Background: Stroke is a leading cause of mortality and long-term disability, and aphasia is among its most common and debilitating sequelae. Diffusion tensor imaging (DTI) and advanced diffusion imaging techniques enable the assessment of white matter integrity and provide clinically relevant measures in post-stroke aphasia. Methods: We conducted a comprehensive review of studies applying DTI or advanced diffusion imaging to investigate structural connectivity in adults with post-stroke aphasia (PSA). PubMed, CENTRAL, Ovid MEDLINE, and Embase were searched, and eligible studies were synthesized according to their diagnostic, prognostic, or therapeutic focus. Results: Ninety-five studies were included. Of these, 59 were classified as diagnostic, 17 as prognostic, and 19 as therapeutic. Most studies employed conventional DTI (n = 77), while a growing body of research utilized advanced diffusion models, including CSD, DSI, and DKI (n = 18). Conclusions: This comprehensive synthesis demonstrates the evolution of diffusion imaging in PSA research. While conventional DTI has provided foundational insights, advanced diffusion methods offer superior characterization of complex fiber architecture and improved clinical–anatomical correlation. Diffusion-derived markers of dorsal and ventral language pathways were consistently associated with language performance, while connectome-level analyses highlighted the importance of preserved global network architecture for recovery. Continued efforts are needed to translate diffusion imaging findings into clinical applicable biomarkers to guide personalized aphasia rehabilitation, with greater use of advanced methods.
White matter predictors of cerebellar tDCS treatment effects in aphasia rehabilitation
Introduction Cerebellar transcranial direct current stimulation (tDCS) combined with language therapy can aid in chronic aphasia recovery, but the neural mechanisms and biomarkers of treatment efficacy remain uncertain. Methods In this secondary analysis of data from a previously conducted clinical trial, we used a randomized, double-blind, sham-controlled, within-subject crossover design with a study sample of 19 participants with post-stroke aphasia. We assessed the degree to which baseline properties of cerebro-cerebellar white matter tracts can predict or moderate longitudinal treatment effects at three time points: post-treatment, 2 weeks post-treatment, and 2 months post-treatment. Tract properties were measured by fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging (DTI). We also tested whether there are differential effects between trained and untrained language tasks and between cerebellar tDCS polarity (anodal and cathodal). Results Baseline measures of tracts connecting the left lesioned cortex to the right posterolateral cerebellum (stimulation target) influenced treatment gains for untrained tasks, relative to sham control. In contrast, for the trained task, treatment gains were influenced by baseline measures of tracts connecting the non-stimulated left cerebellum with the contralateral right cerebral cortex. Although there were no consistent effects from cerebellar tDCS polarity, a highly consistent pattern emerged across all tasks and tracts. Specifically, language improvements were predicted by a baseline tract profile (i.e., higher FA and lower MD) typically associated with higher white matter integrity, especially within the context of stroke-induced white matter decline. Discussion These findings corroborate the potential for baseline tract properties as a biomarker of treatment efficacy and support the notion that adjuvant (cerebellar tDCS + language) therapy preferentially benefits individuals with relatively preserved structural connections within functionally relevant networks. Clinical trial registration ClinicalTrials.gov , identifier (NCT02901574).