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

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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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0991
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

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

Qian Du, Haiyi Wang, Baichuan Liu, Xu Bai et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

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

Qian Du, Haiyi Wang, Baichuan Liu, Xu Bai, Huiyi Ye, Honghao Xu, Lizhi Xie
article en

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.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 64%
Radiomics and Machine Learning in Medical Imaging
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Semi-automated Biparametric MRI Peritumoral Radiomics for Predicting the Risk of Positive Surgical Margin in Patients with Prostate Cancer — Qian Du, Haiyi Wang, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS