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Yu R, Cai L, Cao Q, Liu P, Gong Y, Li K, Wu Q, Zhang Y, Li P, Yang X, Lu Q. Development and Validation of an MRI-Based Nomogram for Preoperative Detection of Muscle Invasion in VI-RADS 3. J Magn Reson Imaging 2024; 60:448-457. [PMID: 37902432 DOI: 10.1002/jmri.29103] [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: 07/31/2023] [Revised: 10/15/2023] [Accepted: 10/17/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND The relationship between tumor and muscle layer in the vesical imaging-reporting and data system (VI-RADS) 3 is ambiguous, and there is a lack of preoperative and non-invasive procedures to detect muscle invasion in VI-RADS 3. PURPOSE To develop a nomogram based on MRI features for detecting muscle invasion in VI-RADS 3. STUDY TYPE Retrospective. POPULATION 235 cases (Age: 67.5 ± 11.5 years) with 11.9% females were randomly divided into a training cohort (n = 164) and a validation cohort (n = 71). FIELD STRENGTH/SEQUENCE 3T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (breathing-free spin echo), and dynamic contrast-enhanced imaging (gradient echo). ASSESSMENT 3 features were selected from the training cohort, including tumor contact length greater than maximum tumor diameter (TCL > Dmax), flat tumor morphology, and lower standard deviation of apparent diffusion coefficient (ADCSD). Three readers assessed VI-RADS scores and the tumor morphology. STATISTICAL TESTS Interobserver agreement was assessed by Kappa analysis. Features for final analysis were selected by logistic regression. The performance of the nomogram was evaluated by the receiver operating characteristic curve, decision curve analysis, and calibration curve. RESULTS TCL > Dmax, flat morphology, and lower ADCSD were the independent risk factors for muscle invasive in VI-RADS 3. The AUCs, accuracy, sensitivity, and specificity of the nomogram 1 composed of three features for detecting muscle invasion were 0.852 (95% CI: 0.793-0.912), 0.756, 0.917, and 0.663 in the training cohort, and 0.885 (95% CI: 0.801-0.969), 0.817, 0.900, and 0.784 in the validation cohort. The nomogram 2 without ADCSD has nearly the same performance as the nomogram 1. DATA CONCLUSION Nomogram can be an efficient tool for preoperative detection of muscle invasion in VI-RADS 3. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ruixi Yu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lingkai Cai
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Urology, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Qiang Cao
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Peikun Liu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuxi Gong
- Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kai Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qikai Wu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yudong Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pengchao Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao Yang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qiang Lu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Prince MR, Shaish H. Editorial for "Detecting Muscle Invasion of Bladder Cancer: An Application of Diffusion Kurtosis Imaging Ratio and Vesical Imaging-Reporting and Data System". J Magn Reson Imaging 2024; 60:65-66. [PMID: 37840196 DOI: 10.1002/jmri.29054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 09/20/2023] [Indexed: 10/17/2023] Open
Affiliation(s)
- Martin R Prince
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
| | - Hiram Shaish
- Department of Radiology, Columbia University Irving Medical Center, New York City, New York, USA
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Qin C, Tian Q, Zhou H, Qin Y, Zhou S, Wu Y, Tianjiao E, Duan S, Li Y, Wang X, Chen Z, Zheng G, Feng F. Detecting Muscle Invasion of Bladder Cancer: An Application of Diffusion Kurtosis Imaging Ratio and Vesical Imaging-Reporting and Data System. J Magn Reson Imaging 2024; 60:54-64. [PMID: 37916908 DOI: 10.1002/jmri.29053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 09/27/2023] [Accepted: 09/27/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND Independent factors are needed to supplement vesical imaging-reporting and data system (VI-RADS) to improve its ability to identify muscle invasive bladder cancer (MIBC). PURPOSE To assess the correlation between MIBC and diffusion kurtosis imaging (DKI) ratio, VI-RADS, and other factors (such as tumor location). STUDY TYPE Retrospective. POPULATION Sixty-eight patients (50 males and 18 females; age: 70.1 ± 9.5 years) with bladder urothelial carcinoma. FIELD STRENGTH/SEQUENCE 1.5 T, conventional diffusion-weighted imaging (DWI), and DKI (single shot echo-planar sequence). ASSESSMENT Three radiologists independently measured the diffusion parameters of each bladder cancer (BCa) and obturator internus, including the mean apparent diffusion coefficient (ADCmean), mean kurtosis (MK), and mean diffusion (MD). And the ratio of diffusion parameters between BCa and obturator internus was calculated (diffusion parameter ratio = bladder cancer:obturator internus). Based on the VI-RADS, the target lesions were independently scored. Furthermore, the actual tumor-wall contact length (ACTCL) and