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J Biomech Eng. Author manuscript; available in PMC 2010 October 1.

Published in final edited form as:

PMCID: PMC2771558

NIHMSID: NIHMS134747

Department of Biomedical Engineering, Texas A&M University, College Station, USA

The publisher's final edited version of this article is available at J Biomech Eng

See other articles in PMC that cite the published article.

Computational models of arterial growth and remodeling promise to increase our understanding of basic biological processes such as development, tissue maintenance, and aging, the biomechanics of functional adaptation, the progression and treatment of disease, responses to injuries, and even the design of improved replacement vessels and implanted medical devices. Ensuring reliability of and confidence in such models requires appropriate attention to verification and validation, including parameter sensitivity studies. In this paper, we classify different types of parameters within a constrained mixture model of arterial growth and remodeling; we then evaluate the sensitivity of model predictions to parameter values that are not known directly from experiments for cases of modest sustained alterations in blood flow and pressure as well as increased axial extension. Particular attention is directed toward complementary roles of smooth muscle vasoactivity and matrix turnover, with an emphasis on mechanosensitive changes in the rates of turnover of intramural fibrillar collagen and smooth muscle in maturity. It is shown that vasoactive changes influence the rapid change in caliber that is needed to maintain wall shear stress near its homeostatic level and the longer term changes in wall thickness that are needed to maintain circumferential wall stress near its homeostatic target. Moreover, it is shown that competing effects of intramural and wall shear stress regulated rates of turnover can develop complex coupled responses. Finally, results demonstrate that the sensitivity to parameter values depends upon the type of perturbation from normalcy, with changes in axial stretch being most sensitive consistent with empirical reports.

Ubiquitous mechanosensitive growth and remodeling (G&R) processes are fundamental to many aspects of vascular biology and pathobiology as well as diverse arterial responses to injury and clinical intervention. Because of the complexity of such processes at molecular, cellular, and tissue levels, there is a pressing need for integrative multiscale computational models having both descriptive and predictive capability. Toward this end, there is first a need for reliable models at each of the individual scales. We have proposed a constrained mixture model for tissue-level G&R of arteries that accounts for individual material properties, natural configurations, and rates and extents of turnover of different structurally significant constituents that constitute the wall. This basic framework and illustrative constitutive relations have represented well the salient features of both normal arterial adaptations to altered pressure and flow [1] and different types of disease progression [2–5]. Moreover, by numerically testing multiple null hypotheses [6], we have shown the reasonableness of many of the fundamental hypotheses upon which the constrained mixture model is based. The goal of this paper, therefore, is to extend our previous investigations by classifying the types of material parameters that exist in constrained mixture models of arterial G&R and then assesing the sensitivity of model predictions to realistic ranges of these material parameters, particularly those that are not well known or easily determined from experiments.

Parameter sensitivity studies based on numerical simulations can play fundamental roles within the overall verification and validation process in modeling [7]. By allowing values of parameters to approach particular limits, one can generate and test basic hypotheses in a cost- and time-efficient manner; by comparing predictions over reasonable ranges of parameter values, one can estimate the resolution needed in an experimental measurement or restrict the search space for a best-fit regression based on data; and by comparing predictions based on different sets of parameter values, one can elucidate possible complex mechanisms of coupling and thereby provide important guidance for the design and interpretation of an experiment. Indeed, given the advances in computational methods, numerical simulation has become an important addition to the traditional method of scientific inquiry based solely on theory and experiment (figure 1). In this paper, we confirm via numerical simulation that effective cell and matrix turnover require mechano-control in arterial G&R. We also confirm that vasoactivity and matrix remodeling represent complex, complementary, coupled mechanisms of arterial adaptation to altered flows, pressures, and axial extension, including those characterized by competing effects due to wall shear and intramural stress mediated turnover. Finally, sensitivity of model predictions to parameter values in particular classes of G&R suggest that vascular cells are more sensitive to perturbations in axial loading than to those in flow or pressure. Overall, the present parameter sensitivity study of a constrained mixture model of the growth and remodeling of a basilar artery suggests that current constitutive relations provide reasonable descriptions of the behavior even though there is strong motivation to identify better, more comprehensive constitutive relations for cell and matrix turnover as a function of altered mechanical stimuli.

