Biomechanical Indices for Rupture Risk Estimation in Abdominal Aortic Aneurysms

AI-powered assessment of biomarkers for growth prediction of abdominal aortic aneurysms

Objective

The purpose of this study was to employ biomechanics-based biomarkers to locally characterize abdominal aortic aneurysm (AAA) tissue and investigate their relation to local aortic growth by means of an artificial intelligence model.

Methods

The study focused on a population of 36 patients with AAAs undergoing serial monitoring with electrocardiogram-gated multiphase computed tomography angiography acquisitions. The geometries of the aortic lumen and wall were reconstructed from the baseline scans and used for the baseline assessment of regional aortic weakness with three functional biomarkers, time-averaged wall-shear stress, in vivo principal strain, and intra-luminal thrombus thickness. The biomarkers were encoded as regional averages on axial and circumferential sections perpendicularly to the aortic centerline. Local diametric growth was obtained as difference in diameter between baseline and follow-up at the level of each axial section. An artificial intelligence model was developed to predict accelerated aneurysmal growth with the Extra Trees algorithm used as a binary classifier where the positive class represented regions that grew more than 2.5 mm/year. Additional clinical biomarkers, such as maximum aortic diameter at baseline, were also investigated as predictors of growth.

Results

The area under the curve for the constructed receiver operating characteristic curve for the Extra Trees classifier showed a very good performance in predicting relevant aortic growth (area under the curve = 0.92), with the three biomechanics-based functional biomarkers being objectively selected as the main predictors of growth.

Conclusions

The use of features based on the functional and local characterization of the aortic tissue resulted in a superior performance in terms of growth prediction when compared with models based on geometrical assessments. With rapid growth linked to increasing risk for patients with AAAs, the ability to access functional information related to tissue weakening and disease progression at baseline has the potential to support early clinical decisions and improve disease management.

Hemostatic Biomarkers and Volumetry Help to Identify High-Risk Abdominal Aortic Aneurysms

Predicting the progression of small aneurysms is a main challenge in abdominal aortic aneurysm (AAA) management. The combination of circulating biomarkers and image techniques might provide an alternative for risk stratification. We evaluated the association of plasma TAT complexes (TAT) and D-dimer with AAA severity in 3 groups of patients: group 1, without AAA (n = 52), group 2, AAA 40−50 mm (n = 51) and group 3, AAA > 50 mm (n = 50). TAT (p < 0.001) and D-dimer (p < 0.001) were increased in patients with AAA (groups 2 and 3) vs. group 1. To assess the association between baseline TAT and D-dimer concentrations, and AAA growth, aortic diameter and volume (volumetry) were measured by computed tomography angiography (CTA) in group 2 at recruitment (baseline) and 1-year after inclusion. Baseline D-dimer and TAT levels were associated with AAA diameter and volume variations at 1-year independently of confounding factors (p ≤ 0.044). Additionally, surgery incidence, recorded during a 4-year follow-up in group 2, was associated with larger aneurysms, assessed by aortic diameter and volumetry (p ≤ 0.036), and with elevated TAT levels (sub-hazard ratio 1.3, p ≤ 0.029), while no association was found for D-dimer. The combination of hemostatic parameters and image techniques might provide valuable tools to evaluate AAA growth and worse evolution.

Wall shear stress and relative residence time as potential risk factors for abdominal aortic aneurysms in males: a 4D flow cardiovascular magnetic resonance case-control study

BACKGROUND

Abdominal aortic aneurysms (AAA) can lead to catastrophic events such as dissection or rupture, and are an expression of general aortic disease. Low wall shear stress (WSS), high oscillatory shear index (OSI), and high relative residence time (RRT) have been correlated against increased uptake of inflammatory markers in the vessel wall and may improve risk stratification of AAA. We sought to obtain a comprehensive view of WSS, OSI, and RRT in the whole aorta for patients with AAA and age-matched elderly controls and young normal controls.

METHODS

4D Flow cardiovascular magnetic resonance images of the whole aorta were acquired in 18 AAA patients (70.8 ± 3.4 years), 22 age-matched controls (71.4 ± 3.4 years), and 23 young subjects (23.3 ± 3.1 years), all males. Three-dimensional segmentations of the whole aorta were created for all timeframes using a semi-automatic approach. The aorta was divided into five segments: ascending aorta, arch, descending aorta, suprarenal and infrarenal abdominal aorta. For each segment, average values of peak WSS, OSI, and RRT were computed. Student's t-tests were used to compare values between the three cohorts (AAA patients vs elderly controls, and elderly controls vs young controls) where the data were normally distributed, and the non-parametric Wilcoxon rank sum tests were used otherwise.

