Mario Gilberto Baez-Yanez1, Alex Bhogal1, Wouter Schellekens1, Jeroen C.W. Siero1,2, and Natalia Petridou1
1Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands, 2Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, Netherlands
Synopsis
The
administration of CO2/O2
gas-challenges during BOLD-fMRI is appealing due to the hemodynamic
impact these stimuli have. With the support of computational
modeling, arterial gas manipulations can provide a means to separate
neuro-vascular signal contributions. Hence, we performed simulations
in virtual vascular architectures for different blood volumes and
oxygen saturation levels. The effect that these states have on the
magnetic field was simulated, separately, for arteries and veins. We
present look-up tables to derive the possible vascular contribution
responsible for measured BOLD signals in clinical or research fMRI
settings including changes in local blood volume, oxygen metabolism
or cereberovascular diseases.
Introduction
Blood-oxygenation-level-dependent (BOLD) fMRI is widely used to study brain function.
However, the BOLD-fMRI signal represents an integration of several
hemodynamic parameters and therefore provides only indirect
information on neuronal functioning[1]. To disentangle hemodynamic
parameters -cerebral blood volume(CBV) and oxygen saturation(SO2)-,
studies have explored the use of gas-challenges to manipulate vessel
caliber(CBV, modulated by CO2)
and hemoglobin saturation state(O2)[2,9,10].
Nonetheless, arterial gas manipulations alone are insufficient to
understand the relationship between vascular properties and the
resulting hemodynamic signals. For this, computational modeling is
necessary. This work aims to simulate the BOLD-fMRI signal change for
different CBV and SO2
changes based on virtual vascular networks. We present look-up tables
that determine the possible arterial/venous contributions to
CO2/O2-inspired
BOLD-fMRI signal changes for gradient-echo(GE) and spin-echo(SE) at
7T.Methods
We
computed the relative BOLD-fMRI signal change in two vascular models.
(1) We simulated susceptibility and diffusion effects in an
artificial vascular network(AVN) to validate our computational
method. (2) We created a representative realistic vascular network(RVN) to simulate susceptibility effects for arteries and veins.
Randomly
oriented cylinders represent the AVN for vessel sizes ranging from
1µm-100µm fulfilling a specific volume fraction in an isotropic
voxel of 1mm3.
Levels of SO2
ranging
from 60-90% were separately imposed with a hematocrit level of 45%.
Diffusion motion was simulated with a Monte Carlo method(1µm2/ms)
and induced-dephasing was recorded for an ensemble of spins(1E9
spins) for GE-BOLD(TE=27ms) and SE-BOLD(TE=45ms) at 7T[3,4]. We
adopted an SO2
of
60% as basal-state. To study vessel dilation effects, we use a basal
CBV of 3%, and simulated CBV changes ranging from -33%(constriction)
to 100%(dilation). Only extravascular effects were considered since
intravascular contributions are assumed to be negligible at 7T[5].
An
RVN was generated based on a modified mouse vascular network[6]; an
artery-to-vein ratio of 3:1 was applied simulating the human
cerebrovasculature[7]. Vectorial description of the RVN provides
detailed information regarding the spatial distribution and vessel
properties in an isotropic 1mm3
simulation voxel. The susceptibility-induced inhomogeneous magnetic
field was computed assuming a separate contribution of arteries and
veins. Variable SO2
levels
for arteries and veins were simulated to examine the impact of each
compartment to the BOLD-fMRI signal change. CBV changes in arteries
and veins were investigated considering only an increase (dilation)
in vessel radius.
Based
on the Fourier transform of the inhomogeneous magnetic field, we
calculated the signal decay for GE-BOLD(TE=27ms) at 7T[8]. Since the
Fourier method assumes a static dephasing regime, the contribution of
capillaries can be superimposed assuming a weighted-microvascular
contribution to the computed BOLD signal change. However, we only
considered the contribution of the arterial and venous compartments.Results
Figure1
shows the simulation obtained with an AVN model for GE (top row) and
SE (bottom row). Our computational method reproduces the well-known
sensitivities of GE and SE to all and small vessels respectively, as
reported in[3,4](Figure1.a;1.d).
Simulation
of changes in SO2
for different vessel sizes shows that about 10% or larger SO2
changes
are necessary to saturate the BOLD-fMRI signal change for GE(Figure1.b). For SE, small vessel contribution to the BOLD-fMRI
signal is relatively larger due to the refocusing pulse. Hence,
larger SO2
changes are required to obtain a comparable GE-like BOLD-fMRI signal
change(Figure1.e). GE has a high sensitivity to CBV changes(Figure1.c) in contrast to SE(Figure1.f).
Figure2
displays the look-up tables of the BOLD-fMRI signal change in which
several SO2
levels
and CBV changes are simulated for arteries and veins (RVN model). A
characteristic non-linear BOLD-fMRI signal behavior is displayed in
Figure2.a which can be attributed to the arterial-to-venous ratio.
Hence, reduction in arterial SO2
sets the negative BOLD-fMRI signal change; only with this condition
set, the venous SO2
change also starts to play a role in showing negative BOLD responses.
For null or increases in arterial SO2,
the BOLD signal is positive for most of the venous SO2
changes.
Figure2.b
displays the impact of the SO2
and
CBV change in the venous compartment while arterial SO2
and CBV is maintained. Figure2.c shows the absolute difference
between the arterial basal-state(Figure2.b) and the dilated arterial
compartment(dilation of 12.5%, 25%, 37.5% and 50%), while keeping
constant the SO2(98%), for different CBV and SO2
changes in the venous compartment. Arterial dilation affects the BOLD
signal only when the degree of dilation is considerable, i.e.
dilation larger than 25% the intrinsic vessel size.Discussion / Conclusion
We
present look-up tables for the relative BOLD-fMRI signal change for
different hemodynamic parameters (i.e. CBV and SO2)
to investigate the arterial and venous contribution in
CO2/O2 gas-challenge
fMRI experiment. Thus, we have performed simulations in artificial
and realistic vascular models for several SO2
levels and CBV changes. Notably a non-linear relation between the contribution
of arteries and veins is displayed by the RVN model. Larger
contributions are obtained from the venous side for small SO2
and CBV changes. Arterial dilation affects the BOLD signal only when
the degree of dilation is considerable, i.e. dilation larger than 25%
the intrinsic vessel size.
Relative
BOLD signal changes (±5-10%) are reported [9,10] under controlled
CO2/O2-gas
stimulus in fMRI measurements. Given the presented look-up tables it may be possible to infer the vascular contributions to the measured BOLD signals and/or particular hemodynamic basal statesAcknowledgements
This work was supported by the National Institute of Mental Health of the National Institutes of Health under the Award Number R01MH111417References
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