Abstract
The measurement of the absolute rate of cerebral metabolic oxygen consumption (CMRO2) is likely to offer a valuable biomarker in many brain diseases and could prove to be important in our understanding of neural function. As such there is significant interest in developing robust MRI techniques that can quantify CMRO2 non-invasively. One potential MRI method for the measurement of CMRO2 is via the combination of fMRI and cerebral blood flow (CBF) data acquired during periods of hypercapnic and hyperoxic challenges. This method is based on the combination of two, previously independent, signal calibration techniques. As such analysis of the data has been approached in a stepwise manner, feeding the results of one calibration experiment into the next. Analysing the data in this manner can result in unstable estimates of the output parameter (CMRO2), due to the propagation of errors along the analysis pipeline. Here we present a forward modelling approach that estimates all the model parameters in a one-step solution. The method is implemented using a regularized non-linear least squares approach to provide a robust and computationally efficient solution. The proposed framework is compared with previous analytical approaches using modelling studies and in vivo acquisitions in healthy volunteers (n=10). The stability of parameter estimates is demonstrated to be superior to previous methods (both in vivo and in simulation). In vivo estimates made with the proposed framework also show better agreement with expected physiological variation, demonstrating a strong negative correlation between baseline CBF and oxygen extraction fraction. It is anticipated that the proposed analysis framework will increase the reliability of absolute CMRO2 measurements made with calibrated BOLD.
Highlights
The rate of metabolic oxygen consumption in the brain (CMRO2) is a valuable biomarker in the assessment of disease and treatment effect (Heiss and Herholz, 1994; Lammertsma, 1987; Tohgi et al, 1998)
The interquartile ranges (IQR) of the error in OEF0 estimates were 0.15, 0.11, 0.18, and 0.17 for the forward model, the forward model, the analytical approach proposed by Bulte et al and the analytical approach proposed by Gauthier et al The IQR of modelled OEF0 estimates is significantly reduced when using the regularised forward modelling method (p b 0.05), as assessed by the Westenberg test for IQR equality
We have demonstrated the measurement of OEF and absolute CMRO2 using a forward signal model and compared the performance of the fitting method to two previously proposed analytical methods
Summary
The rate of metabolic oxygen consumption in the brain (CMRO2) is a valuable biomarker in the assessment of disease and treatment effect (Heiss and Herholz, 1994; Lammertsma, 1987; Tohgi et al, 1998). There is significant interest in the development of alternative methods that can be more routinely employed to map CMRO2 One such emerging technique is through the calibrated measurement of the MRI blood oxygenation level dependent (BOLD) signal (Bulte et al, 2012; Gauthier et al, 2012; Germuska and Bulte, 2014; Wise et al, 2013). This approach, which we shall refer to as dual-calibrated functional MRI (dcfMRI), is based on the quantification of cerebral blood flow (CBF) and the change in venous oxygenation during periods of respiratory challenge
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