Background: Altered systemic and cellular lipid metabolism plays a pivotal role in the pathogenesis of prostate cancer (PCa). In this study, we aimed to characterize T1-magnetic resonance imaging (MRI)-derived radiomic parameters of periprostatic adipose tissue (PPAT) associated with clinically significant PCa (Gleason score ≥7 [3 + 4]) in a cohort of men who underwent robot-assisted prostatectomy. Methods: Preoperative MRI scans of 98 patients were identified. The volume of interest was defined by identifying an annular shell-like region on each MRI slice to include all surgically resectable visceral adipose tissue. An optimal biomarker method was used to identify features from 7631 intensity- and texture-based properties that maximized the classification of patients into clinically significant PCa and indolent tumors at the final pathology analysis. Results: Six highest ranked optimal features were derived, which demonstrated a sensitivity, specificity, and accuracy of association with the presence of clinically significant PCa, and area under a receiver operating characteristic curve of 0.95, 0.39 0.82, and 0.82, respectively. Conclusion: A highly independent set of PPAT features derived from MRI scans that predict patients with clinically significant PCa was developed and tested. With future external validation, these features may provide a more precise scientific basis for deciding to omit biopsies in patients with borderline prostate-specific antigen kinetics and multiparametric MRI readings and help in the decision of enrolling patients into active surveillance.

中文翻译：

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前列腺周围脂肪组织 MRI 放射组学衍生的特征与临床上显着的前列腺癌相关。

背景：全身和细胞脂质代谢的改变在前列腺癌（PCa）的发病机制中起着关键作用。在这项研究中，我们的目的是表征一组接受过前列腺癌治疗的男性中与临床显着性 PCa（格里森评分≥7 [3 + 4]）相关的 T1 磁共振成像 (MRI) 衍生的前列腺周围脂肪组织 (PPAT) 的放射组学参数。机器人辅助前列腺切除术。方法：对 98 例患者的术前 MRI 扫描进行了鉴定。通过识别每个 MRI 切片上的环形壳状区域来定义感兴趣的体积，以包括所有可手术切除的内脏脂肪组织。使用最佳生物标志物方法来识别 7631 个基于强度和纹理的特性，从而在最终病理分析中最大限度地将患者分类为临床显着的 PCa 和惰性肿瘤。结果：得出了六个排名最高的最佳特征，这些特征证明了与临床显着性 PCa 存在相关的敏感性、特异性和准确性，以及受试者工作特征曲线下面积分别为 0.95、0.39、0.82 和 0.82。结论：开发并测试了一组源自 MRI 扫描的高度独立的 PPAT 特征，可预测患有临床意义的 PCa 的患者。通过未来的外部验证，这些功能可能会为决定对具有临界前列腺特异性抗原动力学和多参数 MRI 读数的患者省略活检提供更精确的科学依据，并有助于决定将患者纳入主动监测。