Nicholas P. Blockley

A review of calibrated blood oxygenation level-dependent (BOLD) methods for the measurement of task-induced changes in brain oxygen metabolism

The dynamics of the blood oxygenation level‐dependent (BOLD) response are dependent on changes in cerebral blood flow, cerebral blood volume and the cerebral metabolic rate of oxygen consumption. Furthermore, the amplitude of the response is dependent on the baseline physiological state, defined by the haematocrit, oxygen extraction fraction and cerebral blood volume. As a result of this complex dependence, the accurate interpretation of BOLD data and robust intersubject comparisons when the baseline physiology is varied are difficult. The calibrated BOLD technique was developed to address these issues. However, the methodology is complex and its full promise has not yet been realised. In this review, the theoretical underpinnings of calibrated BOLD, and issues regarding this theory that are still to be resolved, are discussed. Important aspects of practical implementation are reviewed and reported applications of this methodology are presented. Copyright

An improved method for acquiring cerebrovascular reactivity maps

This study aims to improve the method used to produce cerebrovascular reactivity (CVR) maps by MRI. Previous methods have used a standard boxcar presentation of carbon dioxide (CO2). Here this is replaced with a sinusoidally modulated CO2 stimulus. This allowed the use of Fourier analysis techniques to measure both the amplitude and phase delay of the BOLD CVR response, and hence characterize the arrival sequence of blood to different regions of the brain. This characterization revealed statistically significant relative delays between regions of the brain (ANOVA < 0.0001). In addition, post hoc comparison showed that the frontal (P < 0.001) and parietal (P = 0.004) lobes reacted earlier than the occipital lobe. Magn Reson Med, 2011.

Identifying the ischaemic penumbra using pH-weighted magnetic resonance imaging

Harston et al. establish proof of principle for clinical use of pH-weighted MRI in patients with acute ischaemic stroke. Detailed tissue-level analysis reveals that cerebral intracellular pH, a marker of metabolic stress, is associated with eventual tissue outcome, and complements established imaging modalities.

Comparing different analysis methods for quantifying the MRI amide proton transfer (APT) effect in hyperacute stroke patients.

Amide proton transfer (APT) imaging is a pH mapping method based on the chemical exchange saturation transfer phenomenon that has potential for penumbra identification following stroke. The majority of the literature thus far has focused on generating pH‐weighted contrast using magnetization transfer ratio asymmetry analysis instead of quantitative pH mapping. In this study, the widely used asymmetry analysis and a model‐based analysis were both assessed on APT data collected from healthy subjects (n = 2) and hyperacute stroke patients (n = 6, median imaging time after onset = 2 hours 59 minutes). It was found that the model‐based approach was able to quantify the APT effect with the lowest variation in grey and white matter (≤ 13.8 %) and the smallest average contrast between these two tissue types (3.48 %) in the healthy volunteers. The model‐based approach also performed quantitatively better than the other measures in the hyperacute stroke patient APT data, where the quantified APT effect in the infarct core was consistently lower than in the contralateral normal appearing tissue for all the patients recruited, with the group average of the quantified APT effect being 1.5 ± 0.3 % (infarct core) and 1.9 ± 0.4 % (contralateral). Based on the fitted parameters from the model‐based analysis and a previously published pH and amide proton exchange rate relationship, quantitative pH maps for hyperacute stroke patients were generated, for the first time, using APT imaging.

A New Functional MRI Approach for Investigating Modulations of Brain Oxygen Metabolism.

Functional MRI (fMRI) using the blood oxygenation level dependent (BOLD) signal is a common technique in the study of brain function. The BOLD signal is sensitive to the complex interaction of physiological changes including cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral oxygen metabolism (CMRO2). A primary goal of quantitative fMRI methods is to combine BOLD imaging with other measurements (such as CBF measured with arterial spin labeling) to derive information about CMRO2. This requires an accurate mathematical model to relate the BOLD signal to the physiological and hemodynamic changes; the most commonly used of these is the Davis model. Here, we propose a new nonlinear model that is straightforward and shows heuristic value in clearly relating the BOLD signal to blood flow, blood volume and the blood flow-oxygen metabolism coupling ratio. The model was tested for accuracy against a more detailed model adapted for magnetic fields of 1.5, 3 and 7T. The mathematical form of the heuristic model suggests a new ratio method for comparing combined BOLD and CBF data from two different stimulus responses to determine whether CBF and CMRO2 coupling differs. The method does not require a calibration experiment or knowledge of parameter values as long as the exponential parameter describing the CBF-CBV relationship remains constant between stimuli. The method was found to work well for 1.5 and 3T but is prone to systematic error at 7T. If more specific information regarding changes in CMRO2 is required, then with accuracy similar to that of the Davis model, the heuristic model can be applied to calibrated BOLD data at 1.5T, 3T and 7T. Both models work well over a reasonable range of blood flow and oxygen metabolism changes but are less accurate when applied to a simulated caffeine experiment in which CBF decreases and CMRO2 increases.

Calibrating the BOLD response without administering gases: comparison of hypercapnia calibration with calibration using an asymmetric spin echo.

