PI-RADS guided discovery radiomics for characterization of prostate lesions with diffusion-weighted MRI

To demonstrate the added predictive value of radiomic features to prostate radiology scoring scheme (PIRADS), a systematic approach is required to determine whether there is indeed latent predictive information of prostate cancer in diffusion-weighted magnetic resonance images (DW-MRI) that cannot be captured by radiologists’ visual interpretations alone. In this work, we propose a PI-RADS guided discovery radiomics solution where a predictive model for prostate cancer is built by discovering radiomic features that capture information on the phenotype of lesions, which is not visible to radiologists when using PI-RADS scoring system. We investigated patients with PI-RADS scores indicating presence or absence of significant prostate cancer separately and ran experiments on patients with DW-MRI followed by targeted biopsy, using first and second order quantitative imaging features. Our experiments on DW-MRI and pathology data of 50 patients show that the proposed approach improves the overall accuracy of prostate cancer diagnosis significantly compared to PI-RADS scores alone.