Elsevier

NeuroImage

Volume 84, 1 January 2014, Pages 605-614
NeuroImage

Using carbogen for calibrated fMRI at 7 Tesla: Comparison of direct and modelled estimation of the M parameter

https://doi.org/10.1016/j.neuroimage.2013.09.035Get rights and content

Abstract

Task-evoked changes in cerebral oxygen metabolism can be measured using calibrated functional Magnetic Resonance Imaging (fMRI). This technique requires the use of breathing manipulations such as hypercapnia, hyperoxia or a combination of both to determine a calibration factor M. The M-value is usually obtained by extrapolating the BOLD signal measured during the gas manipulation to its upper theoretical physiological limit using a biophysical model. However, a recently introduced technique uses a combination of increased inspired concentrations of O2 and CO2 to saturate the BOLD signal completely. In this study, we used this BOLD saturation technique to measure M directly at 7 Tesla (T). Simultaneous carbogen-7 (7% CO2 in 93% O2) inhalation and visuo-motor task performance were used to elevate venous oxygen saturation in visual and motor areas close to their maximum, and the BOLD signal measured during this manipulation was used as an estimate of M. As accurate estimation of M is crucial for estimation of valid oxidative metabolism values, these directly estimated M-values were assessed and compared with M-values obtained via extrapolation modelling using the generalized calibration model (GCM) on the same dataset. Average M-values measured using both methods were 10.4 ± 3.9% (modelled) and 7.5 ± 2.2% (direct) for a visual-related ROI, and 11.3 ± 5.2% (modelled) and 8.1 ± 2.6% (direct) for a motor-related ROI. Results from this study suggest that, for the CO2 concentration used here, modelling is necessary for the accurate estimation of the M parameter. Neither gas inhalation alone, nor gas inhalation combined with a visuo-motor task, was sufficient to completely saturate venous blood in most subjects. Calibrated fMRI studies should therefore rely on existing models for gas inhalation-based calibration of the BOLD signal.

Introduction

Blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) to map neuronal activity in the brain (Buxton, 2012, Ogawa et al., 1990). BOLD contrast relies on a complex interplay between changes in cerebral blood flow (CBF), cerebral blood volume (CBV) and cerebral metabolic rate of oxygen (CMRO2). The quantitative relationship between these parameters has not, however, been fully elucidated (Aguirre et al., 1998, Buxton, 2010, Turner, 2002). Additionally, since the BOLD response is a relative change from an unknown baseline, differences in baseline physiology may influence BOLD signal changes, precluding truly quantitative BOLD response comparisons across subjects, or within the same subject across days (Gauthier et al., 2011, Lu et al., 2008). However, more physiologically-specific MRI-based methods have been proposed to detect functional activity in the brain. These are typically based on measuring a single physiological quantity rather than an ambiguous combination of several (Davis et al., 1998, Lu et al., 2003, Williams et al., 1993). Of these physiological quantities, CMRO2 is believed to provide one of the most direct indices of neural activity mapping since it reflects oxidative energy consumption of the tissue (Hoge et al., 1999).

Calibrated fMRI techniques used to quantify CMRO2 in the brain commonly rely on the combined acquisition of CBF and BOLD signals during a gas-breathing manipulation. Either hypercapnic (CO2) (Davis et al., 1998, Hoge et al., 1999) or hyperoxic (O2) (Chiarelli et al., 2007c) breathing challenges are used to elevate venous saturation and thereby the BOLD signal. The BOLD signal increase measured during this gas breathing manipulation is extrapolated to its theoretical maximum M via a biophysical calibration model. The recently introduced generalized calibration model (GCM) extends the hyperoxia calibration model (Chiarelli et al., 2007c), making it valid for combined hypercapnia and hyperoxia breathing challenges (Gauthier and Hoge, 2013).

