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Abstract <p>Damage to white matter tracts as a result of stroke leads to aphasia, but the role of these tracts in language recovery remains poorly understood. This systematic review synthesizes evidence on which tracts and which of their volumetric (e.g., volume, fiber number) and microstructural (e.g., diffusivity, anisotropy) characteristics predict recovery. Analysis of 16 eligible studies identified key tracts: the arcuate, superior and inferior longitudinal, inferior frontal-occipital, and uncinate fasciculi. Predictive features included axial diffusivity and mean diffusivity, ratio of axial diffusivity, fractional anisotropy, tract volume, and fiber number. The time post-stroke at which white matter assessments was performed and the design of research influence the predictive relationships. The data obtained on the effect of volumetric and microstructural characteristics of the tracts can be used in theoretical studies to model language recovery in aphasia and in clinical practice to predict rehabilitation potential after stroke.</p>

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White Matter Tract Features as Predictors of Language Outcome in Post-Stroke Aphasia: a Systematic Review

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • K. V. Radusheva,
  • N. I. Ermakova,
  • O. V. Buivolova

摘要

Abstract

Damage to white matter tracts as a result of stroke leads to aphasia, but the role of these tracts in language recovery remains poorly understood. This systematic review synthesizes evidence on which tracts and which of their volumetric (e.g., volume, fiber number) and microstructural (e.g., diffusivity, anisotropy) characteristics predict recovery. Analysis of 16 eligible studies identified key tracts: the arcuate, superior and inferior longitudinal, inferior frontal-occipital, and uncinate fasciculi. Predictive features included axial diffusivity and mean diffusivity, ratio of axial diffusivity, fractional anisotropy, tract volume, and fiber number. The time post-stroke at which white matter assessments was performed and the design of research influence the predictive relationships. The data obtained on the effect of volumetric and microstructural characteristics of the tracts can be used in theoretical studies to model language recovery in aphasia and in clinical practice to predict rehabilitation potential after stroke.