenary Surgery, the Affiliated Shengjing Hospital, China Medical University, Shenyang, China
| | - Wei-Dong Jia
- Department of Hepatic Surgery, Affiliated Provincial Hospital, Anhui Medical University, Hefei, China
| | - Ya-Ming Li
- Department of Nuclear Medicine, the First Hospital of China Medical University, Shenyang, China
| | - Ye-Xiong Li
- Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jun Liang
- Department of Oncology, Peking University International Hospital, Beijing, China
| | - Tian-Shu Liu
- Department of Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guo-Yue Lv
- Department of General Surgery, the First Hospital of Jilin University, Jilin, China
| | - Yi-Lei Mao
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC and Chinese Academy of Medical Sciences, Beijing, China
| | - Wei-Xin Ren
- Department of Interventional Radiology, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Hong-Cheng Shi
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wen-Tao Wang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Xiao-Ying Wang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Bao-Cai Xing
- Department of Hepato-Pancreato-Biliary Surgery, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jian-Ming Xu
- Department of Gastrointestinal Oncology, Affiliated Hospital Cancer Center, Academy of Military Medical Sciences, Beijing, China
| | - Jian-Yong Yang
- Department of Interventional Oncology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ye-Fa Yang
- Department of Hepatic Surgery and Interventional Radiology, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Sheng-Long Ye
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Zheng-Yu Yin
- Department of Hepatobiliary Surgery, Zhongshan Hospital of Xiamen University, Xiamen, China
| | - Bo-Heng Zhang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Shui-Jun Zhang
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wei-Ping Zhou
- Department of Hepatic Surgery, the Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Ji-Ye Zhu
- Department of Hepatobiliary Surgery, Peking University People's Hospital, Beijing, China
| | - Rong Liu
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ying-Hong Shi
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Yong-Sheng Xiao
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Zhi Dai
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China
| | - Gao-Jun Teng
- Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Jian-Qiang Cai
- Department of Abdominal Surgical Oncology, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei-Lin Wang
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jia-Hong Dong
- Department of Hepatobiliary and Pancreas Surgery, Beijing Tsinghua Changgung Hospital (BTCH), School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Qiang Li
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Feng Shen
- Department of Hepatic Surgery, the Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
| | - Shu-Kui Qin
- Department of Medical Oncology, PLA Cancer Center, Nanjing Bayi Hospital, Nanjing, China,**Dr. Shu-Kui Qin, Department of Medical Oncology, PLA Cancer Center, Nanjing Bayi Hospital, Nanjing 210002 (China), E-Mail
| | - Jia Fan
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Fudan University, Shanghai, China,*Dr. Jia Fan, Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032 (China), E-Mail
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Goodman AM, Piccioni D, Kato S, Boichard A, Wang HY, Frampton G, Lippman SM, Connelly C, Fabrizio D, Miller V, Sicklick JK, Kurzrock R. Prevalence of PDL1 Amplification and Preliminary Response to Immune Checkpoint Blockade in Solid Tumors. JAMA Oncol 2018; 4:1237-1244. [PMID: 29902298 PMCID: PMC6139049 DOI: 10.1001/jamaoncol.2018.1701] [Citation(s) in RCA: 195] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 03/29/2018] [Indexed: 12/14/2022]
Abstract
Importance Copy number alterations in programmed cell death ligand 1 (PDL1 or CD274), programmed cell death 1 ligand 2 (PDCD1LG2 or PDL2), and Janus kinase 2 (JAK2) genes (chromosome 9p24.1) characterize Hodgkin lymphoma, resulting in high response rates to programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) blockade. The prevalence and utility of PDL1 amplification as a response biomarker to PD-1/PD-L1 blockade are unknown in other tumors. Objectives To examine the prevalence of PDL1 amplification and its utility as a response biomarker to PD-1/PD-L1 blockade in solid tumors. Design, Setting, and Participants This retrospective study (October 1, 2012, to October 1, 2017) used a deidentified tumor database from a commercial company and annotated clinical records from a subset of patients treated at a university tertiary referral center. The study analyzed 118 187 tumors from the deidentified database, including a clinically annotated subgroup of 2039 malignant tumors. Interventions Comprehensive genomic profiling was performed on all samples to determine PDL1 amplification, microsatellite instability, and tumor mutational burden (TMB). A subset of patients was treated with PD-1/PD-L1 blockade. Main Outcomes and Measures The prevalence of PDL1 amplification was determined among 118 187 patient samples that underwent next-generation sequencing. Solid tumors treated with checkpoint blockade were evaluated for response and progression-free survival (PFS). Results Of the 118 187 deidentified tumor samples, PDL1 amplifications were identified in 843 (0.7%), including more than 100 types of solid tumors. Most PDL1-amplified tumors (84.8%) had a low to intermediate TMB. PDL1 amplification did not always correlate with high-positive PD-L1 expression by immunohistochemical analysis. Six of 9 patients (66.7%) from 1 center with PDL1-amplified solid tumors had objective responses after checkpoint blockade administration. The median PFS among all treated patients was 15.2 months. Responders included 1 patient with glioblastoma (PFS, ≥5.2 months), 2 patients with head and neck squamous cell cancer (PFS, ≥9 and 15.2 months), 2 patients with metastatic basal cell cancer (PFS, 3.8 and ≥24.1 months), and 1 patient with urothelial cancer (PFS, ≥17.8 months). Conclusions and Relevance The results of this study suggest that PDL1 amplification occurs in a small subset of malignant tumors. Additional large-scale, prospective studies of PDL1-amplified cancers are warranted to confirm the responses to checkpoint blockade described herein, even in the absence of microsatellite instability, high PD-L1 expression, and a high TMB.
