基于MRI及临床指标的前列腺被膜外侵犯预测模型

doi:10.3969/j.issn.1006-7795.2025.02.010

首都医科大学学报 ›› 2025, Vol. 46 ›› Issue (2): 243-251.doi: 10.3969/j.issn.1006-7795.2025.02.010

• 前列腺疾病诊疗技术与进展 • 上一篇下一篇

基于MRI及临床指标的前列腺被膜外侵犯预测模型

范云鹏^1，2,熊天宇^1，2,杨坤^1，2,刘占良^1，2,靳松^1，2,谢萍³,牛亦农^{1，2 *}

1.首都医科大学附属北京友谊医院泌尿外科，北京 100050；2.北京市卫生健康委员会泌尿外科研究所，北京 100050；3.首都医科大学基础医学院细胞生物学系，北京 100069

收稿日期:2025-01-13 出版日期:2025-04-21 发布日期:2025-04-14
通讯作者: 牛亦农 E-mail:niuyinong@mail.ccmu.edu.cn
基金资助:
国家自然科学基金项目（82170783），北京市临床重点专科项目（20240930）。

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

Fan Yunpeng^1,2, Xiong Tianyu^1,2, Yang Kun^1,2, Liu Zhanliang^1,2, Jin Song^1,2, Xie Ping³, Niu Yinong^{1,2 *}

1. Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China;2. Institute of Urology, Beijing Municipal Health Commission, Beijing 100050, China;3. Department of Cell Biology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China

Received:2025-01-13 Online:2025-04-21 Published:2025-04-14
Supported by:
This study was supported by National Natural Science Foundation of China (82170783), Beijing Key Clinical Specialty Project (20240930).

摘要/Abstract

摘要： 目的利用简化的部位特异性磁共振（magnetic resonance imaging，MRI）指标及其他临床指标建立前列腺癌根治术后病理中出现前列腺被膜外侵犯（extraprostatic extension, EPE）的Nomogram临床预测模型。方法回顾性纳入181例行前列腺癌根治术的(69.0±7.3)岁患者，他们在术前6个月内行3-特斯拉多参数MRI(3-Tesla multi-parametric MRI，3-T mpMRI)检查。根据被膜接触长度(capsular contact length, CCL) > 15 mm 、被膜膨出/不规则（bulge/irregularity）、目标病灶直径(diameter of index leision, dIL)、MRI上明显的前列腺被膜外侵犯(evident extraprostatic extension, eEPE)等mpMRI测量指标得出dIL*sEPE分级。通过Youden指数确定dIL的最佳截断值，将其分为一个二分类变量，记为dIL。建立基于dIL*sEPE分级和临床指标的Logistic回归模型。同时，比较临床指标、MRI指标、MRI指标联合临床指标的预测效能。最终，建立临床数据联合MRI数据的临床预测模型。结果病理性EPE占25.4%(46/181)。联合dIL*sEPE分级临床指标建立预测EPE的Nomogram预测模型。结论 dIL*sEPE与临床指标联合时可准确预测前列腺被膜外侵犯。基于MRI影像特征及临床指标建立的预测前列腺癌根治术后EPE的Nomogram模型性能良好、使用简便，有益于前列腺癌根治术患者的分层管理，对适合行神经保留手术的患者有一定指导意义。

关键词: 前列腺癌, 磁共振成像, 预测模型, 列线图, 肿瘤分级, 前列腺被膜外侵犯

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

中图分类号:

R737.25

范云鹏, 熊天宇, 杨坤, 刘占良, 靳松, 谢萍, 牛亦农. 基于MRI及临床指标的前列腺被膜外侵犯预测模型[J]. 首都医科大学学报, 2025, 46(2): 243-251.

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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基于MRI及临床指标的前列腺被膜外侵犯预测模型

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

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