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Title: | Observational Study of Neuroimaging Biomarkers of Severe Upper Limb Impairment After Stroke. | Austin Authors: | Hayward, Kathryn S ;Ferris, Jennifer K;Lohse, Keith R;Borich, Michael R;Borstad, Alexandra;Cassidy, Jessica M;Cramer, Steven C;Dukelow, Sean P;Findlater, Sonja E;Hawe, Rachel L;Liew, Sook-Lei;Neva, Jason L;Stewart, Jill C;Boyd, Lara A | Affiliation: | Physiotherapy The Florey Institute of Neuroscience and Mental Health Rehabilitation Sciences Graduate Research Program (J.K.F., L.A.B.), University of British Columbia, Vancouver, British Columbia, Canada; Physical Therapy and Neurology (K.R.L.), Washington University School of Medicine in Saint Louis, MO; Division of Physical Therapy (M.R.B.), Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA; School of Health Sciences (A.B.), Department of Physical Therapy, College of St. Scholastica, Duluth, MN; Department of Allied Health Sciences (J.M.C.), University of North Carolina at Chapel Hill, NC; Department of Neurology (S.C.C.), University of California Los Angeles; California Rehabilitation Institute (S.C.C.), Los Angeles, California; Department of Clinical Neurosciences (S.P.D., S.E.F.), Cumming School of Medicine, University of Calgary, Alberta, Canada; School of Kinesiology (R.L.H.), University of Minnesota, Minneapolis; Chan Division of Occupational Science and Occupational Therapy (S.-L.L.), Biokinesiology and Physical Therapy, Biomedical Engineering, and Neurology, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles; Université de Montréal (J.L.N.), École de Kinésiologie et des Sciences de l'activité Physique, Faculté de Médecine, and Centre de recherche de l'institut universitaire de gériatrie de Montréal, Quebec, Canada; and Physical Therapy Program (J.C.S.), Department of Exercise Science, University of South Carolina, Columbia. Medicine (University of Melbourne) |
Issue Date: | 25-Jul-2022 | Date: | 2022 | Publication information: | Neurology 2022-07-25; 99(4) | Abstract: | It is difficult to predict poststroke outcome for individuals with severe motor impairment because both clinical tests and corticospinal tract (CST) microstructure may not reliably indicate severe motor impairment. Here, we test whether imaging biomarkers beyond the CST relate to severe upper limb (UL) impairment poststroke by evaluating white matter microstructure in the corpus callosum (CC). In an international, multisite hypothesis-generating observational study, we determined if (1) CST asymmetry index (CST-AI) can differentiate between individuals with mild-moderate and severe UL impairment and (2) CC biomarkers relate to UL impairment within individuals with severe impairment poststroke. We hypothesized that CST-AI would differentiate between mild-moderate and severe impairment, but CC microstructure would relate to motor outcome for individuals with severe UL impairment. Seven cohorts with individual diffusion imaging and motor impairment (Fugl-Meyer Upper Limb) data were pooled. Hand-drawn regions-of-interest were used to seed probabilistic tractography for CST (ipsilesional/contralesional) and CC (prefrontal/premotor/motor/sensory/posterior) tracts. Our main imaging measure was mean fractional anisotropy. Linear mixed-effects regression explored relationships between candidate biomarkers and motor impairment, controlling for observations nested within cohorts, as well as age, sex, time poststroke, and lesion volume. Data from 110 individuals (30 with mild-moderate and 80 with severe motor impairment) were included. In the full sample, greater CST-AI (i.e., lower fractional anisotropy in the ipsilesional hemisphere, p < 0.001) and larger lesion volume (p = 0.139) were negatively related to impairment. In the severe subgroup, CST-AI was not reliably associated with impairment across models. Instead, lesion volume and CC microstructure explained impairment in the severe group beyond CST-AI (p's < 0.010). Within a large cohort of individuals with severe UL impairment, CC microstructure related to motor outcome poststroke. Our findings demonstrate that CST microstructure does relate to UL outcome across the full range of motor impairment but was not reliably associated within the severe subgroup. Therefore, CC microstructure may provide a promising biomarker for severe UL outcome poststroke, which may advance our ability to predict recovery in individuals with severe motor impairment after stroke. | URI: | https://ahro.austin.org.au/austinjspui/handle/1/34791 | DOI: | 10.1212/WNL.0000000000200517 | ORCID: | 0000-0001-5240-3264 0000-0003-3624-6996 0000-0002-7643-3887 0000-0001-9897-9867 0000-0003-3645-7312 0000-0003-3469-0399 0000-0002-6214-6211 0000-0002-0609-981X 0000-0002-8255-4853 0000-0002-0915-7755 0000-0001-5935-4215 0000-0002-8211-9923 0000-0002-3275-5729 0000-0002-2828-4549 |
Journal: | Neurology | Start page: | e402 | End page: | e413 | PubMed URL: | 35550551 | ISSN: | 1526-632X | Type: | Journal Article | Subjects: | Diffusion Tensor Imaging/methods Stroke/complications Stroke/diagnostic imaging Stroke/pathology Upper Extremity/pathology Pyramidal Tracts/diagnostic imaging Pyramidal Tracts/pathology |
Appears in Collections: | Journal articles |
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