title: Structural integrity of corticospinal motor fibers predicts motor impairment in chronic stroke.
abstract: OBJECTIVE
  Motor impairment after stroke has been related to infarct size, infarct location, and integrity of motor tracts. To determine the value of diffusion tensor imaging (DTI) as a predictor of motor outcome and its role as a structural surrogate marker of impairment in chronic stroke, we tested correlations between motor impairment and DTI-derived measures of motor tract integrity.
  
  
  METHODS
  Thirty-five chronic stroke patients with varying degrees of recovery underwent DTI and motor impairment assessments. Fibers originating from the precentral gyrus were traced and separated into pyramidal tract (PT) and alternate motor fibers (aMF). Asymmetry indices of fiber number and regional fractional anisotropy (FA) values comparing lesional with nonlesional hemispheres were correlated with motor impairment scores and compared to an age-matched control group.
  
  
  RESULTS
  Fiber number and regional FA value asymmetry significantly differed between the groups with lower values in the patients' lesional hemispheres. Both measures significantly predicted motor impairment with stronger predictions when all motor tracts were combined as compared to predictions using only the PT. The pattern of motor tract damage (PT only vs PT and aMF) led to a classification of mild, moderate, or severe impairment with significant between-group differences in motor impairment scores.
  
  
  CONCLUSIONS
  Diffusion tensor imaging-derived measures are valid structural markers of motor impairment. The integrity of all descending motor tracts, not merely the pyramidal tract, appears to account for stroke recovery. A 3-tier, hierarchical classification of impairment categories based on the pattern of motor tract damage is proposed that might be helpful in predicting recovery potential.
authors.affiliation: Department of Neurology, Beth Israel Deaconess Medical Center/Harvard Medical School, 330 Brookline Ave, Boston, MA 02215, USA.
authors.forename: R
authors.initials: R
authors.lastname: Lindenberg
authors.forename: V
authors.initials: V
authors.lastname: Renga
authors.forename: L L
authors.initials: LL
authors.lastname: Zhu
authors.forename: F
authors.initials: F
authors.lastname: Betzler
authors.forename: D
authors.initials: D
authors.lastname: Alsop
authors.forename: G
authors.initials: G
authors.lastname: Schlaug
mesh_terms: D000704:Analysis of Variance; D016880:Anisotropy; D001931:Brain Mapping; D056324:Diffusion Tensor Imaging; D005260:Female; D007839:Functional Laterality; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009460:Neurologic Examination; D018579:Patient Selection; D011712:Pyramidal Tracts / Q000503:physiopathology*; D020127:Recovery of Function; D020521:Stroke / Q000503:physiopathology*