absolute tumor-wall contact length (ABTCL) were measured. STATISTICAL TESTS Multicollinearity among independent variables was evaluated using the variance inflation factor (VIF). Multivariable logistic regression analysis was used to determine the independent risk factors of MIBC. The receiver operating characteristic curve was used to evaluate the efficacy of each variable in detecting MIBC. The DeLong test was used to compare the area under the curve (AUC). A P < 0.05 was considered statistically significant. RESULTS MKratio (median: 0.62) and VI-RADS were independent risk factors for MIBC. AUCs for MKratio, VI-RADS, and MKratio combined with VI-RADS in assessing MIBC were 0.895, 0.871, and 0.973, respectively. MKratio combined with VI-RADS was more effective in diagnosing MIBC than VI-RADS alone. DATA CONCLUSIONS MKratio has potential to assist the assessment of MIBC. MKratio can be used as a supplement to VI-RADS for detecting MIBC. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Cai Qin
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Qi Tian
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Hui Zhou
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Yihan Qin
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Siyu Zhou
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Yutao Wu
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Tianjiao E
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Shufeng Duan
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Yueyue Li
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Xiaolin Wang
- Department of Urology Surgery, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Zhigang Chen
- Department of Urology Surgery, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Guihua Zheng
- Department of Pathology, Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Feng Feng
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China
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Panebianco V, Briganti A, Boellaard TN, Catto J, Comperat E, Efstathiou J, van der Heijden AG, Giannarini G, Girometti R, Mertens L, Takeuchi M, Muglia VF, Narumi Y, Novara G, Pecoraro M, Roupret M, Sanguedolce F, Santini D, Shariat SF, Simone G, Vargas HA, Woo S, Barentsz J, Witjes JA. Clinical application of bladder MRI and the Vesical Imaging-Reporting and Data System. Nat Rev Urol 2024; 21:243-251. [PMID: 38036666 DOI: 10.1038/s41585-023-00830-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2023] [Indexed: 12/02/2023]
Abstract
Diagnostic work-up and risk stratification in patients with bladder cancer before and after treatment must be refined to optimize management and improve outcomes. MRI has been suggested as a non-invasive technique for bladder cancer staging and assessment of response to systemic therapy. The Vesical Imaging-Reporting And Data System (VI-RADS) was developed to standardize bladder MRI image acquisition, interpretation and reporting and enables accurate prediction of muscle-wall invasion of bladder cancer. MRI is available in many centres but is not yet recommended as a first-line test for bladder cancer owing to a lack of high-quality evidence. Consensus-based evidence on the use of MRI-VI-RADS for bladder cancer care is needed to serve as a benchmark for formulating guidelines and research agendas until further evidence from randomized trials becomes available.
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Affiliation(s)
- Valeria Panebianco
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome, Rome, Italy.
| | - Alberto Briganti
- Unit of Urology/Division of Oncology, Urological Research Institute, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, Milan, Italy
| | - Thierry N Boellaard
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - James Catto
- Academic Urology Unit, University of Sheffield, Sheffield, UK
| | - Eva Comperat
- Department of Pathology, Sorbonne University, Assistance Publique-Hôpitaux de Paris, Hopital Tenon, Paris, France
| | - Jason Efstathiou
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Gianluca Giannarini
- Urology Unit, Academic Medical Centre "Santa Maria della Misericordia", Udine, Italy
| | - Rossano Girometti
- Institute of Radiology, Academic Medical Centre "Santa Maria della Misericordia", Udine, Italy
| | - Laura Mertens
- Department of Surgical Oncology (Urology), Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Valdair F Muglia
- Department of Medical Images, Radiation Therapy and Oncohematology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Brazil
| | | | - Giacomo Novara
- Department of Surgery, Oncology, and Gastroenterology - Urology Clinic, University of Padua, Padua, Italy
| | - Martina Pecoraro
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome, Rome, Italy
| | - Morgan Roupret
- Department of Urology, Sorbonne University, AP-HP, Pitié Salpétrière Hospital, Paris, France
| | - Francesco Sanguedolce
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Daniele Santini
- Division of Medical Oncology A, Policlinico Umberto I, Rome, Italy
- Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University, Latina, Italy
| | - Shahrokh F Shariat
- Department of Urology, Teaching Hospital Motol and 2nd Faculty of Medicine, Charles University Praha, Prague, Czech Republic