RESULTS

AAA patients had lower peak WSS in the descending aorta as well as in the abdominal aorta compared to elderly controls (p ≤ 0.001), similar OSI, but higher RRT in the descending and abdominal aorta (p ≤ 0.001). Elderly controls had lower peak WSS compared to young controls throughout the aorta (p < 0.001), higher OSI in all segments except for the infrarenal aorta (p < 0.001), and higher RRT throughout the aorta, except the infrarenal aorta (p < 0.001).

CONCLUSIONS

This study provides novel insights into WSS, OSI, and RRT in patients with AAA in relation to normal ageing, highlighting how AAA patients have markedly abnormal hemodynamic stresses not only in the infrarenal, but in the entire aorta. Moreover, we identified RRT as a marker for abnormal AAA hemodynamics. Further investigations are needed to explore if RRT or other measures of hemodynamics stresses best predict AAA growth and/or rupture.

Does the Hospital Day of Surgery for Endovascular Repair of Symptomatic Abdominal Aortic Aneurysms Affect Outcomes?

Objective:

Symptomatic abdominal aortic aneurysms (sAAA) are considered surgically urgent. Recent data suggest delaying surgery allows for medical optimization without affecting outcomes. We investigated the association of the hospital day of surgery with 30 day outcomes.

Methods:

Patients with infrarenal sAAA undergoing endovascular aortic repair (EVAR) between 2011 and 2018 in the American College of Surgeons National Surgery Quality Improvement Project database were included. The primary outcome was 30 day mortality. Additional outcomes included myocardial infarction, pulmonary complications, length of stay, and discharge disposition. Days-to-surgery were classified as the day of presentation (D0), day 1, day 2, days 3 and 4, days 5 to 7 (D5), and day 8 or more (D8).

Results:

A total of 804 patients were identified. D8 patients had higher proportions of dyspnea on exertion, chronic obstructive pulmonary disease, congestive heart failure, and history of dialysis. D0 surgery appeared protective of mortality (odds ratio [OR] 0.34, p=0.0132). Each additional day increased the mortality risk (OR 1.23, p<0.001) although not within the first 4 days. There was increased mortality for patients having surgery at D5 (7.7%) and D8 (23.8%) compared with repair earlier (1%–4%, p=0.03). Bivariable analysis revealed no significant differences in secondary outcomes. Multivariable modeling revealed increased mortality for D8 versus D0 (adjusted OR of 6.8, 95% confidence interval 1.7–26.5).

Conclusions:

While D0 appears to have the lowest risk of mortality, EVAR for sAAA up to 4 days may not be associated with increased mortality. Further research should determine delay etiologies and whether they improve operative planning and optimization without impacting morbidity and mortality.

Multiperspective Bistatic Ultrasound Imaging and Elastography of the Ex Vivo Abdominal Aorta

Knowledge of aneurysm geometry and local mechanical wall parameters using ultrasound (US) can contribute to a better prediction of rupture risk in abdominal aortic aneurysms (AAAs). However, aortic strain imaging using conventional US is limited by the lateral lumen-wall contrast and resolution. In this study, ultrafast multiperspective bistatic (MP BS) imaging is used to improve aortic US, in which two curved array transducers receive simultaneously on each transmit event. The advantage of such bistatic US imaging on both image quality and strain estimations was investigated by comparing it to single-perspective monostatic (SP MS) and MP monostatic (MP MS) imaging, i.e., alternately transmitting and receiving with either transducer. Experimental strain imaging was performed in US simulations and in an experimental study on porcine aortas. Different compounding strategies were tested to retrieve the most useful information from each received US signal. Finally, apart from the conventional sector grid in curved array US imaging, a polar grid with respect to the vessel's local coordinate system is introduced. This new reconstruction method demonstrated improved displacement estimations in aortic US. The US simulations showed increased strain estimation accuracy using MP BS imaging bistatic imaging compared to MP MS imaging, with a decrease in the average relative error between 41% and 84% in vessel wall regions between transducers. In the experimental results, the mean image contrast-to-noise ratio was improved by up to 8 dB in the vessel wall regions between transducers. This resulted in an increased mean elastographic signal-to-noise ratio by about 15 dB in radial strain and 6 dB in circumferential strain.

AAA Revisited: A Comprehensive Review of Risk Factors, Management, and Hallmarks of Pathogenesis

Despite declining incidence and mortality rates in many countries, the abdominal aortic aneurysm (AAA) continues to represent a life-threatening cardiovascular condition with an overall prevalence of about 2-3% in the industrialized world. While the risk of AAA development is considerably higher for men of advanced age with a history of smoking, screening programs serve to detect the often asymptomatic condition and prevent aortic rupture with an associated death rate of up to 80%. This review summarizes the current knowledge on identified risk factors, the multifactorial process of pathogenesis, as well as the latest advances in medical treatment and surgical repair to provide a perspective for AAA management.

