查看文章

A novel predictive model of prostate cancer (PCa) on multiparametric MRI was developed that takes into account the spatial distribution of PCa within the prostate and the spatially-autocorrelated nature of mpMRI data. The performance of the proposed model was compared to the LASSO-based model we previously described on 34 PCa cases using both voxel-wise metrics (AUC) and slice-wise metrics ($$$ s_s $$$) we recently developed. The proposed model achieved superior predictive performance both in terms of AUC (0.81 vs 0.77) and $$$ s_s $$$(0.45 vs. 0.35) over the 34 cases, with significant improvements for the majority of cases.