Numerical analysis of biothermal-fluids and cardiac thermal pulse of abdominal aortic aneurysm

A Comprehensive Review on Computational Analysis, Research Advances, and Major Findings on Abdominal Aortic Aneurysms for the Years 2021 to 2023

BACKGROUND

Abdominal aortic aneurysm (AAA) is a pathological condition characterized by the dilation of the lower part of the aorta, where significant hemodynamic forces are present. The prevalence and high mortality risk associated with AAA remain major concerns within the scientific community. There is a critical need for extensive research to understand the underlying mechanisms, pathophysiological characteristics, and effective detection methods for abdominal aortic abnormalities. Additionally, it is imperative to develop and refine both medical and surgical management strategies. This review aims to indicate the role of computational analysis in the comprehension and management of AAAs and covers recent research studies regarding the computational analysis approach conducted between 2021 and 2023. Computational analysis methods have emerged as sophisticated and noninvasive approaches, providing detailed insights into the complex dynamics of AAA and enhancing our ability to study and manage this condition effectively.

METHODS

Computational analysis relies on fluid mechanics principles applied to arterial flow, using the Navier-Stokes equations to model blood flow dynamics. Key hemodynamic indicators relevant to AAAs include Time-Average Wall Shear Stress, Oscillatory Shear Index, Endothelial Cell Activation Potential, and Relative Residence Time. The primary methods employed for simulating the abdominal aorta and studying its biomechanical environment are computational fluid dynamics and Finite Element Methods. This review article encompasses a thorough examination of recent literature, focusing on studies conducted between 2021 and 2023.

RESULTS

The latest studies have elucidated crucial insights into the blood flow characteristics and geometric attributes of AAAs. Notably, blood flow patterns within AAAs are associated with increased rupture risk, along with elevated intraluminal thrombus volume and specific calcification thresholds. Asymmetric AAAs exhibit heightened risks of rupture and thrombus formation due to low and oscillating wall shear stresses. Moreover, larger aneurysms demonstrate increased wall stress, pressure, and energy loss. Advanced modeling techniques have augmented predictive capabilities concerning growth rates and surgical thresholds. Additionally, the influence of material properties and thrombus volume on wall stress levels is noteworthy, while inlet velocity profiles significantly modulate blood flow dynamics within AAAs.

CONCLUSIONS

This review highlights the potential utility of computational modeling. However, the clinical applicability of computational modeling has been limited by methodological variability despite the ongoing accumulation of evidence supporting the prognostic significance of biomechanical and hemodynamic indices in this field. The establishment of standardized reporting is critical for clinical implementation.

Computational Study of Abdominal Aortic Aneurysm Walls Accounting for Patient-Specific Non-Uniform Intraluminal Thrombus Thickness and Distinct Material Models: A Pre- and Post-Rupture Case

An intraluminal thrombus (ILT) is present in the majority of abdominal aortic aneurysms, playing a crucial role in their growth and rupture. Although most computational studies do not include the ILT, in the present study, this is taken into account, laying out the whole simulation procedure, namely, from computed tomography scans to medical image segmentation, geometry reconstruction, mesh generation, biomaterial modeling, finite element analysis, and post-processing, all carried out in open software. By processing the tomography scans of a patient's aneurysm before and after rupture, digital twins are reconstructed assuming a uniform aortic wall thickness. The ILT and the aortic wall are assigned different biomaterial models; namely, the first is modeled as an isotropic linear elastic material, and the second is modeled as the Mooney-Rivlin hyperelastic material as well as the transversely isotropic hyperelastic Holzapfel-Gasser-Ogden nonlinear material. The implementation of the latter requires the designation of local Cartesian coordinate systems in the aortic wall, suitably oriented in space, for the proper orientation of the collagen fibers. The composite aneurysm geometries (ILT and aortic wall structures) are loaded with normal and hypertensive static intraluminal pressure. Based on the calculated stress and strain distributions, ILT seems to be protecting the aneurysm from a structural point of view, as the highest stresses appear in the thrombus-free areas of the aneurysmal wall.

A predictive surrogate model for hemodynamics and structural prediction in abdominal aorta for different physiological conditions

BACKGROUND AND OBJECTIVE

This study investigates the application of a Predictive Surrogate Model (PSM) for the prediction of the fluid and solid variables in the abdominal aorta by integrating Proper Orthogonal Decomposition (POD) and Long Short-Term Memory (LSTM) techniques.

METHODS

The Fluid-Structure Interaction (FSI) solver, which serves as the Full-Order Model (FOM), can capture the blood hemodynamics and structural mechanics precisely for a variety of physiological states, namely the rest and exercise conditions.

RESULTS

Detailed analyses have been conducted on velocity components, pressure, Wall Shear Stress (WSS), and Oscillatory Shear Index (OSI) variables. Firstly, the reconstruction error has been derived based on a specific number of POD bases to assess the Reduced Order Model (ROM). Notably, the reconstruction error for velocity components in the rest condition is one order of magnitude higher than that in the exercise condition, yet both remained below 10%. This error for pressure is even more minimal, being less than 1%.

CONCLUSIONS

The PSM is evaluated against rest and exercise conditions, exhibiting promising results despite the inherent complexities of the physiological conditions. Despite the inherent complexities of phenomena in the aorta, the predictive model demonstrates consistent error magnitudes for velocity components and wall-related indices, while solid variables show slightly higher errors.

Automatic segmentation of abdominal aortic aneurysms from CT angiography using a context-aware cascaded U-Net

We delineate abdominal aortic aneurysms, including lumen and intraluminal thrombosis (ILT), from contrast-enhanced computed tomography angiography (CTA) data in 70 patients with complete automation. A novel context-aware cascaded U-Net configuration enables automated image segmentation. Notably, auto-context structure, in conjunction with dilated convolutions, anisotropic context module, hierarchical supervision, and a multi-class loss function, are proposed to improve the delineation of ILT in an unbalanced, low-contrast multi-class labeling problem. A quantitative analysis shows that the automated image segmentation produces comparable results with trained human users (e.g., DICE scores of 0.945 and 0.804 for lumen and ILT, respectively). Resultant morphological metrics (e.g., volume, surface area, etc.) are highly correlated to those parameters generated by trained human users. In conclusion, the proposed automated multi-class image segmentation tool has the potential to be further developed as a translational software tool that can be used to improve the clinical management of AAAs.

Study of flow, Bioheat transfer and cardiac thermal pulse of aneurysm in the abdominal aortic

Abdominal aortic aneurysms (AAA) are serious and difficult to detect conditions that can be deadly if they rupture. Infrared thermography (IRT) is a promising imaging technique that can detect abdominal aortic aneurysms more quickly and less costly than other imaging techniques. A clinical biomarker of circular thermal elevation on the midriff skin surface of AAA patient at various scenarios was expected during diagnosis using IRT scanner. However, it is important to note that thermography is not a perfect technology, and it does have some limitations, such as lack of clinical trials. There is still work to be done to improve this imaging technique and make it a more viable and accurate method in detecting abdominal aortic aneurysms. Nevertheless, thermography is currently one of the most convenient technologies in imaging, and it has the potential to detect abdominal aortic aneurysms earlier than other techniques. Cardiac thermal pulse (CTP), on the other hand, was used to examine the thermal physics of AAA. AAA had a CTP that only responded to systolic phase at regular body temperature. Whereas the AAA wall would establish thermal homeostasis with blood temperature following a quasi-linear relationship as the body experienced fever or stage-2 hypothermia. In contrast, a healthy abdominal aorta displayed a CTP that responded to the full cardiac cycle, including diastolic phase at all simulated scenarios.