Noninvasive quantification of cerebral blood volume in humans during functional activation
Introduction
Functional magnetic resonance imaging (fMRI) techniques based on local cerebral hemodynamic changes have been used extensively for mapping functional neuroanatomy (Ogawa et al., 1990, Belliveau et al., 1991, Detre et al., 1992). Although there are emerging methods to measure changes in the MRI signal directly caused by neuronal action potentials (Bodurka and Bandettini, 2002, Xiong et al., 2003), the vast majority of fMRI experiments measure changes in cerebral blood oxygenation (Ogawa et al., 1992, Kwong et al., 1992, Bandettini et al., 1992, Frahm et al., 1992), blood flow (Williams et al., 1992, Edelman et al., 1994, Kim, 1995, Kwong et al., 1995), or blood volume (Belliveau et al., 1991, Mandeville et al., 1998) as an indirect measure of neuronal activity. Hemodynamic-based fMRI signals have different characteristics in terms of sensitivity and specificity in detecting brain activity. Techniques based on BOLD (blood oxygenation level-dependent) contrast usually have higher sensitivity; however, physiological interpretation of the BOLD signal is limited since the signal arises from the complex interplay of blood volume, flow and oxygen consumption (Ogawa et al., 1993, Boxerman et al., 1995, Buxton et al., 1998, van Zijl et al., 1998). Perfusion imaging with arterial spin labeling (ASL) provides quantitative measurement of cerebral blood flow (CBF) that targets signal changes more closely associated with neuronal activity compared to the relatively venous-weighted blood oxygenation. However, sensitivity of current ASL perfusion techniques is inherently low due to the low perfusion-related contrast (∼1%) and the image subtraction procedure (Wong et al., 1997). The earliest human fMRI experiment was performed with injections of exogenous susceptibility contrast agents (Belliveau et al., 1991). Although this method has not been widely used in human studies, primarily due to the invasiveness of the technique and the short half-lifetime of Gadolinium (Gd)-based contrast agents, it has been successfully employed in animal fMRI experiments utilizing the much longer half-lifetime monocrystalline iron oxide nanocolloid (MION) (Mandeville et al., 1998). Recently, a noninvasive fMRI technique based on CBV changes during brain activation was proposed (Lu et al., 2003), in which MR signals of blood water were suppressed by acquiring images at the blood-nulling point of an inversion recovery sequence to detect vascular space occupancy (VASO)-dependent signal changes associated with brain activation. VASO imaging is expected to have better spatial specificity than BOLD due to its high sensitivity to microvessels, but it cannot obtain quantitative CBV information during activation without additional baseline CBV data.
Noninvasive quantification of CBV and its change during physiological challenges promise to improve our understanding of brain hemodynamics and fMRI signal mechanisms, including evaluating potential alterations of vascular state versus neuronal activation following drug administration (Salmeron and Stein, 2002). However, CBV imaging with injections of exogenous contrast agents is an invasive method and is not suitable for fMRI studies with complex stimulation paradigms (Belliveau et al., 1991), while VASO imaging detects CBV-weighted signal changes between rest and activation states, but does not provide absolute CBV values at these two states (Lu et al., 2003).
We present here a new method that is able to quantify CBV noninvasively at rest and during activation. This was achieved by measuring fMRI signal at various inversion times (TI), thereby varying the weightings of CBV and blood oxygenation contrasts. The data were fitted to a biophysical model comprised of multiple tissue components to obtain absolute CBV at rest and following activation. Functional experiments with graded visual stimulation were conducted on healthy volunteers to evaluate this method.
Section snippets
Biophysical model for determination of CBV and blood oxygenation
A three-compartment model was used, in which a voxel in the activated region contains FCSF fraction of cerebral-spinal fluid (CSF) and 1-FCSF fraction of brain parenchyma. The parenchyma, in turn, contains fb fraction (also known as CBV) of blood and 1-fb fraction of extravascular tissue. Note that the volume fraction of the blood in the whole voxel is given by:
The MR signal magnitude can be written as:where Si (i = CSF, b or t) is the signal contribution from the
Results
Experimental SNRs (SNRvoxel) were dependent on TI: 144 ± 44 (n = 5, mean ± SD), 54 ± 14, 39 ± 14, 38 ± 9, 33 ± 6, 29 ± 10, 25 ± 4, 34 ± 12, 38 ± 9, 54 ± 16, 67 ± 15, 69 ± 16, 84 ± 11, and 91 ± 15 for TI values of 499 ms, 649 ms, 679 ms, 709 ms, 724 ms, 769 ms, 799 ms, 829 ms, 859 ms, 889 ms, 919 ms, and 949 ms, respectively. Fig. 2a illustrates a representative set of activation maps from the visual stimulation experiments of one subject acquired at 14 different TIs. While activated voxels are
Discussion
We have developed a noninvasive method to quantify absolute CBV values in human at rest and during functional activation. With measurements of functional signals at various TIs, CBV parameters were determined based on a biophysical model. The applicability of this method was demonstrated using visual stimulation.