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Affiliation(s)
- Aaron M. Goodman
- Division of Hematology/Oncology, Department of Medicine, University of California, San Diego, La Jolla
- Moores Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla
- Division of Blood and Marrow Transplantation, Department of Medicine, University of California, San Diego, La Jolla
| | - David Piccioni
- Division of Neurological Oncology, Department of Neurology, University of California, San Diego, La Jolla
| | - Shumei Kato
- Division of Hematology/Oncology, Department of Medicine, University of California, San Diego, La Jolla
- Moores Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla
| | - Amélie Boichard
- Moores Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla
| | - Huan-You Wang
- Department of Pathology, University of California, San Diego, La Jolla
| | | | - Scott M. Lippman
- Division of Hematology/Oncology, Department of Medicine, University of California, San Diego, La Jolla
- Moores Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla
| | | | | | | | - Jason K. Sicklick
- Department of Surgery, Division of Surgical Oncology, University of California, San Diego, La Jolla
| | - Razelle Kurzrock
- Division of Hematology/Oncology, Department of Medicine, University of California, San Diego, La Jolla
- Moores Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla
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Goyal N, Apolo AB, Berman ED, Bagheri MH, Levine JE, Glod JW, Kaplan RN, Machado LB, Folio LR. ENABLE (Exportable Notation and Bookmark List Engine): an Interface to Manage Tumor Measurement Data from PACS to Cancer Databases. J Digit Imaging 2018; 30:275-286. [PMID: 28074302 DOI: 10.1007/s10278-016-9938-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Oncologists evaluate therapeutic response in cancer trials based on tumor quantification following selected "target" lesions over time. At our cancer center, a majority of oncologists use Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 quantifying tumor progression based on lesion measurements on imaging. Currently, our oncologists handwrite tumor measurements, followed by multiple manual data transfers; however, our Picture Archiving Communication System (PACS) (Carestream Health, Rochester, NY) has the ability to export tumor measurements, making it possible to manage tumor metadata digitally. We developed an interface, "Exportable Notation and Bookmark List Engine" (ENABLE), which produces prepopulated RECIST v1.1 worksheets and compiles cohort data and data models from PACS measurement data, thus eliminating handwriting and manual data transcription. We compared RECIST v1.1 data from eight patients (16 computed tomography exams) enrolled in an IRB-approved therapeutic trial with ENABLE outputs: 10 data fields with a total of 194 data points. All data in ENABLE's output matched with the existing data. Seven staff were taught how to use the interface with a 5-min explanatory instructional video. All were able to use ENABLE successfully without additional guidance. We additionally assessed 42 metastatic genitourinary cancer patients with available RECIST data within PACS to produce a best response waterfall plot. ENABLE manages tumor measurements and associated metadata exported from PACS, producing forms and data models compatible with cancer databases, obviating handwriting and the manual re-entry of data. Automation should reduce transcription errors and improve efficiency and the auditing process.
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Affiliation(s)
- Nikhil Goyal
- Radiology and Imaging Sciences, CC, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Andrea B Apolo
- Genitourinary Malignancies Branch, NCI, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Eliana D Berman
- Genitourinary Malignancies Branch, NCI, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Mohammad Hadi Bagheri
- Radiology and Imaging Sciences, CC, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Jason E Levine
- Center for Cancer Research, NCI, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - John W Glod
- Pediatric Oncology Branch, CCR, NCI, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Rosandra N Kaplan
- Pediatric Oncology Branch, CCR, NCI, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Laura B Machado
- Radiology and Imaging Sciences, CC, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Les R Folio
- Radiology and Imaging Sciences, CC, NIH, Building 10, 9000 Rockville Pike, Bethesda, MD, 20892, USA.
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Korkmaz Kirakli E, Oztekin O. Is Hippocampal Avoidance During Whole-Brain Radiotherapy Risky for Patients With Small-Cell Lung Cancer? Hippocampal Metastasis Rate and Associated Risk Factors. Technol Cancer Res Treat 2017; 16:1202-1208. [PMID: 29332467 PMCID: PMC5762091 DOI: 10.1177/1533034617742301] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Objectives: Hippocampal avoidance during whole-brain radiotherapy is performed to prevent neural stem cell injury causing neurocognitive dysfunction. Nevertheless, the estimated risk of metastases in hippocampal avoidance area in small-cell lung cancer is unknown. The current study aimed to characterize the metastatic distribution within the brain relative to the hippocampus, estimate the incidence of hippocampal metastasis in patients with small-cell lung cancer, and identify clinical and radiographic variables that may be associated with the risk of hippocampal avoidance area metastasis. Materials and Methods: Patients with small-cell lung cancer treated with therapeutic whole-brain radiotherapy between January 2010 and December 2015 were reviewed. T1-weighted, postcontrast axial magnetic resonance images obtained just before therapeutic cranial irradiation were retrieved and reviewed for each patient. The hippocampal avoidance area was defined as hippocampus and 5-mm ring area adjacent to the hippocampus to account for necessary dose falloff between the hippocampus and the whole-brain planning target volume. Metastatic lesions within hippocampal avoidance area were defined as hippocampal metastasis. Hippocampal metastasis rate and characteristics of patients with hippocampal metastasis were analyzed and compared to patients without hippocampal metastasis. Results: Fifty-four patients evaluated with cranial magnetic resonance imaging were enrolled. Hippocampal metastasis rate was 32% (17 patients). A total of 4.4% of all metastases involved the hippocampal avoidance area. The most common location was frontal lobe. Being younger than 65 years of age was found to be an independent risk factor for HM (odds ratio: 4.8, 95% confidence interval: 1-23.2, P = .049). The number of brain metastases was significantly higher in patients with hippocampal metastasis (P = .027), and hippocampal metastasis rate was also higher in patients having larger hippocampus (P = .026) and larger brain volumes (P = .02). Conclusion: Hippocampal metastasis might be more common in small-cell lung cancer. Reducing the dose to the hippocampus by hippocampal avoiding whole-brain radiotherapy plan in small-cell lung cancer may be risky for the development of HM compared with other malignant solid tumors.
