Biomechanical changes during abdominal aortic aneurysm growth

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 non-invasive 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 (TAWSS), Oscillatory Shear Index (OSI), Endothelial Cell Activation Potential (ECAP), and Relative Residence Time (RRT). The primary methods employed for simulating the abdominal aorta and studying its biomechanical environment are Computational Fluid Dynamics (CFD) and Finite Element Methods (FEM). This review paper 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 Hemodynamics-Based Growth Prediction for Small Abdominal Aortic Aneurysms: Laminar Simulations Versus Large Eddy Simulations

Prior studies have shown that computational fluid dynamics (CFD) simulations help assess patient-specific hemodynamics in abdominal aortic aneurysms (AAAs); patient-specific hemodynamic stressors are frequently used to predict an AAA's growth. Previous studies have utilized both laminar and turbulent simulation models to simulate hemodynamics. However, the impact of different CFD simulation models on the predictive modeling of AAA growth remains unknown and is thus the knowledge gap that motivates this study. Specifically, CFD simulations were performed for 70 AAA models derived from 70 patients' computed tomography angiography (CTA) data with known growth status (i.e., fast-growing [> 5 mm/yr] or slowly growing [< 5 mm/yr]). We used laminar and large eddy simulation (LES) models to obtain hemodynamic parameters to predict AAAs' growth status. Predicting the growth status of AAAs was based on morphological, hemodynamic, and patient health parameters in conjunction with three classical machine learning (ML) classifiers, namely, support vector machine (SVM), K-nearest neighbor (KNN), and generalized linear model (GLM). Our preliminary results estimated aneurysmal flow stability and wall shear stress (WSS) were comparable in both laminar and LES flow simulations. Moreover, computed WSS and velocity-related hemodynamic variables obtained from the laminar and LES simulations showed comparable abilities in differentiating the growth status of AAAs. More importantly, the predictive modeling performance of the three ML classifiers mentioned above was similar, with less than a 2% difference observed (p-value > 0.05). In closing, our findings suggest that two different flow simulations investigated did not significantly affect outcomes of computational hemodynamics and predictive modeling of AAAs' growth status, given the data investigated.

The role of asymmetry and volume of thrombotic masses in the formation of local deformation of the aneurysmal-altered vascular wall: An in vivo study and mathematical modeling

Currently, the primary factor indicating the necessity of an operation for an abdominal aortic aneurysm (AAA) is the diameter at its widest part. However, in practice, a large number of aneurysm ruptures occur before reaching a critical size. This means that the mechanics of aneurysm growth and remodeling have not been fully elucidated. This study presents a novel method for assessing the elastic properties of an aneurysm using an ultrasound technique based on tracking the oscillations of the vascular wall as well as the inner border of the thrombus. Twenty nine patients with AAA and eighteen healthy volunteers were considered. The study presents the stratification of a group of patients according to the elastic properties of the aneurysm, depending on the relative volume of intraluminal thrombus masses. Additionally, the neural network analysis of CT angiography images of these patients shows direct (r = 0.664271) correlation with thrombus volume according to ultrasound data, the reliability of the Spearman correlation is p = 0.000215. The use of finite element numerical analysis made it possible to reveal the mechanism of the negative impact on the AAA integrity of an asymmetrically located intraluminal thrombus. The aneurysm itself is considered as a complex structure consisting of a wall, intraluminal thrombus masses, and areas of calcification. When the thrombus occupies > 70% of the lumen of the aneurysm, the deformations of the outer and inner surfaces of the thrombus have different rates, leading to tensile stresses in the thrombus. This poses a risk of its detachment and subsequent thromboembolism or the rupture of the aneurysm wall. This study is the first to provide a mechanistic explanation for the effects of an asymmetrical intraluminal thrombus in an abdominal aortic aneurysm. The obtained results will help develop more accurate risk criteria for AAA rupture using non-invasive conventional diagnostic methods.

Narrative Review of Risk Assessment of Abdominal Aortic Aneurysm Rupture Based on Biomechanics-Related Morphology

CLINICAL IMPACT

Studies have shown that the biomechanical indicators based on multi-scale models are more effective in accurately assessing the rupture risk of AAA. To meet the need for clinical monitoring and rapid decision making, the typical morphological parameters associated with AAA rupture and their relationships with the mechanical environment have been summarized, which provide a reference for clinical preoperative risk assessment of AAA.

A review on the biomechanical behaviour of the aorta

Large aortic aneurysm and acute and chronic aortic dissection are pathologies of the aorta requiring surgery. Recent advances in medical intervention have improved patient outcomes; however, a clear understanding of the mechanisms leading to aortic failure and, hence, a better understanding of failure risk, is still missing. Biomechanical analysis of the aorta could provide insights into the development and progression of aortic abnormalities, giving clinicians a powerful tool in risk stratification. The complexity of the aortic system presents significant challenges for a biomechanical study and requires various approaches to analyse the aorta. To address this, here we present a holistic review of the biomechanical studies of the aorta by categorising articles into four broad approaches, namely theoretical, in vivo, experimental and combined investigations. Experimental studies that focus on identifying mechanical properties of the aortic tissue are also included. By reviewing the literature and discussing drawbacks, limitations and future challenges in each area, we hope to present a more complete picture of the state-of-the-art of aortic biomechanics to stimulate research on critical topics. Combining experimental modalities and computational approaches could lead to more comprehensive results in risk prediction for the aortic system.

Three-dimensional growth and biomechanical risk progression of abdominal aortic aneurysms under serial computed tomography assessment

Growth of abdominal aortic aneurysms (AAAs) is often described as erratic and discontinuous. This study aimed at describing growth patterns of AAAs with respect to maximal aneurysm diameter (Dmax) and aneurysm volume, and to characterize changes in the intraluminal thrombus (ILT) and biomechanical indices as AAAs grow. 384 computed tomography angiographies (CTAs) from 100 patients (mean age 70.0, standard deviation, SD = 8.5 years, 22 women), who had undergone at least three CTAs, were included. The mean follow-up was 5.2 (SD = 2.5) years. Growth of Dmax was 2.64 mm/year (SD = 1.18), volume 13.73 cm³/year (SD = 10.24) and PWS 7.3 kPa/year (SD = 4.95). For Dmax and volume, individual patients exhibited linear growth in 87% and 77% of cases. In the tertile of patients with the slowest Dmax-growth (< 2.1 mm/year), only 67% belonged to the slowest tertile for volume-growth, and 52% and 55% to the lowest tertile of PWS- and PWRI-increase, respectively. The ILT-ratio (ILT-volume/aneurysm volume) increased with time (2.6%/year, p < 0.001), but when adjusted for volume, the ILT-ratio was inversely associated with biomechanical stress. In contrast to the notion that AAAs grow in an erratic fashion most AAAs displayed continuous and linear growth. Considering only change in Dmax, however, fails to capture the biomechanical risk progression, and parameters such as volume and the ILT-ratio need to be considered.

