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4.2 Phenomenological Constitutive Models 185
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of energy form may also make it difcult to investigate the material stability of the model, such as polyconvexit y or rank-one convexity. On the other hand, the model has been found to be stable in nite element simulations (Liu, Zhao, et al., 2011) where the arteries deform within the typical in vivo range. In summary, due to the need for fewer independent parameters, greater ease of interpretation, the stability of the model in nite element situations, and that this model has been embedded in certain simulation tools, the generalized Hookes model may be a simpler alternative to existing models of coronary arteries.
4.2.7 Linear Viscoelasticity and Maxwells Model
4.2.7.1 Artery
It is well known that the mechanical properties of blood vessels exhibit viscoelastic properties such as creep (time-dependent increase in length while the force is constant), relaxation (time-dependent decrease in force while the length is constant), and hysteresis (differences in the loading and unloading curves) (Fung, 1993). The viscoelastic mechanical behavior is relatively insensitive to strain rate within several decades of time (Fung, 1993). The classical linear viscoelastic models (i.e., Max­well, Voigt, or Kelvin, see de nitions below) have a single characteristic frequency (Fung, 1993), and hence are unable to account for the rate-insensitive feature of biological tissues. Moreover, stress–strain relationships of soft tissues are usually highly nonlinear and strongly anisotropic (Fung, 1993). To this end, the quasi-linear viscoelastic theory developed by Fung (1993) has been extensively used to describe biological constitutive behaviors.
In the quasi-linear viscoelastic formulation, the dependence of stress on time (loading history) and strain (total deformation) is separated, and the stre ss relaxation response (dependence on time) is linear (Fung, 1993). The stress–strain relationship, however, remains nonlinear. Since the stress–strain relationship of coronary arteries in the full range of elasticity can be linearized by dening a new strain measure to absorb the nonlinearity, the stress in quasi-linear viscoelastic materials can be linearly dependent on both time and strain. In this regard, a linear viscoelastic model that is insensitive to the loading frequency can sufciently capture the constitutive behavior of biological soft tissues.
There are three kinds of classical linear viscoelastic models: (1) Maxwell model which is composed of a linear spring and a linear viscous dashpot connected in series; (2) Voigt model is formed by a line ar spring and a linear dashpot in parallel; and (3) Kelvin model (standard linear solid) consists of a linear spring in parallel with a Maxwell body (Fung, 1993). A common feature of these models is that they have a single relaxation time (or characteristic frequency) and their hysteresis loops notably depend on loading rate. To capture the rate-insensitive hysteresis behavior of soft tissues, continuous spectrum relaxation functions must be considered (Fung, 1993).
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In principle, many of the classic linear viscoelastic models with various charac­teristic frequencies can be used to approximate the continuous spectrum functions of blood vessels. The parameter determination, howe ver, can be problematic because of the increased number of material constants. On the other hand, a continuous spec­trum function may need fewer parameters albeit it is usually hard to obtain closed­form solutions. Zhang, Chen, and Kassab (2007) considered a generalized Maxwell model with a nite number of characteristic frequencies that form a geometric series and cover multiple time scales (Appendix Coronary Arteries (Zhang, Chen, et al.,
2007)). As a result, the rate-insensitive feature of biological tissues can be captured
with signicantly reduced number of model parameters as outlined below.
4.2.8 Opening Angle
The generalized Maxwell model can also be used to describe the viscoelasticity of the opening angle as described in Sect. 3.4 where Rehal, Guo, Lu, and Kassab (2006) showed that the opening angle decreases with time if the artery is cut from the loaded state, while it increases if the cut is made from the no-load state due to viscoelasticity (Fig. 3.13). In both cases, the opening angle approaches the same value in 3 h which implies that the characteristic relaxation time is about 10,000 s. The creep function of a generalized Maxwell model (a spring in series with six Voigt bodies) is used to predict the temporal change of opening angle in multiple time scales (Appendix Opening Angle Zhang, Guo, & Kassab, 2008). It is demonstrated that the gener­alized Maxwell model captures the salient features of the experimental results (Zhang et al., 2008).
