Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms

BACKGROUND: Ruptured abdominal aortic aneurysms (AAAs) are the 13(th )leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm) and AAA-growth rate (>0.5 cm/year). These criteria may be insufficient for reliable AAA-rupture risk assessment especially when predicting possible rupture of smaller AAAs. METHODS: Based on clinical evidence, eight biomechanical factors with associated weighting coefficients were determined and summed up in terms of a dimensionless, time-dependent severity parameter, SP(t). The most important factor is the maximum wall stress for which a semi-empirical correlation has been developed. RESULTS: The patient-specific SP(t) indicates the risk level of AAA rupture and provides a threshold value when surgical intervention becomes necessary. The severity parameter was validated with four clinical cases and its application is demonstrated for two AAA cases. CONCLUSION: As part of computational AAA-risk assessment and medical management, a patient-specific severity parameter 0 < SP(t) < 1.0 has been developed. The time-dependent, normalized SP(t) depends on eight biomechanical factors, to be obtained via a patient's pressure and AAA-geometry measurements. The resulting program is an easy-to-use tool which allows medical practitioners to make scientific diagnoses, which may save lives and should lead to an improved quality of life

Passive biomechanics of abdominal aortic aneurysms

En esta tesis se estudia la respuesta elástica de aneurismas aórticos abdominales (AAA), buscando ahondar en su conocimiento y con la finalidad de proveer un mejor criterio de decisión para la realización, o no, de una intervención quirúrgica para la reparación de la lesión. Parámetros biomecánicos como la tensión pico de la pared arterial (singlas en inglés: PWS) o el riesgo de ruptura de la pared arterial (siglas en inglés: PWRR) han mostrado ser una alternativa posible y prometedora a ser utilizada para determinar el riesgo de ruptura. De la misma manera, el entender la biomecánica pasiva de los AAA permite realizar una evaluación más correcta de las tensiones, lo que se puede realizar mediante el uso de modelos de material adecuados para los tejidos junto con modelos geométricos fiables en los que se apliquen condiciones de frontera realistas. Esta tesis presenta un novedoso algoritmo iterativo para determinar la geometría cero-presión de un AAA para pacientes específicos, la cual supera las limitaciones de las metodologías existentes y permite una mejor estimación de las tensiones. La importancia de este algoritmo se debe a que los modelos de AAA de pacientes específicos son generados a partir de imágenes médicas de CT (tomografía axial computarizada) sincronizadas en las cuales la arteria está bajo presión, por lo tanto la identificación de la geometría cero-presión de AAAs permite una estimación más realista de la respuesta mecánica de la pared arterial. La metodología permite considerar el comportamiento hiperelástico anisótropo de la pared arterial, su espesor y la presencia del trombo intraluminal (ILT). Resultados en doce geometrías de de AAAs, paciente específico, indican que el algorítmo es computacionalmente tratable y eficiente, a la vez que preserva el volumen global del modelo. Adicionalmente, una comparación de resultados de PWS calculados usando geometría cero-presión y geometría basada en CT al aplicar la presión sistólica indica que los resultados a partir de geometría CT subestiman (significativamente) la tensión pico de la pared arterial en casos de modelos isótropo y anisótropo de la pared arterial. Adicionalmente, en base a los resultados experimentales publicados para la pared arterial del aneurisma y aorta sana, los resutados de esta tesis no encuentran diferencias significativas entre el uso de un modelo de material isótropo o anisótropo. Con respecto al ILT, el cual es un pseudo-tejido que se desarrolla a partir de sangre coagulada y se encuentra en la mayor parte de los AAAs de tamaño relevante, algunos estudios sugieren que las características mecánicas del ILT pueden estar relacionadas con el riesgo de ruptura del AAA, aunque existe una gran controversia en este respecto. Esta tesis investiga como la constitución y topología del ILT influye en la magnitud y localización de las tensiones pico en la pared arterial. El ILT, isótropo y no homogéneo, puede aparecer como un tejido flexible (una capa) o rígido (fibrótico multicapa). El estudio se extendió a 21 AAAs, pacientes específicos, (diámetro: 4.2-5.4 cm) que fueron reconstruidos a partir de imágenes CT y analizados numéricamente