# Diffusion Tensor Imaging and Advanced Diffusion Imaging in Post-Stroke Aphasia Recovery

## TL;DR

This paper reviews how advanced diffusion imaging techniques can improve understanding and treatment of post-stroke aphasia by analyzing brain white matter changes.

## Contribution

The study provides a comprehensive synthesis of how advanced diffusion imaging methods outperform conventional DTI in post-stroke aphasia research.

## Key findings

- Advanced diffusion methods like CSD, DSI, and DKI offer better characterization of complex fiber architecture.
- Diffusion-derived markers of language pathways correlate with language performance in aphasia patients.
- Preserved global brain network architecture is important for recovery in post-stroke aphasia.

## Abstract

Post-stroke aphasia represents a significant clinical challenge, as damage to the brain’s white matter is just as critical as damage to the language centers themselves. While diffusion tensor imaging (DTI) is more established, this study reviews how advanced diffusion imaging findings can provide a deeper understanding of white matter changes. We specifically assess the utility of these tools in informing diagnosis, prognostic assessment, and treatment-related recovery in post-stroke aphasia.

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.