4.2.9 Active Properties
Although some multi-axial active models have been proposed, they have been of theoretical forms not rooted in experimental measurements (Stålhand, Klarbring, & Holzapfel, 2011; Zulliger, Rachev, & Stergiopulos, 2004). Huo, Cheng, Lu, Liu, and Kassab (2012) provided experimental data on the passive and active properties of both intact coronary artery wall and the intima-media layer. Figure 4.4a, b show the data for the circumferential stress as a function of the circumferential stretch ratios at axial stretches of 1.3 and 1.5, respectively. Figure 4.5a, b show the axial stress as a function of circumferential stretch ratios at the same axial stretches in Fig. 4.4a, b. The biomechanical formulation for the determination of active material properties of coronary arteries is outlined in Appendix 10. Table 4.21 (Appendix 10) summarizes the material constants of the passive energy function (from Eqs. (4.154a, 4.154b), Appendix 10) while Table 4.22 lists material constants of the K strain energy function (from Eq. (4.157), Appendix 10) for six RCAs. At axial stretch ratio of 1.3 and pressure of 80 mmHg, the mean circumferential stress and
+
-induced active
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(kPa)
θθ
T
λ
θ
(A)
(kPa)
θθ
T
Fig. 4.4 Circumferential rst PiolaKirchhoff stress (Tθθ) as a function of circumferential stretch
)atλzof (a) 1.3 and (b) 1.5 measured at K+-induced vasoconstriction and Ca2+-free-induced
ratio (λ
θ
vasodilation. Total Stress at vasoconstriction (square marker); Passive Stress at vasodilation
λ
(B)
θ
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strain (averaged through the wall) are 40.3 kPa and 0.80 in passive state and 35.9 kPa and 0.58 in active state, respectively. Given the decreased inner diameter and increased wall thickness, the isobaric constriction signicantly decreased mean circumferential stress and strain.
Results from Huo et al. (2012) illustrate that as the transmural pressure increases in the physiological pressure range, the active stress–strain relationship resembles a Gaussian (normal) distribution, which has a maximal value when the passi ve and active pressures are in the range of 80–100 mmHg and 140–160 mmHg, respec­tively, as shown in Figs. 4.4 and 4.5. This relationship is consistent with the sliding actin–myosin molecules, where the number of active cross-bridges is proportional to the active stress (Fung, 1993; Mulvany & Warshaw, 1979). Although vascular smooth muscle cell (SMC) contraction shows an in vitro optimal point at the passive pressure of 80–100 mmHg and at the active pressure of 140–160 mmHg, the in vivo optimal point for SMC contraction in coronary arteries needs further study.
Huo, Zhao, Che ng, Lu, and Kassab (2013) extended the measurements and analysis to a two-layer model where the intima-media layer is mechanically tested under both passive and active conditions using a method similar to that described above. Figure 4.6a, b show the theoretical a nd experi mental data for the circumfer­ential stress as a function of circumferential stretch ratios at axial stretch ratio of 1.2 and 1.3, respectively. Similarly, Fig. 4.7a, b show the axial stress as a function of circumferential stretch ratio at axial stretch ratio of 1.2 and 1.3 in correspondence with Figs. 4.6a, b, respectively. Table 4.23 summarizes the passive material con­stants while Table 4.24 lists the material constants for six RCA intima-media layers. The radius, circumferential length, and opening angle are increased in the intima­media layer but decreased in adventitia layer in zero-stress state in comparison with those of an intact vessel wall. Furthermore, the active stress–stretch relationship (intima-media layer) shows less curvature and lower stress than that in the intact vessel. The implications of these ndings on circumferential stress and stretch will be examined in Chap. 8.
4.3 Microstructure-Based Constitutive Models
The idea of relating the macroscopic mechanical properties of arteries to the arterial microstructures, including elastin and collagen bers and cells, is rst demonstrated by Burton and Yamada (1951). Roach and Burton ( 1957) made a quantitative study by differential digestion of elastin or collagen and measured the mechanical proper­ties of the partially digested artery. Oka (1972) proposed a theoretical analysis of the arterial wall, culminating in several well-known papers (Azuma & Hasegawa, 1971;
Fig. 4.4 (continued) (triangle marker); and Active Stress (thin solid line with standard error bars of SE value). Thick dotted line (theoretical total stress), dashed line (theoretical passive stress), and solid line (theoretical active stress). Reproduced from Huo et al. (2012) with permission
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(kPa)
zz
T
λ
θ
(A)
(kPa)
zz
T
Fig. 4.5 Axial rst PiolaKirchhoff stress (Tzz) as a function of circumferential stretch ratio (λθ)at
of (a) 1.3 and (b) 1.5 measured at K+-induced vasoconstriction and Ca2+-free-induced vasodi-
λ
z
lation. Total Stress at vasoconstriction (square marker), Passive Stress at vasodilation (triangle
λ
(B)
θ
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Azuma & Oka, 1971; Oka & Azuma, 1970). Azuma and Hasegawa (1971) discussed the rheological properties of arteries and veins in terms of the networks of collagen, elastin, and smooth muscle cells. Their works showed that the mechanical properties of the vessels are intimately associated with microstructural components such as elastin and collagen bers, cells, and ground substance. Based on this idea, much effort has been made to derive the constitutive model of the soft tissue from the geometry, distribution, and the mechanical properties of the individual microstructures.