Platelets at the Vessel Wall in Non-Thrombotic Disease

Platelets are small, anucleate entities that bud from megakaryocytes in the bone marrow. Among circulating cells, platelets are the most abundant cell, traditionally involved in regulating the balance between thrombosis (the terminal event of platelet activation) and hemostasis (a protective response to tissue injury). Although platelets lack the precise cellular control offered by nucleate cells, they are in fact very dynamic cells, enriched in preformed RNA that allows them the capability of de novo protein synthesis which alters the platelet phenotype and responses in physiological and pathological events. Antiplatelet medications have significantly reduced the morbidity and mortality for patients afflicted with thrombotic diseases, including stroke and myocardial infarction. However, it has become apparent in the last few years that platelets play a critical role beyond thrombosis and hemostasis. For example, platelet-derived proteins by constitutive and regulated exocytosis can be found in the plasma and may educate distant tissue including blood vessels. First, platelets are enriched in inflammatory and anti-inflammatory molecules that may regulate vascular remodeling. Second, platelet-derived microparticles released into the circulation can be acquired by vascular endothelial cells through the process of endocytosis. Third, platelets are highly enriched in mitochondria that may contribute to the local reactive oxygen species pool and remodel phospholipids in the plasma membrane of blood vessels. Lastly, platelets are enriched in proteins and phosphoproteins which can be secreted independent of stimulation by surface receptor agonists in conditions of disturbed blood flow. This so-called biomechanical platelet activation occurs in regions of pathologically narrowed (atherosclerotic) or dilated (aneurysmal) vessels. Emerging evidence suggests platelets may regulate the process of angiogenesis and blood flow to tumors as well as education of distant organs for the purposes of allograft health following transplantation. This review will illustrate the potential of platelets to remodel blood vessels in various diseases with a focus on the aforementioned mechanisms.

Effect of Sac Asymmetry, Neck and Iliac Angle on the Hemodynamic Behavior of Idealized Abdominal Aortic Aneurysm Geometries

BACKGROUND

Abdominal aortic aneurysms (AAAs) are currently treated based on the universal maximum diameter criterion, but other geometric variables may play a role in the risk of rupture. The hemodynamic environment inside the AAA sac has been shown to interact with several biologic processes which can affect prognosis. AAA geometric configuration has a significant impact in the hemodynamic conditions that develop, which has only been recently realized, with implications for rupture risk estimations. We aim to perform a parametric study to evaluate the effect of aortic neck angulation, angle between the iliac arteries, and sac asymmetry (SA) on the hemodynamic variables of AAAs.

METHODS

This study uses idealized AAA models and it is parametrized in terms of 3 quantities as follows: the neck angle, φ (°), iliac angle, θ (°), and SA (%), each of which accepts 3 different values, specifically φ = (0°, 30°, 60°), θ = (40°, 60°, 80°), and SA = (S, °SS, °OS), where the SA can either be on the same side with respect to neck (SS) or on the opposite side (OS). Time average wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and the velocity profile are calculated for different geometric configurations, while the percentage of the total surface area under thrombogenic conditions, using thresholds previously reported in the literature, is also recorded.

RESULTS

In case of an angulated neck and a higher angle between iliac arteries, favorable hemodynamic conditions are predicted with higher TAWSS and lower OSI and RRT values. The area under thrombogenic conditions reduces by 16-46% as the neck angle increases from 0° to 60°, depending on the hemodynamic variable under consideration. The effect of iliac angulation is present but less pronounced with 2.5-7.5% change between the lower and the higher angle. The effect of SA seems to be significant for OSI, with a nonsymmetrical configuration being hemodynamically favorable, which in the presence of an angulated neck is more pronounced for the OS outline.

CONCLUSIONS

Favorable hemodynamic conditions develop inside the sac of idealized AAAs with increasing neck and iliac angles. Regarding the SA parameter, asymmetrical configurations most often appear advantageous. Concerning the velocity profile the triplet (φ, θ, SA) may affect outcomes under certain conditions and thus should be taken into account when parametrizing the geometric characteristics of AAAs.

A systematic review summarizing local vascular characteristics of aneurysm wall to predict for progression and rupture risk of abdominal aortic aneurysms

OBJECTIVE

At present, the rupture risk prediction of abdominal aortic aneurysms (AAAs) and, hence, the clinical decision making regarding the need for surgery, is determined by the AAA diameter and growth rate. However, these measures provide limited predictive information. In the present study, we have summarized the measures of local vascular characteristics of the aneurysm wall that, independently of AAA size, could predict for AAA progression and rupture.

METHODS

We systematically searched PubMed and Web of Science up to September 13, 2021 to identify relevant studies investigating the relationship between local vascular characteristics of the aneurysm wall and AAA growth or rupture in humans. A quality assessment was performed using the ROBINS-I (risk of bias in nonrandomized studies of interventions) tool. All included studies were divided by four types of measures of arterial wall characteristics: metabolism, calcification, intraluminal thrombus, and compliance.

RESULTS

A total of 20 studies were included. Metabolism of the aneurysm wall, especially when measured by ultra-small superparamagnetic iron oxide uptake, and calcification were significantly related to AAA growth. A higher intraluminal thrombus volume and thickness had correlated positively with the AAA growth in one study but in another study had correlated negatively. AAA compliance demonstrated no correlation with AAA growth and rupture. The aneurysmal wall characteristics showed no association with AAA rupture. However, the metabolism, measured via ultra-small superparamagnetic iron oxide uptake, but none of the other measures, showed a trend toward a relationship with AAA rupture, although the difference was not statistically significant.

CONCLUSIONS

The current measures of aortic wall characteristics have the potential to predict for AAA growth, especially the measures of metabolism and calcification. Evidence regarding AAA rupture is scarce, and, although more work is needed, aortic wall metabolism could potentially be related to AAA rupture. This highlights the role of aortic wall characteristics in the progression of AAA but also has the potential to improve the prediction of AAA growth and rupture.

Rupture risk parameters upon biomechanical analysis independently change from vessel geometry during abdominal aortic aneurysm growth

Objective

The indication for abdominal aortic aneurysm (AAA) repair is based on a diameter threshold. However, mechanical properties, such as peak wall stress (PWS) and peak wall rupture index (PWRI), influence the individual rupture risk. This study aims to correlate biomechanical and geometrical AAA characteristics during aneurysm growth applying a new linear transformation-based comparison of sequential imaging.

Methods

Patients with AAA with two sequential computed tomography angiographies (CTA) were identified from a single-center aortic database. Patient characteristics included age, gender, and comorbidities. Semiautomated segmentation of CTAs was performed using Endosize (Therenva) for geometric variables (diameter, neck configuration, α/β angle, and vessel tortuosity) and for finite element method A4 Clinics Research Edition (Vascops) for additional variables (intraluminal thrombus [ILT]), vessel volume, PWS, PWRI). Maximum point coordinates from at least one CTA 6 to 24 months before their final were predicted for the final preoperative CTA using linear transformation along fix and validation points to estimate spatial motion. Pearson's correlation and the t test were used for comparison.

Results

Thirty-two eligible patients (median age, 70 years) were included. The annual AAA growth rate was 3.7 mm (interquartile range [IQR], 2.25-5.44; P < .001) between CTs. AAA (+17%; P < .001) and ILT (+43%; P < .001) volume, maximum ILT thickness (+35%; P < .001), β angle (+1.96°; P = .017) and iliac tortuosity (+0.009; P = .012) increased significantly. PWS (+12%; P = .0029) and PWRI (+16%; P < .001) differed significantly between both CTAs. Both mechanical parameters correlated most significantly with the AAA volume increase (r = 0.68 [P < .001] and r = 0.6 [P < .001]). Changes in PWS correlated best with the aneurysm neck configuration. The spatial motion of maximum ILT thickness was 14.4 mm (IQR, 7.3-37.2), for PWS 8.4 mm (IQR, 3.8-17.3), and 11.5 mm (IQR, 5.9-31.9) for PWRI. Here, no significant correlation with any of the aforementioned parameters, patient age, or time interval between CTs were observed.

