Computational Fluid Dynamics Simulations to Predict False Lumen Enlargement After Surgical Repair of Type-A Aortic Dissection

Mechanisms of aortic dissection: From pathological changes to experimental and in silico models

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

Predicting Aneurysmal Degeneration in Uncomplicated Residual Type B Aortic Dissection

The formation of an aneurysm in the false lumen (FL) is a long-term complication in a significant percentage of type B aortic dissection (AD) patients. The ability to predict which patients are likely to progress to aneurysm formation is key to justifying the risks of interventional therapy. The investigation of patient-specific hemodynamics has the potential to enable a patient-tailored approach to improve prognosis by guiding disease management for type B dissection. CFD-derived hemodynamic descriptors and geometric features were used to retrospectively assess individual aortas for a population of residual type B AD patients and analyze correlations with known outcomes (i.e., rapid aortic growth, death). The results highlight great variability in flow patterns and hemodynamic descriptors. A rapid aortic expansion was found to be associated with a larger FL. Time-averaged wall shear stress at the tear region emerged as a possible indicator of the dynamics of flow exchange between lumens and its effect on the evolution of individual aortas. High FL flow rate and tortuosity were associated with adverse outcomes suggesting a role as indicators of risk. AD induces complex changes in vessel geometry and hemodynamics. The reported findings emphasize the need for a patient-tailored approach when evaluating uncomplicated type B AD patients and show the potential of CFD-derived hemodynamics to complement anatomical assessment and help disease management.

Advanced risk prediction for aortic dissection patients using imaging-based computational flow analysis

Patients with either a repaired or medically managed aortic dissection have varying degrees of risk of developing late complications. High-risk patients would benefit from earlier intervention to improve their long-term survival. Currently serial imaging is used for risk stratification, which is not always reliable. On the other hand, understanding aortic haemodynamics within a dissection is essential to fully evaluate the disease and predict how it may progress. In recent decades, computational fluid dynamics (CFD) has been extensively applied to simulate complex haemodynamics within aortic diseases, and more recently, four-dimensional (4D)-flow magnetic resonance imaging (MRI) techniques have been developed for in vivo haemodynamic measurement. This paper presents a comprehensive review on the application of image-based CFD simulations and 4D-flow MRI analysis for risk prediction in aortic dissection. The key steps involved in patient-specific CFD analyses are demonstrated. Finally, we propose a workflow incorporating computational modelling for personalised assessment to aid in risk stratification and treatment decision-making.

Fluid-Structure Interaction Simulations of Repaired Type A Aortic Dissection: a Comprehensive Comparison With Rigid Wall Models

This study aimed to evaluate the effect of aortic wall compliance on intraluminal hemodynamics within surgically repaired type A aortic dissection (TAAD). Fully coupled two-way fluid-structure interaction (FSI) simulations were performed on two patient-specific post-surgery TAAD models reconstructed from computed tomography angiography images. Our FSI model incorporated prestress and different material properties for the aorta and graft. Computational results, including velocity, wall shear stress (WSS) and pressure difference between the true and false lumen, were compared between the FSI and rigid wall simulations. It was found that the FSI model predicted lower blood velocities and WSS along the dissected aorta. In particular, the area exposed to low time-averaged WSS ( ≤ 0.2   P a ) was increased from 21 cm2 (rigid) to 38 cm2 (FSI) in patient 1 and from 35 cm2 (rigid) to 144 cm2 (FSI) in patient 2. FSI models also produced more disturbed flow where much larger regions presented with higher turbulence intensity as compared to the rigid wall models. The effect of wall compliance on pressure difference between the true and false lumen was insignificant, with the maximum difference between FSI and rigid models being less than 0.25 mmHg for the two patient-specific models. Comparisons of simulation results for models with different Young's moduli revealed that a more compliant wall resulted in further reduction in velocity and WSS magnitudes because of increased displacements. This study demonstrated the importance of FSI simulation for accurate prediction of low WSS regions in surgically repaired TAAD, but a rigid wall computational fluid dynamics simulation would be sufficient for prediction of luminal pressure difference.