Abstract
There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.
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This work was supported, in part, via NIH grants HL-082838 (to SMP) and HL-086418 (to JDH).
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Appendix
Appendix
Symbol (units) | Classification | Definition |
---|---|---|
\( K_{{\sigma_{\theta } }}^{\text{c}} \) | CMM: Bounded | Gain parameter governing circumferential-stress mediated rate of production of collagen. See Eq. (1) |
\( K_{{\sigma_{\theta } }}^{\text{m}} \) | CMM: Bounded | Gain parameter governing circumferential-stress mediated rate of production of smooth muscle. See Eq. (1) |
\( K_{{\tau_{w} }}^{\text{c}} \) | CMM: Bounded | Gain parameter governing shear-stress mediated rate of production of collagen. See Eq. (1) |
\( K_{{\tau_{w} }}^{\text{m}} \) | CMM: Bounded | Gain parameter governing shear-stress mediated rate of production of smooth muscle. See Eq. (1) |
MMP-10 (pg) | ABM: Bounded | Baseline mass of MMP-1 |
MMP-1%A (%) | ABM: Bounded | Percent of MMP-1 that is active |
C0 (pg) | ABM: Bounded | Baseline mass of collagen |
C TGF | ABM: Bounded | Rate parameter governing TBFb mediated rate of production of collagen (pg of collagen per pg of TGFb) |
M p | ABM: Bounded | Rate parameter governing PDGF mediated SMC proliferation rate (pg of SMC per pg of PDGF) |
M 0 (pg) | ABM: Bounded | Baseline SMC proliferation rate (pg) |
M a1 | ABM: Bounded | Apoptosis chance for SMC (1) |
M a2 | ABM: Bounded | Baseline apoptosis chance for SMC (2) |
\( {\text{PDGF}}_{{\sigma_{\theta } }} \) (pg/kPa) | ABM: Bounded | Rate parameter governing hoop stress mediated rate of production of PDGF (pg of PDGF per kPa of stress) |
PDGF0 (pg) | ABM: Bounded | Baseline mass of PDGF |
\( {\text{TGF}}\beta_{{\sigma_{\theta } }} \) (pg) | ABM: Bounded | Rate parameter governing hoop stress mediated rate of production of TGFb (pg of TGFb per kPa of stress) |
TGFβ0 (pg) | ABM: Bounded | Baseline mass of TGFb |
\( G_{h}^{\text{e}} \) | CMM: Observed | Homeostatic stretch when elastin is deposited |
\( G_{h}^{\text{c}} \) | CMM: Observed | Homeostatic stretch when collagen is deposited |
\( G_{h}^{\text{m}} \) | CMM: Observed | Homeostatic stretch when SMC is deposited |
\( c^{\text{e}} \) (kPa) | CMM: Calculated | Neo-Hookean material parameter for the stored energy of elastin |
\( c_{1}^{\text{c}} \) (kPa) | CMM: Calculated | Fung-type exponential material parameter for the stored energy of collagen (1) |
\( c_{1}^{\text{m}} \) (kPa) | CMM: Calculated | Fung-type exponential material parameter for the stored energy of SMC (1) |
\( c_{2}^{\text{c}} \) | CMM: Observed | Fung-type exponential material parameter for the stored energy of collagen (2) |
\( c_{2}^{\text{m}} \) | CMM: Observed | Fung-type exponential material parameter for the stored energy of SMC (2) |
\( T_{\text{M}} \) (kPa) | CMM: Observed | Maximum stress generated by SMC |
\( \lambda_{\text{M}} \) | CMM: Observed | Circumferential stretch where active stress is maximum |
\( \lambda_{0} \) | CMM: Observed | Circumferential stretch where active stress is zero |