Conclusions

PWS correlates highly significant with vessel volume and aneurysm neck configuration. Spatial motion of maximum ILT thickness, PWS, and PWRI is detectable and predictable and might expose different aneurysm wall segments to maximum stress throughout aneurysm growth. Linear transformation could thus add to patient-specific rupture risk analysis.

Clinical Relevance

Abdominal aortic aneurysm rupture risk assessment is a key feature in future individualized therapy approaches for patients, since more and more data are obtained concluding a heterogeneous disease entity that might not be addressed ideally looking only at diameter enlargement. The approach presented in this pilot study demonstrates the feasibility and importance of measuring peak wall stress and rupture risk indices based on predicted and actual position of maximum stress points including intraluminal thrombus.

Cohort Study Examining the Association of Optimal Blood Pressure Control at Entry With Infrarenal Abdominal Aortic Aneurysm Growth

Background and Aim

The benefit of controlling cardiovascular risk factors in slowing the progression of small abdominal aortic aneurysm (AAA) is controversial. This study investigated the association of optimal blood pressure control at entry with the growth of small AAA.

Methods and Results

A total of 1,293 patients with initial AAA diameter <50 mm were followed by a median 5 (inter-quartile range, IQR, 3–7) ultrasound scans for a median of 3.6 years (IQR 1.8, 5.3). Optimal blood pressure control was defined as blood pressure ≤140/90 mmHg at recruitment. The association of optimal blood pressure control at entry with AAA growth was assessed using linear mixed effects models adjusted for established risk factors of AAA growth and factors which were unequally distributed among the blood pressure groups. Optimal blood pressure control at entry was not significantly associated with AAA growth. In the risk factor adjusted model the mean difference in AAA growth between blood pressure groups was 0.04 mm/year (95% CI −0.20, 0.13; p = 0.65). The results were similar in sensitivity analyses excluding outliers or focused on systolic or diastolic blood pressure alone.

Conclusions

This observational study suggests that optimal blood pressure control at entry is not associated with slower AAA growth.

Combined Curvature and Wall Shear Stress Analysis of Abdominal Aortic Aneurysm: An Analysis of Rupture Risk Factors

PURPOSE

To discuss the risk factors for abdominal aortic aneurysm rupture based on geometric and hemodynamic parameters.

METHODS

We retrospectively reviewed the clinical data of those who were diagnosed with an abdominal aortic aneurysm by computed tomography angiography at our hospital between October 2019 and December 2020. Thirty-five patients were included in the ruptured group (13 patients) and the unruptured group (22 patients). We analyzed the differences and correlations of anatomical factors and hemodynamic parameters between the two groups using computational fluid dynamics based on computed tomography angiography.

RESULTS

There were significant differences in the maximum diameter [(79.847 ± 10.067) mm vs. (52.320 ± 14.682) mm, P < 0.001], curvature [(0.139 ± 0.050) vs. 0.080 (0.123 - 0.068), P = 0.021], and wall shear stress at the site of maximal blood flow impact [0.549(0.839 - 0.492) Pa vs. (1.378 ± 0.255) Pa, P < 0.001] between the ruptured and unruptured groups, respectively. And in the ruptured group, wall shear stress at the rupture site was significantly different from that at the site of maximal blood flow impact [0.025 (0.049 - 0.018) Pa vs. 0.549 (0.839 - 0.492) Pa, P = 0.001]. Then, the maximum diameter and curvature were associated with rupture (maximum diameter: OR: 1.095, P = 0.003; curvature: OR: 1.142E + 10, P = 0.012). Most importantly, curvature is negatively correlated with wall shear stress (r = - 0.366, P = 0.033).

CONCLUSIONS

Both curvature and wall shear stress can evaluate the rupture risk of aneurysm. Also, curvature can be used as the geometric substitution of wall shear stress.

Pharmacotherapy in Clinical Trials for Abdominal Aortic Aneurysms: A Systematic Review and Meta-Analysis

OBJECTIVE

There is no medical treatment proven to limit abdominal aortic aneurysm (AAA) progression. This systematic review aimed to summarise available trial evidence on the efficacy of pharmacotherapy in limiting AAA growth and AAA-related events.

METHODS

A systematic literature search was performed to examine the efficacy of pharmacotherapy in reducing AAA growth and AAA-related events. Pubmed, Embase (Excerpta Medica Database), and the Cochrane library were searched from March, 1999 to March 29, 2022. AAA growth (mm/year) in the intervention and control groups was expressed as mean and standard deviation (SD). The results of AAA growth were expressed as mean difference (MD) and its 95% confidence interval (95% CI). Odds ratios (ORs) were calculated for the AAA-related events.Heterogeneity was quantified using the I² statistic. Forest plots were created to show the pooled results of each outcome.

OUTCOMES

A total of 1373 articles were found in different databases according to the search strategy, and 10 articles were identified by hand searching. A total of 26 articles were included in our systematic review after the screening. For the studies of metformin, the meta-analysis demonstrated that metformin use was associated with a lower AAA growth rate (MD: -0.81 mm/y, 95% CI: -1.19 to -0.42, P < 0.0001, I² = 87%), Metformin use also was related to the lower rates of AAA-related events (OR: 0.53, 95% CI: 0.36 to 0.76, P = 0.0007, I² = 60%). The hypotensive drugs of the studies mainly included angiotensin-converting enzyme inhibitors (ACEI), angiotensin II type 1 receptor blockers (ARB), and propranolol. The overall meta-analysis of blood pressure-lowering drugs reported no significant effect in limiting the AAA growth (MD: 0.31mm/year, 95%CI: -0.03 to 0.65, P = 0.07, I² = 66%) and AAA-related events (OR: 1.33, 95%CI: 0.76 to 2.32, P = 0.32, I² = 98%), In the subgroup analysis of the hypotensive drugs, the ACEI/ARB and propranolol also showed no significant in reducing the AAA growth and AAA-related events. The meta-analysis of the antibiotics demonstrated that the antibiotics were not associated with a lower AAA growth rate (MD: -0.27 mm/y, 95% CI: -0.88 to 0.34, P = 0.39, I² = 77%) and AAA-related events (OR: 0.94, 95%CI: 0.65 to 1.35, P = 0.72, I² = 0%). The results of statins also showed no significant effect in limiting AAA growth (MD: -1.11mm/year, 95%CI: -2.38 to 0.16, P = 0.09, I² = 96%) and AAA-related events (OR: 0.53, 95%CI: 0.26 to 1.06, P = 0.07, I² = 92%).

CONCLUSION

In conclusion, effective pharmacotherapy for AAA was still lacking. Although the meta-analysis showed that metformin use was associated with lower AAA growth and AAA-related events, all of the included studies about metformin were cohort studies or case-control studies. More randomized controlled trials (RCTs) are needed for further verification.

Assessment of the Global and Regional Circumferential Strain of Abdominal Aortic Aneurysm with Different Size by Speckle-Tracking Echocardiography

OBJECTIVES

We aimed to use speckle-tracking echocardiography (STE) to quantify circumferential aortic strain of abdominal aortic aneurysms (AAA) with different size.

