Get access

Estimating cerebral oxygen metabolism from fMRI with a dynamic multicompartment Windkessel model

Authors

  • Theodore J. Huppert,

    Corresponding author
    1. Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
    2. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
    • University of Pittsburgh, UPMC Presbyterian, 200 Lothrop St., Pittsburgh, PA 15213
    Search for more papers by this author
  • Monica S. Allen,

    1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, Texas
    Search for more papers by this author
  • Solomon G. Diamond,

    1. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
    2. Department of Engineering, Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
    Search for more papers by this author
  • David A. Boas

    1. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
    2. Department of Radiology, HMS, MGH and Member of the Affiliated Faculty Member in the Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts
    Search for more papers by this author

Abstract

Stimulus evoked changes in cerebral blood flow, volume, and oxygenation arise from responses to underlying neuronally mediated changes in vascular tone and cerebral oxygen metabolism. There is increasing evidence that the magnitude and temporal characteristics of these evoked hemodynamic changes are additionally influenced by the local properties of the vasculature including the levels of baseline cerebral blood flow, volume, and blood oxygenation. In this work, we utilize a physiologically motivated vascular model to describe the temporal characteristics of evoked hemodynamic responses and their expected relationships to the structural and biomechanical properties of the underlying vasculature. We use this model in a temporal curve-fitting analysis of the high-temporal resolution functional MRI data to estimate the underlying cerebral vascular and metabolic responses in the brain. We present evidence for the feasibility of our model-based analysis to estimate transient changes in the cerebral metabolic rate of oxygen (CMRO2) in the human motor cortex from combined pulsed arterial spin labeling (ASL) and blood oxygen level dependent (BOLD) MRI. We examine both the numerical characteristics of this model and present experimental evidence to support this model by examining concurrently measured ASL, BOLD, and near-infrared spectroscopy to validate the calculated changes in underlying CMRO2. Hum Brain Mapp 2009. © 2008 Wiley-Liss, Inc.

Get access to the full text of this article

Ancillary