The mean Cauchy stress response for an artery, accounting for a constrained mixture of structurally significant passive constituents and active smooth muscle, was approximated using a rule of mixtures as

$$\mathit{\sigma}=\frac{1}{det\mathbf{F}}\mathbf{F}\frac{\partial W}{\partial {\mathbf{F}}^{T}}+{\sigma}^{\mathit{act}}([{\text{Ca}}^{2+}],{\lambda}^{m(\mathit{act})}){\mathbf{e}}_{m}\otimes {\mathbf{e}}_{m},$$

(1)

where **F** is the 2-D deformation gradient tensor, *W* = Σ* _{k}W^{k}* is the strain energy function for the mixture, with

$$\begin{array}{l}{W}^{k}(s)=\frac{{M}^{k}(0)}{\rho (s)}{Q}^{k}(s){\widehat{W}}^{k}\left({\mathbf{F}}_{n(0)}^{k}(s)\right)\\ +\underset{0}{\overset{s}{\int}}\frac{{m}^{k}(\tau )}{\rho (s)}{q}^{k}(s,\tau ){\widehat{W}}^{k}\left({\mathbf{F}}_{n(\tau )}^{k}(s)\right)\phantom{\rule{0.16667em}{0ex}}d\tau ,\end{array}$$

(2)

where *M ^{k}*(0) is the apparent mass density of constituent

Previous implementations of constrained mixture models for arterial G&R involved several classes of parameters for the requisite geometry, constitutive relations, and applied loads [cf. 1, 3]. The chosen functional forms and parameter values were motivated both by reported observations and hypothesized behaviors; they were merely required to yield biologically and physically realistic predictions. Herein, however, we classify these constitutive relations and parameters by level of consensus and function (see tables 1 and and2)2) and study parametrically those for which only bounds are known. Quantities such as arterial geometry, volumetric flowrates, and local blood pressures are easily measured *in vivo* [cf. 8] and thus are well-known. Bulk mechanical behaviors are also easily quantified *in vitro* [9] and similarly for constituent mass fractions, given appropriate histological preparations [10, 11]. In contrast, values for quantities such as the stretch at which constituents are incorporated within extant matrix, values of shear stress-regulated vasoactive molecule production, and the changing rates of of cell and matrix turnover as a function of changes in mechanical stimuli are less well known and thus amenable to parametric study.

Classification of specific functional forms of constitutive relations employed in a constrained mixture model of the basilar artery. ‘Well Accepted’ relations represent those for which experimental data have established some level of consensus; **...**

Classification of the requisite material parameters and their values for a representative mature basilar artery under homeostatic conditions. ‘Observed’ parameters include those reported in literature; these are readily obtained via direct **...**

Consistent with prior studies [1, 3], we used a neo-Hookean strain energy function for elastin [12, 13]

$${\widehat{W}}^{e}(s)=c\phantom{\rule{0.16667em}{0ex}}\left({\lambda}_{\theta}^{e}{(s)}^{2}+{\lambda}_{z}^{e}{(s)}^{2}+\frac{1}{{\lambda}_{\theta}^{e}{(s)}^{2}{\lambda}_{z}^{e}{(s)}^{2}}-3\right),$$

(3)

where
${\lambda}_{\theta}^{e}(s)={\stackrel{\sim}{G}}_{h}^{e}{\lambda}_{\theta}(s)$ and
${\lambda}_{z}^{e}(s)={\stackrel{\sim}{G}}_{h}^{e}{\lambda}_{z}(s)$ are constituent-specific stretches, which can be determined from arterial stretches (*λ _{θ}*,(

$${\widehat{W}}^{c}(s)={c}_{1}^{c}\left({e}^{{c}_{2}^{c}{({\lambda}_{n(\tau )}^{c}{(s)}^{2}-1)}^{2}}-1\right),$$

(4)

and passive smooth muscle [16]

$${\widehat{W}}^{m}(s)={c}_{1}^{m}\left({e}^{{c}_{2}^{m}{({\lambda}_{n(\tau )}^{m}{(s)}^{2}-1)}^{2}}-1\right).$$

(5)

The stretch
${\lambda}_{n(\tau )}^{k}(s)$ experienced by each of these constituents depends on its deposition stretch, original orientation, and the stretch experienced by the arterial wall; as in Valentín et al. [1], we assumed four families of collagen (axial, circumferential, and symmetric diagonal). In the G&R formalism, values for the parameters
${c}_{2}^{c}$ and
${c}_{2}^{m}$ (table 2) were specified such that the artery exhibits reasonable passive behavior while the remaining parameters *c*,
${c}_{1}^{c}$, and
${c}_{1}^{m}$ were computed rather than prescribed so as not to overprescribe the basal behavior given the prescription of both “deposition stretches” and “homeostatic target stresses,” which are discussed below.