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Affiliation(s)
| | - Ozgur Oztekin
- 2 Tepecik Education and Research Hospital, Izmir, Turkey
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Bang JI, Lim Y, Paeng JC, Han SW, Park S, Lee JM, Kim HJ, Cheon GJ, Lee DS, Chung JK, Kim TY, Kang KW. Comparison of Quantitative Methods on FDG PET/CT for Treatment Response Evaluation of Metastatic Colorectal Cancer. Nucl Med Mol Imaging 2017; 51:147-153. [PMID: 28559939 DOI: 10.1007/s13139-016-0449-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 08/21/2016] [Accepted: 08/30/2016] [Indexed: 11/26/2022] Open
Abstract
PURPOSE FDG PET is effective in treatment response evaluation of cancer. However, there is no standard method for quantitative evaluation of FDG PET, particularly regarding cytostatic drugs. We compared various FDG PET quantitative methods in terms of response determination. METHODS A total of 39 refractory metastatic colorectal cancer patients who received a multikinase inhibitor treatment were included. Baseline and posttreatment FDG PET/CT scans were performed before and two cycles after treatment. Standardized uptake value (SUV) and total lesion glycolysis (TLG) values using various margin thresholds (30-70 % of maximum SUV with increment 10 %, twice mean SUV of blood pool, SUV 3.0, and SUV 4.0) were measured, with measurement target of the hottest lesion or a maximum of five hottest lesions. Treatment response by the PERCIST criteria was also determined. Predictive values of the PET indexes were evaluated in terms of the treatment response determined by the RECIST 1.1 criteria. RESULTS The agreement rate was 38 % between response determined by the PERCIST and the RECIST criteria (κ = 0.381). When patients were classified into disease control group (PR, SD) and non-control group (PD) by the RECIST criteria, percent changes of TLG with various margin thresholds (particularly, 30-50 % of maximum SUV) exhibited significant differences between the two groups, and high diagnostic power for the response by the RECIST criteria. TLG-based criteria, which used a margin threshold of 50 % of maximum SUV, exhibited a high agreement with the RECIST criteria compared with the PERCIST criteria (κ = 0.606). CONCLUSION In metastatic colorectal cancer, FDG PET/CT could be effective for treatment response evaluation by using TLG measured by margin thresholds of 30-50 % of maximum SUV. Further studies are warranted regarding the optimal cutoff values for this method.
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Affiliation(s)
- Ji-In Bang
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Yoojoo Lim
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Jin Chul Paeng
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Sae-Won Han
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Sohyun Park
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Jung Min Lee
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Hyun Joo Kim
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Gi Jeong Cheon
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - June-Key Chung
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Tae-You Kim
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
| | - Keon Wook Kang
- Department of Nuclear Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080 Korea
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Radiology Reports With Hyperlinks Improve Target Lesion Selection and Measurement Concordance in Cancer Trials. AJR Am J Roentgenol 2017; 208:W31-W37. [PMID: 28112557 DOI: 10.2214/ajr.16.16845] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Radiology reports often lack the measurements of target lesions that are needed for oncology clinical trials. When available, the measurements in the radiology reports often do not match those in the records used to calculate therapeutic response. This study assessed the clinical value of hyperlinked tumor measurements in multimedia-enhanced radiology reports in the PACS and the inclusion of a radiologist assistant in the process of assessing tumor burden. MATERIALS AND METHODS We assessed 489 target lesions in 232 CT examinations of 71 patients with metastatic genitourinary cancer enrolled in two therapeutic trials. We analyzed target lesion selection and measurement concordance between oncology records (used to calculate therapeutic response) and two types of radiology reports in the PACS: multimedia-enhanced radiology reports and text-only reports. For statistical tests, we used the Wilcoxon signed rank, Wilcoxon rank sum test, and Fisher method to combine p values from the paired and unpaired results. The Fisher exact test was used to compare overall measurement concordance. RESULTS Concordance on target lesion selection was greater for multimedia-enhanced radiology reports (78%) than the text-only reports (52%) (p = 0.0050). There was also improved overall measurement concordance with the multimedia-enhanced radiology reports (68%) compared with the text-only reports (38%) (p < 0.0001). CONCLUSION Compared with text-only reports, hyperlinked multimedia-enhanced radiology reports improved concordance of target lesion selection and measurement with the measurements used to calculate therapeutic response.
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Pre-therapeutic factors for predicting survival after radioembolization: a single-center experience in 389 patients. Eur J Nucl Med Mol Imaging 2017; 44:1185-1193. [PMID: 28197686 DOI: 10.1007/s00259-017-3646-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Accepted: 02/02/2017] [Indexed: 12/13/2022]
Abstract
PURPOSE To determine pre-therapeutic predictive factors for overall survival (OS) after yttrium (Y)-90 radioembolization (RE). METHODS We retrospectively analyzed the pre-therapeutic characteristics (sex, age, tumor entity, hepatic tumor burden, extrahepatic disease [EHD] and liver function [with focus on bilirubin and cholinesterase level]) of 389 consecutive patients with various refractory liver-dominant tumors (hepatocellular carcinoma [HCC], cholangiocarcinoma [CCC], neuroendocrine tumor [NET], colorectal cancer [CRC] and metastatic breast cancer [MBC]), who received Y-90 radioembolization for predicting survival. Predictive factors were selected by univariate Cox regression analysis and subsequently tested by multivariate analysis for predicting patient survival. RESULTS The median OS was 356 days (95% CI 285-427 days). Stable disease was observed in 132 patients, an objective response in 71 (one of which was complete remission) and progressive disease in 122. The best survival rate was observed in patients with NET, and the worst in patients with MBC. In the univariate analyses, extrahepatic disease (P < 0.001), large tumor burden (P = 0.001), high bilirubin levels (>1.9 mg/dL, P < 0.001) and low cholinesterase levels (CHE <4.62 U/I, P < 0.001) at baseline were significantly associated with poor survival. Tumor entity, tumor burden, extrahepatic disease and CHE were confirmed in the multivariate analysis as independent predictors of survival. Sex, applied RE dose and age had no significant influence on OS. CONCLUSIONS Pre-therapeutic baseline bilirubin and CHE levels, extrahepatic disease and hepatic tumor burden are associated with patient survival after RE. Such parameters may be used to improve patient selection for RE of primary or metastatic liver tumors.
