Tractography-Based Predictors of Poststroke Aphasia: A Systematic Review.

Background

Poststroke aphasia is a common and disabling consequence of ischemic stroke, affecting communication and quality of life. Early identification of patients at risk is essential for prognosis and rehabilitation planning. Diffusion tractography has recently been used to map white matter pathways implicated in language processing and to evaluate their predictive value for poststroke aphasia.

Purpose

In this study, we aimed to evaluate the prognostic value of DTI characteristics of key white matter tracts.

Data sources

A systematic search was conducted in PubMed, Embase, and Scopus until April 2025.

Study selection

We considered studies eligible if they used diffusion MRI tractography to assess structural language pathways in patients with stroke and investigated their association with poststroke aphasia occurrence or severity.

Data analysis

Extracted data included study characteristics, tractography methodology, language assessment tools, and key imaging findings, including tract specific diffusion metrics and tractography derived measures. Because of data insufficiency, qualitative synthesis was conducted.

Data synthesis

Twenty-one studies comprising 550 patients with poststroke aphasia were included. Participants were predominantly older adults, with mean/median ages generally in the late 50s to early 70s. Baseline NIHSS values were commonly in the ∼5-14 range. The timing of diffusion/DTI acquisition varied substantially, spanning hyperacute/acute imaging, early subacute assessments, and later evaluations in the chronic phase. Studies identified left arcuate fasciculus integrity, fractional anisotropy, axial diffusivity, or reconstruction status as the strongest single predictor of aphasia severity and recovery. Loss of arcuate fasciculus reconstruction was associated with markedly lower follow-up Western Aphasia Battery Aphasia Quotient. Ventral stream involvement added prognostic value in several studies. Right hemisphere contributions were inconsistent, although higher callosal anisotropy predicted comprehension gains in 1 cohort. Overall, tract specific microstructure improved prognostic models beyond lesion volume or NIHSS, accounting for an additional 12%-29% of outcome variance in several multivariate analyses.

Limitations

Methodologic variability limited cross-study comparability and precluded quantitative pooling and, as a result, generalizability.

Conclusions

Tractography provides valuable insights into the structural substrates of poststroke aphasia, with the arcuate fasciculus emerging as the most robust predictor. Standardization of tractography protocols and multicenter validation are needed before routine clinical translation.