Vasoactive function is a fundamental determinant of arterial mechanical behavior and thus G&R. Among others, Price et al. [17] reported constrictor dose-response curves exhibiting sigmoidal behavior and active force-length curves exhibiting inversely parabolic behavior [cf. 18]. The combined effect of these two observations was expressed as

$$\begin{array}{l}{\sigma}_{\theta}^{\mathit{act}}(s)={T}_{\mathit{max}}\phantom{\rule{0.16667em}{0ex}}{\phi}^{m}(s)\phantom{\rule{0.16667em}{0ex}}\left(1-{e}^{-C{(s)}^{2}}\right)\\ \times {\lambda}_{\theta}^{m(\mathit{act})}(s)\phantom{\rule{0.16667em}{0ex}}\left[1-{\left(\frac{{\lambda}_{M}-{\lambda}_{\theta}^{m(\mathit{act})}(s)}{{\lambda}_{M}-{\lambda}_{0}}\right)}^{2}\right],\end{array}$$

(6)

where *T _{max}* is a scaling factor with units kPa,

$$C(s)={C}_{B}-{C}_{S}\left(\frac{{\tau}_{w}(s)-{\tau}_{w}^{h}}{{\tau}_{w}^{h}}\right),$$

(7)

where *τ _{w}*(

Note that equation (7) was motivated by interpretations by Rodbard [19] and Zamir [20] of Murray’s observation [21] of an optimal (target) condition: arteries constrict or dilate to maintain a target wall shear stress. For fully developed laminar flow of a Newtonian fluid through a rigid cylindrical tube, mean wall shear stress can be approximated as *τ _{w}* = 4

It is well known that arteries can functionally adapt to changing physiological demands or hemodynamic loads, in part, by changing rates of constituent turnover [22]. Mass density production rates of collagen and smooth muscle are known to vary with changing mechanical stimuli [23–26]. Altered flow [27–29], pressure [30–33], axial extension [34, 35], and responses to clinical interventions such as balloon angioplasty [36–42] can each induce substantial changes from basal rates of turnover. For example, coarctation-induced hypertension has been observed to elicit a 15-fold increase in smooth muscle production [30] and an ~3 fold increase in collagen production [33]. Matrix metalloproteinase (MMP) levels increased by 4–5 fold in cases of hypoxia-induced hypertension [43]. Such changes are complicated by the multifunctional effects of other molecules such as nitric oxide (NO) and endothelin-1 (ET-1), which vary with imposed wall shear stress and affect cell and matrix turnover rates [28, 44–49].

For illustrative purposes, we let the production rate of constituent *k* be a linear function of the two primary mechanical stimuli, intramural and wall shear stresses [cf. 50, 51], namely

$${m}^{k}(s)={m}_{0}^{k}(1+{K}_{\sigma}^{k}\mathrm{\Delta}{\sigma}^{k}-{K}_{{\tau}_{w}}^{k}\mathrm{\Delta}{\tau}_{w}),$$

(8)

where Δ*σ ^{k}* is the difference between the current

Despite the complex kinetics of smooth muscle and matrix turnover, half-lives for these structurally significant constituents appear to be well described by first order type kinetics [53–57]. We thus prescribed survival functions

$${q}^{k}(s,\tau )={e}^{-\underset{\tau}{\overset{s}{\int}}{K}^{k}(\stackrel{\sim}{\tau})d\stackrel{\sim}{\tau}},$$

