Zhang Zhichao, Xiao Weixiong, Wang Yiqian, Zhang Wei, Luo Min
Department of Radiology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Department of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Abdom Radiol (NY). 2025 Jan 2. doi: 10.1007/s00261-024-04788-6.
This study investigates the diagnostic value of Vesical Imaging Reporting and Data System (VI-RADS) in biparametric MRI (bp-MRI) for the detection of muscular infiltration in bladder cancer, and to investigate whether apparent diffusion coefficient (ADC) value can function as a potential indicator of bp-MRI VI-RADS for patient benefit.
This single-center retrospective study enrolled 81 patients with pathologically confirmed bladder cancer from October 2019 to November 2021. Two readers independently scored the T2-weighted images and diffusion-weighted images of each index lesion based on the VI-RADS criteria, subsequently deriving the bp-MRI VI-RADS scores. Both ADC values and bp-MRI VI-RADS scores were utilized to develop a simple model by logistic regression. Receiver-operating characteristic curve assessed all systems, while decision curve analysis (DCA) and calibration curves evaluated the model's performance.
The area under the curve (AUC) of bp-MRI VI-RADS was 0.886 (95% confidence interval [CI]: 0.801-0.971), with the diagnostic accuracy, sensitivity, and specificity being 0.753, 0.962, and 0.655 respectively. Regarding the ADC value, its AUC was 0.899 (95% CI: 0.821-0.977), and the diagnostic accuracy, sensitivity, and specificity were 0.877, 0.846, and 0.891. The AUC of the simple combined model achieved 0.942 (95% CI: 0.881-0.999), and the diagnostic accuracy, sensitivity, and specificity were 0.889, 0.885, and 0.891. The DeLong test verified that there was a statistically significant difference in AUC between the model and bp-MRI VI-RADS alone (P < 0.05). The simple model demonstrated excellent clinical applicability via DCA and calibration plots.
The contrast-free bp-MRI VI-RADS demonstrates commendable diagnostic efficacy for diagnosing muscular infiltration in bladder cancer. Additionally, ADC values can complement bp-MRI VI-RADS, enhancing diagnostic performance.
本研究探讨膀胱影像报告和数据系统(VI-RADS)在双参数磁共振成像(bp-MRI)中对膀胱癌肌层浸润检测的诊断价值,并研究表观扩散系数(ADC)值是否可作为bp-MRI VI-RADS的潜在指标以造福患者。
本单中心回顾性研究纳入了2019年10月至2021年11月期间81例经病理证实的膀胱癌患者。两名阅片者根据VI-RADS标准对每个索引病变的T2加权图像和扩散加权图像进行独立评分,随后得出bp-MRI VI-RADS评分。利用ADC值和bp-MRI VI-RADS评分通过逻辑回归建立一个简单模型。采用受试者操作特征曲线评估所有系统,同时用决策曲线分析(DCA)和校准曲线评估模型的性能。
bp-MRI VI-RADS的曲线下面积(AUC)为0.886(95%置信区间[CI]:0.801 - 0.971),诊断准确性、敏感性和特异性分别为0.753、0.962和0.655。关于ADC值,其AUC为0.899(95% CI:0.821 - 0.977),诊断准确性、敏感性和特异性分别为0.877、0.846和0.891。简单联合模型的AUC达到0.942(95% CI:0.881 - 0.999),诊断准确性、敏感性和特异性分别为0.889、0.885和0.891。DeLong检验证实模型与单独的bp-MRI VI-RADS在AUC上存在统计学显著差异(P < 0.05)。通过DCA和校准图,简单模型显示出优异的临床适用性。
无对比剂的bp-MRI VI-RADS在诊断膀胱癌肌层浸润方面显示出值得称赞的诊断效能。此外,ADC值可补充bp-MRI VI-RADS,提高诊断性能。