English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration

Merola, A., Murphy, K., Stone, A. J., Germuska, M. A., Griffeth, V. E. M., Blockley, N. P., et al. (2016). Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration. NeuroImage, 129, 159-174. doi:10.1016/j.neuroimage.2016.01.021.

Item is

Files

show Files
hide Files
:
Merola_2016.pdf (Publisher version), 6MB
Name:
Merola_2016.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Merola, Alberto1, Author              
Murphy, Kevin1, Author
Stone, Alan J.1, Author
Germuska, Michael A.1, Author
Griffeth, Valerie E. M.2, Author
Blockley, Nicholas P.3, 4, Author
Buxton, Richard B.4, 5, Author
Wise, Richard G.1, Author
Affiliations:
1Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom, ou_persistent22              
2Department of Bioengineering, University of California San Diego, La Jolla, CA, USA, ou_persistent22              
3Nuffield Department Clinical Neurosciences, FMRIB Centre, University of Oxford, United Kingdom, ou_persistent22              
4Department of Radiology, Center for Functional Magnetic Resonance Imaging, University of California San Diego, La Jolla, CA, USA, ou_persistent22              
5Kavli Institute for Brain and Mind, University of California San Diego, La Jolla, CA, USA, ou_persistent22              

Content

show
hide
Free keywords: Calibrated BOLD; Mathematical modelling; Cerebral metabolic rate of oxygen consumption; Functional MRI; Respiratory tasks
 Abstract: Several techniques have been proposed to estimate relative changes in cerebral metabolic rate of oxygen consumption (CMRO2) by exploiting combined BOLD fMRI and cerebral blood flow data in conjunction with hypercapnic or hyperoxic respiratory challenges. More recently, methods based on respiratory challenges that include both hypercapnia and hyperoxia have been developed to assess absolute CMRO2, an important parameter for understanding brain energetics. In this paper, we empirically optimize a previously presented “original calibration model” relating BOLD and blood flow signals specifically for the estimation of oxygen extraction fraction (OEF) and absolute CMRO2. To do so, we have created a set of synthetic BOLD signals using a detailed BOLD signal model to reproduce experiments incorporating hypercapnic and hyperoxic respiratory challenges at 3 T. A wide range of physiological conditions was simulated by varying input parameter values (baseline cerebral blood volume (CBV0), baseline cerebral blood flow (CBF0), baseline oxygen extraction fraction (OEF0) and hematocrit (Hct)). From the optimization of the calibration model for estimation of OEF and practical considerations of hypercapnic and hyperoxic respiratory challenges, a new “simplified calibration model” is established which reduces the complexity of the original calibration model by substituting the standard parameters α and β with a single parameter θ. The optimal value of θ is determined (θ = 0.06) across a range of experimental respiratory challenges. The simplified calibration model gives estimates of OEF0 and absolute CMRO2 closer to the true values used to simulate the experimental data compared to those estimated using the original model incorporating literature values of α and β. Finally, an error propagation analysis demonstrates the susceptibility of the original and simplified calibration models to measurement errors and potential violations in the underlying assumptions of isometabolism. We conclude that using the simplified calibration model results in a reduced bias in OEF0 estimates across a wide range of potential respiratory challenge experimental designs.

Details

show
hide
Language(s): eng - English
 Dates: 2015-08-202016-01-092016-01-202016-04-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2016.01.021
PMID: 26801605
Other: Epub 2016
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: NeuroImage
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 129 Sequence Number: - Start / End Page: 159 - 174 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166