Can biparametric MRI accurately detect prostate cancer?
Research from the last 17 years shows that biparametric MRI (bpMRI) gives radiologists an accurate tool for detecting prostate cancer (PCa), according to a new meta-analysis published by the American Journal of Roentgenology.
The authors noted that interest in bpMRI has grown in recent years as healthcare providers continue to search for ways to reduce costs and improve patient comfort, but questions about its overall effectiveness remain.
“The clinical significance of bpMRI of the prostate remains unclear and controversial,” wrote lead author Xiang-ke Niu, MD, department of radiology at the Affiliated Hospital of Chengdu University in Chengdu, Sichuan, China. “Accordingly, we sought to collect as much extractable data as possible by conducting a systematic review and meta-analysis to determine the diagnostic accuracy and technical considerations of bpMRI for the diagnosis of PCa.”
Niu et al. examined the results of 33 studies conducted from January 2000 to July 2017. The studies included more than 2,300 patients. The pooled sensitivity of bpMRI was 0.81 and the pooled specificity was 0.77.
“Our meta-analysis showed that bpMRI is an accurate diagnostic imaging tool in the detection of PCa,” the authors wrote.
Eleven studies the team examined compared bpMRI with multiparametric MRI (mpMRI). The pooled sensitivity of mpMRI was significantly superior to bpMRI, but there was no significant difference in the specificity of these two modalities.
Niu and colleagues did note that they found “significant heterogeneity among the included studies,” but they were sure to address it.
“To deal with this issue, we used meta-regression to explore the sources of heterogeneity and then performed the subgroup analysis,” the authors wrote. “Interestingly, the characteristics of the study affected only sensitivity. There is higher sensitivity in high-bias (e.g., retrospective study, nonconsecutive enrollment of patients) research than in low-bias research, because high-bias studies overestimate the accuracy of test methods.”
Michael has more than 18 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.