METHODS

A total of 87 AAA patients were included. The morphological variables, including aortic maximum diameter (MD), end systolic area (ESA), end diastolic area (EDA), and thickness and area of intraluminal thrombus (ILT), were measured by ultrasound. STE was applied to calculate circumferential strain (CS) at 6 equally divided segments of the aorta at MD. We evaluated the mean value of peak strain along the 6 segments as global circumferential strain (GCS).

RESULTS

Large AAA (≥5.5 cm) patients had higher MD, ESA, EDA, AAA length, ILT thickness, and area, but lower fractional area change, GCS, and segmental CSs than small AAA (<5.5 cm) subjects (all P < .05). Compared with AAA <4.5 cm group, AAA patients ≥4.5 cm possessed increased MD, ESA, EDA, AAA length, ILT thickness, and area, which results were also reflected in the comparison between AAA <6.5 and ≥6.5 cm group. In small AAA patients, GCS and regional strains in CS1, CS3, and CS5 segments were lower in AAA subjects ≥4.5 cm than those <4.5 cm (all P<.05). However, no significant differences in the GCS and regional CS between ≥6.5 and <6.5 cm group were found. Correlation analysis revealed a significant negative association of GCS with MD, ESA, and EDA, even after adjusting the potential confounding factors (all P < .05).

CONCLUSIONS

Our findings may yield insight into the structural strain characteristics of AAA wall with different size, which adds the benefit of using simple echocardiography-derived biomechanics to stratify AAA patients.

Stress Analysis in AAA does not Predict Rupture Location Correctly in Patients with Intraluminal Thrombus

BACKGROUND

A biomechanical approach to the rupture risk of an abdominal aortic aneurysm could be a solution to ensure a personalized estimate of this risk. It is still difficult to know in what conditions, the assumptions made by biomechanics, are valid. The objective of this work was to determine the individual biomechanical rupture threshold and to assess the correlation between their rupture sites and the locations of their maximum stress comparing two computed tomography scan (CT) before and at time of rupture.

METHODS

We included 5 patients who had undergone two CT; one within the last 6 months period before rupture and a second CT scan just before the surgical procedure for the rupture. All DICOM data, both pre- and rupture, were processed following the same following steps: generation of a 3D geometry of the abdominal aortic aneurysm, meshing and computational stress analysis using the finite element method. We used two different modelling scenarios to study the distribution of the stresses, a "wall" model without intraluminal thrombus (ILT) and a "thrombus" model with ILT.

RESULTS

The average time between the pre-rupture and rupture CT scans was 44 days (22-97). The median of the maximum stresses applied to the wall between the pre-rupture and rupture states were 0.817 MPa (0.555-1.295) and 1.160 MPa (0.633-1.625) for the "wall" model; and 0.365 MPa (0.291-0.753) and 0.390 MPa (0.343-0.819) for the "thrombus" model. There was an agreement between the site of rupture and the location of maximum stress for only 1 patient, who was the only patient without ILT.

CONCLUSIONS

We observed a large variability of stress values at rupture sites between patients. The rupture threshold strongly varied between individuals depending on the intraluminal thrombus. The site of rupture did not correlate with the maximum stress except for 1 patient.

Geometric and biomechanical modeling aided by machine learning improves the prediction of growth and rupture of small abdominal aortic aneurysms

It remains difficult to predict when which patients with abdominal aortic aneurysm (AAA) will require surgery. The aim was to study the accuracy of geometric and biomechanical analysis of small AAAs to predict reaching the threshold for surgery, diameter growth rate and rupture or symptomatic aneurysm. 189 patients with AAAs of diameters 40-50 mm were included, 161 had undergone two CTAs. Geometric and biomechanical variables were used in prediction modelling. Classifications were evaluated with area under receiver operating characteristic curve (AUC) and regressions with correlation between observed and predicted growth rates. Compared with the baseline clinical diameter, geometric-biomechanical analysis improved prediction of reaching surgical threshold within four years (AUC 0.80 vs 0.85, p = 0.031) and prediction of diameter growth rate (r = 0.17 vs r = 0.38, p = 0.0031), mainly due to the addition of semiautomatic diameter measurements. There was a trend towards increased precision of volume growth rate prediction (r = 0.37 vs r = 0.45, p = 0.081). Lumen diameter and biomechanical indices were the only variables that could predict future rupture or symptomatic AAA (AUCs 0.65-0.67). Enhanced precision of diameter measurements improves the prediction of reaching the surgical threshold and diameter growth rate, while lumen diameter and biomechanical analysis predicts rupture or symptomatic AAA.

MiR-137 regulates low-intensity shear stress-induced human aortic endothelial cell apoptosis via JNK/AP-1 signaling

The objective of this study is to evaluate the role of miR-137 in low-intensity shear stress-induced endoplasmic reticulum (ER) stress and cell apoptosis in human aortic endothelial cells (HAECs). HAECs were transfected with miR-137 mimic, miR-137 inhibitor, or the corresponding negative control and then exposed to pulsatile shear stress in a parallel-plate flow chamber at 1, 2, 5, 10, and 15 dyn/cm² for 3 h. Real-time polymerase chain reaction was used to detect mRNA expression of miR-137 and SDS22. A dual-luciferase reporter assay was employed to verify the direct interaction between miR-137 and SDS22. The internal morphology of cells and cell apoptosis was assessed by TUNEL staining observed under a transmission electron microscope. Meanwhile, the protein expression of oxidative stress-related, apoptosis-related, and activated c-Jun N-terminal kinase (JNK)/activator protein-1 (AP-1) signaling-related genes were analyzed by western blotting. Low strength shear stress (0-5 dyn/cm²) caused a negative change of HAEC surface and internal morphology in an intensity-dependent manner, and these changes were gradually weakened when shear stress was increased more than 5 dyn/cm². Furthermore, low-intensity shear stress promoted oxidative stress response, accelerated cell apoptosis, and upregulated miR-137 expression and JNK/AP-1 signaling in HAECs. MiR-137 directly targets SDS22. Knockdown of miR-137 noticeably reduced activation of JNK/AP-1 signaling, oxidative stress response, and cell apoptosis induced by shear stress. MiR-137 regulated low-intensity shear stress-induced human aortic endothelial cell ER stress and cell apoptosis via JNK/AP-1 signaling.

Systematic Review and Meta-Analysis of Peak Wall Stress and Peak Wall Rupture Index in Ruptured and Asymptomatic Intact Abdominal Aortic Aneurysms

Background Prior studies have suggested aortic peak wall stress (PWS) and peak wall rupture index (PWRI) can estimate the rupture risk of an abdominal aortic aneurysm (AAA), but whether these measurements have independent predictive ability over assessing AAA diameter alone is unclear. The aim of this systematic review was to compare PWS and PWRI in participants with ruptured and asymptomatic intact AAAs of similar diameter. Methods and Results Web of Science, Scopus, Medline, and The Cochrane Library were systematically searched to identify studies assessing PWS and PWRI in ruptured and asymptomatic intact AAAs of similar diameter. Random-effects meta-analyses were performed using inverse variance-weighted methods. Leave-one-out sensitivity analyses were conducted to assess the robustness of findings. Risk of bias was assessed using a modification of the Newcastle-Ottawa scale and standard quality assessment criteria for evaluating primary research papers. Seven case-control studies involving 309 participants were included. Meta-analyses suggested that PWRI (standardized mean difference, 0.42; 95% CI, 0.14-0.70; P=0.004) but not PWS (standardized mean difference, 0.13; 95% CI, -0.18 to 0.44; P=0.418) was greater in ruptured than intact AAAs. Sensitivity analyses suggested that the findings were not dependent on the inclusion of any single study. The included studies were assessed to have a medium to high risk of bias. Conclusions Based on limited evidence, this study suggested that PWRI, but not PWS, is greater in ruptured than asymptomatic intact AAAs of similar maximum aortic diameter.

