To evaluate if computer-aided diagnosis (CAD) prior to prostate multi-parametric MRI (mpMRI) can improve sensitivity and agreement between radiologists.
Nine radiologists (three each high, intermediate, low experience) from eight institutions participated. A total of 163 patients with 3-T mpMRI from 4/2012 to 6/2015 were included: 110 cancer patients with prostatectomy after mpMRI, 53 patients with no lesions on mpMRI and negative TRUS-guided biopsy. Readers were blinded to all outcomes and detected lesions per PI-RADSv2 on mpMRI. After 5 weeks, readers re-evaluated patients using CAD to detect lesions. Prostatectomy specimens registered to MRI were ground truth with index lesions defined on pathology. Sensitivity, specificity and agreement were calculated per patient, lesion level and zone-peripheral (PZ) and transition (TZ).
Index lesion sensitivity was 78.2% for mpMRI alone and 86.3% for CAD-assisted mpMRI (p = 0.013). Sensitivity was comparable for TZ lesions (78.7% vs 78.1%; p = 0.929); CAD improved PZ lesion sensitivity (84% vs 94%; p = 0.003). Improved sensitivity came from lesions scored PI-RADS < 3 as index lesion sensitivity was comparable at PI-RADS ≥ 3 (77.6% vs 78.1%; p = 0.859). Per patient specificity was 57.1% for CAD and 70.4% for mpMRI (p = 0.003). CAD improved agreement between all readers (56.9% vs 71.8%; p < 0.001).
CAD-assisted mpMRI improved sensitivity and agreement, but decreased specificity, between radiologists of varying experience.
• Computer-aided diagnosis (CAD) assists clinicians in detecting prostate cancer on MRI. • CAD assistance improves agreement between radiologists in detecting prostate cancer lesions. • However, this CAD system induces more false positives, particularly for less-experienced clinicians and in the transition zone. • CAD assists radiologists in detecting cancer missed on MRI, suggesting a path for improved diagnostic confidence.
European radiology. 2018 Apr 12 [Epub ahead of print]
Matthew D Greer, Nathan Lay, Joanna H Shih, Tristan Barrett, Leonardo Kayat Bittencourt, Samuel Borofsky, Ismail Kabakus, Yan Mee Law, Jamie Marko, Haytham Shebel, Francesca V Mertan, Maria J Merino, Bradford J Wood, Peter A Pinto, Ronald M Summers, Peter L Choyke, Baris Turkbey
Molecular Imaging Program, NCI, NIH, 10 Center Drive, Room B3B85, Bethesda, MD, 20892, USA., Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA., Biometric Research Program, NCI, NIH, Bethesda, MD, USA., Department of Radiology, University of Cambridge School of Medicine, Cambridge, UK., Universidade Federal Fluminense and CDPI Clinics/DASA, Rio de Janeiro, RJ, Brazil., George Washington University Hospital, Washington, DC, USA., Hacettepe University, Ankara, Turkey., Singapore General Hospital, Singapore, Singapore., Radiology and Imaging Sciences Department, Clinical Center, NIH, Bethesda, MD, USA., Department of Radiology, Nephrology Center, Mansoura University, Mansoura, 35516, Egypt., Laboratory of Pathology, NCI, NIH, Bethesda, MD, USA., Center for Interventional Oncology, NCI and Radiology Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA., Urologic Oncology Branch, NCI, NIH, Bethesda, MD, USA., Molecular Imaging Program, NCI, NIH, 10 Center Drive, Room B3B85, Bethesda, MD, 20892, USA. .