Background:
DL-CAD for prediction of clinically significant prostate cancer (csPCa) in mpMRI is developed to aid radiologists in PI-RADS evaluation. DL-CAD predictions have low accuracy, possibly due to clinical risk factors of csPCa that are not taken into account by DL-CAD.
Purpose:
Aim is to identify patient subgroups of clinical characteristics in which DL-CAD predictions differ from radiologists.
Methods:
DL-CAD was applied to a test cohort of men examined for PCa according to PI-RADSv2 between 2016 and 2017. Ground truth was provided by manually annotated PI-RADS >=4 lesions. Patient age and PSA were derived from the electronic patient record and other variables were mined from the written radiological reports. False and correct predicted patients were compared on variable distributions and false positive rates were compared between variable categories.
Results:
CsPCa was predicted for a total of 482 men (36.9% PIRADS >=4). Benign and malignant patients statistically differed on all clinical variables (P<.05). DL-CAD negative predictive value and positive predictive value were 0.912 and 0.457, respectively. False and correct positive predicted patients significantly differed on age (P<.05), PSA (P<.001), and PSAD (P<.001) as well as prostate volume (P<.001), number of lesions (P<.001), and number of affected zones (P<.001). Analysis of negative predictions was inconclusive due to small population size.
Conclusions:
False positive DL-CAD csPCa predictions are due to unavailable clinical variables that are used in radiologists' PI-RADS risk assessment. We advise to study the effect of including age, PSA and PSAD information in DL-CAD input on prediction accuracy.