Quantification of Oxygen Metabolic Rates in Human Brain with Dynamic 17O MRI: Profile Likelihood Analysis

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Abstract

Purpose:

Parameter identifiability and confidence intervals were determined using a profile likelihood (PL) analysis method in a quantification model of the cerebral metabolic rate of oxygen consumption (CMRO2) with direct 17O MRI.

Methods:

Three-dimensional dynamic 17O MRI datasets of the human brain were acquired after inhalation of 17O2 gas with the help of a rebreathing system, and CMRO2 was quantified with a pharmacokinetic model. To analyze the influence of the different model parameters on the identifiability of CMRO2, PLs were calculated for different settings of the model parameters. In particular, the 17O enrichment fraction of the inhaled 17O2 gas, α, was investigated assuming a constant and a linearly varying model. Identifiability was analyzed for white and gray matter, and the dependency on different priors was studied.

Results:

Prior knowledge about only one α-related parameter was sufficient to resolve the CMRO2 nonidentifiability, and CMRO2 rates (0.72–0.99 μmol/gtissue/min in white matter, 1.02–1.78 μmol/gtissue/min in gray matter) are in a good agreement with the results of 15O positron emission tomography studies. Nonconstant α values significantly improved model fitting.

Conclusion:

The profile likelihood analysis shows that CMRO2 can be measured reliably in 17O gas MRI experiment if the 17O enrichment fraction is used as prior information for the model calculations.Magn Reson Med, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

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