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Simplified response monitoring criteria for multiple myeloma in patients undergoing therapy with novel agents using computed tomography. Eur J Radiol 2016; 85:2195-2199. [PMID: 27842666 DOI: 10.1016/j.ejrad.2016.10.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 08/24/2016] [Accepted: 10/14/2016] [Indexed: 11/22/2022]
Abstract
INTRODUCTION Multiple myeloma is a malignant hematological disorder of the mature B-cell lymphocytes originating in the bone marrow. While therapy monitoring is still mainly based on laboratory biomarkers, the additional use of imaging has been advocated due to inaccuracies of serological biomarkers or in a-secretory myelomas. Non-enhanced CT and MRI have similar sensitivities for lesions in yellow marrow-rich bone marrow cavities with a favourable risk and cost-effectiveness profile of CT. Nevertheless, these methods are still limited by frequently high numbers of medullary lesions and its time consumption for proper evaluation. OBJECTIVE To establish simplified response criteria by correlating size and CT attenuation changes of medullary multiple myeloma lesions in the appendicular skeleton with the course of lytic bone lesions in the entire skeleton. Furthermore to evaluate these criteria with respect to established hematological myeloma-specific parameters for the prediction of treatment response to bortezomib or lenalidomide. MATERIALS AND METHODS Non-enhanced reduced-dose whole-body CT examinations of 78 consecutive patients (43 male, 35 female, mean age 63.69±9.2years) with stage III multiple myeloma were retrospectively re-evaluated. On per patient basis, size and mean CT attenuation of 2-4 representative lesions in the limbs were measured at baseline and at a follow-up after a mean of 8 months. Results were compared with the course of lytical bone lesions as well with that of specific hematological biomarkers. Myeloma response was assessed according to the International Myeloma Working Group (IMWG) uniform response criteria. Testing for correlation between response of medullary lesions (Respmed) and response of all myeloma manifestations including osteolyses (Resptotal) was performed using the corrected contingency coefficient (Ccorr). RESULTS The correlation between Respmed based on length diameter and transverse diameter and Resptotal was perfect (Ccorr=1.0; p<0.0001) whereas the correlation based on density was moderate (Ccorr=0.54; p<0.0001). The evaluation of simplified response criteria with a measurement of only 2 medullary lesions yielded the best sensitivity and specificity valued for treatment-induced changes for the length diameter evaluation with 94.4%/95.7% for prediction of progressive disease and 78.6%/93.3% for prediction of therapy response. There were no significant differences between patients treated with bortezomib and lenalidomide (p>0.05). CONCLUSION Measurements of size of a minimum of two medullary lesions is sufficient for response assessment and correlates very well with the course of lytic bone lesions and that of hematologic parameters.
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Sheikhbahaei S, Mena E, Pattanayak P, Taghipour M, Solnes LB, Subramaniam RM. Molecular Imaging and Precision Medicine: PET/Computed Tomography and Therapy Response Assessment in Oncology. PET Clin 2016; 12:105-118. [PMID: 27863562 DOI: 10.1016/j.cpet.2016.08.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
A variety of methods have been developed to assess tumor response to therapy. Standardized qualitative criteria based on 18F-fluoro-deoxyglucose PET/computed tomography have been proposed to evaluate the treatment effectiveness in specific cancers and these allow more accurate therapy response assessment and survival prognostication. Multiple studies have addressed the utility of the volumetric PET biomarkers as prognostic indicators but there is no consensus about the preferred segmentation methodology for these metrics. Heterogeneous intratumoral uptake was proposed as a novel PET metric for therapy response assessment. PET imaging techniques will be used to study the biological behavior of cancers during therapy.
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Affiliation(s)
- Sara Sheikhbahaei
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD 21287, USA
| | - Esther Mena
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD 21287, USA
| | - Puskar Pattanayak
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD 21287, USA
| | - Mehdi Taghipour
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD 21287, USA
| | - Lilja B Solnes
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD 21287, USA
| | - Rathan M Subramaniam
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD 21287, USA; Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Department of Biomedical Engineering, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.
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Robust evidence for long-term survival with 90Y radioembolization in chemorefractory liver-predominant metastatic colorectal cancer. Eur Radiol 2016; 27:113-119. [PMID: 27059858 DOI: 10.1007/s00330-016-4345-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2015] [Revised: 02/14/2016] [Accepted: 03/21/2016] [Indexed: 12/16/2022]
Abstract
OBJECTIVES Our aim was to provide further evidence for the efficacy/safety of radioembolization using yttrium-90-resin microspheres for unresectable chemorefractory liver metastases from colorectal cancer (mCRC). METHODS We followed 104 consecutively treated patients until death. Overall survival (OS) was calculated from the day of the first radioembolization procedure. Response was defined by changes in tumour volume as defined by Response Evaluation Criteria in Solid Tumours (RECIST) v1.0 and/or a ≥30 % reduction in serum carcinoembryonic antigen (CEA) at 3 months. RESULTS Survival varied between 23 months in patients who had a complete response to prior chemotherapy and 13 months in patients with a partial response or stable disease. Median OS also significantly improved (from 5.8 months to 17.1 months) if response durability to radioembolization extended beyond 6 months. Patients with a positive trend in CEA serum levels (≥30 % reduction) at 3 months post-radioembolization also had a survival advantage compared with those who did not: 15.0 vs 6.7 months. Radioembolization was well tolerated. Grade 3 increases in bilirubin were reported in 5.0 % of patients at 3 months postprocedure. CONCLUSIONS After multiple chemotherapies, many patients still have a good performance status and are eligible for radioembolization. This single procedure can achieve meaningful survivals and is generally well tolerated. KEY POINTS • After multiple chemotherapies, many patients are still eligible for radioembolization (RE). • RE can achieve meaningful survival in patients with chemorefractory liver-predominant metastatic colorectal cancer (mCRC). • Tumour responsiveness to prior systemic treatments is a significant determinant of overall survival (OS) after RE. • Radioembolization in patients with a good performance status is generally well tolerated.