- Department of Urology, Comprehensive Cancer Center, Medical University Vienna, Vienna General Hospital, Vienna, Austria
| | - Giuseppe Simone
- IRCCS "Regina Elena" National Cancer Institute, Department of Urology, Rome, Italy
| | - Hebert A Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jelle Barentsz
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands
| | - J Alfred Witjes
- Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
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He K, Meng X, Wang Y, Feng C, Liu Z, Li Z, Niu Y. Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review. Diagnostics (Basel) 2024; 14:442. [PMID: 38396481 PMCID: PMC10888296 DOI: 10.3390/diagnostics14040442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/25/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
Magnetic resonance imaging (MRI) has been proven to be an indispensable imaging method in bladder cancer, and it can accurately identify muscular invasion of bladder cancer. Multiparameter MRI is a promising tool widely used for preoperative staging evaluation of bladder cancer. Vesical Imaging-Reporting and Data System (VI-RADS) scoring has proven to be a reliable tool for local staging of bladder cancer with high accuracy in preoperative staging, but VI-RADS still faces challenges and needs further improvement. Artificial intelligence (AI) holds great promise in improving the accuracy of diagnosis and predicting the prognosis of bladder cancer. Automated machine learning techniques based on radiomics features derived from MRI have been utilized in bladder cancer diagnosis and have demonstrated promising potential for practical implementation. Future work should focus on conducting more prospective, multicenter studies to validate the additional value of quantitative studies and optimize prediction models by combining other biomarkers, such as urine and serum biomarkers. This review assesses the value of multiparameter MRI in the accurate evaluation of muscular invasion of bladder cancer, as well as the current status and progress of its application in the evaluation of efficacy and prognosis.
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Affiliation(s)
- Kangwen He
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Yanchun Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Cui Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Zheng Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Yonghua Niu
- Department of Pediatric Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Ahn H, Kim TM, Hwang SI, Lee HJ, Choe G, Hong SK, Byun SS, Oh JJ. Tumor contact length with bladder wall provides effective risk stratification for lesions with a VIRADS score of 2-3. Eur Radiol 2023; 33:8417-8425. [PMID: 37438641 DOI: 10.1007/s00330-023-09925-1] [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: 01/10/2023] [Revised: 04/17/2023] [Accepted: 05/14/2023] [Indexed: 07/14/2023]
Abstract
OBJECTIVES To evaluate the diagnostic performance of the tumor contact length (TCL) in the prediction of MIBC (muscle-invasive bladder cancer) in lesions corresponding to the vesical imaging-reporting and data system (VIRADS) score 2-3. METHODS This is a single institution, retrospective study targeting 191 consecutive patients assigned of VIRADS score 2-3, who had pre-transurethral resection MRI from July 2019 to September 2021. Logistic regression analyses were performed to determine meaningful predictors of MIBC for this score group, and a nomogram was plotted with those variables. The diagnostic performance of each predictor was compared at predefined thresholds (VIRADS score 3 and TCL 3 cm) using the generalized linear model and ROC analysis. RESULTS Both VIRADS score and TCL remained independent predictors of MIBC for this score group (odds ratio 7.3 for VIRADS score, and 1.3 for TCL, p < 0.01 for both). The contribution of TCL to the probability of MIBC in the nomogram was greater than that of the VIRADS score. VIRADS score had a sensitivity of 0.54 (14/26), specificity of 0.92 (203/221), and diagnostic accuracy of 0.88 (217/247), and TCL showed a sensitivity of 0.89 (23/26), specificity of 0.95 (209/221), and diagnostic accuracy of 0.94 (232/247). The difference in sensitivity (p = 0.03) and accuracy (p = 0.04) was statistically significant. The AUC was also significantly wider for TCL than for VIRADS (0.97 vs. 0.73, p < 0.01). CONCLUSION A simple index, TCL, may be helpful in further risk stratification for MIBC in patients with a score of VIRADS 2-3. CLINICAL RELEVANCE STATEMENT For bladder cancer patients with insufficient qualitative evidence of muscle layer invasion using VIRADS categorization, TCL, a simple quantitative indicator defined as the curvilinear contact length between the bladder wall and the tumor, may be helpful in risk stratification. KEY POINTS • Even when only lesions with score 2-3 were targeted, VIRADS was still a meaningful indicator of MIBC. • With a predefined threshold of 3 cm applied, TCL outperformed VIRADS in the score 2-3 group, in predicting MIBC. • A longer TCL for a lesion with a VIRADS score 2 may warrant an additional warning for MIBC, whereas a shorter TCL for a lesion with a score 3 may indicate a lower risk of MIBC.