Common to all models is a dependence on accurate estimation of the calibration parameter M to obtain valid CMRO2 estimates. Previous studies using hypercapnia, hyperoxia or a combination of both have yielded a large range of estimated M-values (Ances et al., 2008, Ances et al., 2009, Bulte et al., 2009, Bulte et al., 2012, Chen and Parrish, 2009, Chiarelli et al., 2007b, Chiarelli et al., 2007c, Driver et al., 2012, Gauthier et al., 2012, Gauthier et al., 2013, Gauthier and Hoge, 2013, Hall et al., 2012, Huber et al., 2013, Ivanov et al., 2012, Leontiev et al., 2007, Leontiev and Buxton, 2007, Lin et al., 2008, Mark et al., 2011, Mark and Pike, 2012, Mohtasib et al., 2012, Perthen et al., 2008). Some of the variance between studies may be explained by differences in haemodynamic and physiological properties across brain regions and subjects (Aguirre et al., 1998, Ances et al., 2008, Chiarelli et al., 2007a, Lu et al., 2008) or the dependence of M on specific measurement parameters, such as echo time (TE) or static magnetic field strength (B0) (Hoge et al., 1999, Uludağ et al., 2009). However, some uncertainty in M is also expected due to the relatively high probability of extrapolation error when starting from noisy measurements or poorly estimated parameters (Chen and Pike, 2010, Chiarelli et al., 2007b).

A recently introduced technique uses carbogen mixtures with high CO2 and O2 content (10% CO2, 90% O2) to saturate the BOLD signal by elevating venous O2 saturation close to 100% (Gauthier et al., 2011). This approach can be used to directly measure the calibration constant M and circumvent the disadvantages associated with M-value modelling. However, CO2 concentrations at 10% can lead to a significant level of discomfort (Banzett et al., 1996, Gauthier et al., 2011) and are therefore not a viable alternative for routine calibrated BOLD studies. In this study we have applied the direct M-value estimation approach at 7 Tesla using a moderate CO2 concentration of 7% with simultaneous visuo-motor activation, based on previous work in our lab (Ivanov et al., 2012). Since breathing discomfort is known to be related to CO2 concentration (Banzett et al., 1996, Gauthier et al., 2011, Gauthier and Hoge, 2013), this lower CO2 concentration is expected to be more tolerable for participants. The directly estimated results are compared to GCM-based M-value modelling also based on carbogen-7 inhalation. Furthermore, this work is the first to quantitatively assess the direct and GCM-based M-value estimation techniques at ultra-high field in the same experiment. Benefits and drawbacks of both techniques are analysed and compared to assess their feasibility for future calibrated fMRI studies.

Section snippets

Methods

Data were acquired in 15 healthy participants (7 women, 26 ± 3 years) on a Siemens Magnetom 7T whole body MRI scanner (Siemens Medical Solutions, Erlangen, Germany) equipped with a 24 channel head coil (NOVA Medical Inc, Wilmington, MA, USA). All participants gave written informed consent for participation in this study. Ethics approval was obtained from the local review board (Ethics Commission, Leipzig University).

Results

Baseline O2 and CO2 partial pressures were comparable for all subjects. The average PetCO2 and PetCO2 at rest were 107.8 ± 2.4 mm Hg and 40.2 ± 2.2 mm Hg, respectively. End-tidal partial pressures of CO2 during carbogen inhalation showed an average of 53.8 ± 2.3 mm Hg. The average manipulated PetCO2 was 600.5 ± 64.5 mm Hg. Participants' end-tidal partial pressures of O2 (PetCO2) and CO2 (PetCO2) measured during rest and gas manipulation periods are given in Supplementary Table 1.

Visually-evoked ROI-based

Discussion

In this study we applied and compared two concurrent calibrated BOLD techniques at 7 Tesla. The direct calibration method was used under the assumption that complete venous oxygen saturation could be reached using a combined hyperoxia–hypercapnia breathing challenge. To assess whether complete saturation of venous blood was reached using this challenge, subjects in this study also performed a visuo-motor task during gas inhalation. Venous oxygenation levels of 91.1% were obtained during gas

Conclusion

In this calibrated fMRI study, we compared the direct estimation of calibrated BOLD M-values to the generalized calibration model-based approach. Calibrated BOLD modelling suffers from important drawbacks, such as the reliance on assumed parameters whose values have not been fully validated. Additionally, M-value modelling is vulnerable to errors in CBF signal quantification. While the direct method does not suffer from these sources of error, it relies on complete venous oxygen saturation

Acknowledgements

We thank Elisabeth Wladimirow and Domenica Wilfing for helping with the data acquisition, subject handling and scanning organisation. We would also like to thank Robert Trampel for helping with the ethics application and Robert Trampel, Gabriele Lohmann and Jenny von Smuda for the helpful discussions.

