Abstract #2871

Robust frequency-dependent diffusional kurtosis computation using an efficient direction scheme, axisymmetric modelling and regularization

Jake Hamilton^1,2, Kathy Xu^3,4, Nicole Geremia^3,4, Vania F. Prado^3,4, Marco A.M. Prado^3,5, Arthur Brown^3,4, and Corey A. Baron^1,2

¹Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, Western University, London, ON, Canada, ²Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada, ³Translational Neuroscience Group, Robarts Research Institute, Western University, London, ON, Canada, ⁴Department of Anatomy & Cell Biology, Western University, London, ON, Canada, ⁵Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada

Synopsis

Keywords: Diffusion Analysis & Visualization, Microstructure

Motivation: While diffusion MRI has proven to be valuable for studying tissue microstructure, there is a need to develop more sensitive and specific methods to detect microstructural changes at various spatial scales.

Goal(s): To develop an acquisition and analysis scheme that can robustly compute frequency-dependent diffusional kurtosis metrics.

Approach: Acquisition parameters such as a novel efficient direction scheme were presented along with an analysis pipeline that utilizes axisymmetric modelling, spatial regularization, and maximizes data usage.

Results: We demonstrate the advantage of using the efficient scheme over conventional methods, and the analysis pipeline improves diffusional kurtosis map quality compared to conventionally used methods.

Impact: We present an acquisition and analysis scheme that generates robust frequency-dependent diffusional kurtosis maps, which may offer increased sensitivity to cytoarchitectural changes that occur at various cellular spatial scales over the course of healthy aging, and due to pathological alterations.

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