CBV is an important parameter in brain physiology and is of clinical value for many neurovascular diseases as well as some diseases of non-vascular origin (e.g., brain tumor,
Conclusion
In summary, we have developed a new MRI method for noninvasive quantification of CBV in humans. Absolute CBV at rest and during activation can be obtained by fitting a series of fMRI data sets acquired at various TIs to a biophysical model. Experiments on healthy volunteers with visual stimulations demonstrated that the obtained CBV values are consistent with previous reports. This technique provides a useful tool for quantifying hemodynamic changes associated with neuronal activity.
Acknowledgments
The authors are thankful to Dr. Peter van Zijl for providing blood R2* values at 3.0 T.
References (39)
- et al.
Combining brains: a survey of methods for statistical pooling of information
NeuroImage
(2002) - et al.
Intervoxel heterogeneity of event-related functional magnetic resonance imaging responses as a function of T(1) weighting
NeuroImage
(2002) - et al.
Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model
Biophys. J.
(1993) - et al.
The relationship between cerebral blood flow and volume in humans
NeuroImage
(2005) - et al.
Time course EPI of human brain function during task activation
Magn. Reson. Med.
(1992) - et al.
Functional mapping of the human visual cortex by magnetic resonance imaging
Science
(1991) - et al.
Toward direct mapping of neuronal activity: MRI detection of ultraweak, transient magnetic field changes
Magn. Reson. Med.
(2002) - et al.
The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusion-weighted studies in vivo
Magn. Reson. Med.
(1995) - et al.
Dynamics of blood flow and oxygenation changes during brain activation: the balloon model
Magn. Reson. Med.
(1998)
Rapid T1 mapping using multislice echo planar imaging
Magn. Reson. Med.
Perfusion imaging
Magn. Reson. Med.
Qualitative mapping of cerebral blood flow and functional localization with echo-plan MR imaging and signal targeting with alternative radio frequency
Radiology
Stimulus rate determines regional brain blood flow in striate cortex
Ann. Neurol.
Dynamic MR imaging of human brain oxygenation during rest and photic stimulation
J. Magn. Reson. Imaging
Density of capillaries in regions of the living human brain affected by stroke
Quantification of relative cerebral blood flow change by flow-sensitive alternating inversion recovery (FAIR) technique: application to functional mapping
Magn. Reson. Med.
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation
Proc. Natl. Acad. Sci. U. S. A.
MR perfusion studies with T1-weighted echo planar imaging
Magn. Reson. Med.
Cited by (38)
Validating layer-specific VASO across species
2021, NeuroImageEffect of reading on blood flow changes in the posterior cerebral artery in early blind and sighted people - A transcranial Doppler study
2016, Journal of the Neurological SciencesCitation Excerpt :The cause of the difference between the two groups (sighted vs blind) that we observed during the “Rest-Reading protocol” was due to the absence of light stimulus in blind people. In line with our observations, visual stimulation was reported to cause an increase of 15–65% in relative flow in sighted subjects [11–24], depending on the experimental protocols (frequency of visual stimulation, complexity and contrast of the visual pattern, and continuous or intermittent stimulation) and the investigation methods (PET, functional MRI, functional TCD). The measure of flow increase in the visual/occipital cortex evoked by reading in sighted people has been mostly investigated by TCD studies.
MRI and fMRI Optimizations and Applications
2015, Brain Mapping: An Encyclopedic ReferenceA review of the development of Vascular-Space-Occupancy (VASO) fMRI
2012, NeuroImageCitation Excerpt :In the following years, several other groups became interested in this technology and made important contributions to its optimization and understanding. These include the combination of VASO with ASL/BOLD acquisitions (Yang et al., 2004), the use of tissue-nulling TIs (Shen et al., 2009; Wu et al., 2008), the use of multiple TIs to simultaneously estimate resting and activated CBV (Glielmi et al., 2009; Gu et al., 2006), the improved suppression of blood signal (Wu et al., 2007), the use of VASO in calibrated fMRI (Lin et al., 2008a), the effect of CSF contributions on VASO signal (Scouten and Constable, 2007, 2008), the spatial specificity of the signal (Jin and Kim, 2008), and the design of methods for faster acquisition and greater spatial coverage of VASO (Poser and Norris, 2007, 2009, 2011). Vasodilatation associated with neural activation is caused by changes in microenvironment immediately adjacent to the active neurons (Kuschinsky, 1996).
Current trends and challenges in MRI acquisitions to investigate brain function
2009, International Journal of Psychophysiology