Evidence for microscopic kurtosis in neural tissue revealed by correlation tensor MRI.

Abstract

PurposeThe impact of microscopic diffusional kurtosis (µK), arising from restricted diffusion and/or structural disorder, remains a controversial issue in contemporary diffusion MRI (dMRI). Recently, correlation tensor imaging (CTI) was introduced to disentangle the sources contributing to diffusional kurtosis, without relying on a‐priori multi‐gaussian component (MGC) or other microstructural assumptions. Here, we investigated µK in in vivo rat brains and assessed its impact on state‐of‐the‐art methods ignoring µK.Theory and MethodsCTI harnesses double diffusion encoding (DDE) experiments, which were here improved for speed and minimal bias using four different sets of acquisition parameters. The robustness of the improved CTI protocol was assessed via simulations. In vivo CTI acquisitions were performed in healthy rat brains using a 9.4T pre‐clinical scanner equipped with a cryogenic coil, and targeted the estimation of µK, anisotropic kurtosis, and isotropic kurtosis.ResultsThe improved CTI acquisition scheme substantially reduces scan time and importantly, also minimizes higher‐order‐term biases, thus enabling robust µK estimation, alongside Kaniso and Kiso metrics. Our CTI experiments revealed positive µK both in white and gray matter of the rat brain in vivo; µK is the dominant kurtosis source in healthy gray matter tissue. The non‐negligible µK substantially were found to bias prior MGC analyses of Kiso and Kaniso.ConclusionsCorrelation Tensor MRI offers a more accurate and robust characterization of kurtosis sources than its predecessors. µK is non‐negligible in vivo in healthy white and gray matter tissues and could be an important biomarker for future studies. Our findings thus have both theoretical and practical implications for future dMRI research.