Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Eur Radiol. 2021 Jul;31(7):4898-4907. doi: 10.1007/s00330-020-07569-z. Epub 2021 Jan 2.
To develop a simplified MRI-based model to predict the risk for positive surgical margins (PSMs) after radical prostatectomy (RP) in patients with prostate cancer (PCa).
Consecutive patients who underwent RP for PCa were retrospectively identified from a tertiary referral hospital. Patients who underwent RP between January 2014 and June 2014 were assigned as derivation cohort (n = 330) and those between January 2018 and February 2018 were assigned as validation cohort (n = 100). MRI-based predictors associated with PSM were assessed: tumor size, tumor-capsule contact length, the Prostate Imaging Reporting and Data System (PI-RADS) category, tumor location (tumor contact to the apex or posterolateral side near the neurovascular bundle), apical depth, and prostate volume. A prediction model was developed by using multivariable logistic regression, and then it was transformed into a scoring system. The prediction and calibration performance of this scoring system was evaluated using the C statistics and Hosmer-Lemeshow goodness-of-fit test.
A total of 121 (36.7%) and 32 (32.0%) of patients in the derivation and validation cohorts had PSMs after RP. The scoring system consisted of the following variables: tumor-capsule contact length, PI-RADS category, tumor located at the apex and/or posterolateral side. This scoring system provided good prediction performance for PSM in the derivation (C statistics, 0.80 [95% CI: 0.76, 0.85]) and validation (C statistics, 0.77 [95% CI: 0.68, 0.87]) cohorts, and also showed good calibration in both cohorts (p = 0.83 and 0.86, respectively).
An MRI-based scoring system can help estimate the risk of PSM after RP.
• An MRI-based scoring system served as a tool to estimate the risk of positive surgical margin (C statistics, 0.80 and 0.77 in the derivation and validation cohorts, respectively) after radical prostatectomy. • Tumor with contact to the apex or posterolateral aspect, the tumor contact length to capsule, and higher PI-RADS category were independent predictors for the presence of positive resection margins after radical prostatectomy in men with prostate cancer. • High-risk patients as determined by the scoring system demonstrated adverse post-surgical outcomes compared with low- or intermediate-risk patients, in regard to longer length (mean length, 13.0 mm versus 3.9 mm in low risk or 6.2 mm in intermediate risk; p ≤ 0.001) and higher Gleason grade at the margin (grades 4 and 5 in 69.4% and 20.4% versus 16.7% and 16.7% in low risk or 46.7% and 5.4% in intermediate risk; p < 0.001).
建立一种简化的 MRI 模型,以预测前列腺癌(PCa)患者根治性前列腺切除术后(RP)发生阳性切缘(PSM)的风险。
从一家三级转诊医院回顾性地确定了接受 PCa RP 的连续患者。将 2014 年 1 月至 2014 年 6 月期间接受 RP 的患者分为推导队列(n=330),并将 2018 年 1 月至 2018 年 2 月期间接受 RP 的患者分为验证队列(n=100)。评估了与 PSM 相关的 MRI 预测因子:肿瘤大小、肿瘤-包膜接触长度、前列腺影像报告和数据系统(PI-RADS)类别、肿瘤位置(肿瘤与尖部或靠近神经血管束的后外侧接触)、顶点深度和前列腺体积。使用多变量逻辑回归建立预测模型,然后将其转化为评分系统。使用 C 统计量和 Hosmer-Lemeshow 拟合优度检验评估该评分系统的预测和校准性能。
在推导和验证队列中,分别有 121 名(36.7%)和 32 名(32.0%)患者在 RP 后发生 PSM。评分系统由以下变量组成:肿瘤-包膜接触长度、PI-RADS 类别、位于尖部和/或后外侧的肿瘤。该评分系统在推导(C 统计量,0.76-0.85)和验证(C 统计量,0.68-0.77)队列中均能很好地预测 PSM,并且在两个队列中均显示出良好的校准(p=0.83 和 0.86,分别)。
基于 MRI 的评分系统有助于估计 RP 后 PSM 的风险。
基于 MRI 的评分系统可作为一种工具,用于估计前列腺癌患者根治性前列腺切除术后(C 统计量分别为 0.80 和 0.77)的 PSM 风险。
在前列腺癌患者中,与尖部或后外侧接触、肿瘤与包膜接触长度和较高的 PI-RADS 类别是阳性切缘存在的独立预测因子。
与低危或中危患者相比,高危患者(根据评分系统确定)的术后结果较差,表现在较长的长度(平均长度,高危为 13.0mm,低危为 3.9mm,中危为 6.2mm;p≤0.001)和更高的切缘处格里森评分(4 级和 5 级分别为 69.4%和 20.4%,低危为 16.7%和 16.7%,中危为 46.7%和 5.4%;p<0.001)。