Ascending aortic aneurysm haemodynamics are associated with aortic wall biomechanical properties

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.

Modelling blood flow in patients with heart valve disease using deep learning: A computationally efficient method to expand diagnostic capabilities in clinical routine

Introduction

The computational modelling of blood flow is known to provide vital hemodynamic parameters for diagnosis and treatment-support for patients with valvular heart disease. However, most diagnosis/treatment-support solutions based on flow modelling proposed utilize time- and resource-intensive computational fluid dynamics (CFD) and are therefore difficult to implement into clinical practice. In contrast, deep learning (DL) algorithms provide results quickly with little need for computational power. Thus, modelling blood flow with DL instead of CFD may substantially enhances the usability of flow modelling-based diagnosis/treatment support in clinical routine. In this study, we propose a DL-based approach to compute pressure and wall-shear-stress (WSS) in the aorta and aortic valve of patients with aortic stenosis (AS).

Methods

A total of 103 individual surface models of the aorta and aortic valve were constructed from computed tomography data of AS patients. Based on these surface models, a total of 267 patient-specific, steady-state CFD simulations of aortic flow under various flow rates were performed. Using this simulation data, an artificial neural network (ANN) was trained to compute spatially resolved pressure and WSS using a centerline-based representation. An unseen test subset of 23 cases was used to compare both methods.

Results

ANN and CFD-based computations agreed well with a median relative difference between both methods of 6.0% for pressure and 4.9% for wall-shear-stress. Demonstrating the ability of DL to compute clinically relevant hemodynamic parameters for AS patients, this work presents a possible solution to facilitate the introduction of modelling-based treatment support into clinical practice.

The pathogenesis of superior mesenteric artery dissection: An in-depth study based on fluid-structure interaction and histology analysis

OBJECTIVE

To explore the role of hemodynamic factors in the occurrence of superior mesenteric artery (SMA) dissection (SMAD) using a fluid-structure interaction (FSI) simulation method, and to identify histopathologic changes occurring in the wall of the SMA.

METHODS

A total of 122 consecutive patients diagnosed with SMAD and 122 controls were included in this study. Hemodynamic factors were calculated using a FSI simulation method. Additionally, SMA specimens obtained from 12 cadavers were stained for histological quantitative analysis.

RESULTS

The mean aortomesenteric angle (59.7° ± 21.4° vs 48.2° ± 16.8°; p < .001) and SMA maximum curvature (0.084 ± 0.078 mm^-1 vs 0.032 ± 0.023 mm^-1; p < .001) were higher in SMAD patients than the controls. Larger aortomesenteric angles and SMA curvatures were associated with higher and more concentrated wall shear stress at anterior wall of the SMA curve segment, co-located with the dissection origins. The mean thickness of media (325.18 ± 44.87 µm vs 556.92 ± 138.32 µm; p = .003) was thinner in the anterior wall of the SMA curve than in the posterior wall. The area fractions of elastin (17.96% ± 3.36% vs 27.06% ± 4.18%; p = .002) and collagen (45.43% ± 6.89% vs 55.57% ± 7.57%; p = .036) were lower in anterior wall of the SMA curve than in posterior wall.

CONCLUSION

Increased aortomesenteric angle and SMA curvature are risk factors for SMAD. Both of these factors can cause local hemodynamic abnormalities, which can lead to histopathologic changes in anterior wall of SMA.