ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1510049
This article is part of the Research TopicAdvancing Cancer Imaging Technologies: Bridging the Gap from Research to Clinical Practice Volume IIView all 8 articles
Prospective Evaluation of mpMRI-Derived Nomograms for Detecting Prostate Cancer in PI-RADS v2.1 Upgraded and Non-upgraded lesions within the Transition and Peripheral zone
Provisionally accepted
- First People's Hospital of Foshan, Foshan, China
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Background: Limited data exist on the performance of Prostate Imaging Reporting and Data System (PI-RADS) v2.1 upgraded and non-upgraded lesions, alone and combined with multiparametric MRI (mpMRI) features, for prostate cancer detection.Objective: To evaluate the rates of prostate cancer (PCa) and clinically significant prostate cancer(csPCa) rates in PI-RADS v2.1 upgraded and non-upgraded lesions, and to identify mpMRI features that improve detection accuracy.Methods: This study included men who underwent mpMRI and ultrasound-guided(US-guided) biopsy from March 2023 to April 2024. MRI scans were prospectively evaluated according to PI-RADS v2.1. MpMRI features were extracted from lesion contours, including three-dimensional maximum diameter, lesion volume, sphericity, surface to volume ratio (SVR), T2-weighted imaging signal intensity(SI), diffusion-weighted imaging(DWI) SI, T1 relaxation time, T2 relaxation time, PD relaxation time, apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE) MRI-derived time intensity curve (TIC). Univariable and Univariate and multivariate logistic regression analyses was performed to identify features associated with PCa and csPCa in different prostate zones (transition zone and peripheral zone).Results: A total of 94 patients(mean age, 65.7 years) with 234 lesions were included. Significant differences were observed between upgraded and non-upgraded PI-RADS 4 lesions(p < 0.05) in the peripheral zone (PZ), whereas no significant differences were found in the Transition Zone (TZ). Risk factors for csPCa in the TZ included lesion diameter, TIC III, capsule, T1 relaxation time and PD relaxation time. For csPCa in PZ, T1 relaxation time, SVR, DWI SI, and ADC were important risk factors. ROC analysis demonstrated high diagnostic accuracy for csPCa detection, with AUCs of 0.93 (TZ) and 0.96 (PZ).PI-RADS v2.1 upgrading rules in TZ improve cancer detection, but upgrading PI-RADS category 3 lesions in the PZ may lead to unnecessary biopsies. MpMRI-based Nomograms enhance predictive accuracy for both PCa and csPCa.
Keywords: prostate cancer, Multiparametric magnetic resonance imaging, nomogram, predictive model, synMRI, PI-RADS 2.1
Received: 12 Oct 2024; Accepted: 30 Apr 2025.
Copyright: © 2025 Yi, Wang, Cheng, Xu, Zhang, Luo and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xianhai Zhang, First People's Hospital of Foshan, Foshan, China
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