A systematic review of diffusion microstructure imaging (DMI): Current and future applications in neurology research

Abstract

Diffusion Microstructure Imaging (DMI) has emerged as a transformative neuroimaging technique that offers unprecedented insights into brain tissue microstructure by disentangling contributions from the volumes of the intra-axonal (V-intra), extra-axonal (V-extra), and free-fluid (V-CSF) compartments. We aimed to systematically review the current applications and future directions of the DMI for neurology research. Following the PRISMA 2020 guidelines, PubMed, Scopus, Web of Science, and Embase were searched for articles published up to May 2025. Our review synthesized narratively, DMI’s applications in neurology, and evaluated its diagnostic and prognostic potential across neurological disorders. Twenty-one studies were included. Across various studies on tumors, neurodegeneration, stroke, aging, hydrocephalus, epilepsy, and pain, DMI consistently identified microstructural alterations that could not be detected by conventional diffusion tensor imaging and diffusion kurtosis imaging. In brain tumors, the DMI demonstrated high diagnostic accuracy by distinguishing lymphoma from glioblastoma and characterizing peritumoral infiltration in glioblastoma compared to metastases. In Parkinsonian syndromes, elevated free-water fractions in the basal ganglia and cerebellopontine tracts were strongly correlated with clinical severity and enabled subtype differentiation. In cases of acute stroke and COVID-19, DMI metrics provided more sensitive mapping of cytotoxic and vasogenic edema than the Apparent Diffusion Coefficient. Normative aging studies revealed distinct patterns of tract-specific maturation and senescence. Furthermore, applications in idiopathic normal pressure hydrocephalus, epilepsy, and migraine showed DMI’s capability to detect fluid accumulation, axonal loss, and the integrity of nociceptive pathways, respectively. This review underscores that DMI demonstrates superior sensitivity compared to conventional diffusion techniques.