title: Connectivity-Based Predictions of Hand Motor Outcome for Patients at the Subacute Stage After Stroke.
abstract: BACKGROUND
  Connectivity-based predictions of hand motor outcome have been proposed to be useful in stroke patients. We intended to assess the prognostic value of different imaging methods on short-term (3 months) and long-term (6 months) motor outcome after stroke.
  
  
  METHODS
  We measured resting state functional connectivity (rsFC), diffusion weighted imaging (DWI) and grip strength in 19 stroke patients within the first days (5-9 days) after stroke. Outcome measurements for short-term (3 months) and long-term (6 months) motor function was assessed by the Motricity Index (MI) of the upper limb and the box and block test (BB). Patients were predominantly mildly affected since signed consent was necessary at inclusion. We performed a multiple stepwise regression analysis to compare the predictive value of rsFC, DWI and clinical measurements.
  
  
  RESULTS
  Patients showed relevant improvement in both motor outcome tests. As expected grip strength at inclusion was a predictor for short- and long-term motor outcome as assessed by MI. Diffusion-based tract volume (DTV) of the tracts between ipsilesional primary motor cortex and contralesional anterior cerebellar hemisphere showed a strong trend (p = 0.05) for a predictive power for long-term motor outcome as measured by MI. DTV of the interhemispheric tracts between both primary motor cortices was predictive for both short- and long-term motor outcome in BB. rsFC was not associated with motor outcome.
  
  
  CONCLUSIONS
  Grip strength is a good predictor of hand motor outcome concerning strength-related measurements (MI) for mildly affected subacute patients. Therefore additional connectivity measurements seem to be redundant in this group. Using more complex movement recruiting bilateral motor areas as an outcome parameter, DTV and in particular interhemispheric pathways might enhance predictive value of hand motor outcome.
authors.affiliation: Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald Greifswald, Germany.
authors.forename: Julia
authors.initials: J
authors.lastname: Lindow
authors.affiliation: Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald Greifswald, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Domin
authors.affiliation: Institute of Neurology, University of Greifswald Greifswald, Germany.
authors.forename: Matthias
authors.initials: M
authors.lastname: Grothe
authors.affiliation: Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald Greifswald, Germany.
authors.forename: Ulrike
authors.initials: U
authors.lastname: Horn
authors.affiliation: Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University DüsseldorfDüsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1), Research Centre JülichJülich, Germany.
authors.forename: Simon B
authors.initials: SB
authors.lastname: Eickhoff
authors.affiliation: Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald Greifswald, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Lotze
keywords: diffusion weighted imaging; motor outcome; prediction; recovery; resting state fMRI; stroke