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 (I2), >90%), although heterogeneity of specificity was substantially improved after excluding an outlier study in terms of diagnostic threshold (I2 = 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.
Written by:
Haghighi M, Shah S, Taneja SS, Rosenkrantz AB. Are you the author?
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.
Reference: J Comput Assist Tomogr. 2013 Nov-Dec;37(6):980-8.
doi: 10.1097/RCT.0b013e3182a3f9c7
PubMed Abstract
PMID: 24270122
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