What type of study is this?

This is a Quantitative Study study.

September 17, 2025

Semi-automated Biparametric MRI Peritumoral Radiomics for Predicting the Risk of Positive Surgical Margin in Patients with Prostate Cancer

Key Points

A semi-automated bpMRI model significantly predicts positive surgical margins in prostate cancer patients, improving prognosis.
Corresponding PTRT2+ADC models achieved an AUC of 0.79, outperforming the clinical model's AUC of 0.64.
Statistical methods employed included the Mann-Whitney U test and multivariable logistic regression analysis for evaluation.
The findings indicate that biparametric MRI-based peritumoral radiomics can aid in preoperative risk assessment for surgeries.

Abstract

Motivation: The occurrence of positive surgical margins (PSM) after robotic-assisted laparoscopic prostatectomy is linked to a higher risk of adverse prognosis in patients with prostate cancer (PCa). Goal(s): To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of the risk of PSM in patientes with PCa. Approach: Statistical methods include the Mann-Whitney U test, multivariable logistic regression analysis, receiver operating characteristic curves and the DeLong test. Results: The corresponding PTRT2+ADC integrated models performed significantly higher AUC value than the clinical model (AUC: 0.79 vs. 0.64) and PTRT2+ADC radiomics (AUC: 0.79 vs. 0.72). Impact: A semi-automated bpMRI-based peritumoral radiomics can efficiently predict the risk of PSM.

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