1. Characterizing stroke motor recovery by structural and functional MRI L.Y. Lin, L.E. Ramsey, N.V. Metcalf, J. Rengachary, G.L. Shulman, J.S. Shimony, M. Corbetta ASNR 2015; Poster # EP-22

2. Background Patients who suffered stroke affecting CST and motor network often have acute loss of motor function on contralateral side with gradual recovery that varies greatly between patients Traditionally prognosis is determined by clinical factors such as age, education, and initial neurological deficits We aim to characterize stroke recovery with structural and functional connectivity imaging.

3. Patients Subjects – 31 patients with acute ischemic stroke (lesion distribution: 13 cortical, 4 cortical-subcortical, 11 subcortical, 1 cerebella, 2 other) – Patients characteristics: mean age 52.8 (range 22-77), 29 right handed, 14 female – 20 healthy age matched controls Follow-up: Stroke patients were evaluated with motor tests at recruitment (within 4 weeks after stroke), 3 months after stroke, and a year after stroke. At these time points, fMRI was taken to get BOLD data. DTI scans were obtained at 3 months and one year post stroke.

4. Methods Motor behavior was characterized by the factor score which is based on factor analysis of shoulder flexion, wrist extension, hand dynameter, nine hole peg, action research arm test, timed walk, motoricity, and ankle flexion Functional connectivity (FC) was characterized by the correlation of the homotopic pairs of seed regions in the motor network by the BOLD signal Structural connectivity of the CST was characterized by the average FA value obtained from DTI ANOVAs were used to test for changes in FC, FA, and motor behavior scores over time Regression analysis related motor outcome to clinical and neuroimaging variables

5. Color scale of lesion locations with red representing one patient with lesion at that location and yellow representing six. The cortical spinal tract is in teal. Table shows number of patients at each lesion location. Motor Factor Score Ipsilateral Contralateral Acute 3 mo 12 mo Control This graph shows the motor factor scores over time in all three groups. The improvement of contralateral motor factor scores is more notable than the ipsilateral motor factor scores.

6. Fractional anisotropy Ipsilesional Control A Acute 3 mo 12 mo Contralesional Imaging changes over time BOLD Homotopic B Acute 3 mo 12 mo Control Stroke subjects Graphs show FA (A) and BOLD homotopic (B) values at each time point. There is a significant interaction between time and side with FA (p=0.0039 on two factor ANOVA). For BOLD homotopic values, there is improvement in homotopic connectivity in the first three months, but not between three and twelve months.

7. Diffusion FA vs. Factor Score R 2 = 0.5934 p-value = 4.0189e-007 R 2 = 0.080756 p-value = 0.1213 R 2 = 0.63606 p-value = 7.8058e-008 R 2 = 0.051144 p-value = 0.22121 Ipsilesional FA Contralesional FA Contralateral motor factor score Ipsilateral motor factor score 12 months 3 months A B C D Graphs show the correlation between the FA of the CST outside of the lesion and the motor factor score of the corresponding side at 3 months and 12 months. The correlation of FA to factor score is significant on the abnormal side, and has a wider range of values than the normal side.

8. BOLD homotopic vs. Factor Score Acute 3 mo A B BOLD Homotopic 12 mo C Contralateral motor factor score Graphs show the correlation between the BOLD homotopic connectivity of the SMN and the motor factor score of the corresponding side at recruitment (acute) and 12 months. The correlation of FA to factor score is significant at the acute time period only.

9. Multivariable Linear Regression Predicting 12 month Factor Score PredictorsModel 1Model 2Model 3 Age0.053--0.1350 Education level0.0707--0.2696 Acute motor factor score<.0001--<.0001 Acute BOLD Homotopic--0.95910.9344 3 mo FA ratio--<.00010.0145 Total<.0001 R2R2 0.8040. 6544440.846404 This table shows p-value of each model. In the all inclusive model, only acute motor factor score and FA ratio are significant predictors of motor factor score at one year post stroke.

10. Conclusions Stroke causes changes to the CST microstructure that can account for behavioral variability even in the absence of demonstrable lesion within the CST Ipsilesional CST undergoes remodeling post-stroke, even past the three-month window when most of the motor recovery happens FA of the CST, but not inter-hemispheric FC, can improve the prediction of motor outcome based on acute motor scores

11. Acknowledgements This work was supported by a grant from the Doris Duke Charitable Foundation to Washington University to fund Doris Duke Clinical Research Fellow Leanne Lin. Dr. Shimony & Dr. Corbetta for being the PI’s in the project People who helped me Lenny Ramsey Nick Metcalf Jennifer Rengachary Dr. Gordon Shulman Contact & References