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Quantitative General Linear Model Analysis of Arterial Spin labeling Data

NeuroImage (Orlando, Fla.), 2009-07, Vol.47, p.S82-S82 [Peer Reviewed Journal]

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Title:
Quantitative General Linear Model Analysis of Arterial Spin labeling Data
Author: Hernandez-Garcia, L. ; Rowe, D.B.
Subjects: Estimates
Is Part Of: NeuroImage (Orlando, Fla.), 2009-07, Vol.47, p.S82-S82
Description: Typicallly one would use a kinetic model to compute a perfusion image at every pair of time points (tag and control) of the series, then average together the appropriate time segments of the resulting series. Perfusion can then be computed by translating the usual parameter estimates (1). into perfusion directly by adapting a kinetic model (e.g., see (2)) as follows: where feffect is the perfusion change due to the effect of interest, [alpha] is the inversion efficiency, [beta]effect is the parameter estimate of the regressor representing the effect of interest, [lambda] is the blood brain partition coefficient, R1, R1a, R1app are the longitudinal relaxation rates of arterial blood, tissue, and tissue in the presence of perfusion. [delta] is the arterial transit time, TR, w, and [tau] are repetition time, post labeling delay, and labeling duration.
Publisher: Amsterdam: Elsevier Inc
Language: English
Identifier: ISSN: 1053-8119
EISSN: 1095-9572
DOI: 10.1016/S1053-8119(09)70588-9
Source: ProQuest One Psychology
Alma/SFX Local Collection
ProQuest Central

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