An MRI-based grading system for preoperative risk estimation of positive surgical margin after radical prostatectomy

作者：Lili Xu, Gumuyang Zhang, Daming Zhang, Jiahui Zhang, Xiaoxiao Zhang, Xin Bai, Li Chen, Qianyu Peng, Yu Xiao, Hao Wang, Zhengyu Jin, Hao Sun · 发表于：Insights into Imaging · 年份：2023 · DOI：10.1186/s13244-023-01516-4 · 被引用次数：13 · 研究领域：Prostate Cancer Diagnosis and Treatment、Advanced Radiotherapy Techniques、MRI in cancer diagnosis

OBJECTIVE: To construct a simplified grading system based on MRI features to predict positive surgical margin (PSM) after radical prostatectomy (RP). METHODS: Patients who had undergone prostate MRI followed by RP between January 2017 and January 2021 were retrospectively enrolled as the derivation group, and those between February 2021 and November 2022 were enrolled as the validation group. One radiologist evaluated tumor-related MRI features, including the capsule contact length (CCL) of lesions, frank extraprostatic extension (EPE), apex abutting, etc. Binary logistic regression and decision tree analysis were used to select risk features for PSM. The area under the curve (AUC), sensitivity, and specificity of different systems were calculated. The interreader agreement of the scoring systems was evaluated using the kappa statistic. RESULTS: There were 29.8% (42/141) and 36.4% (32/88) of patients who had PSM in the derivation and validation cohorts, respectively. The first grading system was proposed (mrPSM1) using two imaging features, namely, CCL ≥ 20 mm and apex abutting, and then updated by adding frank EPE (mrPSM2). In the derivation group, the AUC was 0.705 for mrPSM1 and 0.713 for mrPSM2. In the validation group, our grading systems showed comparable AUC with Park et al.'s model (0.672-0.686 vs. 0.646, p > 0.05) and significantly higher specificity (0.732-0.750 vs. 0.411, p < 0.001). The kappa value was 0.764 for mrPSM1 and 0.776 for mrPSM2. Decision curve analysis...