用于预测膀胱癌肌肉浸润情况的多参数MRI膀胱成像报告和数据系统
Vesical Imaging-Reporting and Data System for Multiparametric MRI to Predict the Presence of Muscle Invasion for Bladder Cancer.
作者信息
Hong Seung Baek, Lee Nam Kyung, Kim Suk, Son Il Wan, Ha Hong Koo, Ku Ja Yoon, Kim Kyung Hwan, Park Won Young
机构信息
Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Busan, Korea.
Department of Urology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Busan, Korea.
出版信息
J Magn Reson Imaging. 2020 Oct;52(4):1249-1256. doi: 10.1002/jmri.27141. Epub 2020 Mar 27.
BACKGROUND
The Vesical Imaging-Reporting and Data System (VI-RADS) is a newly developed system of bladder cancer staging with multiparametric MRI (mpMRI), which can be used to predict the presence of muscle invasion for bladder cancer.
PURPOSE
To evaluate the accuracy of three mpMRI series (T WI, diffusion-weighted imaging [DWI], and dynamic contrast-enhanced image [DCEI]) and VI-RADS for diagnosing the muscle invasive bladder cancer (MIBC).
STUDY TYPE
Retrospective.
POPULATION
In all, 66 pathologically proven bladder cancers in 32 patients.
FIELD STRENGTH/SEQUENCE: Before the diagnostic MRI with an intramuscular antispasmodic agent, optimal bladder distension was confirmed. 3.0T MRI with T WI, DWI, and DCEI.
ASSESSMENT
Three reviewers independently assessed and scored the bladder cancers in T WI, DWI, and DCEI using a five-point score system. Based on the scores in the three sequences, reviewers scored each bladder cancer with reference to VI-RADS categories. We evaluated the diagnostic performance of each of three mpMRI sequences and the final VI-RADS categorization for diagnosing MIBC.
STATISTICAL TESTS
Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the curve (AUC) of each of three sequences separately and VI-RADS categorization for diagnosing the MIBC.
RESULTS
The diagnostic performances of each of the three mpMRI series and VI-RADS for diagnosing MIBC were excellent. Especially using the optimal cutoff score >3 for predicting MIBC on DWI, DCEI, and VI-RADS, the sensitivity, specificity, PPV, NPV, and AUC values were 90% (95% confidence interval [CI]: 0.56, 1.00), 100% (95% CI: 0.94, 1.00), 100% (95% CI: 0.66. 1.00), 98.3% (95% CI: 0.91, 1.00), and 0.95, respectively. DATA CONCLUSION: mpMRI based on VI-RADS can stratify patients with bladder cancer according to the presence of muscle invasion.
LEVEL OF EVIDENCE
TECHNICAL EFFICACY STAGE
- J. Magn. Reson. Imaging 2020;52:1249-1256.
背景
膀胱影像报告和数据系统（VI-RADS）是一种新开发的利用多参数磁共振成像（mpMRI）对膀胱癌进行分期的系统，可用于预测膀胱癌是否存在肌肉浸润。
目的
评估三个mpMRI序列（TWI、扩散加权成像[DWI]和动态对比增强成像[DCEI]）以及VI-RADS诊断肌肉浸润性膀胱癌（MIBC）的准确性。
研究类型
回顾性研究。
研究对象
共32例患者的66例经病理证实的膀胱癌。
场强/序列：在使用肌肉解痉剂进行诊断性MRI之前，确认膀胱最佳充盈状态。采用3.0T MRI，序列包括TWI、DWI和DCEI。
评估
三位阅片者使用五分制评分系统对TWI、DWI和DCEI中的膀胱癌进行独立评估和评分。根据三个序列的评分，阅片者参照VI-RADS分类对每个膀胱癌进行评分。我们评估了三个mpMRI序列以及最终的VI-RADS分类对诊断MIBC的诊断性能。
统计分析
分别计算三个序列以及VI-RADS分类诊断MIBC的敏感度、特异度、阳性预测值（PPV）、阴性预测值（NPV）和曲线下面积（AUC）。
结果
三个mpMRI序列以及VI-RADS对诊断MIBC的诊断性能均优异。特别是在DWI、DCEI和VI-RADS上使用预测MIBC的最佳截断分数>3时，敏感度、特异度、PPV、NPV和AUC值分别为90%（95%置信区间[CI]：0.56，1.00）、100%（95%CI：0.94，1.00）、100%（CI：0.66，1.00）、98.3%（95%CI：0.91，1.00）和0.95。
数据结论
基于VI-RADS的mpMRI可根据肌肉浸润情况对膀胱癌患者进行分层。
证据等级
3级。
技术效能阶段
2级。《磁共振成像杂志》2020年；52：1249 - 1256。
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