Prediction model for extraprostatic extension of prostate based on MRI and clinical indicators

doi:10.3969/j.issn.1006-7795.2025.02.010

Abstract

Abstract: Objective To develop a Nomogram clinical prediction model for the pathological occurrence of extraprostatic extension (EPE) after radical prostatectomy in prostate cancer patients, using simplified site-specific magnetic resonance imaging (MRI) indicators and other clinical parameters. Methods A total of 181 prostate cancer patients ［mean age (69.0±7.3) years］ who underwent radical prostatectomy were included. These patients had received 3-Tesla multi-parametric magnetic resonance imaging (3-T mpMRI) within 6 months prior to surgery. Based on mpMRI measurements ［capsular contact length (CCL)　> 15 mm, capsular bulging/irregularities, diameter of index lesion(dIL), and evident extraprostatic extension (eEPE)］, the dIL*sEPE grading system was derived. The optimal cut-off value of dIL (denoted as dIL) was determined using the Youden J index, and categorized it into a binary variable. A Logistic regression model was established based on the dIL*sEPE grading and clinical scores. The predictive performance of clinical indicators, MRI indicators, and combined clinical and MRI indicators were compared. Finally, a clinical prediction model integrating both clinical and MRI data was developed. Results Pathological EPE was found in 46 out of 181 cases (25.4%). A Nomogram prediction model for EPE was established with a combination of the dIL*sEPE grading and clinical indicators. Conclusion The combination of dIL*sEPE grading with clinical indicators accurately predicts extracapsular extension in prostate cancer. The Nomogram model that established, based on MRI imaging characteristics and clinical indicators has good performance and is easy to use. It is beneficial to stratifying management for prostate cancer patients, and it provides valuable guidance for patients suitable for nerve-sparing surgery.

Key words: prostate cancer, magnetic resonance imaging, prediction model, Nomogram, neoplasm grading, extraprostatic extension

CLC Number:

R737.25

Fan Yunpeng, Xiong Tianyu, Yang Kun, Liu Zhanliang, Jin Song, Xie Ping, Niu Yinong. Prediction model for extraprostatic extension of prostate based on MRI and clinical indicators[J]. Journal of Capital Medical University, 2025, 46(2): 243-251.

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