Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study.


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Type
Article
Change log
Authors
Greer, Matthew D 
Lay, Nathan 
Shih, Joanna H 
Bittencourt, Leonardo Kayat 
Abstract

OBJECTIVES: To evaluate if computer-aided diagnosis (CAD) prior to prostate multi-parametric MRI (mpMRI) can improve sensitivity and agreement between radiologists. METHODS: 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). RESULTS: 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). CONCLUSIONS: CAD-assisted mpMRI improved sensitivity and agreement, but decreased specificity, between radiologists of varying experience. KEY POINTS: • 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.

Description
Keywords
Computer-assisted diagnosis, Image interpretation, MRI scans, Prostate cancer, computer assisted, Aged, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Prostatectomy, Prostatic Neoplasms, Retrospective Studies, Sensitivity and Specificity
Journal Title
Eur Radiol
Conference Name
Journal ISSN
0938-7994
1432-1084
Volume Title
28
Publisher
Springer Science and Business Media LLC