(9)

where *K ^{k}*() are rate-type parameters for mass removal having units of days

$${K}^{k}(\stackrel{\sim}{\tau})=\{\begin{array}{ll}{K}_{h}^{k}\hfill & \mathrm{\Delta}\zeta (\stackrel{\sim}{\tau})\le 0\hfill \\ {K}_{h}^{k}+{K}_{h}^{k}\mathrm{\Delta}\zeta (\stackrel{\sim}{\tau})\hfill & \mathrm{\Delta}\zeta (\stackrel{\sim}{\tau})>0\hfill \end{array},$$

(10)

with higher tensions accelerating removal via MMP activity [35, 58–60].
${K}_{h}^{k}$ are basal arterial constituent rate-type parameters with values of approximately 1/80 day^{−1} [22, 61]. Finally, Δ*ζ*() is the difference between the current and homeostatic tensions for a fiber deposited at time *τ*[1]. Note that Δ*ζ*= 0 in normalcy and that
${K}^{k}(\stackrel{\sim}{\tau})={K}_{h}^{k}$ recovers a simple first order decay. Moreover, elastin is stable biologically under normal conditions in maturity, during which *Q ^{e}*(

The hypothesis that newly produced constituents are incorporated within extant matrix at preferred mechanical states is fundamental to the basic constrained mixture model [63]. The stretch at G&R time *s* experienced by a fibrous constituent deposited at time *τ* is [2]

$${\lambda}_{n(\tau )}^{k}(s)={G}_{h}^{k}\frac{\lambda (s)}{\lambda (\tau )},$$

(11)

where
${G}_{h}^{k}$ is the homeostatic deposition stretch for the *k ^{th}* constituent and

It thus appears that cells can and do incorporate new constituents within extant matrix at a preferred stress or stretch. Although we do not know the precise values of these deposition stretches, they must be less than maximum values of stretch in normal tissues. Clearly, this requires deposition stretches greater than 1 and typically less than 2. Functional elastin is deposited almost exclusively during development. As such, it is likely to experience a relatively high prestretch (
${\stackrel{\sim}{G}}_{h}^{e}\in (1.4,1.8)$) in most arteries. Stiff collagen constantly turns over and is assumed to have a relatively low deposition stretch (
${G}_{h}^{c}\in (1.05,1.1)$) consistent with observations from purely collagenous tissues such as tendons and intracranial saccular aneurysms [68]. Smooth muscle is less stiff, and is likely deposited as some intermediate stretch (
${G}_{h}^{m}\in (1.2,1.7)$), which would place it within its normal vasoactive range at basal tone. It is important to note that these are not experimentally derived quantities. Rather, these are estimates that fall within reasonable bounds and yield expected behavior, as, for example, results consistent with the good agreement on mean homeostatic intramural biaxial stresses *σ ^{h}* of approximately 100 kPa [11, 69].

Figure 2 shows the simulated vasoactive stress response as a function of muscle fiber stretch
${\lambda}_{\theta}^{m(\mathit{act})}(0)$ for a range of basal constrictor to dilator ratios *C _{B}* (cf. equation (6)). The homeostatic inner radius

Active stress-stretch muscle responses for indicated basal values of constrictor to dilator ratio *C*_{B} at time *σ* = 0 (cf. equations (6) and (7)). All other parameters are as listed in table 2. Each curve represents a functionally different artery. **...**

The shear stress scaling parameter *C _{S}* (cf. equation (7)) plays a similarly important role in vasoactivity. Figure 4 shows effects of changing the constrictor to dilator ratio

In addition to instantaneous passive and active behavior, the constrained mixture G&R framework relates mechanical stimuli to constituent mass density production rates. For example, an increase in blood pressure at a constant flow results initially in passive dilation due to wall distensibility. This dilation, along with isochoric thinning, elevates stresses in circumferentially aligned constituents while decreasing *τ _{w}*, which in turn leads to increases in

Figure 5 illustrates relationships between changing mechanical and mechanically induced stimuli (Δ*σ* and Δ*C*) and the mass density production rate of circumferential collagen for a sustained 30% decrease in flow. Recalling equation (8), consider cases in which
${K}_{\sigma}^{k}=1$ and
${K}_{{\tau}_{w}}^{k}=0$ (panels a and b),
${K}_{\sigma}^{k}=0$ and
${K}_{{\tau}_{w}}^{k}=1$ (panels c and d), and
${K}_{\sigma}^{k}={K}_{{\tau}_{w}}^{k}=1$ (panels e and f). As prescribed, setting
${K}_{\sigma}^{k}=1$ and
${K}_{{\tau}_{w}}^{k}=0$ yields a direct relationship between Δ*σ* and *m ^{k}* (figure 5, panel a). Similarly, setting
${K}_{\sigma}^{k}=0$ and
${K}_{{\tau}_{w}}^{k}=1$ yields a direct relationship between Δ

