Perfusion maps based on temporal blood-oxygen-level-dependent signal delays are 
driven by alterations in low frequency oscillations between 0.01 and 0.1 Hz

Khalil, A.; Kirilina, Evgeniya; Villringer, K.; Fiebach, J.; Villringer, Arno

doi:10.1177/0271678X17695989

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Perfusion maps based on temporal blood-oxygen-level-dependent signal delays are driven by alterations in low frequency oscillations between 0.01 and 0.1 Hz

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Villringer, Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Khalil, A., Kirilina, E., Villringer, K., Fiebach, J., & Villringer, A. (2017). Perfusion maps based on temporal blood-oxygen-level-dependent signal delays are driven by alterations in low frequency oscillations between 0.01 and 0.1 Hz. Journal of Cerebral Blood Flow and Metabolism, 37(Suppl. 1): PS02-001, 169-170. doi:10.1177/0271678X17695989.

Cite as: http://hdl.handle.net/21.11116/0000-0004-DB64-5

Abstract

Objectives: Assessing brain perfusion without the need for intravenous contrast agents can be achieved by examining the temporal properties of the blood-oxygen-level-dependent (BOLD) signal [1]. We investigated the characteristics of these perfusion-related BOLD signal changes in stroke patients. Methods: Six patients with acute ischemic stroke received a multiband echo planar imaging sequence (repetition time = 0.4 s, echo time = 30 ms, acquisition time = 340 s, flip angle = 43, sensitive to the BOLD signal) and a standard stroke MRI protocol within 24 hours of symptom onset. The BOLD data underwent spatial independent component analysis (sICA [2]) and time shift analysis (voxelwise cross-correlation with global signal [1]) after bandpass filtering to the following frequencies: low-frequency oscillations (LFOs, 0.01–0.1 Hz), respiration (0.2–0.5 Hz), and cardiac (0.5–1.2 Hz). Bolus-tracking MRI data (time-to-maximum of contrast concentration-time curve, Tmax) are shown for comparison. Results: Hypoperfusion components from sICA were visually identified based on comparison to Tmax maps. These results, along with the time shift analysis maps, are shown for a representative patient in the figure. The spatial distributions of the power in the different frequency bands are also shown [3]. Hypoperfusion showed predominantly slow (<0.05 Hz) BOLD signal oscillations and was not identified using sICA or time shift analysis in the respiratory or cardiac frequency bands in any of the patients.