Microstructural properties in subacute aphasia: concurrent and prospective relationships underpinning recovery.

Abstract

Background: Few investigations examined the relationship between microstructural white matter integrity and subacute post-stroke linguistic performance or the relationship between microstructural integrity and the recovery of language function. We examined two key questions: (1) How does subacute language performance, measured in single words and discourse, relate to the microstructural integrity of key white matter regions of interest in the language network? and (2) Does the integrity of these regions before treatment predict the improvement or resolution of linguistic symptoms immediately and chronically following treatment?

Methods: 58 participants within the first three months of stroke were enrolled in a randomized, single-center, double-blind, sham-controlled, study of anodal transcranial direct current stimulation combined with a computer-delivered speech and language naming therapy for subacute aphasia and were asked to complete magnetic resonance imaging at enrollment. Microstructural integrity was evaluated using diffusion tensor imaging processed with atlas-based segmentation. Regression and correlation analyses were conducted.

Results: A subset of 22 participants received diffusion tensor imaging. Picture naming accuracy significantly correlated with lower mean diffusivity (higher microstructural integrity) in the left posterior inferior temporal gyrus. Recovery of naming performance was predicted by days since stroke and baseline microstructural integrity of the left posterior middle temporal gyrus, arcuate fasciculus, and superior longitudinal fasciculus. Recovery of discourse efficiency was significantly predicted by the same model.

Conclusions: This study demonstrates an association between picture naming and discourse and microstructural integrity of the key regions in the language network for patients with subacute post-stroke aphasia. Baseline microstructural integrity significantly predicts language recovery.