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A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting-state fMRI data

Jiun-Yiing Hu, Evgeniya Kirilina, Till Nierhaus, Smadar Ovadia-Caro, Michelle Livne, Kersten Villringer, Daniel Margulies, Jochen B. Fiebach, Arno Villringer, View ORCID ProfileAhmed A. Khalil
doi: https://doi.org/10.1101/2020.07.17.208058
Jiun-Yiing Hu
1Department of Internal Medicine, University of Maryland Medical Center, Baltimore, USA
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Evgeniya Kirilina
2Department of Neurophysics, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
3Neurocomputation and Neuroimaging Unit, Center for Cognitive Neuroscience Berlin (CCNB), Department of Education and Psychology, Freie Universität Berlin, Germany
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Till Nierhaus
3Neurocomputation and Neuroimaging Unit, Center for Cognitive Neuroscience Berlin (CCNB), Department of Education and Psychology, Freie Universität Berlin, Germany
4Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Smadar Ovadia-Caro
5Department of Cognitive Sciences, School of Psychological Sciences, University of Haifa, Israel
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Michelle Livne
6Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Germany
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Kersten Villringer
6Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Germany
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Daniel Margulies
7Centre National de la Recherche Scientifique (CNRS) UMR 7225, Frontlab, Institut du Cerveau et de la Moelle Épinière, Paris, France
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Jochen B. Fiebach
6Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Germany
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Arno Villringer
4Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
8Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany
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Ahmed A. Khalil
4Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
6Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Germany
8Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany
9Berlin Institute of Health (BIH), Berlin, Germany
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  • ORCID record for Ahmed A. Khalil
  • For correspondence: ahmed-abdelrahim.khalil@charite.de
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Abstract

Objective To identify, characterize, and automatically classify hypoperfusion-related changes in the blood oxygenation level dependent (BOLD) signal in acute stroke using spatial independent component analysis of resting-state functional MRI data.

Methods We applied spatial independent component analysis to resting-state functional MRI data of 37 stroke patients scanned within 24 hours of symptom onset, 17 of whom received follow-up scans the next day. All patients also received dynamic susceptibility contrast MRI. After denoising and manually classifying the components, we extracted a set of temporal and spatial features from each independent component and used a generalized linear model to automatically identify components related to tissue hypoperfusion.

Results Our analysis revealed “Hypoperfusion spatially-Independent Components” (HICs) whose BOLD signal spatial patterns resembled regions of delayed perfusion depicted by dynamic susceptibility contrast MRI. These HICs were detected even in the presence of excessive patient motion, and disappeared following successful tissue reperfusion. The unique spatial and temporal features of HICs allowed them to be distinguished with high accuracy from other components in a user-independent manner (AUC = 0.95, accuracy = 0.96, sensitivity = 1.00, specificity = 0.96).

Interpretation Our study presents a new, non-invasive method for assessing blood flow in acute stroke that minimizes interpretative subjectivity and is robust to severe patient motion.

Competing Interest Statement

J-Y.H., A.A.K., K.V., and J.B.F. are co-inventors of a method for automatically delineating perfusion lesions on perfusion MRI data (European Patent application 17179320.01-1906), distinct from the method described in this study, which is now in the public domain. J.B.F. reports grants from European Union 7th Framework Program and personal fees from Bioclinica, Artemida, Cerevast, Brainomix, BMS, Merck, Eisai, Biogen, Guerbet, and Nicolab outside the submitted work.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted July 18, 2020.
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A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting-state fMRI data
Jiun-Yiing Hu, Evgeniya Kirilina, Till Nierhaus, Smadar Ovadia-Caro, Michelle Livne, Kersten Villringer, Daniel Margulies, Jochen B. Fiebach, Arno Villringer, Ahmed A. Khalil
bioRxiv 2020.07.17.208058; doi: https://doi.org/10.1101/2020.07.17.208058
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A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting-state fMRI data
Jiun-Yiing Hu, Evgeniya Kirilina, Till Nierhaus, Smadar Ovadia-Caro, Michelle Livne, Kersten Villringer, Daniel Margulies, Jochen B. Fiebach, Arno Villringer, Ahmed A. Khalil
bioRxiv 2020.07.17.208058; doi: https://doi.org/10.1101/2020.07.17.208058

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