empleando el algoritmo de tirón propuesto para identificar la geometría cero presión. Los resultados indican que la PWS está mayormente correlacionada con el volumen de ILT (¿=0.44, p=0.05) y con el espesor de capa mínimo de ILT (¿=0.73, p=0.001) que con el diámetro máximo de AAA (¿=0.05, p=0.82). En promedio la PWS fue un 20% (desv estándar 12%) más alta para modelos en los que se usaron modelos suaves de ILT en lugar de modelos rígidos de ILT (p<0.001). La localización del PWS está altamente correlacionada con los puntos de menor espesor de ILT, en las secciones de máximo diámetro del AAA, y esto fue independiente de la rigidez del ILT. Adicionalmente, la heterogeneidad del ILT, i.e. la composición espacial de trombo suave o rígido, puede influenciar sustancialmente la tensión de la pared arterial. El presente estudio está limitado a identificar la influencia de factores biomecánicos, el cómo estos resultados se trasladan a la evaluación del riesgo de ruptura de AAA debe ser desarrollado a partir de estudios clínicos.The passive biomechanics of abdominal aortic aneurysms (AAA) is studied, seeking to deepen in its knowledge and with the aim of providing better decision criteria to undergo surgical intervention for AAA repair. Biomechanical parameters as the peak wall stress (PWS) or the peak wall rupture risk (PWRR) have shown to be a feasible and promising alternative that can be used to better ascertain the risk of rupture. In addition, the understanding of the passive biomechanics of AAA allows obtaining a more accurate stress assessment, which can be done by using appropriate material models for the tissues along with accurate geometric models and more realistic boundary conditions for the lesion. This thesis presents a novel iterative algorithm to determine the zeropressure geometry of a patient-specific AAA that overcomes limitations on existing methodologies and allows a better estimation of the stresses. The importance of this algorithm lays in that patient-specific AAA models are generated from gated CT (Computer Tomography) medical images in which the artery is under pressure (diastolic), therefore the identification of the AAA zero pressure geometry would allow for a more realistic estimate of the aneurismal wall mechanics. The methodology allows considering the anisotropic hyperelastic behavior of the aortic wall, its thickness and accounts for the presence of the intraluminal thrombus (ILT). The results on twelve patientspecific AAA geometric models indicate that the procedure is computational tractable and efficient, and preserves the global volume of the model. In addition, a comparison of the peak wall stress computed with the zero pressure and CT-based geometries during systole indicate that computations using CTbased geometric models underestimate (significantly) the peak wall stress for both, isotropic and anisotropic material models of the arterial wall. In addition, based on the reported experimental results for aneurysmal and aortic wall mechanics, no significant differences among isotropic and anisotropic material models have been found. With respect to the ILT, which is a pseudo-tissue that develops from coagulated blood and it is found in most AAAs of clinically relevant size, a number of studies have suggested that ILT mechanical characteristics may be related to AAA risk of rupture, even though there is still great controversy on this regard. This thesis investigates how ILT constitution and topology influence the magnitude and location of PWS. ILT is isotropic and inhomogeneous and may appear as a soft (single-layered) or stiff (multilayered fibrotic) tissue. An extended study was conducted involving twenty-one patient-specific AAAs (diameter: 4.2-5.4 cm) which were reconstructed from CT images and biomechanically analyzed using the proposed methodology. Results indicated that PWS correlated stronger with ILT volume (ρ=0.44, p=0.05) and the minimum thickness of the ILT layer (ρ=0.73, p=0.001) than with maximum AAA diameter (ρ=0.05, p=0.82). In average PWS was 20% (SD 12%) higher for FE models that used a soft instead of stiff ILT models (p<0.001). PWS location strongly correlated with sites of minimum ILT thickness in the section of maximum AAA diameter and was independent from the ILT stiffness. In addition, ILT heterogeneity, i.e. the spatial composition of soft and stiff thrombus tissue, can considerably influence the stress in the AAA wall. The present study is limited to the identification of influential biomechanical factors, and how its findings translate to an AAA rupture risk assessment remains to be explored by clinical studies