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Kennedy AS, Ball DS, Cohen SJ, Cohn M, Coldwell DM, Drooz A, Ehrenwald E, Kanani S, Nutting CW, Moeslein FM, Putnam SG, Rose SC, Savin MA, Schirm S, Sharma NK, Wang EA. Hepatic imaging response to radioembolization with yttrium-90-labeled resin microspheres for tumor progression during systemic chemotherapy in patients with colorectal liver metastases. J Gastrointest Oncol 2015; 6:594-604. [PMID: 26697190 DOI: 10.3978/j.issn.2078-6891.2015.082] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND To assess response and the impact of imaging artifacts following radioembolization with yttrium-90-labeled resin microspheres ((90)Y-RE) based on the findings from a central independent review of patients with liver-dominant metastatic colorectal cancer (mCRC). METHODS Patients with mCRC who received (90)Y-RE (SIR-Spheres(®); Sirtex Medical, Sydney, Australia) at nine US institutions between July 2002 and December 2011 were included in the analysis. Tumor response was assessed at baseline and 3 months using either the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.0 or 1.1. For each lesion, known artifacts affecting the interpretation of response (peri-tumoral edema and necrosis) were documented. Survivals (Kaplan-Meier analyses) were compared in responders [partial response (PR)] and non-responders [stable (SD) or progressive disease (PD)]. RESULTS Overall, 195 patients (mean age 62 years) received (90)Y-RE after a median of 2 (range, 1-6) lines of prior chemotherapy. Using RECIST 1.0 and RECIST 1.1, 7.6% and 6.9% of patients were partial responders, 47.3% and 48.1% had SD, and 55.0% and 55.0% PD, respectively. RECIST 1.0 and RECIST 1.1 showed excellent agreement {Kappa =0.915 [95% confidence interval (CI): 0.856-0.975]}. Peri-tumoral edema was documented in 32.8%, necrosis in 48.1% and both in 57.3% of cases (using RECIST 1.0). Although baseline characteristics were similar in responders and non-responders (P>0.05), responders survived significantly longer in an analysis according to RECIST 1.0: PR median (95% CI) 25.2 (range, 9.2-49.4) months vs. SD 15.8 (range, 9.3-21.1) months vs. PD 7.1 (range, 6.0-9.5) months (P<0.0001). CONCLUSIONS RECIST 1.0 and RECIST 1.1 imaging responses provide equivalent interpretations in the assessment of hepatic tumors following (90)Y-RE. Radiologic lesion responses at 3 months must be interpreted with caution due to the significant proportion of patients with peri-tumoral edema and necrosis, which may lead to an under-estimation of PR/SD. Nevertheless, 3-month radiologic responses were predictive of prolonged survival.
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Affiliation(s)
- Andrew S Kennedy
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - David S Ball
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Steven J Cohen
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Michael Cohn
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Douglas M Coldwell
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Alain Drooz
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Eduardo Ehrenwald
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Samir Kanani
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Charles W Nutting
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Fred M Moeslein
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Samuel G Putnam
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Steven C Rose
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Michael A Savin
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Sabine Schirm
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Navesh K Sharma
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Eric A Wang
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
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Venturini M, Colantoni C, Modorati G, Di Nicola M, Colucci A, Agostini G, Picozzi P, De Cobelli F, Parmiani G, Mortini P, Bandello F, Del Maschio A. Preliminary results of contrast-enhanced sonography in the evaluation of the response of uveal melanoma to gamma-knife radiosurgery. JOURNAL OF CLINICAL ULTRASOUND : JCU 2015; 43:421-430. [PMID: 25703863 DOI: 10.1002/jcu.22262] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2014] [Revised: 09/19/2014] [Accepted: 09/27/2014] [Indexed: 06/04/2023]
Abstract
PURPOSE Our aim was to prospectively analyze the use of contrast-enhanced ultrasound (CEUS) in the quantitative assessment of the response of uveal melanoma (UM) to gamma-knife radiosurgery (GKR), investigating whether changes in tumor vascularization precede thickness reduction, which on average occurs at 12 months after GKR. METHODS Ten patients with UM treated with GKR underwent sonography (US) and CEUS at baseline and at 3, 6, and 12 months after GKR. The transverse diameter, thickness, and quantitative parameters of the UM (ie, area under the curve in the wash-in phase, wash-in perfusion index, peak enhancement, and wash-in rate) were calculated by using dedicated software and compared by using Wilcoxon's signed-rank test. RESULTS The mean tumor thickness on US was significantly less at both 6 (6.6 mm) and 12 months after GKR (5.8 mm) than it was at baseline (8.3 mm; p < 0.05, both comparisons). Compared with baseline data, the median flow quantitative parameters on CEUS were significantly changed as follows: the peak enhancement (in arbitrary units [au]) at baseline was 5 × 10(6) ; 6 months after GKR, it was 2 × 10(1) (p < 0.05), and 12 months after GKR, it was 4 × 10(1) (p < 0.05). The wash-in rate (in au) at baseline was 1 × 10(6) ; 6 months after GKR, it was 2.1 (p < 0.05), and 12 months after GKR, it was 9.3 (p < 0.05). The wash-in perfusion index (in au) at baseline was 2 × 10(7) ; 6 months after GKR, it was 7 × 10(1) (p < 0.05), and 12 months after GKR, it was 1 × 10(2) (p < 0.05). The area under the curve during the wash-in phase (in au) at baseline was 1 × 10(8) ; 12 months after GKR, it was reduced to 6 × 10(2) (p < 0.05). CONCLUSIONS At 6 months after GKR, a reduction of tumor thickness, as detected on US, occurred in 6 of the 10 patients, whereas a reduction in all the quantitative parameters measured on CEUS occurred in all 10 patients. However, a larger population is needed to investigate whether CEUS could become the first-choice technique for monitoring the response of UM to GKR.
