The relationship between blood oxygenation level-dependent (BOLD) MRI signals, cerebral blood flow (CBF), and oxygen consumption (CMR O 2 ) in the physiological steady state was investigated. A quantitative model, based on flow-dependent dilution of metabolically generated deoxyhemoglobin, was validated by measuring BOLD signals and relative CBF simultaneously in the primary visual cortex (V1) of human subjects (N ‫؍‬ 12) during graded hypercapnia at different levels of visual stimulation. BOLD and CBF responses to specific conditions were averaged across subjects and plotted as points in the BOLD-CBF plane, tracing out lines of constant CMR O 2 . The quantitative deoxyhemoglobin dilution model could be fit to these measured iso-CMR O 2 contours without significant (P I 0.05) residual error and yielded MRI-based CMR O 2 measurements that were in agreement with PET results for equivalent stimuli. BOLD and CBF data acquired during graded visual stimulation were then substituted into the model with constant parameters varied over plausible ranges. Relative changes in CBF and CMR O 2 appeared to be coupled in an approximate ratio of D2:1 for all realistic parameter settings. Magn Reson Med 42:849

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In this study, we have preformed simultaneous near-infrared spectroscopy (NIRS) along with BOLD (blood oxygen level dependent) and ASL (arterial spin labeling)-based fMRI during an event-related motor activity in human subjects in order to compare the temporal dynamics of the hemodynamic responses recorded in each method. These measurements have allowed us to examine the validity of the biophysical models underlying each modality and, as a result, gain greater insight into the hemodynamic responses to neuronal activation. Although prior studies have examined the relationships between these two methodologies through similar experiments, they have produced conflicting results in the literature for a variety of reasons. Here, by employing a short-duration, event-related motor task, we have been able to emphasize the subtle temporal differences between the hemodynamic parameters with a high contrast-to-noise ratio. As a result of this improved experimental design, we are able to report that the fMRI measured BOLD response is more correlated with the NIRS measure of deoxy-hemoglobin (R = 0.98; P < 10(-20)) than with oxy-hemoglobin (R = 0.71), or total hemoglobin (R = 0.53). This result was predicted from the theoretical grounds of the BOLD response and is in agreement with several previous works [Toronov, V.A.W., Choi, J.H., Wolf, M., Michalos, A., Gratton, E., Hueber, D., 2001. "Investigation of human brain hemodynamics by simultaneous near-infrared spectroscopy and functional magnetic resonance imaging." Med. Phys. 28 (4) 521-527.; MacIntosh, B.J., Klassen, L.M., Menon, R.S., 2003. "Transient hemodynamics during a breath hold challenge in a two part functional imaging study with simultaneous near-infrared spectroscopy in adult humans". NeuroImage 20 1246-1252.; Toronov, V.A.W., Walker, S., Gupta, R., Choi, J.H., Gratton, E., Hueber, D., Webb, A., 2003. "The roles of changes in deoxyhemoglobin concentration and regional cerebral blood volume in the fMRI BOLD signal" Neuroimage 19 (4) 1521-1531]. These data have also allowed us to examine more detailed measurement models of the fMRI signal and comment on the roles of the oxygen saturation and blood volume contributions to the BOLD response. In addition, we found high correlation between the NIRS measured total hemoglobin and ASL measured cerebral blood flow (R = 0.91; P < 10(-10)) and oxy-hemoglobin with flow (R = 0.83; P < 10(-05)) as predicted by the biophysical models. Finally, we note a significant amount of cross-modality, correlated, inter-subject variability in amplitude change and time-to-peak of the hemodynamic response. The observed co-variance in these parameters between subjects is in agreement with hemodynamic models and provides further support that fMRI and NIRS have similar vascular sensitivity.

