Background Stroke-induced aphasia is associated with adverse effects on quality
of life and the ability to return to work. However, the predictors of recovery are still poorly understood. Anatomical variability of the arcuate fasciculus, connecting Broca’s and Wernicke’s areas, has been reported in the healthy population using diffusion tensor imaging tractography. In about 40% of the population the arcuate fasciculus is bilateral and this pattern is advantageous for certain language related functions, such as auditory verbal learning (Catani et al. 2007). Methods In this prospective longitudinal study, anatomical predictors of post-stroke aphasia recovery were investigated using diffusion tractography and arterial spin labelling.
Patients An 18-subject strong aphasia cohort with first-ever unilateral left
hemispheric middle cerebral artery infarcts underwent post stroke language (mean 5±5 days) and neuroimaging (mean 10±6 days) assessments and
neuropsychological follow-up at six months. Ten of these patients were available for reassessment one year after symptom onset. Aphasia was assessed with the Western Aphasia Battery, which provides a global measure of severity (Aphasia Quotient, AQ).
Results Better recover from aphasia was observed in patients with a right arcuate
fasciculus [beta=.730, t(2.732), p=.020] (tractography) and increased fractional
anisotropy in the right hemisphere (p<0.05) (Tract-based spatial statistics). Further, an increase in left hemisphere perfusion was observed after one year (p<0.01) (perfusion). Lesion analysis identified maximal overlay in the periinsular white matter (WM). Lesion-symptom mapping identified damage to periinsular structure as predictive for overall aphasia severity and damage to frontal lobe white matter as predictive of repetition deficits.
Conclusion These findings suggest an important role for the right hemisphere
language network in recovery from aphasia after left hemispheric stroke.
IDENTIFICATION OF ANATOMICAL PREDICTORS OF LANGUAGE RECOVERY AFTER STROKE WITH DIFFUSION TENSOR IMAGING
Forkel, S. J. (Author). 2014
Student thesis: Doctoral Thesis › Doctor of Philosophy