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Performance Comparison of Different Neuroimaging Methods for Predicting Upper Limb Motor Outcomes in Patients after Stroke

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  • معلومة اضافية
    • بيانات النشر:
      Hindawi Limited, 2022.
    • الموضوع:
      2022
    • نبذة مختصرة :
      Several neuroimaging methods have been proposed to assess the integrity of the corticospinal tract (CST) for predicting recovery of motor function after stroke, including conventional structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI). In this study, we aimed to compare the predicative performance of these methods using different neuroimaging modalities and optimize the prediction protocol for upper limb motor function after stroke in a clinical environment. We assessed 28 first-ever stroke patients with upper limb motor impairment. We used the upper extremity module of the Fugl-Meyer assessment (UE-FM) within 1 month of onset (baseline) and again 3 months poststroke. sMRI (T1- and T2-based) was used to measure CST-weighted lesion load (CST-wLL), and DTI was used to measure the fractional anisotropy asymmetry index (FAAI) and the ratio of fractional anisotropy (rFA). The CST-wLL within 1 month poststroke was closely correlated with upper limb motor outcomes and recovery potential. CST ‐ wLL ≥ 2.068 cc indicated serious CST damage and a poor outcome (100%). CST ‐ wLL < 1.799 cc was correlated with a considerable rate (>70%) of upper limb motor function recovery. CST-wLL showed a comparable area under the curve (AUC) to that of the CST-FAAI ( p = 0.71 ). Inclusion of extra-CST-FAAI did not significantly increase the AUC ( p = 0.58 ). Our findings suggest that sMRI-derived CST-wLL is a precise predictor of upper limb motor outcomes 3 months poststroke. We recommend this parameter as a predictive imaging biomarker for classifying patients’ recovery prognosis in clinical practice. Conversely, including DTI appeared to induce no significant benefits.
    • File Description:
      text/xhtml
    • ISSN:
      1687-5443
      2090-5904
    • Rights:
      OPEN
    • الرقم المعرف:
      edsair.doi.dedup.....f2fd5fe507e27d68b20ce3a82d254cc5