Diffusion kurtosis decomposition (DKD) is a novel advanced diffusion MRI modality relying on customized pulse sequences and high-performance hardware to assess cell shapes and density heterogeneity via the anisotropic and isotropic mean kurtosis parameters, MKa and MKi, which are fundamentally different microstructural properties that are inextricably entangled in conventional diffusion kurtosis imaging (DKI). We have investigated DKD imaging of gliomas in a clinical setting, and for the first time established the correlations between MKa, MKi, and tumor grade. In comparison to conventional diffusion methods, DKD more accurately describes the microstructural changes and provides a useful tool for glioma diagnosis.
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