Biomechanical Properties of Human Ascending Thoracic Aortic Dissections

Babu, Anju R.; Byju, Achu G.; Gundiah, Namrata

doi:10.1115/1.4030752

Cited by 34 publications

(23 citation statements)

References 28 publications

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“…Tissue from the ascending aorta has been tested in a variety of configurations (reviewed by Avanzini et al [17]), with uniaxial and equibiaxial stretch tensile tests being the most common. In-plane uniaxial [18][19][20] and biaxial tension tests [21][22][23][24] provide information on tensile failure in the plane of the medial lamella ðr hh ; r zz Þ; and the biaxial tests can provide some additional information on in-plane shear ðr hz Þ. Although the dominant stresses in these tests may be the primary stresses during vessel rupture, they are not those driving dissection.…”

Section: Introductionmentioning

confidence: 99%

Failure of the Porcine Ascending Aorta: Multidirectional Experiments and a Unifying Microstructural Model

Witzenburg

Dhume

Shah

et al. 2017

Journal of Biomechanical Engineering

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The ascending thoracic aorta is poorly understood mechanically, especially its risk of dissection. To make better predictions of dissection risk, more information about the multidimensional failure behavior of the tissue is needed, and this information must be incorporated into an appropriate theoretical/computational model. Toward the creation of such a model, uniaxial, equibiaxial, peel, and shear lap tests were performed on healthy porcine ascending aorta samples. Uniaxial and equibiaxial tests showed anisotropy with greater stiffness and strength in the circumferential direction. Shear lap tests showed catastrophic failure at shear stresses (150-200 kPa) much lower than uniaxial tests (750-2500 kPa), consistent with the low peel tension ($60 mN/mm). A novel multiscale computational model, including both prefailure and failure mechanics of the aorta, was developed. The microstructural part of the model included contributions from a collagenreinforced elastin sheet and interlamellar connections representing fibrillin and smooth muscle. Components were represented as nonlinear fibers that failed at a critical stretch. Multiscale simulations of the different experiments were performed, and the model, appropriately specified, agreed well with all experimental data, representing a uniquely complete structure-based description of aorta mechanics. In addition, our experiments and model demonstrate the very low strength of the aorta in radial shear, suggesting an important possible mechanism for aortic dissection.

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Section: Introductionmentioning

confidence: 99%

Failure of the Porcine Ascending Aorta: Multidirectional Experiments and a Unifying Microstructural Model

Witzenburg

Dhume

Shah

et al. 2017

Journal of Biomechanical Engineering

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“…The algorithm was validated by ensuring that the parameters selected for the HGO constitutive model could fit the measured data from each protocol with a R 2 ≥0.8 and a mean error value of ϵ ≤ 0.25. This was in contrast with the approaches followed traditionally in literature (Zeinali-Davarani et al, 2013 ; Babu et al, 2015 ), where data collected from only equibiaxial protocol was considered or parameters were estimated from entire data set (Billiar and Sacks, 2000 ) without validating the constitutive model response to new data. This study proposed a rigorous algorithm for considering multiple combinations of material testing protocols.…”

Section: Discussionmentioning

confidence: 93%

“…The research and development of effective mechanical devices for endovascular grafting would require the use of computational techniques to analyze the structural interaction between the rigid stents (usually composed of Stainless steel or Nitinol alloy) and different tissue segments of the dissected aorta (i.e., Intimal flap, FL wall, and TL wall). Unfortunately, the “building elements” for computational model such as a suitable constitutive model that characterizes the mechanical behavior of a dissected aorta by providing a mathematical formulation for the stress–strain relation is currently lacking (Babu et al, 2015 ). Structural continuum constitutive models of the different layers of aorta integrate information about the tissue morphology and therefore assess the interrelation between the structure and response to mechanical loading.…”

