Numerical Insights for AAA Growth Understanding and Predicting: Morphological and Hemodynamic Risk Assessment Features and Transient Coherent Structures Uncovering

Les anévrismes de l'aorte abdominale (AAA) sont des dilatations localisées et fréquentes de l'aorte. En cas de rupture, seul un traitement immédiat peut prévenir la morbidité et la mortalité. Le diamètre maximal AAA ($D_{max}$) et la croissance sont les paramètres actuels pour évaluer le risque associé et planifier l'intervention, avec des seuils inférieurs pour les femmes. Cependant, ces critères ne sont pas personnalisés ; la rupture peut se produire à un diamètre inférieur et les patients vivre avec un AAA important. Si l'on sait que la maladie est associée à une modification de la morphologie et de la circulation sanguine, à un dépôt de thrombus intra-luminal et à des symptômes cliniques, les mécanismes de croissance ne sont pas encore entièrement compris. Dans cette étude longitudinale, une analyse morphologique et des simulations de flux sanguins sont effectuées et comparées aux sujets témoins chez 32 patients ayant reçu un diagnostic clinique d'AAA et au moins 3 tomodensitogrammes de suivi par patient. L'objectif est d'abord d'examiner quels paramètres stratifient les patients entre les groupes sains, à faible risque et à risque élevé. Les corrélations locales entre les paramètres hémodynamiques et la croissance de l'AAA sont également explorées, car la croissance hétérogène de l'AAA n'est actuellement pas comprise. Enfin, les paramètres composites sont construits à partir de données cliniques, morphologiques et hémodynamiques et de leur capacité à prédire si un patient sera soumis à un test de risque. La performance de ces modèles construits à partir de l'apprentissage supervisé est évaluée par les ROC AUC : ils sont respectivement de 0.73 ± 0.09, 0.93 ± 0.08 et 0.96 ± 0.10 . En incorporant tous les paramètres, on obtient une AUC de 0.98 ± 0.06. Pour mieux comprendre les interactions entre la croissance et la topologie de l'écoulement de l'AAA, on propose un worflow spécifique au patient pour calculer les exposants de Lyapunov en temps fini et extraire les structures lagrangiennes-cohérentes (SLC). Ce modèle de calcul a d'abord été comparé à l'imagerie par résonance magnétique (IRM) par contraste de phase 4-D chez 5 patients. Pour mieux comprendre l'impact de la topologie de l'écoulement et du transport sur la croissance de l'AAA, des SLC hyperboliques répulsives ont été calculées chez un patient au cours d'un suivi de 8 ans, avec 9 mesures morphologiques volumétriques de l'AAA par tomographie-angiographie. Les SLC ont défini les frontières du jet entrant dans l'AAA. Les domaines situés entre le SLC et le mur aortique ont été considérés comme des zones de stagnation. Leur évolution a été étudiée lors de la croissance de l'AAA. En plus des SLC hyperboliques (variétés attractives et répulsives) découvertes par FTLE, les SLC elliptiques ont également été considérées. Il s'agit de régions dominées par la rotation, ou tourbillons, qui sont de puissants outils pour comprendre les phénomènes de transport dans les AAA.Abdominal aortic aneurysms (AAA) are localized, commonly-occurring dilations of the aorta. In the event of rupture only immediate treatment can prevent morbidity and mortality. The AAA maximal diameter ($D_{max}$) and growth are the current metrics to evaluate the associated risk and plan intervention, with lower thresholds for women. However, these criteria lack patient specificity; rupture may occur at lower diameter and patients may live with large AAA. If the disease is known to be associated with altered morphology and blood flow, intra-luminal thrombus deposit and clinical symptoms, the growth mechanisms are yet to be fully understood. In this longitudinal study, morphological analysis and blood flow simulations for 32 patients with clinically diagnosed AAA and at least 3 follow-up CT-scans per patient, are performed and compared to control subjects. The aim is first to investigate which metrics stratify patients between healthy, low risk and high risk groups. Local correlations between hemodynamical metrics and AAA growth are also explored, as AAA heterogeneous growth is currently not understood. Finally, composite metrics are built from clinical, morphological, and hemodynamical data, and their ability to predict if a patient will become at risk tested. Performance of these models built from supervised learning is assessed by ROC AUCs: they are respectively, 0.73 ± 0.09, 0.93 ± 0.08 and 0.96 ± 0.10. Mixing all metrics, an AUC of 0.98 ± 0.06 is obtained. For further insights into AAA flow topology/growth interaction, a workout of patient-specific computational flow dynamics (CFD) is proposed to compute finite-time Lyapunov exponents and extract Lagrangian-coherent structures (LCS). This computational model was first compared with 4-D phase-contrast magnetic resonance imaging (MRI) on 5 patients. To better understand the impact of flow topology and transport on AAA growth, hyperbolic, repelling LCS were computed in 1 patient during 8-years follow-up, including 9 volumetric morphologic AAA measures by computed tomography-angiography (CTA). LCS defined barriers to Lagrangian jet cores entering AAA. Domains enclosed between LCS and the aortic wall were considered to be stagnation zones. Their evolution was studied during AAA growth. In addition to hyperbolic (attracting and repelling) LCS uncovered by FTLE, elliptic LCS were also considered. Those encloses rotation-dominated regions, or vortices, which are powerful tools to understand the flow transport in AAA