Comparison of intramural and wall shear stress regulation of circumferential collagen production rates. Values given as functions of changes in the scalar measure of stress borne by circumferential collagen (panels a, c, and e) and changes in constrictor **...**

Changing axial length elicits similar competing effects. Figure 6 illustrates relationships between changing Δ*σ* and Δ*C* and the mass density production rate of axially aligned collagen for a 2% increase in *in vivo* axial length at a constant pressure and flow. This increase in axial length reduces slightly the inner radius and the wall thickness, due to an initial isochoric response. As the inner radius decreases, *τ _{w}* increases and causes the vessel to dilate, thus restoring

Time courses of evolving radius, thickness, unloaded inner radius, and unloaded axial length depend greatly on mechanical stimuli and the associated mass density production parameters [1]. To appreciate better the complex coupled roles of changing wall shear stress and intramural constituent stresses, we analyzed the observable evolving geometric quantities as functions of the kinetic parameters ${K}_{\sigma}^{k}$ and ${K}_{{\tau}_{w}}^{k}$ for cases of increased transmural pressure, decreased luminal flow, and increased axial length. These parameter sensitivity studies over multiple orders of magnitude (from 0.1 to 10) provide important insight and intuition regarding the differing modes of interaction among similarly involved mechanisms.

Figure 7 illustrates time varying consequences of a sustained 50% increase in pressure, at a constant flow and length, as functions of
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$. *In vivo* geometries generally approached their targets more rapidly with larger values of both
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$, but important differences surfaced. Note that the “singular” behavior at
${K}_{\sigma}^{k}={K}_{{\tau}_{w}}^{k}=0$, which models constant mass density production, is not biologically relevant [6]. Inner radius (figure 7, panel a) shifts toward its target rapidly and is least sensitive to
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$. This finding suggests that inner radius is mostly regulated by an early vasoactive behavior as expected. In contrast,
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$ exert a greater influence on the evolution of wall thickness (figure 7, panel b); larger values of
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$ accelerate evolution. In the limiting case of
${K}_{\sigma}^{k}={K}_{{\tau}_{w}}^{k}=0$, mass density production rates are constant while mass removal remains a function of fiber tension (see equation (9)). After 100 days, the artery atrophies appreciably as degradation outpaces production, resulting in a dilation of 3% and a reduction in thickness of ~40%. Such a loss of stiff collagen and muscle requires a higher level of muscle activation to maintain inner radius constant, which would seem to be energetically unfavorable. Figure 7 (panel c) shows that after 100 days, the artery’s unloaded inner radius (without vasoactivity) increases when
${K}_{\sigma}^{k}={K}_{{\tau}_{w}}^{k}=0$. For
${K}_{\sigma}^{k}>0$ or
${K}_{{\tau}_{w}}^{k}>0$, unloaded inner radius remains nearly constant as it should in response to constant flow.

Percent changes in inner radius (panel a), thickness (panel b), unloaded inner radius (panel c), and unloaded length (panel d) for a sustained 50% increase in pressure; results shown at days 1, 7, 14, and 100 of G&R with the arrows denoting advancing **...**

Evolution of the unloaded axial length is more complex (figure 7, panel d). For the limiting case of
${K}_{\sigma}^{k}={K}_{{\tau}_{w}}^{k}=0$, the unloaded axial length decreases (which implies a larger *in vivo* axial stretch), as decreased axial and helical collagen allow highly prestretched (unchanging) elastin to recoil the artery further. Focus, however, on values of
${K}_{\sigma}^{k}>0$ and
${K}_{{\tau}_{w}}^{k}>0$ and recall that each fiber family’s mass production rate was defined individually as a function of its unique scalar measure of stress but a common *τ _{w}* (equation (8)). Moreover, note that helically and axially oriented collagen fiber families greatly influence the unloaded axial length. As pressure increases,

