Abstract
Simultaneous implementation of magnetic resonance imaging methods for Arterial Spin Labeling (ASL) and Blood Oxygenation Level Dependent (BOLD) imaging makes it possible to quantitatively measure the changes in cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO2) that occur in response to neural stimuli. To date, however, the range of neural stimuli amenable to quantitative analysis is limited to those that may be presented in a simple block or event related design such that measurements may be repeated and averaged to improve precision. Here we examined the feasibility of using the relationship between cerebral blood flow and the BOLD signal to improve dynamic estimates of blood flow fluctuations as well as to estimate metabolic-hemodynamic coupling under conditions where a stimulus pattern is unknown. We found that by combining the information contained in simultaneously acquired BOLD and ASL signals through a method we term BOLD Constrained Perfusion (BCP) estimation, we could significantly improve the precision of our estimates of the hemodynamic response to a visual stimulus and, under the conditions of a calibrated BOLD experiment, accurately determine the ratio of the oxygen metabolic response to the hemodynamic response. Importantly we were able to accomplish this without utilizing a priori knowledge of the temporal nature of the neural stimulus, suggesting that BOLD Constrained Perfusion estimation may make it feasible to quantitatively study the cerebral metabolic and hemodynamic responses to more natural stimuli that cannot be easily repeated or averaged.
Highlights
Functional hyperemia is a phenomenon by which blood flow to a volume of brain tissue increases rapidly and dramatically in response to a local increase in neural activity
We propose that the precision of an estimate of the instantaneous cerebral blood flow (CBF), f^1⁄2t may be improved by assuming that the expected values of the measured Arterial Spin Labeling (ASL) and blood oxygenation level dependent (BOLD) signals, E1⁄2A1⁄2t and E1⁄2B1⁄2t are the true underlying CBF and BOLD signals, f 1⁄2t and b1⁄2t, and that the unknown parameter k of our BOLD model has a constant value over a window of interest T samples in length
In this study we report a new method of measuring dynamic CBF fluctuations by combining information obtained through simultaneous acquisition of ASL and BOLD image time series
Summary
Functional hyperemia is a phenomenon by which blood flow to a volume of brain tissue increases rapidly and dramatically in response to a local increase in neural activity. Functional hyperemia leads to a local decrease in the fraction of oxygen extracted from capillaries, increasing the oxygenation of hemoglobin in downstream venules [3] and producing a robust increase in the BOLD signal. BOLD imaging is highly sensitive to fluctuations in blood oxygenation and is often used to localize regions of the brain where blood oxygen saturation changes in response to neural activity. BOLD imaging is limited in two ways It cannot be interpreted in a quantitative physiological sense, as both the rate of delivery and rate of consumption of oxygen affect the magnitude of the BOLD signal and cannot be disentangled by BOLD imaging alone [4]. The BOLD signal is a change between two acutely defined states, and so is not directly sensitive to chronic physiological changes that would affect the baseline state
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