Computer-aided diagnosis in prostate cancer: a retrospective evaluation of the Watson Elementary system for preoperative tumor characterization in patients treated with robot-assisted radical prostatectomy.

PURPOSE

Computer-aided diagnosis (CAD) may improve prostate cancer (PCa) detection and support multiparametric magnetic resonance imaging (mpMRI) readers for better characterization. We evaluated Watson Elementary (WE) CAD system results referring to definitive pathological examination in patients treated with robot-assisted radical prostatectomy (RARP) in a tertiary referral center.

METHODS

Patients treated with RARP between 2020 and 2021 were selected. WE calculates the Malignancy Attention Index (MAI), starting from the information contained in the mpMRI images. Outcome measures were the capability to predict the presence of PCa, to correctly locate the dominant lesion, to delimit the largest diameter of the dominant lesion, and to predict the extraprostatic extension (EPE).

RESULTS

Overall, tumor presence was confirmed in 46 (92%) WE highly suspicious areas, while it was confirmed in 43 (86%) mpMRI PI-RADS ≥ 4 lesions. The WE showed a positive agreement with mpMRI of 92%. In 98% of cases, visible tumor at WE showed that the highly suspicious areas were within the same prostate sector of the dominant tumor nodule at pathology. WE showed a 2.5 mm median difference of diameter with pathology, compared with a 3.8 mm of mpMRI versus pathology (p = 0.019). In prediction of EPE, WE and mpMRI showed sensitivity, specificity, positive and negative predictive value of 0.81 vs 0.71, 0.56 vs 0.60, 0.88 vs 0.85 and 0.42 vs 0.40, respectively.

CONCLUSION

The WE system resulted accurate in the PCa dominant lesion detection, localization and delimitation providing additional information concerning EPE prediction.