Interpreting oxygenation-based neuroimaging signals: the importance and the challenge of understanding brain oxygen metabolism

Abstract

Functional magnetic resonance imaging is widely used to map patterns of brain activation based on blood oxygenation level dependent (BOLD) signal changes associated with changes in neural activity. However, because oxygenation changes depend on the relative changes in cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO(2)), a quantitative interpretation of BOLD signals, and also other functional neuroimaging signals related to blood or tissue oxygenation, is fundamentally limited until we better understand brain oxygen metabolism and how it is related to blood flow. However, the positive side of the complexity of oxygenation signals is that when combined with dynamic CBF measurements they potentially provide the best tool currently available for investigating the dynamics of CMRO(2). This review focuses on the problem of interpreting oxygenation-based signals, the challenges involved in measuring CMRO(2) in general, and what is needed to put oxygenation-based estimates of CMRO(2) on a firm foundation. The importance of developing a solid theoretical framework is emphasized, both as an essential tool for analyzing oxygenation-based multimodal measurements, and also potentially as a way to better understand the physiological phenomena themselves. The existing data, integrated within a simple theoretical framework of O(2) transport, suggests the hypothesis that an important functional role of the mismatch of CBF and CMRO(2) changes with neural activation is to prevent a fall of tissue pO(2). Future directions for better understanding brain oxygen metabolism are discussed.

Keywords: blood oxygenation level dependent; cerebral blood flow; cerebral metabolic rate of oxygen; functional magnetic resonance imaging; positron emission tomography; tissue oxygenation.

Figure 1

CBF and BOLD responses to a brief stimulus in human subjects. (A) Two seconds of finger tapping evoke a strong CBF change in primary motor cortex, measured here with an arterial spin labeling (ASL) MRI method. (B) The CBF change is accompanied by a local increase in blood oxygenation, giving rise to the BOLD response measured with fMRI. Because of the nature of the measurements, BOLD-fMRI has intrinsically higher sensitivity than ASL, despite the small magnitude of the signal changes. Data from Miller et al. (2001).

Figure 2

Theoretical curves derived from the theoretical framework in Table 1. (A) Equations 1 and 2 define contours (in red) of equal BOLD signal change in the CBF/CMRO₂ plane, here illustrated for M = 8%. The contour of zero BOLD response has a slope slightly greater than 1 because of the way blood volume effects are included. (B) Equations 1, 3, and 4 define contours (in blue) of equal tissue pO₂ change, calculated with the assumption that at baseline p_TO₂ = 25 mmHg. (C) Hypothetical CBF and CMRO₂ responses to a simple stimulus are shown. These two responses define a trajectory in the CBF/CMRO₂ plane, shown in (A,B) as the black curve. The points on the curve represent equal time increments in the evolving CBF and CMRO₂ curves in (C). (D) The resulting BOLD and tissue pO₂ responses are shown for the CBF and CMRO₂ responses in (C). Note that in this example the CBF and CMRO₂ responses are approximately in the ratio 2:1 (i.e., n ∼ 2), and this causes the trajectory to pass over and under the zero change contour of p_TO₂, leading to the complex dynamics in (D). In addition, the CBF response was constructed with a weak post-stimulus undershoot to illustrate that this can create a more pronounced undershoot in the BOLD signal. In this example the ratio of the undershoot to the peak response is only ∼8% for CBF, but ∼30% for the BOLD response.

Figure 3

Experimental measurements of CBF/CMRO₂ coupling in human brain. PET measurements are indicated by open symbols, and calibrated-BOLD measurements are indicated by filled symbols. Different symbol shapes are used for different brain areas, as indicated. Lines of constant n are shown as dashed lines, and the solid red curve is the contour of constant tissue pO₂ calculated from the theoretical framework and shown in Figure 2B. The fact that the points are all well above the line n = 1 produces the BOLD effect with activation. A speculation discussed in the text is that the function served by a large value of n is to prevent a fall in tissue pO₂ as CMRO₂ increases.