Corticospinal tract lesion load: An imaging biomarker for stroke motor outcomes.
OBJECTIVE
The aim of this work was to investigate whether an imaging measure of corticospinal tract (CST) injury in the acute phase can predict motor outcome at 3 months in comparison to clinical assessment of initial motor impairment.


METHODS
A two-site prospective cohort study followed up a group of first-ever ischemic stroke patients using the Upper-Extremity Fugl-Meyer (UE-FM) Scale to measure motor impairment in the acute phase and at 3 months. A weighted CST lesion load (wCST-LL) was calculated by overlaying the patient's lesion map on magnetic resonance imaging with a probabilistic CST constructed from healthy control subjects. Regression models were fit to assess the predictive value of wCST-LL and compared with initial motor impairment.


RESULTS
Seventy-six patients (37 from cohort 1 and 39 from cohort 2) completed the study. wCST-LL as well as assessment of motor impairment (UE-FM) in the acute phase correlated with motor impairment (UE-FM) at 3 months in both cohort 1 (R(2)  = 0.69 vs. R(2)  = 0.67; p = 0.43) and cohort 2 (R(2)  = 0.69 vs. R(2)  = 0.62; p = 0.25). In the severely impaired subgroup (defined as UE-FM ≤ 10 at baseline), wCST-LL correlated with outcomes significantly better than clinical assessment (R(2)  = 0.47 vs. R(2)  = 0.11; p = 0.03). In the nonseverely impaired subgroup, stroke patients recovered approximately 70% of their maximal recovery potential. All stroke patients in both cohorts had poor motor outcomes at 3 months (defined as UE-FM ≤ 25) when wCST-LL was ≥ 7.0 cc (positive predictive value was 100%).


CONCLUSIONS
wCST-LL, an imaging biomarker determined in the acute phase, can predict poststroke motor outcomes at 3 months, especially in patients with severe impairment at baseline.
Department of Neurology, MUSC Stroke Center, Medical University of South Carolina, Charleston, SC.|Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC.
Wuwei
W
Feng
Neuroimaging & Stroke Recovery Laboratory, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
Jasmine
J
Wang
Department of Neurology, MUSC Stroke Center, Medical University of South Carolina, Charleston, SC.
Pratik Y
PY
Chhatbar
Neuroimaging & Stroke Recovery Laboratory, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
Christopher
C
Doughty
Section on Biomarkers and Prediction Modeling, Department of Medicine, University of Pittsburgh, Pittsburgh, PA.
Douglas
D
Landsittel
Neuroimaging & Stroke Recovery Laboratory, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
Vasileios-Arsenios
VA
Lioutas
Ralph H. Johnson VA Medical Center, Charleston, SC.|Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC.
Steven A
SA
Kautz
Neuroimaging & Stroke Recovery Laboratory, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
Gottfried
G
Schlaug
D000328:Adult; D000368:Aged; D015415:Biomarkers; D002545:Brain Ischemia / Q000473:pathology / Q000503:physiopathology; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011379:Prognosis; D011712:Pyramidal Tracts / Q000473:pathology / Q000503:physiopathology; D020127:Recovery of Function / Q000502:physiology*; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis / Q000473:pathology* / Q000503:physiopathology*; D013997:Time Factors; D034941:Upper Extremity / Q000503:physiopathology*
D015415:Biomarkers