Abstract
Structural magnetic resonance imaging (sMRI) plays a pivotal role in the evaluation of neurological disorders by providing high-resolution anatomical information. Recent advances in quantitative postprocessing techniques have expanded the utility of sMRI beyond visual assessments by enabling the detection of subtle morphological changes associated with various neurological and psychiatric conditions. This review summarizes current clinical applications of sMRI-based analysis, including brain volumetry, shape analysis, voxel-based morphometry (VBM), surface-based morphometry, source-based morphometry, and voxel-based lesion-symptom mapping (VLSM). Volumetric and shape-based analyses allow for assessments of region-specific atrophy and subregional morphological alterations, while VBM and surface-based morphometry provide complementary insights into tissue volumes and the architecture of the cortical surface. Source-based morphometry reveals network-level patterns of structural covariance, and VLSM directly correlates lesion locations with functional outcomes, particularly in stroke. It has been demonstrated that these methodologies are clinically relevant in conditions such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, and major depressive disorder. By quantifying structural brain alterations that are not readily detectable using conventional imaging methods, these tools improve diagnostic accuracy, support prognostication, and facilitate monitoring of treatment effects. This review highlights the growing integration of sMRI postprocessing techniques into clinical neurology.