Abstract

Abstract Diffusion magnetic resonance imaging offers unique in vivo sensitivity to tissue microstructure in brain white matter, which undergoes significant changes during development and is compromised in virtually every neurological disorder. Yet, the challenge is to develop biomarkers that are specific to micrometer-scale cellular features in a human MRI scan of a few minutes. Here, we quantify the sensitivity and specificity of a multicompartment diffusion modeling framework to the density, orientation, and integrity of axons. We demonstrate that using a machine learning-based estimator, our biophysical model captures the morphological changes of axons in early development, acute ischemia, and multiple sclerosis (total N = 821). The methodology of microstructure mapping is widely applicable in clinical settings and in large imaging consortium data to study development, aging, and pathology.

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