The calibrated BOLD (blood oxygen level dependent) technique was developed to quantify the BOLD signal in terms of changes in oxygen metabolism. In order to achieve this a calibration experiment must be performed, which typically requires a hypercapnic gas mixture to be administered to the participant. However, an emerging technique seeks to perform this calibration without administering gases using a refocussing based calibration. Whilst hypercapnia calibration seeks to emulate the physical removal of deoxyhaemoglobin from the blood, the aim of refocussing based calibration is to refocus the dephasing effect of deoxyhaemoglobin on the MR signal using a spin echo. However, it is not possible to refocus all of the effects that contribute to the BOLD signal and a scale factor is required to estimate the BOLD scaling parameter M. In this study the feasibility of a refocussing based calibration was investigated. The scale factor relating the refocussing calibration to M was predicted by simulations to be approximately linear and empirically measured to be 0.88±0.36 for the visual cortex and 0.93±0.32 for a grey matter region of interest (mean±standard deviation). Refocussing based calibration is a promising approach for greatly simplifying the calibrated BOLD methodology by eliminating the need for the subject to breathe special gas mixtures, and potentially provides the basis for a wider implementation of quantitative functional MRI.

An analysis of the use of hyperoxia for measuring venous cerebral blood volume: Comparison of the existing method with a new analysis approach

Hyperoxia is known to cause an increase in the blood oxygenation level dependent (BOLD) signal that is primarily localised to the venous vasculature. This contrast mechanism has been proposed as a way to measure venous cerebral blood volume (CBVv) without the need for more invasive contrast media. In the existing method the analysis modelled the data as a dynamic contrast agent experiment, with the assumption that the BOLD signal of tissue was dominated by intravascular signal. The effects on the accuracy of the method due to extravascular BOLD signal changes, as well as signal modulation by intersubject differences in baseline physiology, such as haematocrit and oxygen extraction fraction, have so far been unexplored. In this study the effect of extravascular signal and intersubject physiological variability was investigated by simulating the hyperoxia CBVv experiment using a detailed BOLD signal model. This analysis revealed substantial uncertainty in the measurement of CBVv using the existing analysis based on dynamic contrast agent experiments. Instead, the modelling showed a simple and direct relationship between the BOLD signal change and CBVv, and an alternative analysis method with much reduced uncertainty was proposed based on this finding. Both methods were tested experimentally, with the new method producing results that are consistent with the limited literature in this area.

Measuring venous blood volume changes during activation using hyperoxia.

This study describes a novel method for measuring relative changes in venous cerebral blood volume (CBVv) using hyperoxia as a contrast agent. This method exploits the extravascular BOLD effect and its dependency on both task-related activation induced changes in venous blood oxygenation and changes due to breathing an oxygen enriched gas mixture. Changes in CBVv on activation can be estimated by comparing the change in transverse relaxation rate, R2*, due to hyperoxia in both baseline and activation states. Furthermore these measurements can be converted into a measure of the percentage change in CBVv. Experiments were performed to measure changes in a CBVv-weighted signal in response to a simple motor task. Both positive and negative changes in CBVv-weighted signal were detected in the positively activated BOLD region.

Sources of systematic error in calibrated BOLD based mapping of baseline oxygen extraction fraction.

Recently a new class of calibrated blood oxygen level dependent (BOLD) functional magnetic resonance imaging (MRI) methods were introduced to quantitatively measure the baseline oxygen extraction fraction (OEF). These methods rely on two respiratory challenges and a mathematical model of the resultant changes in the BOLD functional MRI signal to estimate the OEF. However, this mathematical model does not include all of the effects that contribute to the BOLD signal, it relies on several physiological assumptions and it may be affected by intersubject physiological variability. The aim of this study was to investigate these sources of systematic error and their effect on estimating the OEF. This was achieved through simulation using a detailed model of the BOLD signal. Large ranges for intersubject variability in baseline physiological parameters such as haematocrit and cerebral blood volume were considered. Despite this the uncertainty in the relationship between the measured BOLD signals and the OEF was relatively low. Investigations of the physiological assumptions that underlie the mathematical model revealed that OEF measurements are likely to be overestimated if oxygen metabolism changes during hypercapnia or cerebral blood flow changes under hyperoxia. Hypoxic hypoxia was predicted to result in an underestimation of the OEF, whilst anaemic hypoxia was found to have only a minimal effect.

Investigating the field-dependence of the Davis model: Calibrated fMRI at 1.5, 3 and 7T.

Gas calibrated fMRI in its most common form uses hypercapnia in conjunction with the Davis model to quantify relative changes in the cerebral rate of oxygen consumption (CMRO2) in response to a functional stimulus. It is most commonly carried out at 3 T but, as 7 T research scanners are becoming more widespread and the majority of clinical scanners are still 1.5 T systems, it is important to investigate whether the model used remains accurate across this range of field strengths. Ten subjects were scanned at 1.5, 3 and 7 T whilst performing a bilateral finger-tapping task as part of a calibrated fMRI protocol, and the results were compared to a detailed signal model. Simulations predicted an increase in value and variation in the calibration parameter M with field strength. Two methods of defining experimental regions of interest (ROIs) were investigated, based on (a) BOLD signal and (b) BOLD responses within grey matter only. M values from the latter ROI were in closer agreement with theoretical predictions; however, reassuringly, ROI choice had less impact on CMRO2 than on M estimates. Relative changes in CMRO2 during motor tasks at 3 and 7 T were in good agreement but were over-estimated at 1.5 T as a result of the lower signal to noise ratio. This result is encouraging for future studies at 7 T, but also highlights the impact of imaging and analysis choices (such as ASL sequence and ROI definition) on the calibration parameter M and on the calculation of CMRO2.