title: Structural connectome disruption at baseline predicts 6-months post-stroke outcome.
abstract: In this study, models based on quantitative imaging biomarkers of post-stroke structural connectome disruption were used to predict six-month outcomes in various domains. Demographic information and clinical MRIs were collected from 40 ischemic stroke subjects (age: 68.1 ± 13.2 years, 17 female, NIHSS: 6.8 ± 5.6). Diffusion-weighted images were used to create lesion masks, which were uploaded to the Network Modification (NeMo) Tool. The NeMo Tool, using only clinical MRIs, allows estimation of connectome disruption at three levels: whole brain, individual gray matter regions and between pairs of gray matter regions. Partial Least Squares Regression models were constructed for each level of connectome disruption and for each of the three six-month outcomes: applied cognitive, basic mobility and daily activity. Models based on lesion volume were created for comparison. Cross-validation, bootstrapping and multiple comparisons corrections were implemented to minimize over-fitting and Type I errors. The regional disconnection model best predicted applied cognitive (R(2)  = 0.56) and basic mobility outcomes (R(2)  = 0.70), while the pairwise disconnection model best predicted the daily activity measure (R(2)  = 0.72). These results demonstrate that models based on connectome disruption metrics were more accurate than ones based on lesion volume and that increasing anatomical specificity of disconnection metrics does not always increase model accuracy, likely due to statistical adjustments for concomitant increases in data dimensionality. This work establishes that the NeMo Tool's measures of baseline connectome disruption, acquired using only routinely collected MRI scans, can predict 6-month post-stroke outcomes in various functional domains including cognition, motor function and daily activities. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Department of Radiology, Weill Cornell Medical College, New York, New York.|Feil Family Brain and Mind Research Institute, New York, New York.
authors.forename: Amy
authors.initials: A
authors.lastname: Kuceyeski
authors.affiliation: Feil Family Brain and Mind Research Institute, New York, New York.|Department of Neurology, Weill Cornell Medical College, New York, New York.
authors.forename: Babak B
authors.initials: BB
authors.lastname: Navi
authors.affiliation: Feil Family Brain and Mind Research Institute, New York, New York.|Department of Neurology, Weill Cornell Medical College, New York, New York.
authors.forename: Hooman
authors.initials: H
authors.lastname: Kamel
authors.affiliation: Department of Radiology, Weill Cornell Medical College, New York, New York.|Feil Family Brain and Mind Research Institute, New York, New York.
authors.forename: Ashish
authors.initials: A
authors.lastname: Raj
authors.affiliation: Feil Family Brain and Mind Research Institute, New York, New York.|Department of Neurology, Weill Cornell Medical College, New York, New York.
authors.forename: Norman
authors.initials: N
authors.lastname: Relkin
authors.affiliation: Rehabilitation Medicine, New York, New York.|School of Health and Natural Sciences, Mercy College, New York, New York.
authors.forename: Joan
authors.initials: J
authors.lastname: Toglia
authors.affiliation: Feil Family Brain and Mind Research Institute, New York, New York.|Department of Neurology, Weill Cornell Medical College, New York, New York.
authors.forename: Costantino
authors.initials: C
authors.lastname: Iadecola
authors.affiliation: Department of Neurology, Weill Cornell Medical College, New York, New York.|Rehabilitation Medicine, New York, New York.
authors.forename: Michael
authors.initials: M
authors.lastname: O'Dell
mesh_terms: D000368:Aged; D001921:Brain / Q000000981:diagnostic imaging*; D002545:Brain Ischemia / Q000000981:diagnostic imaging*; D063132:Connectome; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016018:Least-Squares Analysis; D008297:Male; D011379:Prognosis; D020521:Stroke / Q000000981:diagnostic imaging*; D000071939:Stroke Rehabilitation; D016896:Treatment Outcome
keywords: connectome; imaging biomarkers; magnetic resonance imaging; outcome assessment; statistical modeling; stroke