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Affiliation(s)
- Hyungwoo Ahn
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea.
| | - Taek Min Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Sung Il Hwang
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Hak Jong Lee
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Gheeyoung Choe
- Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sung Kyu Hong
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Seok-Soo Byun
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jong Jin Oh
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
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Li J, Cao K, Lin H, Deng L, Yang S, Gao Y, Liang M, Lin C, Zhang W, Xie C, Zhang K, Luo J, Pan Z, Yue P, Zou Y, Huang B. Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system. Eur Radiol 2023; 33:2699-2709. [PMID: 36434397 DOI: 10.1007/s00330-022-09272-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 09/18/2022] [Accepted: 10/24/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVES To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting and data system (VI-RADS) in predicting muscle invasion in bladder cancer (MIBC). METHODS A total of 215 tumours (129 for training and 31 for internal validation, centre 1; 55 for external validation, centre 2) were included. MIBC was confirmed by pathological examination. VI-RADS scores were provided by two groups of radiologists (readers 1 and readers 2) independently. A deep convolutional neural network was constructed in the training set, and validation was conducted on the internal and external validation sets. ROC analysis was performed to evaluate the performance for MIBC diagnosis. RESULTS The AUCs of the DL model, readers 1, and readers 2 were as follows: in the internal validation set, 0.963, 0.843, and 0.852, respectively; in the external validation set, 0.861, 0.808, and 0.876, respectively. The accuracy of the DL model in the tumours scored VI-RADS 2 or 3 was higher than that of radiologists in the external validation set: for readers 1, 0.886 vs. 0.600, p = 0.006; for readers 2, 0.879 vs. 0.636, p = 0.021. The average processing time (38 s and 43 s in two validation sets) of the DL method was much shorter than the readers, with a reduction of over 100 s in both validation sets. CONCLUSIONS Compared to radiologists using VI-RADS, the DL method had a better diagnostic performance, shorter processing time, and robust generalisability, indicating good potential for diagnosing MIBC. KEY POINTS • The DL model shows robust performance for MIBC diagnosis in both internal and external validation. • The diagnostic performance of the DL model in the tumours scored VI-RADS 2 or 3 is better than that obtained by radiologists using VI-RADS. • The DL method shows potential in the preoperative assessment of MIBC.
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Affiliation(s)
- Jianpeng Li
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Kangyang Cao
- Medical AI Lab, School of Biomedical Engineering, Health Science Centre, Shenzhen University, Shenzhen, China
| | - Hongxin Lin
- Medical AI Lab, School of Biomedical Engineering, Health Science Centre, Shenzhen University, Shenzhen, China
| | - Lei Deng
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Shuiqing Yang
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Yun Gao
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Manqiu Liang
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Chuxuan Lin
- Medical AI Lab, School of Biomedical Engineering, Health Science Centre, Shenzhen University, Shenzhen, China
| | - Weijing Zhang
- Imaging Department, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Chuanmiao Xie
- Imaging Department, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Kunlin Zhang
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Jiexin Luo
- Department of Urology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China
| | - Zhaohong Pan
- Medical AI Lab, School of Biomedical Engineering, Health Science Centre, Shenzhen University, Shenzhen, China
| | - Peiyan Yue
- Medical AI Lab, School of Biomedical Engineering, Health Science Centre, Shenzhen University, Shenzhen, China
| | - Yujian Zou
- Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China.
| | - Bingsheng Huang
- Medical AI Lab, School of Biomedical Engineering, Health Science Centre, Shenzhen University, Shenzhen, China.
