A classification approach to improve out of sample predictability of structure-based constitutive models for ascending thoracic aortic tissue.

In this research, a pipeline was developed to assess the out-of-sample predictive capability of structure-based constitutive models of ascending aortic aneurysmal tissue. The hypothesis being tested is that a biomarker can help establish similarities among tissues sharing the same level of a quantifiable property, thus enabling the development of biomarker-specific constitutive models. Biomarker-specific averaged material models were constructed from biaxial mechanical tests of specimens that shared similar biomarker properties such as level of blood-wall shear stress or microfiber (elastin or collagen) degradation in the extracellular matrix. Using a cross-validation strategy commonly used in classification algorithms, biomarker-specific averaged material models were assessed in contrast to individual tissue mechanics of out of sample specimens that fell under the same category but did not contribute to the averaged model's generation. The normalized root means square errors (NRMSE) calculated on out-of-sample data were compared with average models when no categorization was performed versus biomarker-specific models and among different level of a biomarker. Different biomarker levels exhibited statistically different NRMSE when compared among each other, indicating more common features shared by the specimens belonging to the lower error groups. However, no specific biomarkers reached a significant difference when compared to the average model created when No Categorization was performed, possibly on account of unbalanced number of specimens. The method developed could allow for the screening of different biomarkers or combinations/interactions in a systematic manner leading the way to larger datasets and to more individualized constitutive approaches.

Magnetic resonance imaging-based hemodynamic wall shear stress alters aortic wall tissue biomechanics in bicuspid aortic valve patients.

OBJECTIVE: In this study we aimed to conclusively determine whether altered aortic biomechanics are associated with wall shear stress (WSS) independent of region of tissue collection. Elevated WSS in the ascending aorta of patients with bicuspid aortic valve has been shown to contribute to local maladaptive aortic remodeling and might alter biomechanics. METHODS: Preoperative 4-dimensional flow magnetic resonance imaging was performed on 22 patients who underwent prophylactic aortic root and/or ascending aorta replacement. Localized elevated WSS was identified in patients using age-matched healthy atlases (n = 60 controls). Tissue samples (n = 78) were collected and categorized according to WSS (elevated vs normal) and region. Samples were subjected to planar biaxial testing. To fully quantify the nonlinear biomechanical response, the tangential modulus (local stiffness) at a low-stretch (LTM) and high-stretch (HTM) linear region and the onset (TZo) and end stress of the nonlinear transition zone were measured. A linear mixed effect models was implemented to determine statistical relationships. RESULTS: A higher LTM in the circumferential and axial direction was associated with elevated WSS (P = .007 and P = .018 respectively) independent of collection region. Circumferential TZo and HTM were higher with elevated WSS (P = .024 and P = .003); whereas the collection region was associated with variations in axial TZo (P = .013), circumferential HTM (P = .015), and axial HTM (P = .001). CONCLUSIONS: This study shows strong evidence that biomechanical changes in the aorta are strongly associated with hemodynamics, and not region of tissue collection for bicuspid valve aortopathy patients. Elevated WSS is associated with tissue behavior at low stretch ranges (ie, LTM and TZo).

Elastin integrity in bicuspid valve-associated aortopathy is associated with altered biomechanical properties and influenced by age.

Background: Aortic wall remodelling in bicuspid aortic valve (BAV) patients is heterogeneous and characterized by elastin fiber breakdown alongside impaired biomechanics. However, the relationship between aortic histopathological changes and biomechanics are incompletely understood. We clarify the influence of elastin fiber integrity on ex vivo aortic wall mechanical properties in BAV patients, and explore the influence of patient age. Methods: Aortic tissue samples (N=66) from 19 BAV patients undergoing prophylactic ascending aortic resection surgery were analyzed. Semi-quantitative histopathological analysis was conducted to assess elastin fiber integrity including elastin content and elastic fiber fragmentation. Ex vivo biaxial mechanical testing generated stress-strain curves from which physiological [low-strain tangential modulus (LTM), transition zone onset stress (TZo)] and supraphysiological [transition zone end stress (TZe) and high-strain tangential modulus (HTM)] mechanical properties were obtained. Relationships between histopathology and mechanical properties were determined using a linear mixed effect model. BAV patients were subdivided according to 'younger' and 'older' age groups (i.e., 51-60 and 61-70 years old, respectively). Results: No statistically significant differences in elastin content were observed between younger and older BAV patients. Older patients showed greater elastin fiber fragmentation compared to their younger cohort (74% versus 61%). Elastin fiber histopathology was associated with differences in physiological mechanical properties: elastin fragmentation corresponded with lower LTM (P=0.005) and TZo (P=0.044) in younger BAV patients and higher LTM (P=0.049) and TZo (P=0.001) in older BAV patients. Histopathology changes were significantly associated with supraphysiological mechanical properties only in older BAV patients: decreased elastin integrity was associated with increased TZe (P=0.049) and HTM (P<0.001). Conclusions: Elastin histopathologic changes in BAV aortopathy correspond with differences in mechanical properties and this relationship is influenced by patient age. These novel findings provide additional mechanistic insights into aortic wall remodeling and support a more nuanced stratification of BAV patients by age.

Biomechanics in ascending aortic aneurysms correlate with tissue composition and strength.

Objective: This study correlates low strain tangential modulus (LTM) and transition zone onset (TZo) stress, biomechanical parameters that occur within the physiological range of stress seen in vivo, with tissue strength and histopathologic changes in aneurysmal ascending aortic tissue. Method: Ascending aortic aneurysm tissue samples were collected from 41 patients undergoing elective resection. Samples were subjected to planar biaxial testing to quantify LTM and TZo. These were then correlated with strength assessed from uniaxial testing and with histopathologic quantification of pathologic derangements in elastin, collagen, and proteoglycan (PG). Results: Decreased LTM and TZo were correlated with reduced strength (P < .05), PG content (P < .05), and elastin content (P < .05). Reduced TZo also was correlated with increased elastin fragmentation (P < .05). Conclusions: LTM and TZo are correlated with common biomechanical and histopathologic alterations in ascending aortic aneurysm tissue that are thought to relate to the risk of acute aortic syndromes. LTM and TZo are measured under conditions approximating in vivo physiology and have the potential to be obtained noninvasively using medical imaging techniques. Therefore, they represent parameters that warrant future study as potential contributors to our growing knowledge of pathophysiology, disease progression, and risk stratification of aortic disease.

Material characterization of cardiovascular biomaterials using an inverse finite-element method and an explicit solver.

The ability to accurately model soft tissue behavior, such as that of heart valve tissue, is essential for developing reliable numerical simulations and determining patient-specific care options. Although several material models can predict soft tissue behavior, complications may arise when these models are implemented into finite element (FE) programs, due to the addition of an arbitrary penalty parameter for numerically enforcing material incompressibility. Herein, an inverse methodology was developed in MATLAB to use previously published stress-strain data from experimental planar equibiaxial testing of five biomaterials used in heart valve cusp replacements, in conjunction with commercial explicit FE solver LS-DYNA, to optimize the material parameters and the penalty parameter for an anisotropic hyperelastic strain energy function. A two-parameter optimization involving the scaling constant of the strain energy function and the penalty parameter proved sufficient to produce acceptable material responses when compared with experimental behaviors under the same testing conditions, as long as analytically derived material constants were available for the other non-optimized parameters and the actual tissue thickness was not much less than 1 mm. Variations in the penalty parameter had a direct effect on the accuracy of the simulated responses, with a practical range determined to be 5×108-9×108 times the scaling constant of the strain energy function.