Yi Ying, Wang Hang, Cheng Dongliang, Xu Zhifeng, Zhang Xianhai, Luo Chun, Zhao Hai
Department of Radiology, First People's Hospital of Foshan, Foshan, China.
Front Oncol. 2025 Jun 4;15:1510049. doi: 10.3389/fonc.2025.1510049. eCollection 2025.
Limited data exist on the performance of Prostate Imaging Reporting and Data System (PI-RADS) v2.1 upgraded and non-upgraded lesions, both alone and in combined with multiparametric MRI (mpMRI) features, for prostate cancer detection.
To evaluate the rates of prostate cancer (PCa) and clinically significant prostate cancer(csPCa) rates in PI-RADS v2.1 upgraded and non-upgraded lesions, and to identify mpMRI features that improve detection accuracy.
This study included men who underwent mpMRI and ultrasound-guided (US-guided) biopsy from March 2023 to April 2024. MRI scans were prospectively evaluated according to PI-RADS v2.1. MpMRI features were extracted from lesion contours, including three-dimensional maximum diameter, lesion volume, sphericity, surface-to-volume ratio (SVR), T-weighted imaging signal intensity(TWI SI), diffusion-weighted imaging(DWI) SI, T, T, proton density (PD), apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE) MRI-derived time intensity curve (TIC). Univariable and multivariable logistic regression analyses were performed to identify features associated with PCa and csPCa in different prostate zones (transition zone and peripheral zone).
A total of 94 patients(mean age, 65.7 years) with 234 lesions were included. Significant differences were observed between upgraded and non-upgraded PI-RADS 4 lesions( < 0.05) in the peripheral zone (PZ), whereas no significant differences were found in the transition zone (TZ). Risk factors for csPCa in the TZ included lesion diameter, TIC type III, capsule, T and PD values. For csPCa in the PZ, T1, SVR, DWI SI, and ADC values were identified as important risk factors. ROC analysis demonstrated high diagnostic accuracy for csPCa detection, with AUCs of 0.93 (TZ) and 0.96 (PZ).
PI-RADS v2.1 upgrading rules improve cancer detection in the TZ, but upgrading PI-RADS category 3 lesions in the PZ may lead to unnecessary biopsies. MpMRI-based nomograms enhance predictive accuracy for both PCa and csPCa.
关于前列腺影像报告和数据系统（PI-RADS）v2.1升级和未升级病变单独以及与多参数MRI（mpMRI）特征相结合用于前列腺癌检测的性能数据有限。
评估PI-RADS v2.1升级和未升级病变中的前列腺癌（PCa）和临床显著前列腺癌（csPCa）发生率，并确定可提高检测准确性的mpMRI特征。
本研究纳入了2023年3月至2024年4月期间接受mpMRI和超声引导（US引导）活检的男性。根据PI-RADS v2.1对MRI扫描进行前瞻性评估。从病变轮廓中提取mpMRI特征，包括三维最大直径、病变体积、球形度、表面积与体积比（SVR）、T加权成像信号强度（TWI SI）、扩散加权成像（DWI）SI、T1、T2、质子密度（PD）、表观扩散系数（ADC）以及动态对比增强（DCE）MRI衍生的时间强度曲线（TIC）。进行单变量和多变量逻辑回归分析，以确定不同前列腺区域（移行区和外周区）中与PCa和csPCa相关的特征。
共纳入94例患者（平均年龄65.7岁），有234个病变。在外周区（PZ），PI-RADS 4级升级和未升级病变之间观察到显著差异（P<0.05），而在移行区（TZ）未发现显著差异。TZ中csPCa的危险因素包括病变直径、TIC III型、包膜、T1和PD值。对于PZ中的csPCa，T1、SVR、DWI SI和ADC值被确定为重要危险因素。ROC分析显示csPCa检测具有较高的诊断准确性，TZ的AUC为0.93，PZ的AUC为0.96。
PI-RADS v2.1升级规则提高了TZ中的癌症检测率，但升级PZ中的PI-RADS 3类病变可能导致不必要的活检。基于mpMRI的列线图提高了PCa和csPCa的预测准确性。