A Systematic Review and Discussion of the Clinical Potential

Funding Information: Funding by Portuguese Foundation for Science and Technology (FCT-MCTES) under the following projects: PTDC/EMD-EMD/1230/2021—Fluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice ; UNIDEMI UIDB/00667/2020; A. Mourato PhD grant UI/BD/151212/2021; R. Valente PhD grant 2022.12223.BD. Publisher Copyright: © 2022 by the authors.Aortic aneurysm is a cardiovascular disease related to the alteration of the aortic tissue. It is an important cause of death in developed countries, especially for older patients. The diagnosis and treatment of such pathology is performed according to guidelines, which suggest surgical or interventional (stenting) procedures for aneurysms with a maximum diameter above a critical threshold. Although conservative, this clinical approach is also not able to predict the risk of acute complications for every patient. In the last decade, there has been growing interest towards the development of advanced in silico aortic models, which may assist in clinical diagnosis, surgical procedure planning or the design and validation of medical devices. This paper details a comprehensive review of computational modelling and simulations of blood vessel interaction in aortic aneurysms and dissection, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In particular, the following questions are addressed: “What mathematical models were applied to simulate the biomechanical behaviour of healthy and diseased aortas?” and “Why are these models not clinically implemented?”. Contemporary evidence proves that computational models are able to provide clinicians with additional, otherwise unavailable in vivo data and potentially identify patients who may benefit from earlier treatment. Notwithstanding the above, these tools are still not widely implemented, primarily due to low accuracy, an extensive reporting time and lack of numerical validation.publishersversionpublishe

Design of a comprehensive modeling, characterization, rupture risk assessment and visualization pipeline for Abdominal Aortic Aneurysms

Abdominal aortic aneurysms (AAA) is a dilation of the abdominal aorta, typically within the infra-renal segment of the vessel that cause an expansion of at least 1.5 times the normal vessel diameter. It is becoming a leading cause of death in the United States and around the world, and consequentially, in 2009, the Society for Vascular Surgery (SVS) practice guidelines expressed the critical need to further investigate the factors associated with the risk of AAA rupture, along with potential treatment methods. For decades, the maximum diameter (Dmax) was introduced as the main parameter used to assess AAA behavior and its rupture risk. However, it has been shown that three main categories of parameters including geometrical indices, such as the maximum transverse diameter, biomechanical parameters, such as material properties, and historical clinical parameters, such as age, gender, hereditary history and life-style affect AAA and its rupture risk. Therefore, despite all efforts that have been undertaken to study the relationship among different parameters affecting AAA and its rupture, there are still limitations that require further investigation and modeling; the challenges associated with the traditional, clinical quality images represent one class of these limitations. The other limitation is the use of the homogenous hyper-elastic material property model to study the entire AAA, when, in fact, there is evidence that different degrees of degradation of the elastin and collagen network of the AAA wall lead to different regions of the AAA exhibiting different material properties, which, in turn, affect its biomechanical behavior and rupture. Moreover, the effects of all three main categories of parameters need to be considered simultaneously and collectively when studying the AAAs and their rupture, so once again, the field can further benefit from such studies. Therefore, in this work, we describe a comprehensive pipeline consisting of three main components to overcome some of these existing limitations. The first component of the proposed method focuses on the reconstruction and analysis of both synthetic and human subject-specific 3D models of AAA, accompanied by a full geometric parameter analysis and their effects on wall stress and peak wall stress. The second component investigates the effect of various biomechanical parameters, specifically the use of various homogeneous and heterogeneous material properties to model the behavior of the AAA wall. To this extent, we introduce two different patient-specific regional material property models to better mimic the physiological behavior of the AAA wall. Finally, the third component utilizes machine learning methods to develop a comprehensive predictive model that incorporates the effect of the geometrical, biomechanical and historical clinical data to predict the rupture severity of AAA in a patient-specific manner. This is the first comprehensive semi-automated method developed for the assessment of AAA. Our findings illustrate that using a regional material property model that mimics the realistic heterogeneity of the vessel’s wall leads to more reliable and accurate predictions of AAA severity and associated rupture risk. Additionally, our results indicate that using only Dmax as an indicator for the rupture risk is insufficient, while a combination of parameters from different sources along with PWS could serve as a more reliable rupture assessment. These methods can help better characterize the severity of AAAs, better predict their associated rupture risk, and, in turn, help clinicians with earlier, patient-customized diagnosis and patient-customized treatment planning approaches, such as stent grafting

