Literature DB >> 35803717

Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome.

Anna K Bonkhoff1, Sungmin Hong2, Martin Bretzner2, Markus D Schirmer2, Robert W Regenhardt2, E Murat Arsava2, Kathleen Donahue2, Marco Nardin2, Adrian Dalca2, Anne-Katrin Giese2, Mark R Etherton2, Brandon L Hancock2, Steven J T Mocking2, Elissa McIntosh2, John Attia2, Oscar Benavente2, John W Cole2, Amanda Donatti2, Christoph Griessenauer2, Laura Heitsch2, Lukas Holmegaard2, Katarina Jood2, Jordi Jimenez-Conde2, Steven Kittner2, Robin Lemmens2, Christopher Levi2, Caitrin W McDonough2, James Meschia2, Chia-Ling Phuah2, Arndt Rolfs2, Stefan Ropele2, Jonathan Rosand2, Jaume Roquer2, Tatjana Rundek2, Ralph L Sacco2, Reinhold Schmidt2, Pankaj Sharma2, Agnieszka Slowik2, Martin Soederholm2, Alessandro Sousa2, Tara M Stanne2, Daniel Strbian2, Turgut Tatlisumak2, Vincent Thijs2, Achala Vagal2, Johan Wasselius2, Daniel Woo2, Ramin Zand2, Patrick McArdle2, Bradford B Worrall2, Christina Jern2, Arne G Lindgren2, Jane Maguire2, Polina Golland2, Danilo Bzdok2, Ona Wu2, Natalia S Rost2.   

Abstract

BACKGROUND AND OBJECTIVES: To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.
METHODS: MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.
RESULTS: A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location. DISCUSSION: Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.
© 2022 American Academy of Neurology.

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Year:  2022        PMID: 35803717      PMCID: PMC9576289          DOI: 10.1212/WNL.0000000000200926

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   11.800


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