Diffusion kurtosis imaging (DKI), an extension to diffusion tensor imaging (DTI), aims to improve quantification of the hindered/restricted diffusion pattern due to microstructural complexity in the brain. But in order to capture the non-Gaussian diffusion behaviour of water molecules in biological tissues, stronger gradients larger than those employed in standard diffusion weighted imaging (DWI) are required. Here, we explored the test-retest reliability of DKI derived metrics with respect to different gradient strength in a high spatial resolution dataset. It was observed that DKI precision was comparable between b-value=1000, 2000, 3000 s/mm2 and b-value=1000 & 3000 s/mm2 dataset.
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