医学
前列腺癌
前列腺切除术
生化复发
危险分层
介入放射学
断点群集区域
前列腺
风险评估
比例危险模型
放射科
肿瘤科
癌症
内科学
计算机科学
受体
计算机安全
作者
Lars A. R. Reisæter,Jurgen J. Fütterer,Are Losnegård,Yngve Nygård,Jan Ankar Monssen,Karsten Gravdal,Ole J. Halvorsen,Lars A. Akslen,Martin Biermann,Svein A. Haukaas,Jarle Rørvik,Christian Beisland
出处
期刊:European Radiology
[Springer Science+Business Media]
日期:2017-10-06
卷期号:28 (3): 1016-1026
被引量:22
标识
DOI:10.1007/s00330-017-5031-5
摘要
To improve preoperative risk stratification for prostate cancer (PCa) by incorporating multiparametric MRI (mpMRI) features into risk stratification tools for PCa, CAPRA and D'Amico.807 consecutive patients operated on by robot-assisted radical prostatectomy at our institution during the period 2010-2015 were followed to identify biochemical recurrence (BCR). 591 patients were eligible for final analysis. We employed stepwise backward likelihood methodology and penalised Cox cross-validation to identify the most significant predictors of BCR including mpMRI features. mpMRI features were then integrated into image-adjusted (IA) risk prediction models and the two risk prediction tools were then evaluated both with and without image adjustment using receiver operating characteristics, survival and decision curve analyses.37 patients suffered BCR. Apparent diffusion coefficient (ADC) and radiological extraprostatic extension (rEPE) from mpMRI were both significant predictors of BCR. Both IA prediction models reallocated more than 20% of intermediate-risk patients to the low-risk group, reducing their estimated cumulative BCR risk from approximately 5% to 1.1%. Both IA models showed improved prognostic performance with a better separation of the survival curves.Integrating ADC and rEPE from mpMRI of the prostate into risk stratification tools improves preoperative risk estimation for BCR.• MRI-derived features, ADC and EPE, improve risk stratification of biochemical recurrence. • Using mpMRI to stratify prostate cancer patients improves the differentiation between risk groups. • Using preoperative mpMRI will help urologists in selecting the most appropriate treatment.
科研通智能强力驱动
Strongly Powered by AbleSci AI