Keywords: Cancer, Prostate, ADC, Biomarkers, Diagnosis/Prediction, Tumors
Motivation: Cribriform growth (GP4Crib+) is a Gleason 4 sub-pattern associated with worse prostate cancer outcomes. Identification of GP4Crib+ based on MRI would benefit personalized treatment-decision for intermediate-risk patients.
Goal(s): To differentiate GP4Crib+ from non-cribriform and Gleason 3 patterns (GP4Crib-/GP3) using MRI.
Approach: T2-weighted, apparent diffusion coefficient (ADC) and fractional blood volume maps from 1.5/3T MRI were used. Histological GP3, GP4Crib- and GP4Crib+ regions were segmented on whole-mount specimens and co-registered to MRI sequences. Radiomics features were extracted and a logistic regression was trained.
Results: The model based on 90th percentile ADC feature achieved a ROC-AUC of 0.75 and a Precision-Recall AUC of 0.35 (chance-level:0.10).
Impact: This fundamental analysis suggests that 90th Percentile ADC could be useful to identify GP4Crib+ regions in a diagnostic setting.
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