title: Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging.
abstract: Electrophysiological and neuroimaging studies suggest that the integrity of ipsilesional and inter-hemispheric motor circuits is important for motor recovery after stroke. However, the extent to which each of these tracts contributes to the variance in outcome remains unclear. We examined whether diffusion tensor imaging (DTI)-derived measures of corticospinal and transcallosal tracts predict motor improvement in an experimental neurorehabilitation trial. 15 chronic stroke patients received bihemispheric transcranial direct current stimulation and simultaneous physical/occupational therapy for five consecutive days. Motor impairment was assessed prior to and after the intervention. At baseline, the patients underwent DTI; probabilistic fiber tracking was used to reconstruct the pyramidal tract (PT), alternate descending motor fibers (aMF), and transcallosal fibers connecting primary motor cortices (M1-M1). Ipsilesional corticospinal tracts (PT, aMF) and M1-M1 showed significantly decreased fractional anisotropy (FA) and increased directional diffusivities when compared to age-matched healthy controls. Partial correlations revealed that greater gains in motor function were related to higher FA values and lower directional diffusivities of transcallosal and ipsilesional corticospinal tracts. M1-M1 diffusivity had the greatest predictive value. An additional slice-by-slice analysis of FA values along the corticospinal tracts demonstrated that the more the ipsilesional FA profiles of patients resembled those of healthy controls, the greater their functional improvement. In conclusion, our study shows that DTI-derived measures can be used to predict functional potential for subsequent motor recovery in chronic stroke patients. Diffusivity parameters of individual tracts and tract combinations may help in assessing a patient's individual recovery potential and in determining optimal neurorehabilitative interventions.
authors.affiliation: Department of Neurology, Neuroimaging and Stroke Recovery Laboratories, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts 02215, USA. rlindenb@bidmc.harvard.edu
authors.forename: Robert
authors.initials: R
authors.lastname: Lindenberg
authors.forename: Lin L
authors.initials: LL
authors.lastname: Zhu
authors.forename: Theodor
authors.initials: T
authors.lastname: Rüber
authors.forename: Gottfried
authors.initials: G
authors.lastname: Schlaug
mesh_terms: D000328:Adult; D000368:Aged; D002908:Chronic Disease; D056324:Diffusion Tensor Imaging / Q000379:methods*; D004311:Double-Blind Method; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009044:Motor Cortex / Q000502:physiology*; D011237:Predictive Value of Tests; D011712:Pyramidal Tracts / Q000502:physiology; D020521:Stroke / Q000175:diagnosis* / Q000503:physiopathology*