Impact of Vessel Removal on Classification of Chronic Liver Disease using Radiomics Features and Quantitative T2 Mapping

Motivation: MRI radiomics with T2-mapping has been proposed to detect changes of chronic liver disease (CLD) but may be hampered by liver vasculature. Goal(s): Our goal is to evaluate radiomics features of T2 maps and the impact of vessel removal on CLD classification. Approach: T2 liver maps from a clinical cohort were analyzed using radiomics features and a T2 thresholding-based feature, followed by feature selection and random forest classification. Experiments were conducted on both full liver T2 maps and T2 maps with vessel removal using the Frangi filter. Results: Vessel removal significantly enhanced CLD classification performance as measured by mean AUC. Impact: Our findings have the potential for clinical translation to help establish MRI radiomics with T2-mapping for CLD diagnosis and treatment monitoring.