Abstract

Neurodegenerative diseases and neuromuscular disorders impose massive individual and societal burdens. Magnetic resonance (MR) neuroimaging has emerged as an indispensable tool for evaluating many of these conditions. Conventional structural MRI provides morphological data and measures atrophy. Diffusion MRI techniques, including diffusion tensor imaging, reveal microstructural alterations, especially in white matter. Functional MRI maps abnormalities in neural connectivity and networks. MR spectroscopy detects biochemical changes in the brain. Novel quantitative mapping methods enhance subcortical iron quantification. Perfusion MRI assesses alterations in cerebral blood flow. The future of MR neuroimaging lies in multimodal integration and advanced computational analysis. Combining structural, functional, and metabolic MRI data allows multidimensional characterization of pathology. Hybrid imaging with other neuroimaging techniques and modalities further enriches the information. Machine learning and deep learning hold immense potential for extracting subtle disease signatures from big neuroimaging data. MR neuroimaging already plays a pivotal role in elucidating disease mechanisms and improving diagnosis and monitoring. Ongoing advances promise to provide even more sensitive biomarkers to detect preclinical disease stages, track progression, predict prognosis, and guide interventions. MR neuroimaging seems poised to transform the management of major neurodegenerative and neuromuscular diseases.