Virtuelle endovaskuläre Versorgung von abdominalen Aortenaneurysmen

This thesis is focused on computational methods that predict the outcome of endovascular repair of abdominal aortic aneurysms. Novelties include improvements of the aneurysm model, the stent-graft model as well as the in-silico stent-graft placement methodology. The newly developed methods are applied to patient-specific cases and are validated against real-world postinterventional data. Further, directions for using the in-silico model of endovascular aneurysm repair as personalized preinterventional planning tool in clinical practice are provided.Die vorliegende Arbeit beschäftigt sich mit numerischen Methoden um den Ausgang einer endovaskulären Versorgung von abdominalen Aortenaneurysmen vorherzusagen. Neuheiten umfassen Verbesserungen des Aneurysmenmodells, des Stentgraftmodells sowie der virtuellen Platzierungsmethode des Stentgrafts. Die neu entwickelten Methoden werden auf patientenspezifische Fälle angewandt und werden mit realen postoperativen Daten validiert. Weiterhin werden klinische Anwendungen des Modells der endovaskulären Aneurysmenversorgung als personalisiertes präoperatives Planungswerkzeug präsentiert

Computational estimation of haemodynamics and tissue stresses in abdominal aortic aneurysms

&apos;o e Abdominal aortic aneurysm is a vascular disease involving a focal dilation of the aorta. The exact cause is unknown but possibilities include infection and weakening of the connective tissue. Risk factors include a history of atherosclerosis, current smoking and a close relative with the disease. Although abdominal aortic aneurysm can affect anyone, it is most often seen in older men, and may be present in up to 5.9 % of the population aged 80 years. Biomechanical factors such as tissue stresses and shear stresses have been shown to play a part in aneurysm progression, although the specific mechanisms are still to be determined. The growth rate of the abdominal aortic aneurysm has been found to correlate with the peak stress in the aneurysm wall and the blood flow is thought to influence disease development. In order to resolve the connections between biology and biomechanics, accurate estimations of the forces involved are required. The first part of this thesis assesses the use of computational fluid dynamics for modelling haemodynamics in abdominal aortic aneurysms. Boundary conditions from the literature o

Enhanced stress prediction correlation for abdominal aortic aneurysm using fluid structure interaction technique

The rupture of the abdominal aortic aneurysm (AAA) occurs when the acting stress exceeds the ultimate stress of the wall. Therefore, the ability to accurately estimate the acting stress is very useful to predict the rupture of an AAA. In this study, previously developed equation which included the effect of inter lumen thrombus, systolic pressure, maximum aneurysm diameter, wall thickness, asymmetry parameter, is improved by applying fully coupling-fluid structure interaction technique (f-FSI). Further improvements of the equation is also done by including the aneurysm length and iliac bifurcation angle. Various case studies are analyzed to investigate the hemodynamic behavior as well as stress distribution on the wall using modified models as well as Computed Tomography scan (CT scan). The results show that the geometry parameters as well as hypertension affect the flow pattern, displacement and stress distribution. Exponential correlation is observed between the maximum acting stress and the asymmetric parameter. In addition, a linear correlation with the maximum aneurysm, aneurysm length, iliac bifurcation angle and wall thickness is determined. The parametric correlations confirm that these geometry parameters are important parameters to predict the maximum acting stress. The inclusion of the effect of hemodynamic by using f-FSI technique predicted a higher maximum acting stress in AAA wall compared to previous equations. Consequently, the current research has concluded that the newly developed equation can be easily used for rupture prediction with even more accurate results than the currently used clinical tools

