Abstract 101: Predicting Motor Recovery at One Week After Ischemic Stroke a Combined Transcranial Magnetic Stimulation and MRI Study

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Introduction: The failure of numerous stroke clinical trials partially lies in the difficulty in predicting motor recovery in the acute phase. Because of the interindividual variability in subsequent recovery, better prediction of motor prognosis and earlier patient stratification are required to design a promising protocol for clinical trials. Recently, an algorithm to predict motor recovery at 2 weeks after stroke has been reported by combining diffusion-weighted MRI and transcranial magnetic stimulation (TMS); however, 2 weeks may be too late for therapeutic intervention. The aim of this study was therefore to explore how to predict motor recovery even earlier at 1 week after ischemic stroke.Subjects and Methods: Twenty-five patients with acute ischemic stroke (67.9±10.5 years old) who showed supratentorial lesions and hemiparesis of the upper extremity were prospectively enrolled. Integrity of the corticospinal tract was assessed structurally with MRI and functionally with TMS within 7 days after onset (acute phase), at 10-20 days (subacute), and at 6 months (chronic). The fractional anisotropy (FA) asymmetry index (FAcontra-FAipsi)/(FAcontra+FAipsi) at the level of the cerebral peduncle was calculated on MRI, while motor evoked potential (MEP) was recorded on TMS. The Fugl-Meyer scale was used to evaluate upper limb impairment in the subacute and chronic phase.Results: Patients with detectable MEP at 1 week after onset showed significantly higher Fugl-Meyer score at 6 months compared to those without MEP (65.4 versus 33.6, p=0.011). Those with FA asymmetry index of less than 0.024 at 1 week showed significantly higher Fugl-Meyer score at 6 months compared to those with the index above 0.024 (64.2 versus 40.1, p=0.037).Conclusion: Presence of MEP and smaller asymmetry of FA at 1 week after ischemic stroke could be a useful biomarker for predicting better motor recovery. This finding can be useful in earlier patient stratification in future clinical trials.

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