Development of an FEA framework for analysis of subject-specific aortic compliance based on 4D flow MRI

This paper presents a subject-specific in-silico framework in which we uncover the relationship between the spatially varying constituents of the aorta and the non-linear compliance of the vessel during the cardiac cycle uncovered through our MRI investigations. A microstructurally motivated constitutive model is developed, and simulations reveal that internal vessel contractility, due to pre-stretched elastin and actively generated smooth muscle cell stress, must be incorporated, along with collagen strain stiffening, in order to accurately predict the non-linear pressure-area relationship observed in-vivo. Modelling of elastin and smooth muscle cell contractility allows for the identification of the reference vessel configuration at zero-lumen pressure, in addition to accurately predicting high- and low-compliance regimes under a physiological range of pressures. This modelling approach is also shown to capture the key features of elastin digestion and SMC activation experiments. The volume fractions of the constituent components of the aortic material model were computed so that the in-silico pressure-area curves accurately predict the corresponding MRI data at each location. Simulations reveal that collagen and smooth muscle volume fractions increase distally, while elastin volume fraction decreases distally, consistent with reported histological data. Furthermore, the strain at which collagen transitions from low to high stiffness is lower in the abdominal aorta, again supporting the histological finding that collagen waviness is lower distally. The analyses presented in this paper provide new insights into the heterogeneous structure-function relationship that underlies aortic biomechanics. Furthermore, this subject-specific MRI/FEA methodology provides a foundation for personalised in-silico clinical analysis and tailored aortic device development. STATEMENT OF SIGNIFICANCE: This study provides a significant advance in in-silico medicine by capturing the structure/function relationship of the subject-specific human aorta presented in our previous MRI analyses. A physiologically based aortic constitutive model is developed, and simulations reveal that internal vessel contractility must be incorporated, along with collagen strain stiffening, to accurately predict the in-vivo non-linear pressure-area relationship. Furthermore, this is the first subject-specific model to predict spatial variation in the volume fractions of aortic wall constituents. Previous studies perform phenomenological hyperelastic curve fits to medical imaging data and ignore the prestress contribution of elastin, collagen, and SMCs and the associated zero-pressure reference state of the vessel. This novel MRI/FEA framework can be used as an in-silico diagnostic tool for the early stage detection of aortic pathologies.

Mechanical characterization of abdominal aortas using multi-perspective ultrasound imaging

Mechanical characterization of abdominal aortic aneurysms using personalized biomechanical models is being widely investigated as an alternative criterion to assess risk of rupture. These methods rely on accurate wall motion detection and appropriate model boundary conditions. In this study, multi-perspective ultrasound is combined with finite element models to perform mechanical characterization of abdominal aortas in volunteers. Multi-perspective biplane radio frequency ultrasound recordings were made under seven angles (-45° to 45°) in one phantom set-up and eight volunteers, which were merged using automatic image registration. 2-D displacement fields were estimated in the seven longitudinal ultrasound views, creating a sparse, high resolution 3-D map of the wall motion at relatively high frame rates (20-27 Hz). The displacements were used to personalize the subject-specific finite element model of which the geometry of the aorta, spine, and surrounding tissue were determined from a single 3-D ultrasound acquisition. Automatic registration of the multi-perspective images was successful in six out of eight cases with an average error of 5.4° compared to the ground truth. Displacements of the aortic wall were measured and cyclic strain of the aortic diameter was found ranging from 4.2% to 8.6%. The subject-specific mesh and inverse FE analysis was performed yielding shear moduli estimates for the wall between 104 and 215 kPa. Comparative results from a single-perspective workflow revealed very low aortic wall motion signal, which resulted in relatively high modulus estimates, between 230 and 754 kPa. Multi-perspective biplane ultrasound imaging was used to personalize finite element models of the abdominal aorta and its surroundings, and performing mechanical characterization of the aortic shear modulus. The method was found to be a more robust method compared to a single-perspective 3-D ultrasound approach. Future research will focus on investigating the use of multiple 3-D ultrasound acquisitions, the feasibility of free-hand scanning, the creation of a full 3-D automatic registration process, and with that, enable a clinical continuation of this study.

Heterogeneity of Ex Vivo and In Vivo Properties along the Length of the Abdominal Aortic Aneurysm

The current clinical guidelines for the management of aortic abdominal aneurysms (AAAs) overlook the structural and mechanical heterogeneity of the aortic tissue and its role in the regional weakening that drives disease progression. This study is a comprehensive investigation of the structural and biomechanical heterogeneity of AAA tissue along the length and circumference of the aorta, by means of regional ex vivo and in vivo properties. Biaxial testing and histological analysis were performed on ex vivo human aortic specimens systematically collected during open repair surgery. Wall-shear stress and three-dimensional principal strain analysis were performed to allow for in vivo regional characterization of individual aortas. A marked effect of position along the aortic length was observed in both ex vivo and in vivo properties, with the central regions corresponding to the aneurysmal sac being significantly different from the adjacent regions. The heterogeneity along the circumference of the aorta was reflected in the ex vivo biaxial response at low strains and histological properties. Present findings uniquely show the importance of regional characterization for aortic assessment and the need to correlate heterogeneity at the tissue level with non-invasive measurements aimed at improving clinical outcomes.

Methodology for Estimation of Annual Risk of Rupture for Abdominal Aortic Aneurysm

BACKGROUND AND OBJECTIVE

Estimating patient specific annual risk of rupture of abdominal aortic aneurysm (AAA) is currently based only on population. More accurate knowledge based on patient specific data would allow surgical treatment of only those AAAs with significant risk of rupture. This would be beneficial for both patients and health care system.

METHODS

A methodology for estimating annual risk of rupture (EARR) of abdominal aortic aneurysms (AAA) that utilizes Bayesian statistics, mechanics and patient-specific blood pressure monitoring data is proposed. EARR estimation takes into consideration, peak wall stress in AAA computed by patient-specific finite element modeling, the probability distributions of wall thickness, wall strength, systolic blood pressure and the period of time that the patient is known to have already survived with the intact AAA. Initial testing of proposed approach was performed on fifteen patients with intact AAA (mean maximal diameter 51mm±8mm). They were equipped with a pressure holter and their blood pressure was recorded over 24 hours. Then, we calculated EARR values for four possible scenarios - without considering any days of survival prior identification of AAA at computed tomography scans (EARR_0), considering past survival of 30 (EARR_30), 90 (EARR_90) and 180 days (EARR_180). Finally, effect of patient-specific blood pressure variability was analyzed.

RESULTS

Consideration of past survival does indeed significantly improve predictions of future risk: EARR_30 (1.04%± 0.87%), EARR_90 (0.67%± 0.56%) and EARR_180 (0.47%± 0.39%) which are unrealistically high otherwise (EARR_0 5.02%± 5.24%). Finally, EARR values were observed to vary by an order as a consequence of blood pressure variability and by factor of two as a consequence of neglected growth.

