Prostate cancer risk stratification with magnetic resonance imaging

被引:24
|
作者
Felker, Ely R. [1 ]
Margolis, Daniel J. [1 ]
Nassiri, Nima [2 ]
Marks, Leonard S. [2 ]
机构
[1] Ronald Reagan UCLA Med Ctr, Dept Radiol, Los Angeles, CA USA
[2] Univ Calif Los Angeles, David Geffen Sch Med, Dept Urol, Los Angeles, CA 90095 USA
关键词
MRI; Prostate cancer; Risk stratification; PELVIC LYMPH-NODES; DIFFUSION-WEIGHTED MR; CONTRAST-ENHANCED MRI; ULTRASOUND FUSION; ENDORECTAL COIL; MULTIPARAMETRIC MRI; EXTRACAPSULAR EXTENSION; POTENTIAL BIOMARKERS; ACTIVE SURVEILLANCE; PREDICTIVE-VALUE;
D O I
10.1016/j.urolonc.2016.03.001
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
In recent years, multiparametric magnetic resonance imaging (mpMRI) has shown promise for prostate cancer (PCa) risk stratification. mpMRI, often followed by targeted biopsy, can be used to confirm low-grade disease before enrollment in active surveillance. In patients with intermediate or high-risk PCa, mpMRI can be used to inform surgical management. mpMRI has sensitivity of 44% to 87% for detection of clinically significant PCa and negative predictive value of 63% to 98% for exclusion of significant disease. In addition to tumor identification, mpMRI has also been shown to contribute significant incremental value to currently used clinical nomograms for predicting extraprostatic extension. In combination with conventional clinical criteria, accuracy of mpMRI for prediction of extraprostatic extension ranges from 92% to 94%, significantly higher than that achieved with clinical criteria alone. Supplemental sequences, such as diffusion-weighted imaging and dynamic contrast-enhanced imaging, allow quantitative evaluation of cancer-suspicious regions. Apparent diffusion coefficient appears to be an independent predictor of PCa aggressiveness. Addition of apparent diffusion coefficient to Epstein criteria may improve sensitivity for detection of significant PCa by as much as 16%. Limitations of mpMRI include variability in reporting, underestimation of PCa volume and failure to detect clinically significant disease in a small but significant number of cases. (c) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:311 / 319
页数:9
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