Can computer-aided diagnosis assist in the identification of prostate cancer on prostate MRI? A multi-center, multi-reader investigation
Document Type
Journal Article
Publication Date
9-1-2018
Journal
Oncotarget
Volume
9
Issue
73
DOI
10.18632/oncotarget.26100
Keywords
Computer-aided diagnosis; Multiparametric MRI; PI-RADSv2; Prostate cancer; Tumor detection
Abstract
© Gaur et al. For prostate cancer detection on prostate multiparametric MRI (mpMRI), the Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) and computeraided diagnosis (CAD) systems aim to widely improve standardization across radiologists and centers. Our goal was to evaluate CAD assistance in prostate cancer detection compared with conventional mpMRI interpretation in a diverse dataset acquired from five institutions tested by nine readers of varying experience levels, in total representing 14 globally spread institutions. Index lesion sensitivities of mpMRI-alone were 79% (whole prostate (WP)), 84% (peripheral zone (PZ)), 71% (transition zone (TZ)), similar to CAD at 76% (WP, p=0.39), 77% (PZ, p=0.07), 79% (TZ, p=0.15). Greatest CAD benefit was in TZ for moderately-experienced readers at PI-RADSv2 <3 (84% vs mpMRI-alone 67%, p=0.055). Detection agreement was unchanged but CAD-assisted read times improved (4.6 vs 3.4 minutes, p<0.001). At PI-RADSv2 . 3, CAD improved patientlevel specificity (72%) compared to mpMRI-alone (45%, p<0.001). PI-RADSv2 and CAD-assisted mpMRI interpretations have similar sensitivities across multiple sites and readers while CAD has potential to improve specificity and moderately-experienced radiologistsf detection of more difficult tumors in the center of the gland. The multi-institutional evidence provided is essential to future prostate MRI and CAD development.
APA Citation
Gaur, S., Lay, N., Harmon, S., Doddakashi, S., Mehralivand, S., Argun, B., Barrett, T., Bednarova, S., Girometti, R., Karaarslan, E., Kural, A., Oto, A., Purysko, A., Antic, T., Magi-Galluzzi, C., Saglican, Y., Sioletic, S., Warren, A., Bittencourt, L., Fütterer, J., Gupta, R., Kabakus, I., Law, Y., Margolis, D., Shebel, H., Westphalen, A., Wood, B., Pinto, P., Shih, J., Choyke, P., Summers, R., & Turkbey, B. (2018). Can computer-aided diagnosis assist in the identification of prostate cancer on prostate MRI? A multi-center, multi-reader investigation. Oncotarget, 9 (73). http://dx.doi.org/10.18632/oncotarget.26100