CONCLUSIONS

Methodology for computing annual risk of rupture of AAA was developed for the first time. Sensitivity analyses showed respecting patient specific blood pressure is important factor and should be included in the AAA rupture risk assessment. Obtained EARR values were generally low and in good agreement with confirmed survival time of investigated patients so proposed method should be further clinically validated.

Linking Aortic Mechanical Properties, Gene Expression and Microstructure: A New Perspective on Regional Weakening in Abdominal Aortic Aneurysms

Background: Current clinical practice for the assessment of abdominal aortic aneurysms (AAA) is based on vessel diameter and does not account for the multifactorial, heterogeneous remodeling that results in the regional weakening of the aortic wall leading to aortic growth and rupture. The present study was conducted to determine correlations between a novel non-invasive surrogate measure of regional aortic weakening and the results from invasive analyses performed on corresponding ex vivo aortic samples. Tissue samples were evaluated to classify local wall weakening and the likelihood of further degeneration based on non-invasive indices.

Methods: A combined, image-based fluid dynamic and in-vivo strain analysis approach was used to estimate the Regional Aortic Weakness (RAW) index and assess individual aortas of AAA patients prior to elective surgery. Nine patients were treated with complete aortic resection allowing the systematic collection of tissue samples that were used to determine regional aortic mechanics, microstructure and gene expression by means of mechanical testing, microscopy and transcriptomic analyses.

Results: The RAW index was significantly higher for samples exhibiting lower mechanical strength (p = 0.035) and samples classified as low elastin content (p = 0.020). Samples with higher RAW index had the greatest number of genes differentially expressed compared to any constitutive metric. High RAW samples showed a decrease in gene expression for elastin and a down-regulation of pathways responsible for cell movement, reorganization of cytoskeleton, and angiogenesis.

Conclusions: This work describes the first AAA index free of assumptions for material properties and accounting for patient-specific mechanical behavior in relation to aneurysm strength. Use of the RAW index captured biomechanical changes linked to the weakening of the aorta and revealed changes in microstructure and gene expression. This approach has the potential to provide an improved tool to aid clinical decision-making in the management of aortic pathology.

Biomechanical rupture risk assessment of abdominal aortic aneurysms using clinical data: A patient-specific, probabilistic framework and comparative case-control study

We present a data-informed, highly personalized, probabilistic approach for the quantification of abdominal aortic aneurysm (AAA) rupture risk. Our novel framework builds upon a comprehensive database of tensile test results that were carried out on 305 AAA tissue samples from 139 patients, as well as corresponding non-invasively and clinically accessible patient-specific data. Based on this, a multivariate regression model is created to obtain a probabilistic description of personalized vessel wall properties associated with a prospective AAA patient. We formulate a probabilistic rupture risk index that consistently incorporates the available statistical information and generalizes existing approaches. For the efficient evaluation of this index, a flexible Kriging-based surrogate model with an active training process is proposed. In a case-control study, the methodology is applied on a total of 36 retrospective, diameter matched asymptomatic (group 1, n = 18) and known symptomatic/ruptured (group 2, n = 18) cohort of AAA patients. Finally, we show its efficacy to discriminate between the two groups and demonstrate competitive performance in comparison to existing deterministic and probabilistic biomechanical indices.

Effect of blood pressure lowering drugs and antibiotics on abdominal aortic aneurysm growth: a systematic review and meta-analysis

OBJECTIVE

There is currently no medical treatment proven to limit abdominal aortic aneurysm (AAA) progression. The aim of this systematic review and meta-analysis was to pool data from previous randomised controlled trials assessing the efficacy of blood pressure-lowering and antibiotic medications in limiting AAA growth and AAA-related events, that is, rupture or repair.

METHODS

A systematic literature search was performed to identify randomised controlled trials that examined the efficacy of blood pressure-lowering medications or antibiotics in reducing AAA growth and AAA-related events. AAA growth (mm/year) was measured by ultrasound or computed tomography imaging. Meta-analyses were performed using random effects models. A subanalysis was conducted including trials that investigated tetracycline or macrolide antibiotics.

RESULTS

Ten randomised controlled trials including 2045 participants with an asymptomatic AAA were included. Follow-up was between 18 and 63 months. Neither blood pressure-lowering medications (mean growth±SD 2.0±2.4 vs 2.3±2.7 mm/year; standardised mean difference (SMD) -0.07, 95% CI -0.19 to 0.06; p=0.288) or antibiotics (mean growth±SD 2.6±2.1 vs 2.6±2.5 mm/year; SMD -0.11, 95% CI -0.38 to 0.16; p=0.418) reduced AAA growth or AAA-related events (blood pressure-lowering medications: 92 vs 95 events; risk ratio (RR) 0.86, 95% CI 0.66 to 1.11; p=0.244; and antibiotics: 69 vs 73 events; RR 0.93, 95% CI 0.69 to 1.25; p=0.614). The subanalysis of antibiotics showed similar results.

CONCLUSIONS

This meta-analysis suggests that neither blood pressure-lowering medications or antibiotics limit growth or clinically relevant events in people with AAAs.

Intraluminal thrombus effect on the progression of abdominal aortic aneurysms by using a multistate continuous-time Markov chain model

OBJECTIVE

To investigate the relationship between the characteristics of intraluminal thrombus (ILT) with abdominal aortic aneurysm (AAA) expansion.

METHODS

This retrospective clinical study applied homogeneous multistate continuous-time Markov chain models to longitudinal computed tomography (CT) data from Korean patients with AAA. Four AAA states were considered (early, mild, severe, fatal) and the maximal thickness of the ILT (max_ILT), the fraction of the wall area covered by the ILT (area_frac) and the fraction of ILT volume (vol_frac) were used as covariates.

RESULTS

The analysis reviewed longitudinal CT images from 26 patients. Based on likelihood-ratio statistics, the area_frac was the most significant biomarker and max_ILT was the second most significant. In addition, within AAAs that developed an ILT layer, the analysis found that the AAA expands relatively quickly during the early stage but the rate of expansion reduces once the AAA has reached a larger size.

CONCLUSION

The results recommend surgical intervention when a patient has an area_frac more than 60%. Although this recommendation should be considered with caution given the limited sample size, physicians can use the proposed model as a tool to find such recommendations with their own data.

Image-Based Displacements Analysis and Computational Blood Dynamics after Endovascular Aneurysm Repair

BACKGROUND

To examine intraheartbeat displacements (IHD) and geometrical changes of endografts for abdominal aortic aneurysm repair over the course of years, defined as follow-up displacements (FUD), and to correlate them with computational fluid dynamics (CFD). Despite the widespread use of endovascular aneurysm repair (EVAR), we still know little about endograft behavior after deployment.

METHODS

Two cases, treated with either expanded polytetrafluoroethylene on a nitinol stent frame (PI) or with woven polyester fabric sutured to a stainless-steel Z stent skeleton (PII), were submitted to dynamic computed tomography angiography at 1, 12, and 60 months after implantation. After segmentation, IHD were computed as displacements of the reconstructed surface with respect to the diastolic instant. Similarly, FUD were studied using imaging techniques that align temporal successive segmentations. In addition, numerical simulations for blood dynamics were performed to compute viscous forces, specifically wall shear stress and time-averaged wall shear stress (TAWSS).

