Radiomics Enhances Diagnostic and Prognostic Value of Diffusion Kurtosis Imaging in Diffuse Axonal Injury

Abstract

The aim of our study was to investigate the potential of advanced radiomics in analyzing diffusion kurtosis MRI (DKI) to increase the informativeness of DKI in diffuse axonal injury (DAI). We hypothesized that DKI radiomic features could be used to detect microstructural brain injury and predict outcomes in DAI. The study enrolled 31 patients with DAI (mean age 31.48 ± 11.10 years, 8 (25.8%) female) and 12 healthy volunteers (mean age 33.67 ± 11.06 years, 4 (33.3%) female). A total of 342,300 radiomic features were calculated (2282 features per each combination of 10 parametric DKI maps with 15 ROIs). Our results showed that several radiomic features were capable of distinguishing between healthy and injured brain tissue and accurately predicting outcomes with an accuracy of over 0.9. Advanced DKI radiomic features show high diagnostic and prognostic potential in DAI and may outperform average ROI values in DKI maps.