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Article Dans Une Revue Stroke Année : 2016

Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke

Résumé

Background and purpose: The contribution of imaging metrics to predict post-stroke motor recovery needs to be clarified. We tested the added value of early diffusion tensor imaging (DTI) of the corticospinal-tract (CST) towards predicting long-term motor recovery. Methods: 117 patients were prospectively assessed at 24h-72h and 1 year after ischemic stroke with DTI and motor scores (Fugl-Meyer). The initial and final fiber number ratios (iFNr and fFNr) were computed as the number of streamlines along the affected CST normalized to the unaffected side and were compared to each other. The prediction of motor recovery (ΔFugl-Meyer) was first modeled using initial Fugl-Meyer and iFNr. Multivariate ordinal logistic regression models were also used to study the association of iFNr, initial Fugl- Meyer, age and stroke volume with Fugl-Meyer at 1 year. Results: The iFNr correlated with the fFNr at 1 year (r=0.70, p<0.0001). The initial Fugl- Meyer strongly predicted motor recovery (~73% of initial impairment) for all patients except those with initial severe stroke (Fugl-Meyer<50). For these severe patients (n=26), initial Fugl-Meyer was not correlated to motor recovery (R2=0.13, p=ns), while iFNr showed strong correlation (R2=0.56, p<0.0001). In multivariate analysis the iFNr was an independent predictor of motor outcome (β=2.601, 95%CI=0.304-5.110, p=0.031), improving prediction compared to using only initial Fugl-Meyer, age and stroke volume (p=0.026). Conclusion: Early measurement of FNr at 24h-72h post-stroke is a surrogate marker of CST integrity and provides independent prediction of motor outcome at 1 year especially for patients with severe initial impairment.
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hal-01294872 , version 1 (29-03-2016)

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Antoine Bigourdan, Fanny Munsch, Pierrick Coupé, Charles R. G. Guttmann, Sharmila Sagnier, et al.. Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke. Stroke, 2016, ⟨10.1161/STROKEAHA.115.011576⟩. ⟨hal-01294872⟩

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