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Affiliation(s)
- Massimo Venturini
- Department of Radiology, San Raffaele Scientific Institute, Milan, Italy
| | - Caterina Colantoni
- Department of Radiology, San Raffaele Scientific Institute, Milan, Italy
| | - Giulio Modorati
- Department of Ophthalmology, San Raffaele Scientific Institute, Milan, Italy
| | - Maura Di Nicola
- Department of Ophthalmology, San Raffaele Scientific Institute, Milan, Italy
| | - Annalisa Colucci
- Department of Ophthalmology, San Raffaele Scientific Institute, Milan, Italy
| | - Giulia Agostini
- Department of Radiology, San Raffaele Scientific Institute, Milan, Italy
| | - Piero Picozzi
- Department of Neurosurgery, San Raffaele Scientific Institute, Milan, Italy
| | - Francesco De Cobelli
- Department of Radiology, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Giorgio Parmiani
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Oncology, San Raffaele Scientific Institute, Milan, Italy
| | - Pietro Mortini
- Department of Neurosurgery, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Francesco Bandello
- Department of Ophthalmology, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Alessandro Del Maschio
- Department of Radiology, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
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Folio LR, Turkbey EB, Steinberg SM, Apolo AB. Viable tumor volume: Volume of interest within segmented metastatic lesions, a pilot study of proposed computed tomography response criteria for urothelial cancer. Eur J Radiol 2015; 84:1708-14. [PMID: 26149529 DOI: 10.1016/j.ejrad.2015.05.026] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 05/16/2015] [Accepted: 05/18/2015] [Indexed: 01/11/2023]
Abstract
OBJECTIVES To evaluate the ability of new computed tomography (CT) response criteria for solid tumors such as urothelial cancer (VTV; viable tumor volume) to predict overall survival (OS) in patients with metastatic bladder cancer treated with cabozantinib. MATERIALS AND METHODS We compared the relative capabilities of VTV, RECIST, MASS (morphology, attenuation, size, and structure), and Choi criteria, as well as volume measurements, to predict OS using serial follow-up contrast-enhanced CT exams in patients with metastatic urothelial carcinoma. Kaplan-Meier curves and 2-tailed log-rank tests compared OS based on early RECIST 1.1 response against each of the other criteria. A Cox proportional hazards model assessed response at follow-up exams as a time-varying covariate for OS. RESULTS We assessed 141 lesions in 55CT scans from 17 patients with urothelial metastasis, comparing VTV, RECIST, MASS, and Choi criteria, and volumetric measurements, for response assessment. Median follow-up was 4.5 months, range was 2-14 months. Only the VTV criteria demonstrated a statistical association with OS (p=0.019; median OS 9.7 vs. 3.5 months). CONCLUSION This pilot study suggests that VTV is a promising tool for assessing tumor response and predicting OS, using criteria that incorporate tumor volume and density in patients receiving antiangiogenic therapy for urothelial cancer. Larger studies are warranted to further validate these findings.
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Affiliation(s)
- Les Roger Folio
- Lead Radiologist for CT, NIH Radiology and Imaging Sciences, 10 Center Drive, Bethesda, MD 20892, USA.
| | | | - Seth M Steinberg
- Head, Biostatistics and Data Management Section, Office of the Clinical Director, Center for Cancer Research, National Cancer Institute, 9609 Medical Center Drive, Room 2W334, MSC 9716, Bethesda, MD 20892, USA.
| | - Andrea B Apolo
- Genitourinary Malignancies Branch, National Cancer Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD 20892, USA
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Kundapur V, Ellchuk T, Ahmed S, Gondi V. Risk of hippocampal metastases in small cell lung cancer patients at presentation and after cranial irradiation: a safety profile study for hippocampal sparing during prophylactic or therapeutic cranial irradiation. Int J Radiat Oncol Biol Phys 2015; 91:781-6. [PMID: 25752392 DOI: 10.1016/j.ijrobp.2014.12.026] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Revised: 12/05/2014] [Accepted: 12/10/2014] [Indexed: 01/25/2023]
Abstract
PURPOSE Neurocognitive impairment (NI) in patients with small cell lung cancer (SCLC) after whole brain radiation treatment (WBRT) is a significant cause of morbidity. Hippocampal avoidance (HA) during WBRT may mitigate or prevent NI in such patients. However, this has not been tested in SCLC patients. The estimated risk of metastases in the HA region (HM) in patients with SCLC at diagnosis or after WBRT is unknown. Our study aimed to determine the risk of HM in patients with SCLC and to assess correlated clinical factors. METHODS AND MATERIALS Patients with SCLC who experienced brain metastases (BM) at presentation (de novo) or after WBRT treated at the Saskatoon Cancer Centre between 2005 and 2012 were studied. Relevant neuroimaging was independently reviewed by a neuroradiologist. HM was defined as metastases within 5 mm of the hippocampus. Logistic regression analysis was performed to assess correlation between various clinical variables and HM. RESULTS Seventy eligible patients were identified. Of 59 patients presenting with de novo BM, 3 patients (5%, 95% confidence interval [CI]: 0%-10.7%) had HM. Collectively there were 359 (range, 1-33) de novo BM with 3 (0.8%, 95% CI: 0%-1.7%) HM deposits. Twenty patients experienced progression of metastatic disease in the brain after WBRT. Of the 20 patients, only 1 patient (5%, 95% CI: 0%-14.5%) experienced HM. On logistic regression, no factors significantly correlated with HM. CONCLUSION The overall incidence of HM before or after WBRT in SCLC patients is low, providing preliminary support for the safety of HA during planned clinical trials of HA-WBRT for SCLC.
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Affiliation(s)
- Vijayananda Kundapur
- Saskatoon Cancer Center, College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
| | - Tasha Ellchuk
- Department of Radiology, College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Shahid Ahmed
- Saskatoon Cancer Center, College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Vinai Gondi
- Cadence Health Brain Tumor Center and Cadence Health Proton Center, Chicago, Illinois
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Lam MGEH, Banerjee A, Goris ML, Iagaru AH, Mittra ES, Louie JD, Sze DY. Fusion dual-tracer SPECT-based hepatic dosimetry predicts outcome after radioembolization for a wide range of tumour cell types. Eur J Nucl Med Mol Imaging 2015; 42:1192-201. [PMID: 25916740 PMCID: PMC4480819 DOI: 10.1007/s00259-015-3048-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2014] [Accepted: 03/12/2015] [Indexed: 12/15/2022]
Abstract
Purpose Fusion dual-tracer SPECT imaging enables physiological rather than morphological voxel-based partitioning and dosimetry for 90Y hepatic radioembolization (RE). We evaluated its prognostic value in a large heterogeneous cohort of patients with extensive hepatic malignancy. Methods A total of 122 patients with primary or secondary liver malignancy (18 different cell types) underwent SPECT imaging after intraarterial injection of 99mTc macroaggregated albumin (TcMAA) as a simulation of subsequent 90Y microsphere distribution, followed by administration of an excess of intravenous 99mTc-labelled sulphur colloid (TcSC) as a biomarker for functional liver, and a second SPECT scan. TcMAA distribution was used to estimate 90Y radiation absorbed dose in tumour (DT) and in functional liver. Laboratory and clinical follow-up were recorded for 12 weeks after RE, and radiographic responses according to (m)RECIST were evaluated at 3 and 6 months. Dose–response relationships were determined for efficacy and toxicity. Results Patients were treated with a median of 1.73 GBq activity of resin microspheres (98 patients) or glass microspheres (24 patients), in a whole-liver approach (97 patients) or a lobar approach (25 patients). The objective response rate was 41 % at 3 months and 48 % at 6 months. Response was correlated with DT (P < 0.01). Median overall survival was 10.1 months (95 % confidence interval 7.4 – 12.8 months). Responders lived for 36.0 months compared to 8.7 months for nonresponders (P < 0.01). Stratified for tumour cell type, DT was independently associated with survival (P < 0.01). Absorbed dose in functional liver was correlated with toxicity grade change (P < 0.05) and RE-induced liver disease (P < 0.05). Conclusion Fusion dual-tracer SPECT imaging offers a physiology-based functional imaging tool to predict efficacy and toxicity of RE. This technique can be refined to define dosing thresholds for specific tumour types and treatments, but appears generally predictive even in a heterogeneous cohort. Electronic supplementary material The online version of this article (doi:10.1007/s00259-015-3048-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marnix G E H Lam