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Inter-reader reliability of the vesical imaging-reporting and data system (VI-RADS) for muscle-invasive bladder cancer: a systematic review and meta-analysis. ABDOMINAL RADIOLOGY (NEW YORK) 2022; 47:4173-4185. [PMID: 36112202 DOI: 10.1007/s00261-022-03669-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/24/2022] [Accepted: 08/27/2022] [Indexed: 01/18/2023]
Abstract
To evaluate the diagnostic agreement between readers in VI-RADS interpretation to detect muscle-invasive bladder cancer (MIBC) preoperatively, we conducted a systematic review and meta-analysis of the available data. Scopus, PubMed, Web of Science, and Embase databases were systematically searched up to November 13, 2021. Case reports, review articles, editorials, and studies with insufficient data were eliminated. The Quality Appraisal of the Diagnostic Reliability Checklist was used to assess the risk of bias. The degree of agreement was determined by Cohen's kappa coefficient (κ) for comparison of data. The heterogeneity of these studies was explored using subgroup analysis and meta-regression analysis. The level of confidence was set at 0.05. All analyses were conducted in STATA 16.0. Overall, 19 eligible studies, consisting of 2439 participants, were included in this meta-analysis. The inter-reader agreement for VI-RADS in MIBC detection ranged from κ of 0.45 to 0.96 among included studies. The pooled inter-reader reliability was calculated as 0.76 [95% CI 0.73-0.80; I2 = 92.13%, Q(50) = 635.08, p < 0.01]. Sources of heterogeneity included magnetic strength, T2WI slice thickness, number of readers, sample size, study design, number of centers, year of publication, proportion of male patients, and mean age. There is substantial reliability in VI-RADS interpretation for MIBC among radiologists with various levels of expertise. The high degree of inter-reader agreement for MIBC detection supports the implementation of VI-RADS in routine clinical practice for the staging paradigm of bladder cancer.
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Hu X, Li G, Wu S. Advances in Diagnosis and Therapy for Bladder Cancer. Cancers (Basel) 2022; 14:cancers14133181. [PMID: 35804953 PMCID: PMC9265007 DOI: 10.3390/cancers14133181] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 06/19/2022] [Accepted: 06/24/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary The clinical management of bladder cancer has been developing in the past decade, including diagnostic tools and treatment options. Both monotherapy and combination therapy have been undoubtedly upgraded. Multiple diagnostic techniques and therapeutic strategies have been developed to meet the urgent clinical needs, resulting in the emergence of various explorations for cancer diagnosis and therapy. In this review, we mainly focus on the advances in the diagnosis and treatment of bladder cancer. Abstract Bladder cancer (BCa) is one of the most common and expensive urinary system malignancies for its high recurrence and progression rate. In recent years, immense amounts of studies have been carried out to bring a more comprehensive cognition and numerous promising clinic approaches for BCa therapy. The development of innovative enhanced cystoscopy techniques (optical techniques, imaging systems) and tumor biomarkers-based non-invasive urine screening (DNA methylation-based urine test) would dramatically improve the accuracy of tumor detection, reducing the risk of recurrence and progression of BCa. Moreover, intravesical instillation and systemic therapeutic strategies (cocktail therapy, immunotherapy, vaccine therapy, targeted therapy) also provide plentiful measures to break the predicament of BCa. Several exploratory clinical studies, including novel surgical approaches, pharmaceutical compositions, and bladder preservation techniques, emerged continually, which are supposed to be promising candidates for BCa clinical treatment. Here, recent advances and prospects of diagnosis, intravesical or systemic treatment, and novel drug delivery systems for BCa therapy are reviewed in this paper.
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Affiliation(s)
- Xinzi Hu
- Institute of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen 518000, China; (X.H.); (G.L.)
- Department of Urology, South China Hospital, Health Science Center, Shenzhen University, Shenzhen 518116, China
| | - Guangzhi Li
- Institute of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen 518000, China; (X.H.); (G.L.)
- Department of Urology, South China Hospital, Health Science Center, Shenzhen University, Shenzhen 518116, China
| | - Song Wu
- Institute of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen 518000, China; (X.H.); (G.L.)