\( C_{\text{B}} \) | CMM: Observed | Material parameter for the ratio of constrictor concentration to dilator concentration |
\( C_{\text{S}} \) | CMM: Observed | Scaling parameter for shear stress induced change in constrictor concentration scaling factor |
\( \phi^{\text{c}} \left( 0 \right) \) | CMM: Observed | Initial mass fraction of collagen in the arterial wall |
\( \phi^{\text{e}} \left( 0 \right) \) | CMM: Observed | Initial mass fraction of elastin in the arterial wall |
\( \phi^{\text{m}} \left( 0 \right) \) | CMM: Observed | Initial mass fraction of SMC in the arterial wall |
\( K_{h}^{\text{m}} \) (days−1) | CMM: Observed | Half-life of SMC |
\( K_{h}^{\text{c}} \) (days−1) | CMM: Observed | Half-life of collagen |
NO0 (pg) | ABM: Observed | Baseline mass of NO |
NO τw | ABM: Observed | Rate parameter governing shear stress mediated rate of production of NO (pg of NO per kPa of stress) |
\( \delta^{\text{PDGF}} \) (pg) | ABM: Observed | Parameters of the sigmoid function: |
\( \alpha^{\text{PDGF}} \) | \( {\text{PDGF}} = M\left( {\delta + \alpha \left( {1 - e^{{ - kx^{n} }} } \right)} \right) \) | |
\( k^{\text{PDGF}} \) (kPa−1) | ||
\( n^{\text{PDGF}} \) | ||
\( M^{\text{PDGF}} \) | Maximum rate of PDGF production | |
\( \delta^{{{\text{ET{-}}}1}} \) (pg) | ABM: Observed | Parameters of the sigmoid function: |
\( \alpha^{{{\text{ET{-}}}1}} \) | \( {\text{ET}}1 = M\left( {\delta + \alpha \left( {1 - e^{{ - kx^{n} }} } \right)} \right) \) | |
\( k^{{{\text{ET{-}}}1}} \) (kPa−1) | ||
\( n^{{{\text{ET{-}}}1}} \) | ||
\( M^{{{\text{ET{-}}}1}} \) | Maximum rate of ET-1 production | |
\( \delta^{{{\text{MMP{-}}}2}} \) (pg) | ABM: Observed | Parameters of the sigmoid function: |
\( \alpha^{{{\text{MMP{-}}}2}} \) | \( {\text{MMP}}2 = A\left( {M\left( {\delta + \alpha \left( {1 - e^{{ - kx^{n} }} } \right)} \right)} \right) \) | |
\( k^{{{\text{MMP{-}}}2}} \) (kPa−1) | ||
\( n^{{{\text{MMP{-}}}2}} \) | ||
\( M^{{{\text{MMP{-}}}2}} \) | Maximum rate of MMP-2 production | |
\( A^{{{\text{MMP{-}}}2}} \) (%) | Percent of MMP-2 Active | |
\( D^{{{\text{MMP{-}}}2}} \) | ABM: Observed | Degradation rate of MMP-2 |
\( \delta^{{{\text{MMP{-}}}9}} \) (pg) | ABM: Observed | Parameters of the sigmoid function: |
\( \delta^{\text{MMP{-}9}} \) | \( {\text{MMP}}9 = A\left( {M\left( {\delta + \alpha \left( {1 - e^{{ - kx^{n} }} } \right)} \right)} \right) \) | |
\( k^{{{\text{MMP{-}}}2}} \) (kPa−1) | ||
\( n^{{{\text{MMP{-}}}9}} \) | ||
\( M^{{{\text{MMP{-}}}9}} \) | Maximum rate of MMP-9 production | |
\( A^{{{\text{MMP{-}}}9}} \) (%) | Percent of MMP-9 active | |
\( D^{{{\text{MMP{-}}}9}} \) | ABM: Observed | Degradation rate of MMP-9 |
\( D^{{{\text{MMP{-}}}1}} \) | ABM: Observed | Degradation rate of MMP-1 |
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Hayenga, H.N., Thorne, B.C., Peirce, S.M. et al. Ensuring Congruency in Multiscale Modeling: Towards Linking Agent Based and Continuum Biomechanical Models of Arterial Adaptation. Ann Biomed Eng 39, 2669–2682 (2011). https://doi.org/10.1007/s10439-011-0363-9
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DOI: https://doi.org/10.1007/s10439-011-0363-9