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Near-Infrared Spectroscopy (NIRS) measures the functional hemodynamic response occuring at the surface of the cortex. Large pial veins are located above the surface of the cerebral cortex. Following activation, these veins exhibit oxygenation changes but their volume likely stays constant. The back-reflection geometry of the NIRS measurement renders the signal very sensitive to these superficial pial veins. As such, the measured NIRS signal contains contributions from both the cortical region as well as the pial vasculature. In this work, the cortical contribution to the NIRS signal was investigated using (1) Monte Carlo simulations over a realistic geometry constructed from anatomical and vascular MRI and (2) multimodal NIRS-BOLD recordings during motor stimulation. A good agreement was found between the simulations and the modeling analysis of in vivo measurements. Our results suggest that the cortical contribution to the deoxyhemoglobin signal change (ΔHbR) is equal to 16–22% of the cortical contribution to the total hemoglobin signal change (ΔHbT). Similarly, the cortical contribution of the oxyhemoglobin signal change (ΔHbO) is equal to 73–79% of the cortical contribution to the ΔHbT signal. These results suggest that ΔHbT is far less sensitive to pial vein contamination and therefore, it is likely that the ΔHbT signal provides better spatial specificity and should be used instead of ΔHbO or ΔHbR to map cerebral activity with NIRS. While different stimuli will result in different pial vein contributions, our finger tapping results do reveal the importance of considering the pial contribution.

We have measured the changes in oxy-haemoglobin and deoxy-haemoglobin in the adult human brain during a brief finger tapping exercise using near-infrared spectroscopy (NIRS). The cerebral metabolic rate of oxygen (CMRO 2 ) can be estimated from these NIRS data provided certain model assumptions. The change in CMRO 2 is related to changes in the total haemoglobin concentration, deoxy-haemoglobin concentration and blood flow. As NIRS does not provide a measure of dynamic changes in blood flow during brain activation, we relied on a Windkessel model that relates dynamic blood volume and flow changes, which has been used previously for estimating CMRO 2 from functional magnetic resonance imaging (fMRI) data. Because of the partial volume effect we are unable to quantify the absolute changes in the local brain haemoglobin concentrations with NIRS and thus are unable to obtain an estimate of the absolute CMRO 2 change. An absolute estimate is also confounded by uncertainty in the flow-volume relationship. However, the ratio of the flow change to the CMRO 2 change is relatively insensitive to these uncertainties. For the finger tapping task, we estimate a most probable flow-consumption ratio ranging from 1.5 to 3 in agreement with previous findings presented in the literature, although we cannot exclude the possibility that there is no CMRO 2 change. The large range in the ratio arises from the large number of model parameters that must be estimated from the data. A more precise estimate of the flow-consumption ratio will require better estimates of the model parameters or flow information, as can be provided by combining NIRS with fMRI.

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Stimulation of cerebral vasculature using hypercapnia has been widely used to study cerebral vascular reactivity (CVR), which can be expressed as the quantitative change in cerebral blood flow (CBF) per mm Hg change in end-tidal partial pressure of CO 2 (P ET CO 2 ). We investigate whether different respiratory manipulations, with arterial spin labeling used to measure CBF, lead to consistent measures of CVR. The approaches included: (1) an automated system delivering variable concentrations of inspired CO 2 for prospective targeting of P ET CO 2 , (2) administration of a fixed concentration of CO 2 leading to subject-dependent changes in P ET CO 2 , (3) a breath-hold (BH) paradigm with physiologic modeling of CO 2 accumulation, and (4) a maneuver combining breathhold and hyperventilation. When CVR was expressed as the percent change in CBF per mm Hg change in P ET CO 2 , methods 1 to 3 gave consistent results. The CVR values using method 4 were significantly lower. When CVR was expressed in terms of the absolute change in CBF (mL/100 g per minute per mm Hg), greater discrepancies became apparent: methods 2 and 3 gave lower absolute CVR values compared with method 1, and the value obtained with method 4 was dramatically lower. Our findings indicate that care must be taken to ensure that CVR is measured over the linear range of the CBF-CO 2 dose-response curve, avoiding hypocapnic conditions.