Conflict of interest statement

We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work

References (67)

  • P.A. Chiarelli et al.

    A calibration method for quantitative BOLD fMRI based on hyperoxia

    NeuroImage

    (2007)
  • I. Driver et al.

    The change in cerebrovascular reactivity between 3 T and 7 T measured using graded hypercapnia

    NeuroImage

    (2010)
  • I.D. Driver et al.

    Calibrated BOLD using direct measurement of changes in venous oxygenation

    NeuroImage

    (2012)
  • C.J. Gauthier et al.

    Elimination of visually evoked BOLD responses during carbogen inhalation: implications for calibrated MRI

    NeuroImage

    (2011)
  • C.J. Gauthier et al.

    Absolute quantification of resting oxygen metabolism and metabolic reactivity during functional activation using QUO2 MRI

    NeuroImage

    (2012)
  • V.E.M. Griffeth et al.

    A theoretical framework for estimating cerebral oxygen metabolism changes using the calibrated-BOLD method: modeling the effects of blood volume distribution, hematocrit, oxygen extraction fraction, and tissue signal properties on the BOLD signal

    NeuroImage

    (2011)
  • M. Jones et al.

    The effect of hypercapnia on the neural and hemodynamic responses to somatosensory stimulation

    NeuroImage

    (2005)
  • O. Leontiev et al.

    Reproducibility of BOLD, perfusion, and CMRO2 measurements with calibrated-BOLD fMRI

    NeuroImage

    (2007)
  • O. Leontiev et al.

    CBF/CMRO2 coupling measured with calibrated BOLD fMRI: sources of bias

    NeuroImage

    (2007)
  • C.I. Mark et al.

    Improved fMRI calibration: precisely controlled hyperoxic versus hypercapnic stimuli

    NeuroImage

    (2011)
  • R.S. Mohtasib et al.

    Calibrated fMRI during a cognitive stroop task reveals reduced metabolic response with increasing age

    NeuroImage

    (2012)
  • J.E. Perthen et al.

    Caffeine-induced uncoupling of cerebral blood flow and oxygen metabolism: a calibrated BOLD fMRI study

    NeuroImage

    (2008)
  • C. Triantafyllou et al.

    Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters

    NeuroImage

    (2005)
  • R. Turner

    How much cortex can a vein drain? Downstream dilution of activation-related cerebral blood oxygenation changes

    NeuroImage

    (2002)
  • K. Uludağ et al.

    Coupling of cerebral blood flow and oxygen consumption during physiological activation and deactivation measured with fMRI

    NeuroImage

    (2004)
  • K. Uludağ et al.

    An integrative model for neuronal activity-induced signal changes for gradient and spin echo functional imaging

    NeuroImage

    (2009)
  • G. Zaharchuk et al.

    Noninvasive oxygen partial pressure measurement of human body fluids in vivo using magnetic resonance imaging

    Acad. Radiol.

    (2006)
  • A.C. Zappe et al.

    Direct measurement of oxygen extraction with fMRI using 6% CO2 inhalation

    Magn. Reson. Imaging

    (2008)
  • B.M. Ances et al.

    Effects of aging on cerebral blood flow, oxygen metabolism, and blood oxygenation level dependent responses to visual stimulation

    Hum. Brain Mapp.

    (2009)
  • N.P. Blockley et al.

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

    NMR Biomed.

    (2013)
  • N.P. Blockley et al.

    Cross-field analysis of the accuracy of hypercapnia calibrated BOLD

  • J.L. Boxerman et al.

    MR contrast due to intravascular magnetic susceptibility perturbations

    Magn. Reson. Med.

    (1995)
  • D.P. Bulte et al.

    Comparison of hypercapnia-based calibration techniques for measurement of cerebral oxygen metabolism with MRI

    Magn. Reson. Med.

    (2009)
  • Cited by (0)

    View full text