Fast diffusion kurtosis imaging (DKI) with Inherent COrrelation-based Normalization (ICON) enhances automatic segmentation of heterogeneous diffusion MRI lesion in acute stroke

摘要

Diffusion kurtosis imaging (DKI) has been shown to augment DWI for defining irreversible ischemic injury. However, the complexity of cerebral structure/composition makes kurtosis map heterogeneous, limiting the specificity of kurtosis hyperintensity to acute ischemia. We proposed an Inherent COrrelation-based Normalization (ICON) analysis to suppress the intrinsic kurtosis heterogeneity for improved characterization of heterogeneous ischemic tissue injury. Fast DKI and relaxation measurements were performed on normal (N=10) and stroke rats following MCAO (N=20). We evaluated the correlations between mean kurtosis (MK), mean diffusivity (MD), fractional anisotropy (FA) derived from fast DKI sequence and relaxation rates of R1 and R2, and found highly significant correlation between MK and R1 (P<0.001). We showed that ICON analysis suppressed the intrinsic kurtosis heterogeneity in the normal cerebral tissue, enabling automated tissue segmentation in an animal stroke model. We found significantly different kurtosis and diffusivity lesion volumes, being 147±59 and 180±66 mm³, respectively (P=0.003, Paired-t test). The ratio of kurtosis to diffusivity lesion volume was 84±19% (P<0.001, One-sample t-test). We found relaxation normalized MK (RNMK) but not MD values significantly different between kurtosis and diffusivity lesions (P<0.001, ANOVA). Our study showed that fast DKI with ICON analysis provides a promising means for demarcating heterogeneous DWI stroke lesion.