Quantification of oxygen metabolic rates in Human brain with dynamic 17 O MRI: Profile likelihood analysis

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 (CMRO 2 ) with direct 17 O MRI. Methods Three‐dimensional dynamic 17 O MRI datasets of the human brain were acquired after inhalation of 17 O 2 gas with the help of a rebreathing system, and CMRO 2 was quantified with a pharmacokinetic model. To analyze the influence of the different model parameters on the identifiability of CMRO 2 , PLs were calculated for different settings of the model parameters. In particular, the 17 O enrichment fraction of the inhaled 17 O 2 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 CMRO 2 nonidentifiability, and CMRO 2 rates (0.72–0.99 µmol/g tissue /min in white matter, 1.02–1.78 µmol/g tissue /min in gray matter) are in a good agreement with the results of 15 O positron emission tomography studies. Nonconstant α values significantly improved model fitting. Conclusion The profile likelihood analysis shows that CMRO 2 can be measured reliably in 17 O gas MRI experiment if the 17 O enrichment fraction is used as prior information for the model calculations. Magn Reson Med 78:1157–1167, 2017. © 2016 International Society for Magnetic Resonance in Medicine.