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Evaluating NODDI‐based biomarkers of Alzheimer’s disease

Multi‐compartment (MC) diffusion MRI (dMRI) models are increasingly used to evaluate brain microstructure beyond the classic diffusion tensor model (DTI). The ability to separate the neural tissue into distinct compartments, i.e., intracellular volume fraction (ICVF), extracellular volume fraction (ECVF) and free‐water (FW), offers novel biomarkers for early detection of cognitive decline and Alzheimer’s disease. The most commonly used MC model used is Neurite Orientation Dispersion and Density Imaging (NODDI). Recent evidence shows that the voxel‐wise volume fractions compartment can be wrongly estimated if the same T2 relaxation time is assumed for the gray matter (GM), white matter (WM) and corticospinal fluid (CSF). To more accurately estimate the tissue compartments, here we use a novel method recently proposed by the DMIPY package (https://github.com/AthenaEPI/dmipy), that initially estimates a response function for each brain region (GM, WM and CSF) and uses these to better estimate the ICVF and FW compartments.