Neuronal loss is one of the major outcomes of neurodegenerative diseases such as Alzheimer’s disease (AD) [1,2]. Given the microscopic level of changes associated with neurodegeneration, it is challenging to image with conventional MRI techniques. Microstructural diffusion-weighted MRI is a powerful tool, which has been shown to be sensitive to microscopic brain tissue characteristics [3,4]. However, a relative lack of specificity has impeded its transition to clinic.
Here we focus primarily on deriving cell content information in gray matter and apply it to AD. We acquired multi-shell dMRI of two postmortem samples of human hippocampal tissue (one AD and one control) at the same time, with isotropic resolution of 200 mm, using a 16.4T scanner. We modeled signal attenuation based on the observed evidence of faster signal decay of the cellular compartment. Then, we derived the cell volume fraction by fitting the model to the data and compared it within and between our tissues.
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