RESULTS

IHD analysis showed slight translations without deformation for the PI endograft with respect to the stiffer stainless-steel endograft behavior of PII. FUD showed in PI motion of the metallic struts mainly focused on the distal main body of the endograft and in the zone overlapping with iliac branches. In PII, we observed a huge FUD in the middle and inferior-anterior regions of the main body. CFD analysis revealed changes of velocity patterns associated with remodeling of the iliac zone for PI and of the main body region for PII, where flow impinges the lumen wall and progressively induces deformation of the endograft wires. Measurement of TAWSS demonstrated flow disturbances in the enlarged region correlated with displacement analysis.

CONCLUSIONS

Image-based displacement analysis associated with CFD enabled very subtle evaluations of endograft behavior on different temporal scales. This kind of study could be helpful both for physicians, forecasting evolution during the life span of the endograft, and manufacturers, giving them useful information about endograft implant performance and design.

A Comparative Study of Biomechanical and Geometrical Attributes of Abdominal Aortic Aneurysms in the Asian and Caucasian Populations

In this work, we provide a quantitative assessment of the biomechanical and geometric features that characterize abdominal aortic aneurysm (AAA) models generated from 19 Asian and 19 Caucasian diameter-matched AAA patients. 3D patient-specific finite element models were generated and used to compute peak wall stress (PWS), 99th percentile wall stress (99th WS), and spatially averaged wall stress (AWS) for each AAA. In addition, 51 global geometric indices were calculated, which quantify the wall thickness, shape, and curvature of each AAA. The indices were correlated with 99th WS (the only biomechanical metric that exhibited significant association with geometric indices) using Spearman's correlation and subsequently with multivariate linear regression using backward elimination. For the Asian AAA group, 99th WS was highly correlated (R2 = 0.77) with three geometric indices, namely tortuosity, intraluminal thrombus volume, and area-averaged Gaussian curvature. Similarly, 99th WS in the Caucasian AAA group was highly correlated (R2 = 0.87) with six geometric indices, namely maximum AAA diameter, distal neck diameter, diameter-height ratio, minimum wall thickness variance, mode of the wall thickness variance, and area-averaged Gaussian curvature. Significant differences were found between the two groups for ten geometric indices; however, no differences were found for any of their respective biomechanical attributes. Assuming maximum AAA diameter as the most predictive metric for wall stress was found to be imprecise: 24% and 28% accuracy for the Asian and Caucasian groups, respectively. This investigation reveals that geometric indices other than maximum AAA diameter can serve as predictors of wall stress, and potentially for assessment of aneurysm rupture risk, in the Asian and Caucasian AAA populations.

Computational prediction of hemodynamical and biomechanical alterations induced by aneurysm dilatation in patient-specific ascending thoracic aortas

The aim of the present work is to propose a robust computational framework combining computational fluid dynamics (CFD) and 4D flow MRI to predict the progressive changes in hemodynamics and wall rupture index (RPI) induced by aortic morphological evolutions in patients harboring ascending thoracic aortic aneurysms (ATAAs). An analytical equation has been proposed to predict the aneurysm progression based on age, sex, and body surface area. Parameters such as helicity, wall shear stress (WSS), time-averaged WSS, oscillatory shear index, relative residence time, and viscosity were evaluated for two patients at different stages of aneurysm growth, and compared with age-sex-matched healthy subjects. The study shows that evolution of hemodynamics and RPI, despite being very slow in ATAAs, is strongly affected by morphological alterations and, in turn could impact biomechanical factors and aortic mechanobiology. An aspect of the current work is that the patient-specific 4D MRI data sets were obtained with a follow-up of 1 year and the measured time-averaged velocity maps and flow eccentricity were compared with the CFD simulation for validation. The computational framework presented here is capable of capturing the blood flow patterns and the hemodynamic descriptors during the various stages of aneurysm growth. Further investigations will be conducted in order to verify these results on a larger cohort of patients and with long follow-up times to finally elucidate the link between deranged hemodynamics, AA geometry, and wall mechanical properties in ATAAs.

A novel combined fluid dynamic and strain analysis approach identified abdominal aortic aneurysm rupture

Clinical decision-making for surgical repair of abdominal aortic aneurysms based on maximum aortic diameter presents limitations as rupture can occur below threshold for some aneurysms, whereas others are stable at large sizes. The proposed approach combines hemodynamics and geometric indices with in vivo deformation analysis to assess local weakening of the aortic wall for a case of impending rupture that was confirmed during open surgical repair. A new combined index, the Regional Rupture Potential, is introduced to help the assessment of individual aneurysms and their rupture risk, providing a rationale for clinical decisions.

A machine leaning approach for abdominal aortic aneurysm severity assessment using geometric, biomechanical, and patient-specific historical clinical features

Recent studies monitoring severity of abdominal aortic aneurysm (AAA) suggested that reliance on only the maximum transverse diameter ( D _max ) may be insufficient to predict AAA rupture risk. Moreover, geometric indices, biomechanical parameters, material properties, and patient-specific historical data affect AAA morphology, indicating the need for an integrative approach that incorporates all factors for more accurate estimation of AAA severity. We implemented a machine learning algorithm using 45 features extracted from 66 patients. The model was generated using the J48 decision tree algorithm with the aim of maximizing model accuracy. Three different feature sets were used to assess the prediction rate: i) using D _max as a single-feature set, ii) using a set of all features, and, lastly iii) using a feature set selected via the BestFirst feature selection algorithm. Our results indicate that BestFirst feature selection yielded the highest prediction accuracy. These results indicate that a combination of several specific parameters that comprehensively capture AAA behavior may enable a suitable assessment of AAA severity, suggesting the potential benefit of machine learning for this application.

Anatomical Differences Between Intact and Ruptured Large Abdominal Aortic Aneurysms

Purpose: To compare different anatomical characteristics between intact and ruptured large abdominal aortic aneurysms (rAAA >80 mm) with the goal of refining the process of estimating rupture risk. Materials and Methods: A retrospective study involving 62 male patients with large (>80 mm) aneurysms matched for age and smoking produced a 31-patient elective group with a mean maximum aneurysm diameter of 92±9.7 mm and a 31-patient rAAA group (mean maximum aneurysm diameter 95.7±12 mm). Preoperative computed tomography angiography scans were analyzed with a dedicated workstation, and anatomical characteristics of the aortic neck, iliac arteries, and aneurysm were compared in multivariable regression analyses; the outcomes are given as the odds ratio (OR) with 95% confidence interval (CI). The prognostic utility of several characteristics as predictors of rupture occurrence was examined with receiver operating characteristic (ROC) curves. Results: Anatomical characteristics differing significantly between elective and ruptured aneurysms were the infrarenal aortic neck diameters at 5 mm, 10 mm and 15 mm; the neck length and calcification; the common iliac artery (CIA) lengths; the iliac artery indexes; the left CIA and external iliac artery diameters; and the total and true lumen aneurysm volumes. Intraluminal thrombus (ILT) volume did not differ (p=0.76), although its distribution in elective vs ruptured cases did [absent: 0% vs 19%, respectively (p=0.025); circumferential: 61% vs 35%, respectively (p=0.04)]. Total aneurysm volume was higher in rAAA (442±140 mL) vs intact AAA (331±143 mL, p=0.014), while the ILT/total aneurysm volume rate was lower in rAAA (55%) vs intact AAA (70%, p=0.02). Multivariate analysis determined that a shorter left CIA (OR 1.07, 95% CI 1.01 to 1.1, p=0.016) and a smaller total aneurysm volume (OR 1.007, CI. 1.001 to 1.014, p=0.016) were associated with intact AAA. After a ROC curve analysis, left CIA length <50 mm demonstrated a lower incidence of rupture (sensitivity 60% and specificity 78%), while total aneurysm volume <380 mL had 60% sensitivity and specificity. Conclusion: Large rAAAs seem to have different anatomical characteristics than similarly sized intact AAAs. Large intact AAAs have lower total aneurysm volumes and shorter left CIAs, with higher ILT/aneurysm volume rates.

