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

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Kirilina,  Evgeniya
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Neurocomputation and Neuroimaging Unit, Department of Education and Psychology, FU Berlin, Germany;

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Nierhaus,  Till
Neurocomputation and Neuroimaging Unit, Department of Education and Psychology, FU Berlin, Germany;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Berlin School of Mind and Brain, Humboldt University Berlin, Germany;

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Khalil,  Ahmed
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Center for Stroke Research, Charité University Medicine Berlin, Germany;
Berlin School of Mind and Brain, Humboldt University Berlin, Germany;
Berlin Institute of Health (BIH), Germany;

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Zitation

Hu, J., Kirilina, E., Nierhaus, T., Ovadia‐Caro, S., Livne, M., Villringer, K., et al. (2021). A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting‐state fMRI. Human Brain Mapping. doi:10.1002/hbm.25610.


Zitierlink: https://hdl.handle.net/21.11116/0000-0009-2A33-F
Zusammenfassung
Individualized treatment of acute stroke depends on the timely detection of ischemia and potentially salvageable tissue in the brain. Using functional MRI (fMRI), it is possible to characterize cerebral blood flow from blood-oxygen-level-dependent (BOLD) signals without the administration of exogenous contrast agents. In this study, we applied spatial independent component analysis to resting-state fMRI data of 37 stroke patients scanned within 24 hr of symptom onset, 17 of whom received follow-up scans the next day. Our analysis revealed "Hypoperfusion spatially-Independent Components" (HICs) whose spatial patterns of BOLD signal 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 (area under the curve = 0.93, balanced accuracy = 0.90, sensitivity = 1.00, and specificity = 0.85). Our study therefore presents a new, noninvasive method for assessing blood flow in acute stroke that minimizes interpretative subjectivity and is robust to severe patient motion.