Biomechanic and Hemodynamic Perspectives in Abdominal Aortic Aneurysm Rupture Risk Assessment

Abdominal aortic aneurysms (AAAs) pose a significant source of mortality for the elderly, especially if they go on undetected and ultimately rupture. Therefore, elective repair of these lesions is recommended in order to avoid risk of rupture which is associated with high mortality. Currently, the risk of rupture and thus the indication to intervene is evaluated based on the size of the AAA as determined by its maximum diameter. Since AAAs actually present original geometric configurations and unique hemodynamic and biomechanic conditions, it is expected that other variables may affect rupture risk as well. This is the reason why the maximum diameter criterion has often been proven inaccurate. The biomechanical approach considers rupture as a material failure where the stresses exerted on the wall outweigh its strength. Therefore, rupture depends on the pointwise comparison of the stress and strength for every point of the aneurysmal surface. Moreover, AAAs hemodynamics play an essential role in AAAs natural history, progression and rupture. This chapter summarizes advances in AAAs rupture risk estimation beyond the “one size fits all” maximum diameter criterion

A cohort longitudinal study identifies morphology and hemodynamics predictors of abdominal aortic aneurysm growth

International audienceAbdominal aortic aneurysms (AAA) are localized, commonly occurring aortic dilations. Following rupture only immediate treatment can prevent morbidity and mortality. AAA maximal diameter and growth are the current metrics to evaluate the associated risk and plan intervention. Although these criteria alone lack patient specificity, predicting their evolution would improve clinical decision. If the disease is known to be associated with altered morphology and blood flow, intraluminal thrombus deposit and clinical symptoms, the growth mechanisms are yet to be fully understood. In this retrospective longitudinal study of 138 scans, morphological analysis and blood flow simulations for 32 patients with clinically diagnosed AAAs and several follow-up CT-scans, are performed and compared to 9 control subjects. Several metrics stratify patients between healthy, low and high risk groups. Local correlations between hemodynamic metrics and AAA growth are also explored but due to their high inter-patient variability, do not explain AAA heterogeneous growth. Finally, high-risk predictors trained with successively clinical, morphological, hemodynamic and all data, and their link to the AAA evolution are built from supervise learning. Predictive performance is high for morphological, hemodynamic and all data, in contrast to clinical data. The morphology-based predictor exhibits an interesting effort-predictability tradeoff to be validated for clinical translation

A hemodynamic analysis of energy loss in abdominal aortic aneurysm using three-dimension idealized model