- Division of Interventional Radiology, Stanford University, Stanford, CA, USA,
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Castaneda CA, Flores R, Rojas KY, Castillo M, Dolores-Cerna K, Flores C, Belmar-Lopez C, Milla E, Gomez H. Prognostic factors for patients with newly diagnosed brain metastasis from breast cancer. CNS Oncol 2015; 4:137-45. [PMID: 25906174 DOI: 10.2217/cns.15.5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
AIM This retrospective study determined features associated with brain metastasis (BM) in women with breast cancer. PATIENTS & METHODS A total of 215 initially early breast cancer cases were included. We reviewed files and CT scan images of BM. RESULTS Median age was 47 years and most of our cases were stage III (58.6%), grade III (62.8%), ER negative (62.3%) and nonluminal (59.1%). Median survival after BM was 4 months. Nonluminal, extracranial disease, time to CNS shorter than 15 months, >three brain lesions and poor breast-graded prognostic assessment and recursive partitioning analysis scores were associated with shorter survival. Adding extracranial disease to breast-graded prognostic assessment score also predicted survival after BM. Radiation response was assessed in 57 patients and response tended to be associated with nonluminal phenotype but not with survival. CONCLUSION Factors associated with both initial tumor and clinical features at BM time are associated with shorter survival in our Latinas population.
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Affiliation(s)
- Carlos A Castaneda
- Medical Oncology Department, Instituto Nacional de Enfermedades Neoplasicas, Lima, Peru
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[Recommendations for radiological diagnosis and assessment of treatment response in lung cancer: a national consensus statement by the Spanish Society of Medical Radiology and the Spanish Society of Medical Oncology]. RADIOLOGIA 2014; 57:66-78. [PMID: 25530188 DOI: 10.1016/j.rx.2014.10.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Revised: 10/06/2014] [Accepted: 10/07/2014] [Indexed: 11/21/2022]
Abstract
The last decade has seen substantial progress in the diagnostic and therapeutic approach to lung cancer, thus meaning that its prognosis has improved. The Spanish Society of Medical Radiology (SERAM) and the Spanish Society of Medical Oncology (SEOM) have therefore produced a national consensus statement in order to make recommendations for radiological diagnosis and assessment of treatment response in patients with lung cancer. This expert group recommends multi-detector computed tomography (MDCT) as the technique of choice for investigating this disease. The radiology report should include a full assessment by the TNM staging system. Lastly, when the patient is on immunotherapy, response evaluation should employ not only Response Evaluation Criteria in Solid Tumours (RECIST 1.1) but also Immune-Related Response Criteria (irRC).
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Sailer AM, Douwes DCE, Cappendijk VC, Bakers FC, Wagemans BAJM, Wildberger JE, Kessels AG, Beets-Tan RGH. RECIST measurements in cancer treatment: is there a role for physician assistants? - A pilot study. Cancer Imaging 2014; 14:12. [PMID: 25608556 PMCID: PMC4331818 DOI: 10.1186/1470-7330-14-12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2014] [Accepted: 03/20/2014] [Indexed: 11/10/2022] Open
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de Castro J, Cobo M, Isla D, Puente J, Reguart N, Cabeza B, Gayete A, Sánchez M, Torres MI, Ferreirós J. Recommendations for radiological diagnosis and assessment of treatment response in lung cancer: a national consensus statement by the Spanish Society of Medical Radiology and the Spanish Society of Medical Oncology. Clin Transl Oncol 2014; 17:11-23. [PMID: 25373531 DOI: 10.1007/s12094-014-1231-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Accepted: 09/18/2014] [Indexed: 12/25/2022]
Abstract
The last decade has seen substantial progress in the diagnostic and therapeutic approach to lung cancer, thus meaning that its prognosis has improved. The Spanish Society of Medical Radiology and the Spanish Society of Medical Oncology have therefore produced a national consensus statement to make recommendations for radiological diagnosis and assessment of treatment response in patients with lung cancer. This expert group recommends multi-detector computed tomography as the technique of choice for investigating this disease. The radiology report should include a full assessment by the TNM staging system. Lastly, when the patient is on immunotherapy, response evaluation should employ not only response evaluation criteria in solid tumours, but also immune-related response criteria.
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Affiliation(s)
- J de Castro
- Oncology Department, La Paz University Hospital, Paseo de la Castellana, 261, 28046, Madrid, Spain,
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Frezza AM, Benson C, Judson IR, Litiere S, Marreaud S, Sleijfer S, Blay JY, Dewji R, Fisher C, van der Graaf W, Hayward L. Pazopanib in advanced desmoplastic small round cell tumours: a multi-institutional experience. Clin Sarcoma Res 2014; 4:7. [PMID: 25089183 PMCID: PMC4118147 DOI: 10.1186/2045-3329-4-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Accepted: 07/09/2014] [Indexed: 12/11/2022] Open
Abstract
Background We retrospectively reviewed data from nine pre-treated metastatic desmoplastic small round cell tumour (DSRCT) patients who received pazopanib. Patients and methods Three patients received pazopanib within the EORTC phase II 62043, three in the EORTC phase III 62072, and three in the context of UK named patient program. Results Nine patients were retrieved from the databases, the median age was 30 years (range: 21–47), they were all males. All had received prior chemotherapy. At the time of treatment start, 4 patients (44%) had ECOG PS 0, 4 (44%) PS 1, 1 (11%) PS 2. Best response was partial response (PR) in 2/9 (22%) patients, stable disease (SD) in 5/9 (56%) and progressive disease (PD) in 2/9 (22%) with a clinical benefit rate (PR + SD > 12 weeks) of 78%. Median PFS and OS were 9.2 (95%CI: 0–23.2) and 15.4 (95%CI: 1.5-29.3) months respectively. With a median follow-up of 20 months, 2/9 (22%) patients are still alive, all progressed. The most common toxicities included neutropenia (G1-2 45%; G3-4 11%), anaemia (G1-2 45%), fatigue (G1-2 67%), diarrhoea (G1-2 45%; G3-4 11%), nausea (G1-2 45%), hypertension (G1-2 45%) and increase in liver enzymes (G1-2 34%; G3-4 11%). Three patients (34%) required a dose reduction. One of the patients discontinued treatment because of persistent increase in total bilirubin level, one due to patient’s choice. Conclusion In this series, pazopanib showed interesting activity in DSRCT patients who progressed after prior chemotherapy without major toxicity.
