Multiparametric MRI (mpMRI) has recently seen further standardization by introduction of the PI-RADS version 2 system. mpMRI/transrectal ultrasound (TRUS)-guided fusion biopsies have demonstrated ability to closely match the histopathology seen after radical prostatectomy. Radiomics is a novel approach to extract a large number of quantitative features from medical imaging and combination with machine learning has demonstrated potential in the classification of mpMRI of the prostate. Here, we aim to compare state of the art radiomics and machine learning with ADC measurements,and prospective radiologist assessment using PI-RADS version 2 (PIRADSv2) in the evaluation of cancer suspicious lesions of the prostate.
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