The determination of microstructural stress requires a constitutive model based on the ultrastructure and the corresponding material properties. Compl ex microstructure and strong nonlinear mechanical behaviors of soft tissue, however, present signi­cant challenges in const itutive modeling. Despite the complexity, the current trend in biomechanics is to move from phenomenological to microstructural models to predict the overall nonlinear and micromechanical responses of inhomogeneous soft tissues. New developments in imaging and biochemistry will continue to provide more details of the constitutive properties of soft tissues and continue to advance the development of structure-based models.
Based on standard approximations in nonlinear mechanics, the microstructural models can be classied into three categories: (1) Uniform-eld models with solid­like matrix (Holzapfel, Gasser, & Ogden, 2000), (2) Uniform-eld models with uid-like matrix (Hollander, Durban, Lu, Kassab, & Lanir, 2011b; Holzapfel et al.,
2000), and (3) Second-order estimate (SOE) models (Ponte Castañeda, 1996; Ponte
Castañeda & Willis, 1999). The rst two categories assume an afne deformation eld where the deformation of microstructure is the same as that of the tissue, regardless of material heterogeneities, i.e., uniform-eld (UF) model which repre­sents the upper bounds of the effective strain energy and stress of soft tissues. In addition, the rst type is structurally idealized and not necessarily consistent with ultrastructure and hence cannot accurately predict the microscopic mechanical behaviors of soft tissues. The third category considers realistic geometrical features, material properties of microstructure, and interactions among them and allows for exible deformation in each constituent. The UF model with uid-like matrix and the SOE model are microstructure-based and can be applied to different tissues based on microstructural features as described in Appendix 11 and below.
The two major classes of UF micromechanical models are described in Appendix
11. Briey, the rst class of UF models proposed by Lanir (1979, 1983) considers
the tissue as a composite of elastin and collagen bers embedded in a uid-like matrix. Thus, the bers are the only constituent phases that sustain non-hydrostatic loading such as tension and shear, while the contribution of the uid-like matrix is a hydrostatic pressure. The UF assumption leads to a simplication that all the microstructures deform identically to the macroscopic deformation of the tissue
Fig. 4.5 (continued) marker), and Active Stress (thin solid line with error bars of SE value). Thick dotted line (theoretical total stress), dashed line (theoretical passive stress), and solid lines (theo­retical active stress). Reproduced from Huo et al. (2012) with permission
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(kPa)
θθ
T
λ
θ
(A)
(kPa)
θθ
T
Fig. 4.6 Circumferential rst PiolaKirchhoff stress (Tθθ) as a function of circumferential stretch
)atλzof (a) 1.2 and (b) 1.3 measured at K+-induced contraction and Ca2+-free-induced
ratio (λ
θ
vasodilation for intima-media. Total Stress at contraction (square marker), Passive Stress at
λ
(B)
θ
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since no ber interactions are considered, such that the macroscopic SEF is the volumetric sum of the individual bersSEF. On the basis of this assumption and thermodynamic consideration, Lanir developed a general multi-axial theory for the constitutive relations in brous connective tissues Lanir (1979, 1983). Similarly, Decraemer, Maes, and Vanhuyse (1980) proposed a parallel wavy bers model for soft biological tissues in uniaxial tension, followed by Wuyts et al. (1995). More recent developments of uid-l ike matrix-based models can be referred to in Hum­phrey and Yin (1987), Dahl et al. (2008), and Lokshin and Lanir (2009a).
A second class of UF micromechanical models assume the tissue as a collagen ber-reinforced composite, whose matrix is a solid-like material that can take up loading. This assumption is motivated by the fact that the elastin, which is part of the matrix, becomes straightened and starts to take the load in the early deformation of the tissue. For example, the experimental study of Gundiah, Ratcliffe, and Pruitt (2007) suggested that the elastin is described with a neo-H ookean constitutive model. Based on this solid-like matrix assumption, Holzapfel and Weizsäcker (1998) and Holzapfel et al. (2000) modeled the arterial wall as a two-layer ber­reinforced composite where the macroscopic SEF of soft tissue stems from two sources: (1) An isotropic part associated with the mechanical response of the non-collagenous matrix material (elastin bers, cells, and ground substance), and (2) an anisotropic part due to the deformation of two classes of collagen bers symmetrically disposed with respect to the axis of the vessel. Successive develop­ments of this model can be found in Zulliger, Fridez, Hayashi, and Stergiopulos (2004), Kroon and Holzapfel (2008), and Li and Robertson (2009). Specically, Zulliger, Fridez, et al. (2004) made further renement to account for the distribution of the waviness of collagen bers and different SEF of the matrix and collagen bers. Mechanical predictions of these models are more accurate than those of phenome­nological models as they account for heterogeneity of material properties and geometrical features of vessel components. These models, however, cannot accu­rately predict microenvironments of the vessel, i.e., strain and stress of individual ber or cell since they all assume afne deformation in tissue, i.e., the deformati on of the collagen bers and the matrix are identical to the macroscopic deformation of the tissue, and the microstructure is not based on histological measurements in arteries (Chen, Liu, Zhao, Lanir, & Kassab, 2011).