Objective: The aim of this study is to perform specific hemodynamic simulations of idealized abdominal aortic aneurysm (AAA) models with different diameters, curvatures and eccentricities and evaluate the risk of thrombosis and aneurysm rupture.Methods: Nine idealized AAA models with different diameters (3 cm or 5 cm), curvatures (0° or 30°) and eccentricities (centered on or tangent to the aorta), as well as a normal model, were constructed using commercial software (Solidworks; Dassault Systemes S.A, Suresnes, France). Hemodynamic simulations were conducted with the same time-varying volumetric flow rate extracted from the literature and 3-element Windkessel model (3 EWM) boundary conditions were applied at the aortic outlet. Several hemodynamic parameters such as time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), endothelial cell activation potential (ECAP) and energy loss (EL) were obtained to evaluate the risk of thrombosis and aneurysm rupture under different conditions.Results: Simulation results showed that the proportion of low TAWSS region and high OSI region increases with the rising of aneurysm diameter, whereas decreases in the curvature and eccentric models of the corresponding diameters, with the 5 cm normal model having the largest low TAWSS region (68.5%) and high OSI region (40%). Similar to the results of TAWSS and OSI, the high ECAP and high RRT areas were largest in the 5 cm normal model, with the highest wall-averaged value (RRT: 5.18 s, ECAP: 4.36 Pa−1). Differently, the increase of aneurysm diameter, curvature, and eccentricity all lead to the increase of mean flow EL and turbulent EL, such that the highest mean flow EL (0.82 W · 10−3) and turbulent EL (1.72 W · 10−3) were observed in the eccentric 5 cm model with the bending angle of 30°.Conclusion: Collectively, increases in aneurysm diameter, curvature, and eccentricity all raise mean flow EL and turbulent flow EL, which may aggravate the damage and disturbance of flow in aneurysm. In addition, it can be inferred by conventional parameters (TAWSS, OSI, RRT and ECAP) that the increase of aneurysm diameter may raise the risk of thrombosis, whereas the curvature and eccentricity appeared to have a protective effect against thrombosis

IMPACT OF HEMODYNAMIC VORTEX SPATIAL AND TEMPORAL CHARACTERISTICS ON ANALYSIS OF INTRACRANIAL ANEURYSMS

Subarachnoid hemorrhage is a potentially devastating pathological condition in which bleeding occurs into the space surrounding the brain. One of the prominent sources of subarachnoid hemorrhage are intracranial aneurysms (IA): degenerative, irregular expansions of area(s) of the cerebral vasculature. In the event of IA rupture, the resultant subarachnoid hemorrhage ends in patient mortality occurring in ~50% of cases, with survivors enduring significant neurological damage with physical or cognitive impairment. The seriousness of IA rupture drives a degree of clinical interest in understanding these conditions that promote both the development and possible rupture of the vascular malformations. Current metrics for the assessment of this pathology rely on measuring the geometric characteristics of a patient\u27s vessel and/or IA, as well as the hemodynamic stressors existing along the vessel wall. Comparatively less focus has been granted toward understanding the characteristics of much of the bulk-flow within the vasculature and how it may play a role in IAs. Specifically, swirling hemodynamic flow (vortices) have been suggested as a condition which exacerbates vascular changes leading to IAs, yet quantified measurements of the spatial and temporal characteristics of vortices remain overlooked. This dissertation studies the role of the spatial and temporal characteristics of vortex flow and how it plays a role on IA pathology. Its chapters are a collection of five (5) works into this matter. First, established methods for the identification of vortices was investigated, and a novel method for vortex identification and quantification of their characteristics was developed to overcome the limitations of previous methods. Second, the developed method for vortex identification/quantification was then applied to a simulation study to improve predictive models aimed at predicting areas of IA development from those unlikely to suffer this pathology. Third, assessing how the simulated repair of one IA impacts changes to hemodynamic conditions within other nearby un-repaired IAs in a multiple IA system. Fourth, it was determined if vortex identification/quantification improved predictive models aimed at differentiation ruptured from unruptured IAs. Fifth, impart vortical flow of differing characteristics onto cultured vascular cells to determine if vortex stability imparts varied levels of cellular changes

New Insight into Cerebrovascular Diseases

“Brain circulation is a true road map that consists of large extended navigation territories and a number of unimagined and undiscovered routes.” Dr. Patricia Bozzetto Ambrosi This book combines an update on the review of cerebrovascular diseases in the form of textbook chapters, which has been carefully reviewed by Dr. Patricia Bozzetto Ambrosi, Drs. Rufai Ahmad and Auwal Abdullahi and Dr. Amit Agrawal, high-performance academic editors with extensive experience in neurodisciplines, including neurology, neurosurgery, neuroscience, and neuroradiology, covering the best standards of neurological practice involving basic and clinical aspects of cerebrovascular diseases. Each topic was carefully revised and prepared using smooth, structured vocabulary, plus superb graphics and scientific illustrations. In emphasizing the most common aspects of cerebrovascular diseases: stroke burden, pathophysiology, hemodynamics, diagnosis, management, repair, and healing, the book is comprehensive but concise and should become the standard reference guide for this neurological approach