Evolving inner radius in response to a 30% reduction in luminal flow (figure 8, panel a) is nearly insensitive to changing
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$. Similarly, evolution of the unloaded inner radius (figure 8, panel c) is remarkably insensitive to these kinetic parameters. The unloaded inner radius follows *in vivo* inner radius as the artery remodels around its new vasoconstricted state. Evolving thickness (figure 8, panel b) is a function of isochoric motion and mass kinetics, with the initial vasoconstriction resulting in an ~10% isochoric increase in wall thickness. Note that in the limiting case when
${K}_{\sigma}^{k}={K}_{{\tau}_{w}}^{k}=0$, wall thickness does not change because mass production rates remain constant. Setting
${K}_{\sigma}^{k}>0$ or
${K}_{{\tau}_{w}}^{k}>0$ results in gradual thinning in response to reduced intramural constituent stresses, with diminishing rates of evolution beyond
${K}_{\sigma}^{k}>2$ or
${K}_{{\tau}_{w}}^{k}>2$. Long-term evolution of wall thickness is largely insensitive to
${K}_{{\tau}_{w}}^{k}$ because the initial vasoconstriction nearly restores *τ _{w}* to
${\tau}_{w}^{h}$. Also, a decrease in intramural constituent stress results in reduced mass density production below
${m}_{0}^{k}$, with a minimum production rate of zero. Any Δ

Percent changes in inner radius (panel a), thickness (panel b), unloaded inner radius (panel c), and unloaded length (panel d) for a sustained 30% decrease in flow; results shown at days 1, 30, 100, and 1000 of G&R with the arrows denoting advancing **...**

Increased axial stretching, at constant pressure and flow, results in a decreased inner radius and decreased thickness due to an initial isochoric motion. Yet, a 2% increase in axial length (figure 9) causes negligible changes in inner radius (panel a), and thus unloaded inner radius (panel c), as the artery vasodilates to restore
${\tau}_{w}^{h}$. For low values of
${K}_{\sigma}^{k}$ and
${K}_{{\tau}_{w}}^{k}$, the unloaded inner radius decreases more appreciably as the wall atrophies. Evolution of wall thickness (figure 9, panel b) clearly reveals a competition between the effects of shear- and stress-mediated mass production: because luminal flow is constant, the reduced inner radius elevates *τ _{w}*, which works to diminish mass production, while a decreased wall thickness increases intramural constituent stresses, which heightens mass production. For these reasons, the wall thickens the most when
${K}_{\sigma}^{k}=1$ and
${K}_{{\tau}_{w}}^{k}=0$ at any given G&R time

Truesdell and Noll [70] articulated well the complementary roles of theory and experiment:

The task of the theorist is to bring order into the chaos of the phenomena of nature, to invent a language by which a class of these phenomena can be described efficiently and simply. Here is the place for “intuition,” and here the old preconception, common among natural philosophers, that nature is simple and elegant, has led to many great successes. Of course, physical theory must be based on experience, but experiment comes after, not before, theory. Without theoretical concepts one would neither know what experiments to perform nor be able to interpret their outcome.

As theories and experiments have become more detailed and complex, numerical simulations have emerged as a third pillar of scientific research. Numerical simulations allow researchers to generate, test, and refine hypotheses and theoretical concepts with much greater efficiency in terms of both time and expense. This refinement, in turn, permits the design of more rational and fruitful experiments, as called for (albeit differently) by Truesdell and Noll. The emergence of the need for multiscale models to integrate mechanobiological information and increase understanding from the genome to medical or surgical treatment at tissue and organ levels only highlights further the need for iterative observational, theoretical, experimental, and computational studies. Of these, our focus herein was limited to the role of parameter sensitivity studies within numerical simulation.