A novel method for describing biomechanical properties of the aortic wall based on the three-dimensional fluid-structure interaction model

OBJECTIVES

Our goal was to present a novel non-invasive approach for assessment of aortic wall displacement to describe its biomechanical properties during the cardiac cycle.

METHODS

The fluid-structure interaction (FSI) technique was used to reconstruct aortic wall displacement based on computed tomography angiography and 2-dimensional speckle-tracking technique (2DSTT) data collected from 20 patients [10 with healthy aortas (AA) and 10 with abdominal aortic aneurysms (AAAs)]. The mechanical properties of the wall of the aorta were described by the Yeoh hyperelastic materials model with α and β parameters, and wall displacement was determined with 2DSTT. The mechanical parameters of the wall of the aorta in the FSI model were automatically updated in the calculation loop until the calculated and clinically measured wall movements were the same.

RESULTS

Results showed 98% accuracy of FSI compared to 2DSTT for AA and AAA (P > 0.05). The mean wall deformation for AA was 2.45 ± 0.12 mm and 2.49 ± 0.10 mm for FSI and 2DSTT, respectively (P = 0.40), whereas that for AAA was 2.84 ± 0.44 mm and 2.88 ± 0.45 mm, respectively (P = 0.83). The FSI analysis indicated that the α and β parameters for AA were equal to 14.35 ± 1.30 N⋅cm-2 and 9.33 ± 1.08 N⋅cm-2, respectively; and for AAA, α was 11.00 ± 0.49 N⋅cm-2 and β was 79.46 ± 4.32 N⋅cm-2.

CONCLUSIONS

The FSI technique may be successfully applied to assess the mechanical parameters of patient-specific aortic walls using computed tomography angiographic and 2DSTT measurements.

Bayesian Inference-Based Estimation of Normal Aortic, Aneurysmal and Atherosclerotic Tissue Mechanical Properties: From Material Testing, Modeling and Histology

OBJECTIVE

Mechanical properties of healthy, aneurysmal, and atherosclerotic arterial tissues are essential for assessing the risk of lesion development and rupture. Strain energy density function (SEDF) has been widely used to describe these properties, where material constants of the SEDF are traditionally determined using the ordinary least square (OLS) method. However, the material constants derived using OLS are usually dependent on initial guesses.

METHODS

To avoid such dependencies, Bayesian inference-based estimation was used to fit experimental stress-stretch curves of 312 tissue strips from 8 normal aortas, 19 aortic aneurysms, and 21 carotid atherosclerotic plaques to determine the constants, C₁, D₁, and D₂ of the modified Mooney-Rivlin SEDF.

RESULTS

Compared with OLS, material constants varied much less with prior in the Bayesian inference-based estimation. Moreover, fitted material constants differed amongst distinct tissue types. Atherosclerotic tissues associated with the biggest D₂, an indicator of the rate of increase in stress during stretching, followed by aneurysmal tissues and those from normal aortas. Histological analyses showed that C₁ and D₂ were associated with elastin content and details of the collagen configuration, specifically, waviness and dispersion, in the structure.

CONCLUSION

Bayesian inference-based estimation robustly determines material constants in the modified Mooney-Rivlin SEDF and these constants can reflect the inherent physiological and pathological features of the tissue structure.

SIGNIFICANCE

This study suggested a robust procedure to determine the material constants in SEDF and demonstrated that the obtained constants can be used to characterize tissues from different types of lesions, while associating with their inherent microstructures.

Hodge decomposition of wall shear stress vector fields characterizing biological flows

A discrete boundary-sensitive Hodge decomposition is proposed as a central tool for the analysis of wall shear stress (WSS) vector fields in aortic blood flows. The method is based on novel results for the smooth and discrete Hodge-Morrey-Friedrichs decomposition on manifolds with boundary and subdivides the WSS vector field into five components: gradient (curl-free), co-gradient (divergence-free) and three harmonic fields induced from the boundary, which are called the centre, Neumann and Dirichlet fields. First, an analysis of WSS in several simulated simplified phantom geometries (duct and idealized aorta) was performed in order to understand the nature of the five components. It was shown that the decomposition is able to distinguish harmonic blood flow arising from the inlet from harmonic circulations induced by the interior topology of the geometry. Finally, a comparative analysis of 11 patients with coarctation of the aorta (CoA) before and after treatment as well as 10 control patients was done. The study shows a significant difference between the CoA patients before and after the treatment, and the healthy controls. This means a global difference between aortic shapes of diseased and healthy subjects, thus leading to a new type of WSS-based analysis and classification of pathological and physiological blood flow.

Antithrombotic therapy in abdominal aortic aneurysm: beneficial or detrimental?

Abdominal aortic aneurysm (AAA) is a degenerative vascular pathology resulting in significant morbidity and mortality in older adults due to rupture and sudden death. Despite 150 000 new cases and nearly 15 000 deaths annually, the only approved treatment of AAA is surgical or endovascular intervention when the risk for aortic rupture is increased. The goal of the scientific community is to develop novel pharmaceutical treatment strategies to reduce the need for surgical intervention. Because most clinically relevant AAAs contain a complex structure of fibrin, inflammatory cells, platelets, and red blood cells in the aneurysmal sac known as an intraluminal thrombus (ILT), antithrombotic therapies have emerged as potential pharmaceutical agents for the treatment of AAA progression. However, the efficacy of these treatments has not been shown, and the effects of shrinking the ILT may be as detrimental as they are beneficial. This review discusses the prospect of anticoagulant and antiplatelet (termed collectively as antithrombotic) therapies in AAA. Herein, we discuss the role of the coagulation cascade and platelet activation in human and animal models of AAA, the composition of ILT in AAA, a possible role of the ILT in aneurysm stabilization, and the implications of antithrombotic drugs in AAA treatment.

Mechanical and geometrical determinants of wall stress in abdominal aortic aneurysms: A computational study

An aortic aneurysm (AA) is a focal dilatation of the aortic wall. Occurrence of AA rupture is an all too common event that is associated with high levels of patient morbidity and mortality. The decision to surgically intervene prior to AA rupture is made with recognition of significant procedural risks, and is primarily based on the maximal diameter and/or growth rate of the AA. Despite established thresholds for intervention, rupture occurs in a notable subset of patients exhibiting sub-critical maximal diameters and/or growth rates. Therefore, a pressing need remains to identify better predictors of rupture risk and ultimately integrate their measurement into clinical decision making. In this study, we use a series of finite element-based computational models that represent a range of plausible AA scenarios, and evaluate the relative sensitivity of wall stress to geometrical and mechanical properties of the aneurysmal tissue. Taken together, our findings encourage an expansion of geometrical parameters considered for rupture risk assessment, and provide perspective on the degree to which tissue mechanical properties may modulate peak stress values within aneurysmal tissue.