Quantification of oxygen metabolic rates in Human brain with dynamic 17O MRI: Profile likelihood analysis. Issue 3 (1st November 2016)
- Record Type:
- Journal Article
- Title:
- Quantification of oxygen metabolic rates in Human brain with dynamic 17O MRI: Profile likelihood analysis. Issue 3 (1st November 2016)
- Main Title:
- Quantification of oxygen metabolic rates in Human brain with dynamic 17O MRI: Profile likelihood analysis
- Authors:
- Kurzhunov, Dmitry
Borowiak, Robert
Hass, Helge
Wagner, Philipp
Krafft, Axel Joachim
Timmer, Jens
Bock, Michael - Abstract:
- 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 17 O MRI. Methods: Three‐dimensional dynamic 17 O MRI datasets of the human brain were acquired after inhalation of 17 O2 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 17 O enrichment fraction of the inhaled 17 O2 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 15 O positron emission tomography studies. Nonconstant α values significantly improved model fitting. Conclusion: The profile likelihood analysis shows that CMRO2 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 SocietyAbstract : 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 17 O MRI. Methods: Three‐dimensional dynamic 17 O MRI datasets of the human brain were acquired after inhalation of 17 O2 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 17 O enrichment fraction of the inhaled 17 O2 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 15 O positron emission tomography studies. Nonconstant α values significantly improved model fitting. Conclusion: The profile likelihood analysis shows that CMRO2 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. … (more)
- Is Part Of:
- Magnetic resonance in medicine. Volume 78:Issue 3(2017)
- Journal:
- Magnetic resonance in medicine
- Issue:
- Volume 78:Issue 3(2017)
- Issue Display:
- Volume 78, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 78
- Issue:
- 3
- Issue Sort Value:
- 2017-0078-0003-0000
- Page Start:
- 1157
- Page End:
- 1167
- Publication Date:
- 2016-11-01
- Subjects:
- oxygen metabolism -- cerebral metabolic rate of oxygen consumption (CMRO2) -- direct 17O MRI -- non‐proton MRI -- profile likelihood -- identifiability analysis
Nuclear magnetic resonance -- Periodicals
Electron paramagnetic resonance -- Periodicals
616.07548 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2594 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mrm.26476 ↗
- Languages:
- English
- ISSNs:
- 0740-3194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5337.798000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11515.xml