Predicted vasoactive behaviors were consistent with observed trends [17] based on the prescribed material behavior of equation (6) and associated parameters listed in table 2. In particular, active behavior was sensitive to both the initial level of the constrictor to dilator ratio *C _{B}* and the shear stress scaling factor

Vasoactive behavior influences long term G&R by controlling the state in which turnover occurs, thereby affecting changes in wall thickness and unloaded length, which in turn affect intramural stresses [cf. 74, 75]. The competing effects of intramural stress- and wall shear stress-regulated turnover resulted in complex G&R based on our model. This was most evident in cases of decreased flow or increased axial length; decreased (increased) wall shear stress and decreased (increased) intramural stresses provide opposite inputs to mass production. Even for the case of increased transmural pressure, where all mechanical stimuli tend to accelerate turnover, there was a competition between ${K}_{\sigma}^{k}$ and ${K}_{{\tau}_{w}}^{k}$ in the evolution of unloaded axial length. This finding further emphasizes the complex interactions possible even with linear production rates.

Simulations revealed that progression of G&R for some perturbations involved the dominance of one mechanical stimulus during one phase but the emergence of another dominant stimulus during a subsequent phase. For example, reductions in flow and increases in axial extension elicit such responses. Increased MMP activity can precede mass production [37], thus resulting in initial atrophy followed by eventual compensatory hypertrophy and maintenance. These predicted time courses suggest provocative possibilities for designing intervention, as, for example, timed drug delivery. Similarly, such time courses could aid in the decision process when choosing time intervals at which to collect samples and/or use appropriate immunohistological stains or other markers, for example. Finally, predictive models promise to aid in the refinement of tissue engineering strategies to build in desirable properties via appropriately timed stimuli.

The model predicted differing modes of G&R and degrees of sensitivity to parameter values depending upon the type of perturbation, despite the similarly involved mechanisms. Most notably, the model was most sensitive to increases in axial stretch beyond the homeostatic. This extreme sensitivity is similar to the observations reported by Jackson et al. [35], wherein they noted “unprecedented” rates of change *in vivo* when arterial length was increased. Our numerical implementation predicted upper and lower bounds (saturation points) in shear-induced active stress generation and values for
${K}_{i}^{k}$ beyond which the system was no longer sensitive to a particular stimulus. For example, the model predicted little sensitivity beyond
${K}_{\sigma}^{k}=2$ with respect to evolving thickness for cases of reduced flow for this drove mass density productions to zero.

Predicted geometric consequences of G&R, like evolving passive and active behaviors, can be compared to experimentally observed behaviors. Such comparisons will assist in formulating improved constitutive relations and determining best-fit values of the associated parameters. Nevertheless, mixture models require mechanical response parameters for each individual constituent, which increases the overall number of parameters and thereby raises concerns by some that there are too many parameters. We suggest, however, that one advantage of structurally motivated models is that many of the parameter values can be prescribed independently and in many cases prescribed directly, based on experimental data. In this way, one reduces the need to perform nonlinear regressions based on large numbers of unknown parameters, which would otherwise raise issues of non-uniqueness. Moreover, once good estimates are determined for the parameters, one can perform nonlinear regressions based on restricted (physically meaningful) parameter search spaces. We did not study the sensitivity of the constrained mixture model to ranges of observed parameters or certain bounded parameters because they are experimentally available. Indeed, noting that functional forms appear to be preserved across species, whereas parameter values vary with species and to some degree individuals, Stålhand and Klarbring [76] and Masson et al. [77] showed that parameter values can be estimated in individual patients in part because of known bounds on many of the parameters and prior experience in modeling [68]. There is, however, a need for better experimental data where possible to refine further the values of many of the parameters.

Constituent turnover (production and removal) as a function of mechanical stimuli remains the least well-understood aspect of arterial growth and remodeling. That is, there remains a pressing need for a better understanding of cellular responses to mechanical stimuli and how these responses manifest at the tissue and organ levels. To that end, we hope that continuum based constrained mixture models will motivate experimentalists and theorists alike to elucidate these intricately linked behaviors. Although we anticipate the need for a more rigorous analysis, hypothesis testing [6] and parameter sensitivity studies represent an important first step toward verification [7]. While no framework or numerical model can ever be strictly correct, the ultimate measure of a model’s utility is to what extent it can describe and predict what is physically reasonable. Rational theories founded upon realistic fundamental cellular behavior and continuum mechanics promise to help us develop intuition, understand complex biomechanical systems, and design better experiments and ultimately clinical interventions.

This work was supported, in part, NIH grants (HL-64372, 80415, 86418, and EB-08366).

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