Mohammad Haghighi1, Shivam Shah, Samir S Taneja, Andrew B Rosenkrantz. 1. From the *Department of Radiology, NYU Langone Medical Center, New York; †University of Medicine and Dentistry of New Jersey, Newark; and ‡Division of Urologic Oncology, Department of Urology, NYU Langone Medical Center, New York, NY.
Abstract
PURPOSE: The purpose of this study was to compare the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging for prostate cancer (PCa) detection by performing a meta-analysis of studies evaluating these techniques within the same patient cohort. METHODS: Evidence-based online databases were searched for studies reporting the performance of DWI and DCE in PCa detection in the same patient cohorts using histopathology as reference standard and providing sufficient data to construct 2 × 2 contingency tables. Pooled estimates of diagnostic performance were computed across included studies. RESULTS: Of 80 initial studies identified, 5 studies (total of 265 patients and 1730 prostatic regions) met criteria for inclusion in the meta-analysis. Pooled sensitivity was 58.4% (95% confidence interval [CI], 53.5%-63.1%) for DWI and 55.3% (95% CI, 50.4%-60.1%) for DCE. Pooled specificity was 89.0% (95% CI, 87.2%-0.7%) for DWI and 87.9% (95% CI, 86.0%-89.6%) for DCE. At summary receiver-operating-characteristic analysis, area-under-the-curve was 0.810 (0.059) for DWI and 0.786 (0.079) for DCE. Heterogeneity across studies was high for sensitivity and specificity [inconsistency index (I), >90%], although heterogeneity of specificity was substantially improved after excluding an outlier study in terms of diagnostic threshold (I = 0.0%-68.8%). Relative performance of DWI and DCE remained similar after this exclusion CONCLUSIONS: There was a paucity of studies comparing DWI and DCE in the same patient cohorts, and heterogeneity among these studies was substantial. Nevertheless, performance of DWI and DCE was similar across identified studies, with both techniques showing substantially better specificity than sensitivity. Larger studies with uniform methodology are warranted to further understand relative merits of the 2 techniques.
PURPOSE: The purpose of this study was to compare the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging for prostate cancer (PCa) detection by performing a meta-analysis of studies evaluating these techniques within the same patient cohort. METHODS: Evidence-based online databases were searched for studies reporting the performance of DWI and DCE in PCa detection in the same patient cohorts using histopathology as reference standard and providing sufficient data to construct 2 × 2 contingency tables. Pooled estimates of diagnostic performance were computed across included studies. RESULTS: Of 80 initial studies identified, 5 studies (total of 265 patients and 1730 prostatic regions) met criteria for inclusion in the meta-analysis. Pooled sensitivity was 58.4% (95% confidence interval [CI], 53.5%-63.1%) for DWI and 55.3% (95% CI, 50.4%-60.1%) for DCE. Pooled specificity was 89.0% (95% CI, 87.2%-0.7%) for DWI and 87.9% (95% CI, 86.0%-89.6%) for DCE. At summary receiver-operating-characteristic analysis, area-under-the-curve was 0.810 (0.059) for DWI and 0.786 (0.079) for DCE. Heterogeneity across studies was high for sensitivity and specificity [inconsistency index (I), >90%], although heterogeneity of specificity was substantially improved after excluding an outlier study in terms of diagnostic threshold (I = 0.0%-68.8%). Relative performance of DWI and DCE remained similar after this exclusion CONCLUSIONS: There was a paucity of studies comparing DWI and DCE in the same patient cohorts, and heterogeneity among these studies was substantial. Nevertheless, performance of DWI and DCE was similar across identified studies, with both techniques showing substantially better specificity than sensitivity. Larger studies with uniform methodology are warranted to further understand relative merits of the 2 techniques.
Authors: Devkumar Mustafi; Sophie-Charlotte Gleber; Jesse Ward; Urszula Dougherty; Marta Zamora; Erica Markiewicz; David C Binder; Tatjana Antic; Stefan Vogt; Gregory S Karczmar; Aytekin Oto Journal: AJR Am J Roentgenol Date: 2015-09 Impact factor: 3.959
Authors: M Picchio; P Mapelli; V Panebianco; P Castellucci; E Incerti; A Briganti; G Gandaglia; M Kirienko; F Barchetti; C Nanni; F Montorsi; L Gianolli; S Fanti Journal: Eur J Nucl Med Mol Imaging Date: 2015-01-17 Impact factor: 9.236
Authors: Gianluca Giannarini; Michele Zazzara; Marta Rossanese; Vito Palumbo; Martina Pancot; Giuseppe Como; Maria Abbinante; Vincenzo Ficarra Journal: Front Oncol Date: 2014-11-04 Impact factor: 6.244