Keywords: DWI/DTI/DKI, Diffusion/other diffusion imaging techniques
Motivation: Novel Multidimensional diffusion encoding (MDE) technique, diffusional variance decomposition (DIVIDE), may provide more detailed insights into tissue microstructure.
Goal(s): To evaluate the feasibility of DIVIDE imaging for human brain.
Approach: Ten healthy-subjects underwent MDE (2D-EPI sequence with 29 linear and 26 spherical b-tensors) twice using 3T-MRI. Regional values of 20 ROIs was extracted for 10 DIVIDE metrics. Coefficient of variation (CV) and interclass correlation coefficient (ICC) were calculated.
Results: Intra-subject CV was less than 5% in almost all regional metrics. Intra-subject CV was lower than that of inter-subject CV in all regional metrics. ICC showed almost perfect agreements for almost all regional metrics.
Impact: Recently developed MDE technique, diffusional variance decomposition (DIVIDE), may be reliably used for measuring diffusion metrics with a potential to provide more detailed insights into tissue microstructure in complex tissues, such as crossing or kissing fiber configurations in the brain.
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