- Department of Urology, South China Hospital, Health Science Center, Shenzhen University, Shenzhen 518116, China
- Correspondence:
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Diagnostic accuracy of vesical imaging-reporting and data system (VI-RADS) for the detection of muscle-invasive bladder cancer: a meta-analysis. Abdom Radiol (NY) 2022; 47:1396-1405. [PMID: 35181798 DOI: 10.1007/s00261-022-03449-w] [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: 01/07/2022] [Revised: 02/05/2022] [Accepted: 02/07/2022] [Indexed: 11/01/2022]
Abstract
PURPOSE Vesical Imaging-Reporting and Data System (VI-RADS) was proposed and considered as a standardized reporting criterion for bladder magnetic resonance imaging (MRI). VI-RADS could suggest the likelihood of muscle invasion based on the multiparametric MRI (mp-MRI) findings which contain five-point scores. The current study is designed to comprehensively and systematically evaluate the diagnostic performance of VI-RADS (score 3 and 4) for predicting muscle invasion. METHODS The Cochrane Library, Embase, and PubMed were searched comprehensively from inception to October 2021. RESULTS Finally, 19 studies incorporating 2900 patients were enrolled. The pooled sensitivity and specificity of VI-RADS 3 for predicting muscle invasion were 0.92 (95%CI 0.89-0.94) and 0.82 (95%CI 0.76-0.87), respectively. The pooled sensitivity and specificity of VI-RADS 4 were 0.78 (95%CI 0.72-0.83) and 0.96 (95%CI 0.93-0.97), respectively. And the area under the curve (AUCs) of VI-RADS 3 and 4 were all 0.94 (95%CI 0.92-0.96). No significant publication biases were not observed for VI-RADS 3 (P = 0.74) and 4 (P = 0.57). CONCLUSION The VI-RADS reveals a good diagnostic performance for predicting muscle invasive in bladder cancer, which also has good clinical utilities and applicability. And VI-RADS 3 and 4 as cutoff values provide similar overall diagnostic and could be selectively applied individually. Prospective studies with a large scale are further required to validate the accuracy of the VI-RADS score.
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Li Q, Cao B, Liu K, Sun H, Ding Y, Yan C, Wu PY, Dai C, Rao S, Zeng M, Jiang S, Zhou J. Detecting the muscle invasiveness of bladder cancer: an application of diffusion kurtosis imaging and tumor contact length. Eur J Radiol 2022; 151:110329. [DOI: 10.1016/j.ejrad.2022.110329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 11/03/2022]
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Muskelinvasives Blasenkarzinom: weniger falsch positive Ergebnisse mit neuem Befundungsmodell. ROFO-FORTSCHR RONTG 2022. [DOI: 10.1055/a-1692-1676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Proposal for a new Vesical Imaging-Reporting and Data System (VI-RADS)-based algorithm for the management of bladder cancer: A paradigm shift from the current transurethral resection of bladder tumor (TURBT)-dependent practice. Clin Genitourin Cancer 2022; 20:e291-e295. [DOI: 10.1016/j.clgc.2022.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 02/27/2022] [Accepted: 03/01/2022] [Indexed: 11/19/2022]
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Yuan B, Cai L, Cao Q, Wu Q, Zhuang J, Sun X, Zhang Y, Li P, Yang X, Lu Q. Role of Vesical Imaging-Reporting and Data System in predicting muscle-invasive bladder cancer: A diagnostic meta-analysis. Int J Urol 2021; 29:186-195. [PMID: 34923686 DOI: 10.1111/iju.14748] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 11/07/2021] [Indexed: 12/14/2022]
Abstract
The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper studies. We included studies that included data on Vesical Imaging-Reporting and Data System and their associated pathological findings, and we assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The pooled sensitivity and specificity were calculated and plotted using hierarchical summary receiver operating characterisijutic modeling. Meta-regression analysis was carried out to detect heterogeneity. A total of 20 studies with 2725 patients were included. When the cut-off point was 3, the pooled sensitivity and specificity were 0.92 (0.89-0.94) and 0.85 (0.78-0.90), respectively, and 0.82 (0.75-0.88) and 0.95 (0.91-0.97), respectively, when the cut-off point was 4. The area under the curve was 0.95 and 0.95, respectively. Heterogeneity was substantially considerable in sensitivity and specificity. All subgroup variables, including patient number, study design, magnetic resonance imaging field strength, number of radiologists, surgery pattern, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging, contributed to sensitivity heterogeneity when the cut-off point was 3 and specificity heterogeneity when the cut-off point was 4. Multiple image acquisition plane of diffusion-weighted imaging achieved a higher sensitivity than single image acquisition plane of diffusion-weighted imaging in both the Vesical Imaging-Reporting and Data System 3 and 4 groups, and higher specificity in the Vesical Imaging-Reporting and Data System 4 group. Another significant source of heterogeneity was the cut-off point. The diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer was excellent in both cut-off points of the Vesical Imaging-Reporting and Data System 3 and 4. Multiple image acquisition planes of diffusion-weighted imaging should be given more attention in the Vesical Imaging-Reporting and Data System.
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Affiliation(s)
- Baorui Yuan
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Lingkai Cai
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qiang Cao
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qikai Wu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Juntao Zhuang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xueying Sun
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yudong Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Pengchao Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiao Yang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qiang Lu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
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