Quantification of CMRO2 without hypercapnia using simultaneous near-infrared spectroscopy and fMRI measurements

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Estimation of the cerebral metabolic rate of oxygen (CMRO2) and cerebral blood flow (CBF) is important to investigate the neurovascular coupling and physiological components in blood oxygenation level-dependent (BOLD) signals quantitatively. Although there are methods that can determine CMRO2 changes using functional MRI (fMRI) or near-infrared spectroscopy (NIRS), current approaches require a separate hypercapnia calibration process and have the potential to incur bias in many assumed model parameters. In this paper, a novel method to estimate CMRO2 without hypercapnia is described using simultaneous measurements of NIRS and fMRI. Specifically, an optimization framework is proposed that minimizes the differences between the two forms of the relative CMRO2-CBF coupling ratio from BOLD and NIRS biophysical models, from which hypercapnia calibration and model parameters are readily estimated. Based on the new methods, we found that group average CBF, CMRO2, cerebral blood volume (CBV), and BOLD changes within activation of the primary motor cortex during a finger tapping task increased by 39.5 +/- 21.4%, 18.4 +/- 8.7%, 12.9 +/- 6.7%, and 0.5 +/- 0.2%, respectively. The group average estimated flow-metabolism coupling ratio was 2.38 +/- 0.65 and the hypercapnia parameter was 7.7 +/- 1.7%. These values are within the range of values reported from other literatures. Furthermore, the activation maps from CBF and CMRO2 were well localized on the primary motor cortex, which is the main target region of the finger tapping task.
Publisher
IOP PUBLISHING LTD
Issue Date
2010-06
Language
English
Article Type
Article
Keywords

CEREBRAL-BLOOD-FLOW; SUPPLEMENTARY MOTOR AREAS; CALIBRATED FUNCTIONAL MRI; RAT FOREPAW STIMULATION; RODENT BARREL CORTEX; OXIDATIVE-METABOLISM; OXYGEN-CONSUMPTION; BOLD-FMRI; HEMODYNAMIC-RESPONSES; NEURONAL-ACTIVITY

Citation

PHYSICS IN MEDICINE AND BIOLOGY, v.55, no.11, pp.3249 - 3269

ISSN
0031-9155
DOI
10.1088/0031-9155/55/11/017
URI
http://hdl.handle.net/10203/98623
Appears in Collection
AI-Journal Papers(저널논문)
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