Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches

Jann, Kay; Orosz, Ariane; Dierks, Thomas; Wang, Danny J J; Wiest, Roland; Federspiel, Andrea (2013). Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches. Brain topography, 26(4), pp. 569-580. New York, N.Y.: Springer US; http://www.springer-ny.com 10.1007/s10548-013-0280-3

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Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > University Psychiatric Services > University Hospital of Psychiatry and Psychotherapy > Psychiatric Neurophysiology (discontinued)
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology

UniBE Contributor:

Jann, Kay; Orosz, Ariane; Dierks, Thomas; Wiest, Roland and Federspiel, Andrea

Subjects:

600 Technology > 610 Medicine & health

ISSN:

0896-0267

Publisher:

Springer US; http://www.springer-ny.com

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:36

Last Modified:

01 Oct 2018 02:30

Publisher DOI:

10.1007/s10548-013-0280-3

PubMed ID:

23508714

Uncontrolled Keywords:

functional connectivity, arterial spin labeling

BORIS DOI:

10.7892/boris.14355

URI:

https://boris.unibe.ch/id/eprint/14355 (FactScience: 221306)

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