Section: Introductionmentioning

confidence: 99%

Biomechanical Material Characterization of Stanford Type-B Dissected Porcine Aortas

et al. 2018

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Aortic dissection (AD) involves tearing of the medial layer, creating a blood-filled channel called false lumen (FL). To treat dissections, clinicians are using endovascular therapy using stent grafts to seal the FL. This procedure has been successful in reducing mortality but has failed in completely re-attaching the torn intimal layer. The use of computational analysis can predict the radial forces needed to devise stents that can treat ADs. To quantify the hyperelastic material behavior for therapy development, we harvested FL wall, true lumen (TL) wall, and intimal flap from the middle and distal part of five dissected aortas. Planar biaxial testing using multiple stretch protocols were conducted on tissue samples to quantify their deformation behavior. A novel non-linear regression model was used to fit data against Holzapfel–Gasser–Ogden hyperelastic strain energy function. The fitting analysis correlated the behavior of the FL and TL walls and the intimal flap to the stiffness observed during tensile loading. It was hypothesized that there is a variability in the stresses generated during loading among tissue specimens derived from different regions of the dissected aorta and hence, one should use region-specific material models when simulating type-B AD. From the data on material behavior analysis, the variability in the tissue specimens harvested from pigs was tabulated using stress and coefficient of variation (CV). The material response curves also compared the changes in compliance observed in the FL wall, TL wall, and intimal flap for middle and distal regions of the dissection. It was observed that for small stretch ratios, all the tissue specimens behaved isotropically with overlapping stress–stretch curves in both circumferential and axial directions. As the stretch ratios increased, we observed that most tissue specimens displayed different structural behaviors in axial and circumferential directions. This observation was very apparent in tissue specimens from mid FL region, less apparent in mid TL, distal FL, and distal flap tissues and least noticeable in tissue specimens harvested from mid flap. Lastly, using mixed model ANOVAS, it was concluded that there were significant differences between mid and distal regions along axial direction which were absent in the circumferential direction.

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“…First, although we used approximately ten thousands of tension‐strain curves, they were harvested from 10 samples of 6 patients in a relatively uniform age group. As reported in the literature, patients' age, gender, disease conditions, and aortic valve defects can have significant influence on ATAA properties. The samples used in the study certainly do not cover a sufficiently wide range of patient types.…”

Section: Discussionmentioning

confidence: 95%

“…The properties can vary regionally, and directionally . They can be affected by disease conditions such as Marfan syndrome and aortic valve phenotype . Age, gender, family history and aortic diseases and other clinical factors can also have strong influence on the properties .…”

Section: Introductionmentioning

confidence: 99%

Machine learning–aided exploration of relationship between strength and elastic properties in ascending thoracic aneurysm

Luo

Fan

Baek

et al. 2018

Numer Methods Biomed Eng

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Machine learning was applied to classify tension-strain curves harvested from inflation tests on ascending thoracic aneurysm samples. The curves were classified into rupture and nonrupture groups using prerupture response features. Two groups of features were used as the basis for classification. The first was the constitutive parameters fitted from the tension-strain data, and the second was geometric parameters extracted from the tension-strain curve. Based on the importance scores provided by the machine learning, implications of some features were interrogated. It was found that (1) the value of a constitutive parameter is nearly the same for all members in the rupture group and (2) the strength correlates strongly with a tension in the early phase of response as well as with the end stiffness. The study suggests that the strength, which is not available without rupturing the tissue, may be indirectly inferred from prerupture response features.

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Biomechanical Properties of Human Ascending Thoracic Aortic Dissections

Cited by 34 publications

References 28 publications

Failure of the Porcine Ascending Aorta: Multidirectional Experiments and a Unifying Microstructural Model

Failure of the Porcine Ascending Aorta: Multidirectional Experiments and a Unifying Microstructural Model

Biomechanical Material Characterization of Stanford Type-B Dissected Porcine Aortas

Machine learning–aided exploration of relationship between strength and elastic properties in ascending thoracic aneurysm

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