Patients initially diagnosed with MR-visible Gleason 6 prostate cancer: can AI predict upgrade to clinically significant cancer at follow-up?

Abstract

Motivation: Patients with low risk (Gleason 6) MR visible prostate cancer on initial biopsy are frequently upgraded to aggressive higher risk (Gleason 7 or higher) cancer. Identifying this progression early is difficult. Goal(s): To address this using a neural network trained with radiologist labels and whole mount histology of Gleason ≥7 cases to predict pathological upgrading in our cohort. Approach: DecNet was applied to the Gleason 6 initial MRIs to assess if the model could retrospectively identify patients with higher grade disease. Results: Our model had a sensitivity of 84.6% for lesions upgraded to Gleason 7, outperforming PSA density, lesion size and ADC values. Impact: These results showcase the potential of our model in unveiling higher-grade prostate cancer within lesions initially diagnosed as lower grade on pathology.

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