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

Anna K. Bonkhoff, Sungmin Hong, Martin Bretzner, Markus D. Schirmer, Robert W. Regenhardt, E. Murat Arsava, Kathleen Donahue, Marco Nardin, Adrian Dalca, Anne Katrin Giese, Mark R. Etherton, Brandon L. Hancock, Steven J.T. Mocking, Elissa Mcintosh, John Attia, Oscar Benavente, John W. Cole, Amanda Donatti, Christoph Griessenauer, Laura HeitschLukas Holmegaard, Katarina Jood, Jordi Jimenez-Conde, Steven Kittner, Robin Lemmens, Christopher Levi, Caitrin W. Mcdonough, James Meschia, Chia Ling Phuah, Arndt Rolfs, Stefan Ropele, Jonathan Rosand, Jaume Roquer, Tatjana Rundek, Ralph L. Sacco, Reinhold Schmidt, Pankaj Sharma, Agnieszka Slowik, Martin Soederholm, Alessandro Sousa, Tara M. Stanne, Daniel Strbian, Turgut Tatlisumak, Vincent Thijs, Achala Vagal, Johan Wasselius, Daniel Woo, Ramin Zand, Patrick Mcardle, Bradford B. Worrall, Christina Jern, Arne G. Lindgren, Jane Maguire, Polina Golland, Danilo Bzdok, Ona Wu, Natalia S. Rost

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background and ObjectivesTo examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.MethodsMR 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.ResultsA 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.DiscussionHigher 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.

Original languageEnglish
Pages (from-to)E1364-E1379
JournalNeurology
Volume99
Issue number13
DOIs
StatePublished - Sep 27 2022

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