Reduced order fluid-structure interaction models for thin shells with non-zero Gaussian curvatures to understand the response of aneurysms to flow

In this thesis, a reduced-order model is constructed to study the physiological flow and wall shear stress conditions for aneurysms. The method of local proper orthogonal decomposition (POD) is used to construct the reduced-order modes using a series of CFD results, which are subsequently improved using a QR-factorization technique to satisfy the various boundary conditions in physiological flow problems. This method can effectively construct a computationally efficient physiological model, which allows us to examine the fluid velocities and wall shear stress distributions over a range of different physiological flow parameters. Aneurysms are the dilation, bulging, or ballooning-out of part of the wall of a human artery. Repetitive forces on an existing aneurysm can lead either to its gradual expansion or to a devastating event of rupture. Traditionally, clinicians use the largest diameter as the sole parameter for standard risk stratification outside of clinical trials. However, there seems to be no safe small aneurysm size and a more accurate answer depends on the exact distributions of material and geometrical properties of the aneurysms. Aneurysms can have a very non-uniform distribution of thickness, modulus, and failure tension. We focus on the thins-shell fluid-structures interactions (FSI) with thickness inhomogeneity by studying the influence of one or multiple thin spots on the flow-induced instabilities of flexile shells of revolution with non-zero Gaussian curvatures. The results show that for shells with positive Gaussian curvatures conveying fluid, the existence of a thin spot results in a localized flow-induced buckling response of the shell in the neighborhood of the thin spot, and significantly reduces the critical flow velocity for buckling instability. For shells with negative Gaussian curvatures, the buckling response is extended along the shell’s characteristic lines and the critical flow velocity is only slightly reduced. Finally, the shell model with non-uniform thickness is combined with the ROM of hemodynamic loads. We show that based on a growth and remodeling (G&R) model, the rate of aneurysmal wall’s elastin degradation can be predicted efficiently with various degrees of thickness inhomogeneity

Growth description for vessel wall adaptation: a thick-walled mixture model of abdominal aortic aneurysm evolution

(1) Background: Vascular tissue seems to adapt towards stable homeostatic mechanical conditions, however, failure of reaching homeostasis may result in pathologies. Current vascular tissue adaptation models use many ad hoc assumptions, the implications of which are far from being fully understood; (2) Methods: The present study investigates the plausibility of different growth kinematics in modeling Abdominal Aortic Aneurysm (AAA) evolution in time. A structurally motivated constitutive description for the vessel wall is coupled to multi-constituent tissue growth descriptions; Constituent deposition preserved either the constituent’s density or its volume, and Isotropic Volume Growth (IVG), in-Plane Volume Growth (PVG), in-Thickness Volume Growth (TVG) and No Volume Growth (NVG) describe the kinematics of the growing vessel wall. The sensitivity of key modeling parameters is explored, and predictions are assessed for their plausibility; (3) Results: AAA development based on TVG and NVG kinematics provided not only quantitatively, but also qualitatively different results compared to IVG and PVG kinematics. Specifically, for IVG and PVG kinematics, increasing collagen mass production accelerated AAA expansion which seems counterintuitive. In addition, TVG and NVG kinematics showed less sensitivity to the initial constituent volume fractions, than predictions based on IVG and PVG; (4) Conclusions: The choice of tissue growth kinematics is of crucial importance when modeling AAA growth. Much more interdisciplinary experimental work is required to develop and validate vascular tissue adaption models, before such models can be of any practical use