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

PurposeParameter 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 O-17 MRI. MethodsThree-dimensional dynamic O-17 MRI datasets of the human brain were acquired after inhalation of O-17(2) 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 O-17 enrichment fraction of the inhaled O-17(2) gas, , 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. ResultsPrior knowledge about only one -related parameter was sufficient to resolve the CMRO2 nonidentifiability, and CMRO2 rates (0.72-0.99 mu mol/g(tissue)/min in white matter, 1.02-1.78 mu mol/g(tissue)/min in gray matter) are in a good agreement with the results of O-15 positron emission tomography studies. Nonconstant values significantly improved model fitting. ConclusionThe profile likelihood analysis shows that CMRO2 can be measured reliably in O-17 gas MRI experiment if the O-17 enrichment fraction is used as prior information for the model calculations. Magn Reson Med 78:1157-1167, 2017. (c) 2016 International Society for Magnetic Resonance in Medicine.