Grant Hartung1, Joerg Pfannmoeller1, Avery J. L. Berman1, and Jonathan R. Polimeni1
1Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, United States
Synopsis
Here we extend a recent approach employing biophysical
simulations of realistic cortical microvascular anatomy and dynamics to test
whether the topology of the microvasculature impact the BOLD response. We create
3D vascular anatomical networks with varying ratios of arteries to venules and simulated
the effects on cerebral blood flow and volume responses. We observed a
difference in the cerebral blood volume response after we varied the ratio of
diving arteries to ascending veins.
Summary of Main Findings
We adapted realistic models of
cortical microvasculature to alter the topology of the vascular network and
performed dynamical simulations of blood flow and volume changes following
neural activity. We find that the topology changes cause qualitatively
different blood volume responses.Introduction
Although it is well known that vascular anatomy has a strong influence on the functional magnetic resonance imaging (fMRI) signal, recent biophysical simulations based on reconstructions of cortical microvasculature predicted unexpected effects imposed by the geometry of the microvascular network that were later confirmed experimentally. Here we extend this approach by asking whether the topology of the microvascular network imparts similar effects on the BOLD response temporal characteristics. Cortical microvascular topology varies between species, brain regions, and cortical depth1–3, and these changes in the angioarchitecture may be one contributing factor to the observed differences in hemodynamics. In order to investigate in isolation the impact of topological properties of the microvascular network on the hemodynamic response to neural activity, we employed a recently developed methodology to synthesize realistic microvascular models matched to the statistical distributions reported from published optical microscopy studies4,5, which allow for parametric variation of several network parameters of interest while holding other properties constant. In this preliminary study, we varied the ratio of intracortical penetrating arteries to ascending venules, which is known to vary across species1, to investigate whether this results in a measurable effect on the temporal properties of the BOLD response.Methods
Using a previously described simulation platform6, we computed the cerebral
blood volume (CBV) changes during functional hyperemia in image-derived,
realistic vascular anatomical networks (VANs). The native model exhibited a 1:3
ratio of penetrating arterioles to ascending venules7 that is reflected in the
mouse cortex. To isolate and test the opposing topological configuration (3:1
ratio as observed in humans), we imposed the anatomical grouping, simulation
parameters, and the diameter spectra (using a topological matching algorithm5) from the arteries onto the
veins and vice versa. We generated a total of four vascular models8,9, each with a 1:3 and 3:1
configuration. This vascular synthesis approach was implemented in Object
Pascal with simulations conducted in Matlab. With these models in place, the
resulting blood flow and volume dynamics were calculated as previously
described7,8. For both models the arteries
underwent the same amplitude of active arterial dilation for a prolonged period
of 17.5 s during which time the capillaries and veins exhibited a passive
compliance as described previously10.Results
We observed an initial rise in the arterial cerebral blood
volume (CBV) followed by a slow onset of venous and capillary ballooning that
reached its peak at the end of the arterial dilation period as visualized in Figure
1. When comparing the native model (1:3 ratio) to the swapped model (3:1
ratio), we noticed a CBV increase during activation in the swapped model in
conjunction with an increase in overall blood perfusion. Because the swapping
of arteries and veins increases the arterial volume, this increased CBV in all
compartments could be explained by the immediate increase in actively dilated
vessels. The accompanying decrease in baseline venous volume reduces the venous
ballooning, but not enough to eradicate the increased CBV changes seen in the
swapped model.Discussion
One of the fundamental assumptions in functional brain
imaging, specifically in fMRI acquisition, is does not account for vascular
differences between brain regions and species. We note that here we imposed an
identical arteriolar dilation in both cases. While it may be the case in brain
regions with more arteries less dilation is needed to supply the capillary bed,
further simulations are underway to evaluate several possible scenarios of
arterial dilation. Our findings suggest that the microvascular topology may
influence the BOLD signal implying that this may be one contribution to the
observed differences in the BOLD response between brain regions and species. Prior
work has also suggested that differences in vascular topology could impact the
BOLD signal11. This aspect of the BOLD response
is likely independent of neuronal response, although vascular topology may
reflect local neural architecture2. If these
vasculature-dependent effects can be characterized, future fMRI studies can be
enriched by further isolating the vascular-independent portion of the
signal and achieve improved neural specificity.Acknowledgements
This work was supported in part by the NIH NIBIB (grant P41-EB030006 and R01-EB019437), by the BRAIN Initiative (NIH NIMH grants R01-MH111419, R01-MH111438, and F32-MH125599), and by the MGH/HST Athinoula A. Martinos Center for Biomedical Imaging; and was made possible by the resources provided by NIH Shared Instrumentation Grant S10-RR023043.References
1. Schmid, F., Barrett, M. J. P., Jenny, P. & Weber, B. Vascular
density and distribution in neocortex. NeuroImage (2017)
doi:10.1016/j.neuroimage.2017.06.046.
2. Tsai, P. S. et al. Correlations of
Neuronal and Microvascular Densities in Murine Cortex Revealed by Direct
Counting and Colocalization of Nuclei and Vessels. J. Neurosci. 29,
14553–14570 (2009).
3. Smith, A. F. et al. Brain capillary
networks across species: a few simple organizational requirements are
sufficient to reproduce both structure and function. Front. Physiol. 10,
233 (2019).
4. Linninger, A., Hartung, G., Badr, S. &
Morley, R. Mathematical synthesis of the cortical circulation for the whole
mouse brain-part I: theory and image integration. Comput. Biol. Med.
(2019).
5. Hartung, G. et al. Mathematical
synthesis of the cortical circulation for the whole mouse brain-Part II:
microcirculatory closure. Comput. Biol. Med. ((In Review)).
6. Fang, Q. et al. Oxygen Advection and
Diffusion in a Three Dimensional Vascular Anatomical Network. Opt. Express
16, 17530–17541 (2008).
7. Gagnon, L. et al. Quantifying the
Microvascular Origin of BOLD-fMRI from First Principles with Two-Photon
Microscopy and an Oxygen-Sensitive Nanoprobe. J. Neurosci. 35,
3663–3675 (2015).
8. Gagnon, L. et al. Validation and optimization
of hypercapnic-calibrated fMRI from oxygen-sensitive two-photon microscopy. Philos.
Trans. R. Soc. B Biol. Sci. 371, 20150359 (2016).
9. Gagnon, L. et al. Modeling of Cerebral
Oxygen Transport Based on In vivo Microscopic Imaging of Microvascular Network
Structure, Blood Flow, and Oxygenation. Front. Comput. Neurosci. 10,
(2016).
10. Boas, D. A., Jones, S. R., Devor, A., Huppert,
T. J. & Dale, A. M. A vascular anatomical network model of the
spatio-temporal response to brain activation. NeuroImage 40,
1116–1129 (2008).
11. Báez-Yáñez, M. G., Siero, J. & Petridou, N.
Investigation of the dynamic fingerprint of the BOLD fMRI signal based on a
novel statistical 3D cortical vascular network of the human brain.