UF models assume the deformation of all bers to be the same and do not account for the heterogeneity of the bers or ber–ber interactions. To account for the complexity of the microstructural components of the blood vessel, Chen, Liu, Zhao, et al. (
2011) developed a nite strain homogenization approach based on the second-
order estimate (SOE) theory (Appendix 11) to predict the macroscopic stress –strain relation and microstructural deformation of vascular tissue. This micromechanical model considers measured histological geometrical features and material properties
Fig. 4.6 (continued) vasodilation (triangle marker), and Active Stress (thin solid line with error bars of SE value). Thick dotted line (theoretical total stress), dashed line (theoretical passive stress), and solid line (theoretical active stress). Reproduced from Huo et al. (2013) with permission
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of vessel constituents and allows exible deformation in each component. A com­parison of the various model predictions of macro- and microscopic mechanical behavior of vascular tissue is presented below.
4.3.1 Comparison of Microstructural Models
Both the uniform-eld (UF) approaches (solid-like matrix and uid-like matrix) and tangent second-order (SOE) micromechanics model are applied to 2D material with distributed collagen bers, respectively, in comparison with nite element (FE) simulations (Chen, Liu, Zhao, et al., 2011). The planar tissue stretches along the principal direction of the bers but shrinks in the transverse direction to maintain material incompressibility. The material property of the matrix is directly taken from Holzapfel et al. (2000). To simplify the simulations, all the bers are assumed to be isotropically distributed in space and have the same under-formed cross-sectional geometry. The ber orientation is assumed to follow a beta distribution (Sacks,
2003), and the waviness is also assumed to be beta distributed but direction depen-
dent in line with tissue ultrastructure (Brown, 1973; Sverdlik & Lanir, 2002). The orientation distribution is discretized into 13 regions and the waviness is discretized into 5 regions, so that the collagen bers are categorized into 65 phases according to their orientation and waviness. The total volume fraction of collagen bers is taken as 20% and that of the matrix is 80%. The volume fraction of every ber phase is determined by the cumulative probabilities of the orientation and waviness. FE simulations are used for the purpose of model validation. The FE model contained ~200 randomly distributed bers whose orientation angle and waviness are ran­domly assigned according to a beta distribution.
The model predictions of the macroscopic SEF and the tensile Cauchy stress of brous tissue are plotted in Fig. 4.8a, b, in comparison with FE computational results. At low stretch level been straightened and deform the same as the matrix so that effective macroscopic SEF and Cauchy stress of tissue predicted by UF and SOE models are very similar and approximate to that of pure matrix material. When the macroscopic deformation λ is >1.6, predictions of the two models become different. The UF predictions of SEF and Cauchy stress increase rapidly with higher macroscopic stretch ratio while SOE results increase slowly and predicted Cauchy stress is consistent with FE simulation as shown in Fig. 4.8b. At this loading level, collagen bers become straighten completely to take up loads and deform less than the matrix. The UF model, however, overestimates the deformation eld of stiffer bers (assuming it is identical to that of matrix) and hence approaches upper bounds of the exact SEF and Cauchy stress. The SOE model statistically accounts for the heterogeneous defor­mation of the matrix and bers, which is due to the heterogeneities of microstructural geometries and material properties as well as matrix–ber and ber–ber interac­tions. Thus, the deformation eld employed by SOE is more realistic and leads to lower estimates of the macroscopic SEF and stress than the UF upper bounds.
λ < 1:6, most bers are still undulated or have just
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(kPa)
zz
T
λ
θ
(A)
(kPa)
zz
T
Fig. 4.7 Axial rst PiolaKirchhoff stress (Tzz) as a function of circumferential stretch ratio (λθ)at
of (a) 1.2 and (b) 1.3 measured at K+-induced contraction and Ca2+-free-induced vasodilation in
λ
z
the intima-media layer. Total Stress at contraction (square marker), Passive Stress at vasodilation
λ
(B)
θ