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Project

Biomechanics-based diagnosis and prognosis of ascending thoracic aortic aneurysms

An aortic aneurysm is a chronic degenerative disease characterized by a permanent dilatation of the aortic wall. This condition may lead to fatal acute aortic syndromes, i.e. dissection or rupture of the aortic wall. Current clinical practice dictates surgical intervention when the measured diameter exceeds a critical threshold. For ascending thoracic aortic aneurysms, the surgical procedure involves a highly invasive and risky open surgery during which the aneurysm is removed and replaced with a prosthetic graft. However, the conventional diameter-based criterion inadequately represents the aneurysm's risk of aortic wall failure. This results in a significant number of cases of unforeseen aortic rupture and dissections, as well as unnecessary operations on stable aneurysms. This thesis aims to find reliable, clinically measurable predictors to identify patients with an ascending aortic aneurysm at risk of aortic rupture or dissection, based on rigorous in vitro biomechanical characterization and robust in silico simulations of the aortic wall.

In the context of biomechanical experimentation, planar biaxial testing stands out as a prominent method for the in vitro characterization of aneurysmatic tissue. Despite its popularity, it lacks well-defined guidelines for measuring the deformation and identifying the stress-free state. To measure the deformation, the conventional two-dimensional technique measures out-of-plane motion as false strain. A comparison with a three-dimensional method revealed some out-of-plane movement during planar biaxial tests. However, as it was shown to minimally impact accuracy, the two-dimensional technique remains valid for deformation measurement in this application. Additionally, the correct identification of the stress-free state is essential to correctly characterize the tissue. During a tensile test, the sample is mounted and preloaded to avoid sagging, which results in a non-zero state at the start of the loading cycle. Two methods were introduced to identify the stress-free state: the first method assumes an ideal test, while the second method accounts for the boundary effects induced by the gripping mechanism for precise material property values. Both methods differ in complexity and the choice between them depends on the specific intended use by the experimentalist.

To assess the risk of aortic rupture or dissection, in silico modeling of the aneurysm is required. This involves using numerical simulations of aortic wall mechanics, which rely on image-based data to define the in vivo geometry. Prestressing algorithms are then applied to ensure mechanical equilibrium under corresponding in vivo loading conditions. A sensitivity analysis between different prestressing algorithms showed that the mechanical equilibrium of thick-walled geometries is not uniquely defined unless the ex vivo state is known, which is typically inaccessible in a clinical context. Addressing this, a transmural prestretch distribution based on physiological reasoning enhances the reliability of arterial mechanics simulations and ensures a robust assessment of the peak wall stress. Furthermore, arterial tissue is typically assumed to be composed of an isotropic hyperelastic non-collagenous extracellular matrix with embedded collagen fiber families. Collagen defines the artery's behavior as transversely isotropic, making it a crucial factor when assessing peak wall stress in the aortic wall. An algorithm was introduced that determines the collagen fiber distribution according to the stress or stretch experienced by this non-collagenous extracellular matrix. The stress-based method accurately predicted the observed fiber distribution transitions in the healthy aortic wall.

A retrospective clinical study evaluated aneurysm failure risk in 33 patients who underwent surgical repair. Excised aneurysms were subjected to uniaxial and planar biaxial experiments. Clinical information, including blood pressure and aneurysm geometry, were combined with experimental findings to calculate the peak wall stress and wall strength. This allowed for the evaluation of the aortic failure risk in the axial and circumferential directions, using both a deterministic and a probabilistic approach. By examining potential predictors function of these failure risks, the study revealed that aortic distensibility —a measure of the blood vessel's capacity to expand during pressure changes— outperformed purely geometrical parameters to predict aortic rupture or dissection. The volumetric distensibility has the best predictive power as it also takes the axial stretch into account. This finding holds significant implications for guiding surgical practices, emphasizing the importance of imaging the aneurysm throughout both diastolic and systolic phase.

Date:14 Sep 2018 →  22 Nov 2023
Keywords:Dissection risk of the aortic aneurysm, Personalized diagnosis and prognosis, Biomechanical analysis, Growth and remodeling
Disciplines:Orthopaedics, Surgery, Nursing, Biomechanics, Biological system engineering, Biomaterials engineering, Biomechanical engineering, Medical biotechnology, Other (bio)medical engineering
Project type:PhD project