Measurement of OEF and absolute CMRO2: MRI-based methods using interleaved and combined hypercapnia and hyperoxia

Abstract

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is most commonly used in a semi-quantitative manner to infer changes in brain activity. Despite the basis of the image contrast lying in the cerebral venous blood oxygenation level, quantification of absolute cerebral metabolic rate of oxygen consumption (CMRO2) has only recently been demonstrated. Here we examine two approaches to the calibration of fMRI signal to measure absolute CMRO2 using hypercapnic and hyperoxic respiratory challenges. The first approach is to apply hypercapnia and hyperoxia separately but interleaved in time and the second is a combined approach in which we apply hyperoxic challenges simultaneously with different levels of hypercapnia. Eleven healthy volunteers were studied at 3T using a dual gradient-echo spiral readout pulsed arterial spin labelling (ASL) imaging sequence. Respiratory challenges were conducted using an automated system of dynamic end-tidal forcing. A generalised BOLD signal model was applied, within a Bayesian estimation framework, that aims to explain the effects of modulation of CBF and arterial oxygen content to estimate venous deoxyhaemoglobin concentration ([dHb]0). Using CBF measurements combined with the estimated oxygen extraction fraction (OEF), absolute CMRO2 was calculated. The interleaved approach to hypercapnia and hyperoxia, as well as yielding estimates of CMRO2 and OEF demonstrated a significant increase in regional CBF, venous oxygen saturation (SvO2) (a decrease in OEF) and absolute CMRO2 in visual cortex in response to a continuous (20 min) visual task, demonstrating the potential for the method in measuring long term changes in CMRO2. The combined approach to oxygen and carbon dioxide modulation, as well as taking less time to acquire data, yielded whole brain grey matter estimates of CMRO2 and OEF of 184±45 μmol/100 g/min and 0.42±0.12 respectively, along with additional estimates of the vascular parameters α=0.33±0.06, the exponent relating relative increases in CBF to CBV, and β=1.35±0.13, the exponent relating deoxyhaemoglobin concentration to the relaxation rate R2*. Maps of cerebrovascular and cerebral metabolic parameters were also calculated. We show that combined modulation of oxygen and carbon dioxide can offer an experimentally more efficient approach to estimating OEF and absolute CMRO2 along with the additional vascular parameters that form an important part of the commonly used calibrated fMRI signal model.

Keywords: BOLD; CBF; CMRO(2); Hypercapnia; Hyperoxia; Oxygen metabolism.

Figure 1. Experimental design for scans A and B: interleaved hypercapnia and hyperoxia

a) Indicates the timing of hypercapnic and hyperoxic blocks (90 s duration) alternating with blocks of normocapnia and normoxia. For the normocapnic periods end-tidal CO₂ was held at 1mmHg above the resting value measured before the start of the scan to allow the dynamic end-tidal forcing system to perform its control (Wise et al., 2007). For hypercapnia and hyperoxia the targeted increases in end-tidal CO₂ and O₂ respectively are indicated. b) Shows, schematically, the increase of the CBF signal during hypercapnia and the increase of the BOLD signal during both hypercapnia and hyperoxia. For signal modelling mean CBF and BOLD signals for the final 45 s of each block were estimated, CBF_i and S_i respectively. The same experimental design was performed for scan A (rest) and scan B (continuous reversing visual checkerboard).

Figure 2. Experimental design for scan D: combined hypercapnia and hyperoxia

a) Indicates the timing of the hypercapnic levels administered and the hyperoxic blocks. For the normocapnic periods end-tidal CO₂ was held at 1mmHg above the resting value measured before the start of the scan to allow the dynamic end-tidal forcing system to perform its control (Wise et al., 2007). For hypercapnia and hyperoxia the targeted increases in end-tidal CO₂ and O₂ respectively are indicated. b) Shows, schematically, the increase of the CBF and of the BOLD signal during both hypercapnia and hyperoxia. For signal modelling mean CBF and BOLD signals for the final 30 s of each oxygen level block were estimated, CBF_i and S_i respectively.

Figure 3. Summary of experiments and analysis routes to establish cerebro-metabolic parameters

Scans A and B followed the same experimental design of interleaved hypercapnic and hyperoxic stimuli (Fig. 1) with A being performed at rest and B having the continuous high-contrast visual stimulus. The blue and purple analysis routes are the same for scans A and B using assumed values of α and β from the literature. Scan C used no respiratory challenges and presented only 90 s blocks of visual stimulation interleaved with blocks of rest, in order to measure the visually induced increase in CMRO₂ relative to rest (baseline), following the green analysis route having established M from the hypercapnic calibration in scan A and using assumed values of α and β. Scan D was performed at rest with combined hypercapnic and hyperoxic respiratory challenges (Fig. 2). By virtue of the measurement of hyperoxia induced BOLD contrast at different levels of CBF, we estimated M, SvO₂, CMRO₂, α and β from scan D (red analysis route). Using the information from modulation of BOLD signal in scan D we also estimated α-β to constrain values of α and β for applying to data from scan A (orange analysis route).

Figure 4. Group mean maps of estimated cerebrovascular and cerebrometabolic parameters

a) Venous oxygen saturation (SvO₂), b) oxygen extraction fraction (OEF), c) M, the parameter describing the local maximum fractional BOLD signal increase in the absence of venous deoxyhaemoglobin, d) cerebral metabolic rate of oxygen consumption (CMRO₂) e) cerebral blood flow (CBF), f) β, the exponent relating R₂* relaxation rate constant to the concentration of deoxyhaemoglobin g) α, the exponent relating fractional increases in (venous) cerebral blood volume, relevant for generating BOLD signal contrast, to fractional increases in cerebral blood flow and h) a map of the number of subjects from the cohort of 11 who contribute data to the mean value at each voxel. Note that in some voxels not all subjects contribute as the parameter estimation was unreliable in those voxels in those subjects. Values are reported in grey matter only in which the CBF estimates were thought to be more reliable than in white matter. Data is from scan D, the combined hypercapnia, hyperoxia protocol.

Figure 5. Long-term trend of CBF within the visual region of interest

We show the CBF during the normocapnic, normoxic periods relative to the first such period of scans A (rest) and B (continuous reversing checkerboard). CBF is plotted for the region of interest in visual cortex defined as active from the visual stimulus applied in scan C. Error-bars indicate the standard deviation in relative CBF across the cohort of 11 subjects. Seven periods of CBF are plotted. There was a significant downward trend in the CBF during continuous visual stimulation compared to the resting scan.