医学
前列腺癌
前列腺切除术
磁共振成像
脂肪组织
前列腺
接收机工作特性
癌症
生物标志物
放射科
病理
内科学
生物化学
化学
作者
Mohammed Shahait,Rubén Usamentiaga,Yubing Tong,Alex Sandberg,David I. Lee,Jayaram K. Udupa,Drew A. Torigian
出处
期刊:Journal of Endourology
[Mary Ann Liebert]
日期:2023-08-19
卷期号:37 (10): 1156-1161
被引量:2
标识
DOI:10.1089/end.2023.0215
摘要
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.
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