Development of a Radiomic-Based Model Predicting Lymph Node Involvement in Prostate Cancer Patients.

ABSTRACT: Significant advances in lymph node involvement (LNI) risk modeling in prostate cancer (PCa) have been achieved with the addition of visual interpretation of magnetic resonance imaging (MRI) data, but it is likely that quantitative analysis could further improve prediction models. In this study, we aimed to develop and internally validate a novel LNI risk prediction model based on radiomic features extracted from preoperative multimodal MRI. All patients who underwent a preoperative MRI and radical prostatectomy with extensive lymph node dissection were retrospectively included in a single institution. Patients were randomly divided into the training (60%) and testing (40%) sets. Radiomic features were extracted from the index tumor volumes, delineated on the apparent diffusion coefficient

SUBMITTER: Bourbonne V 

PROVIDER: S-EPMC8616049 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature