| Literature DB >> 29580967 |
Hyunyeol Lee1, Erin K Englund1, Felix W Wehrli2.
Abstract
Quantitative BOLD (qBOLD), a non-invasive MRI method for assessment of hemodynamic and metabolic properties of the brain in the baseline state, provides spatial maps of deoxygenated blood volume fraction (DBV) and hemoglobin oxygen saturation (HbO2) by means of an analytical model for the temporal evolution of free-induction-decay signals in the extravascular compartment. However, mutual coupling between DBV and HbO2 in the signal model results in considerable estimation uncertainty precluding achievement of a unique set of solutions. To address this problem, we developed an interleaved qBOLD method (iqBOLD) that combines extravascular R2' and intravascular R2 mapping techniques so as to obtain prior knowledge for the two unknown parameters. To achieve these goals, asymmetric spin echo and velocity-selective spin-labeling (VSSL) modules were interleaved in a single pulse sequence. Prior to VSSL, arterial blood and CSF signals were suppressed to produce reliable estimates for cerebral venous blood volume fraction (CBVv) as well as venous blood R2 (to yield HbO2). Parameter maps derived from the VSSL module were employed to initialize DBV and HbO2 in the qBOLD processing. Numerical simulations and in vivo experiments at 3 T were performed to evaluate the performance of iqBOLD in comparison to the parent qBOLD method. Data obtained in eight healthy subjects yielded plausible values averaging 60.1 ± 3.3% for HbO2 and 3.1 ± 0.5 and 2.0 ± 0.4% for DBV in gray and white matter, respectively. Furthermore, the results show that prior estimates of CBVv and HbO2 from the VSSL component enhance the solution stability in the qBOLD processing, and thus suggest the feasibility of iqBOLD as a promising alternative to the conventional technique for quantifying neurometabolic parameters.Entities:
Keywords: Asymmetric spin echo; Brain metabolism; Hemoglobin oxygen saturation; Magnetic resonance imaging (MRI); Quantitative BOLD; Velocity-selective spin-labeling
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Year: 2018 PMID: 29580967 PMCID: PMC5949279 DOI: 10.1016/j.neuroimage.2018.03.043
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556