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

Biomechanical properties of the aortic root are distinct from those of the ascending aorta in both normal and aneurysmal states

Background

Although aneurysms of the ascending aorta and the aortic root are treated similarly in clinical guidelines, how biomechanical properties differ between these 2 segments of aorta is poorly defined.

Methods

Biomechanical testing was performed on tissue collected from the aortic root (normal = 11, aneurysm = 51) and the ascending aorta (normal = 21, aneurysm = 76). Energy loss, tangent modulus of elasticity, and delamination strength were evaluated. These biomechanical properties were then compared between (1) normal ascending and normal root tissue, (2) normal and aneurysmal root tissue, (3) normal and aneurysmal ascending tissue, and (4) aneurysmal root and aneurysmal ascending tissue. Propensity score matching was performed to further compare aneurysmal root and aneurysmal ascending aortic tissue. Clinical and biomechanical variables associated with decreased delamination strength in the aortic root were evaluated.

Results

The normal aortic root demonstrated greater viscoelastic behavior (energy loss 0.08 [0.06, 0.10] vs 0.05 [0.04, 0.06], P = .008), and greater resistance against delamination (93 [58, 126] mN/mm vs 54 [40, 63] mN/mm, P = .05) compared with the ascending aorta. Delamination strength was significantly reduced in aneurysms in both the root and the ascending aorta compared with their normal states. Aneurysms of the aortic root matched to the ascending aortic aneurysms in terms of baseline characteristics including size, were characterized by a larger decrease in delamination strength from baseline (Δ -59 mN/mm vs Δ -24 mN/mm). Aging (P = .003) and the presence of hypertension (P = .02) were associated with weakening of the aortic root, while diameter did not have this association (P = .29).

Conclusions

The normal aortic root was found to have distinct biomechanical properties compared with the ascending aorta. When aneurysms form in the aortic root, there is less strength against delamination, without other biomechanical changes such as increased energy loss observed in aneurysmal ascending aortas. Age and hypertension were associated decreased aortic wall strength in the aortic root, whereas diameter had no such association.

Aortic area/height ratio, peak wall stresses, and outcomes in veterans with tricuspid versus bicuspid aortic valve-associated ascending thoracic aortic aneurysms

BACKGROUND

In ascending thoracic aortic aneurysm risk stratification, aortic area/height ratio is a reasonable alternative to maximum diameter. Biomechanically, aortic dissection may be initiated by wall stress exceeding wall strength. Our objective was to evaluate the association between aortic area/height and peak aneurysm wall stresses in relation to valve morphology and 3-year all-cause mortality.

METHODS

Finite element analysis was performed on 270 ascending thoracic aortic aneurysms (46 associated with bicuspid and 224 with tricuspid aortic valves) in veterans. Three-dimensional aneurysm geometries were reconstructed from computed tomography and models developed accounting for prestress geometries. Fiber-embedded hyperelastic material model was applied to obtain aneurysm wall stresses during systole. Correlations of aortic area/height ratio and peak wall stresses were compared across valve types. Area/height ratio was evaluated across peak wall stress thresholds obtained from proportional hazards models of 3-year all-cause mortality, with aortic repair treated as a competing risk.

RESULTS

Aortic area/height 10 cm2/m or greater coincided with 23/34 (68%) 5.0 to 5.4 cm and 20/24 (83%) 5.5 cm or greater aneurysms. Area/height correlated weakly with peak aneurysm stresses: for tricuspid valves, r = 0.22 circumferentially and r = 0.24 longitudinally; and for bicuspid valves, r = 0.42 circumferentially and r = 0.14 longitudinally. Age and peak longitudinal stress, but not area/height, were independent predictors of all-cause mortality (age: hazard ratio, 2.20 per 9-year increase, P = .013; peak longitudinal stress: hazard ratio, 1.78 per 73-kPa increase, P = .035).

CONCLUSIONS

Area/height was more predictive of high circumferential stresses in bicuspid than tricuspid valve aneurysms, but similarly less predictive of high longitudinal stresses in both valve types. Peak longitudinal stress, not area/height, independently predicted all-cause mortality. VIDEO ABSTRACT.

Simulating Subject-Specific Aortic Hemodynamic Effects of Valvular Lesions in Rheumatic Heart Disease

Rheumatic heart disease (RHD) is a neglected tropical disease despite the substantial global health burden. In this study, we aimed to develop a lower cost method of modeling aortic blood flow using subject-specific velocity profiles, aiding our understanding of RHD's consequences on the structure and function of the ascending aorta. Echocardiography and cardiovascular magnetic resonance (CMR) are often used for diagnosis, including valve dysfunction assessments. However, there is a need to further characterize aortic valve lesions to improve treatment options and timing for patients, while using accessible and affordable imaging strategies. Here, we simulated effects of RHD aortic valve lesions on the aorta using computational fluid dynamics (CFD). We hypothesized that inlet velocity distribution and wall shear stress (WSS) will differ between RHD and non-RHD individuals, as well as between subject-specific and standard Womersley velocity profiles. Phase-contrast CMR data from South Africa of six RHD subjects with aortic stenosis and/or regurgitation and six matched controls were used to estimate subject-specific velocity inlet profiles and the mean velocity for Womersley profiles. Our findings were twofold. First, we found WSS in subject-specific RHD was significantly higher (p < 0.05) than control subject simulations, while Womersley simulation groups did not differ. Second, evaluating spatial velocity differences (ΔSV) between simulation types revealed that simulations of RHD had significantly higher ΔSV than non-RHD (p < 0.05), these results highlight the need for implementing subject-specific input into RHD CFD, which we demonstrate how to accomplish through accessible methods.

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.