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Affiliation(s)
- Anna Maria Frezza
- Medical Oncology, University Campus Bio-Medico, Via Alvaro del Portillo 200, Rome 00128, Italy
| | | | - Ian R Judson
- Sarcoma Unit, Royal Marsden Hospital, London, UK
| | | | | | - Stefan Sleijfer
- Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | | | - Raz Dewji
- GlaxoSmithKline, Oncology, Uxbridge, UK
| | - Cyril Fisher
- Sarcoma Unit, Royal Marsden Hospital, London, UK
| | - Winette van der Graaf
- Department of Medical Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
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Vourganti S, Donaldson J, Johnson L, Turkbey B, Bratslavsky G, Kotula L. Defining the radiobiology of prostate cancer progression: An important question in translational prostate cancer research. Exp Biol Med (Maywood) 2014; 239:805-812. [PMID: 24879423 DOI: 10.1177/1535370214536669] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Prostate cancer is one of the most common malignancies affecting men worldwide. High mortality rates from advanced and metastatic prostate cancer in the United States are contrasted by a relatively indolent course in the majority of cases. This gives hope for finding methods that could direct personalized diagnostic, preventative, and treatment approaches to patients with prostate cancer. Recent advances in multiparametric magnetic resonance imaging (MP-MRI) offer a noninvasive diagnostic intervention which allows correlation of prostate tumor image characteristics with underlying biologic evidence of tumor progression. The power of MP-MRI includes examination of both local invasion and nodal disease and might overcome the challenges of analyzing the multifocal nature of prostate cancer. Future directions include a careful analysis of the genomic signature of individual prostatic lesions utilizing image-guided biopsies. This review examines the diagnostic potential of MRI in prostate cancer.
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Affiliation(s)
- Srinivas Vourganti
- Department of Urology, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Jeffrey Donaldson
- Department of Urology, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Linda Johnson
- Molecular Imaging Program, Urologic Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Baris Turkbey
- Molecular Imaging Program, Urologic Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Gennady Bratslavsky
- Department of Urology, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Leszek Kotula
- Department of Urology, SUNY Upstate Medical University, Syracuse, NY 13210, USA Department of Biochemistry and Molecular Biology, SUNY Upstate Medical University, Syracuse, NY 13210, USA
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Jang GS, Kim MJ, Ha HI, Kim JH, Kim HS, Ju SB, Zang DY. Comparison of RECIST version 1.0 and 1.1 in assessment of tumor response by computed tomography in advanced gastric cancer. Chin J Cancer Res 2014; 25:689-94. [PMID: 24385696 DOI: 10.3978/j.issn.1000-9604.2013.11.09] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Accepted: 11/28/2013] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE Response Evaluation Criteria in Solid Tumors (RECIST) guideline version 1.0 (RECIST 1.0) was proposed as a new guideline for evaluating tumor response and has been widely accepted as a standardized measure. With a number of issues being raised on RECIST 1.0, however, a revised RECIST guideline version 1.1 (RECIST 1.1) was proposed by the RECIST Working Group in 2009. This study was conducted to compare CT tumor response based on RECIST 1.1 vs. RECIST 1.0 in patients with advanced gastric cancer (AGC). METHODS We reviewed 61 AGC patients with measurable diseases by RECIST 1.0 who were enrolled in other clinical trials between 2008 and 2010. These patients were retrospectively re-analyzed to determine the concordance between the two response criteria using the κ statistic. RESULTS The number and sum of tumor diameters of the target lesions by RECIST 1.1 were significantly lower than those by RECIST 1.0 (P<0.0001). However, there was excellent agreement in tumor response between RECIST 1.1 and RECIST 1.0 (κ=0.844). The overall response rates (ORRs) according to RECIST 1.0 and RECIST 1.1 were 32.7% (20/61) and 34.5% (20/58), respectively. One patient with partial response (PR) based on RECIST 1.0 was reclassified as stable disease (SD) by RECIST 1.1. Of two patients with SD by RECIST 1.0, one was downgraded to progressive disease and the other was upgraded to PR by RECIST 1.1. CONCLUSIONS RECIST 1.1 provided almost perfect agreement with RECIST 1.0 in the CT assessment of tumor response of AGC.
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Affiliation(s)
- Gil-Su Jang
- Department of Internal Medicine, Hallym University Sacred Heart Hospital, Anyang 431-070, South Korea
| | - Min-Jeong Kim
- Department of Diagnostic Radiology, Hallym University Sacred Heart Hospital, Anyang 431-070, South Korea
| | - Hong-Il Ha
- Department of Diagnostic Radiology, Hallym University Sacred Heart Hospital, Anyang 431-070, South Korea
| | - Jung Han Kim
- Department of Internal Medicine, Kangnam Sacred Heart Hospital, Seoul 136-705, South Korea
| | - Hyeong Su Kim
- Department of Internal Medicine, Kangnam Sacred Heart Hospital, Seoul 136-705, South Korea
| | - Sung Bae Ju
- Department of Internal Medicine, Kangnam Sacred Heart Hospital, Seoul 136-705, South Korea
| | - Dae Young Zang
- Department of Internal Medicine, Hallym University Sacred Heart Hospital, Anyang 431-070, South Korea
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