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.

A Predictive Analysis of Wall Stress in Abdominal Aortic Aneurysms Using a Neural Network Model

Rupture risk assessment of abdominal aortic aneurysms (AAAs) by means of quantifying wall stress is a common biomechanical strategy. However, the clinical translation of this approach has been greatly limited due to the complexity associated with the computational tools required for its implementation. Thus, being able to estimate wall stress using nonbiomechanical markers that can be quantified as a direct outcome of clinical image segmentation would be advantageous in improving the potential implementation of said strategy. In the present work, we investigated the use of geometric indices to predict patient-specific AAA wall stress by means of a novel neural network (NN) modeling approach. We conducted a retrospective review of existing clinical images of two patient groups: 98 asymptomatic and 50 symptomatic AAAs. The images were subject to a protocol consisting of image segmentation, processing, volume meshing, finite element modeling, and geometry quantification, from which 53 geometric indices and the spatially averaged wall stress (SAWS) were calculated. SAWS estimated from finite element analysis was considered the gold standard for the predictions. We developed feed-forward NN models composed of an input layer, two dense layers, and an output layer using Keras, a deep learning library in python. The NN models were trained, tested, and validated independently for both AAA groups using all geometric indices, as well as a reduced set of indices resulting from a variable reduction procedure. We compared the performance of the NN models with two standard machine learning algorithms (MARS: multivariate adaptive regression splines and GAM: generalized additive model) and a linear regression model (GLM: generalized linear model). With the reduced sets of indices, the NN-based approach exhibited the highest mean goodness-of-fit (for the symptomatic group 0.71 and for the asymptomatic group 0.79) and lowest mean relative error (17% for both groups). In contrast, MARS yielded a mean goodness-of-fit of 0.59 for the symptomatic group and 0.77 for the asymptomatic group, with relative errors of 17% for the symptomatic group and 22% for the asymptomatic group. GAM had a mean goodness-of-fit of 0.70 for the symptomatic group and 0.80 for the asymptomatic group, with relative errors of 16% for the symptomatic group and 20% for the asymptomatic group. GLM did not perform as well as the other algorithms, with a mean goodness-of-fit of 0.53 for the symptomatic group and 0.70 for the asymptomatic group, with relative errors of 19% for the symptomatic group and 23% for the asymptomatic group. Nevertheless, the NN models required a reduced set of 15 and 13 geometric indices to predict SAWS for the symptomatic and asymptomatic AAA groups, respectively. This was in contrast to the reduced set of nine and eight geometric indices required to predict SAWS with the MARS and GAM algorithms for each AAA group, respectively. The use of NN modeling represents a promising alternative methodology for the estimation of AAA wall stress using geometric indices as surrogates, in lieu of finite element modeling. The performance metrics of NN models are expected to improve with significantly larger group sizes, given the suitability of NN modeling for "big data" applications.

Diseases of the Aorta and Kidney Disease: Conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Chronic kidney disease (CKD) is an independent risk factor for the development of abdominal aortic aneurysm (AAA), as well as for cardiovascular and renal events and all-cause mortality following surgery for AAA or thoracic aortic dissection. In addition, the incidence of acute kidney injury (AKI) after any aortic surgery is particularly high, and this AKI per se is independently associated with future cardiovascular events and mortality. On the other hand, both development of AKI after surgery and the long-term evolution of kidney function differ significantly depending on the type of AAA intervention (open surgery vs. the various subtypes of endovascular repair). Current knowledge regarding AAA in the general population may not be always applicable to CKD patients, as they have a high prevalence of co-morbid conditions and an elevated risk for periprocedural complications. This summary of a Kidney Disease: Improving Global Outcomes Controversies Conference group discussion reviews the epidemiology, pathophysiology, diagnosis, and treatment of Diseases of the Aorta in CKD and identifies knowledge gaps, areas of controversy, and priorities for future research.

3D Modeling of Blood Flow in Simulated Abdominal Aortic Aneurysm

BACKGROUND

Besides biological factors, abdominal aortic aneurysm rupture is also caused by mechanical parameters, which are constantly affecting the wall's tissue due to their abnormal values. The ability to evaluate these parameters could vastly improve the clinical treatment of patients with abdominal aortic aneurysms. The objective of this study was to develop and demonstrate a methodology to analyze the fluid dynamics that cause the wall stress distribution in abdominal aortic aneurysms, using accurate 3D geometry and a realistic, nonlinear, elastic biomechanical model using a computer-aided software.

METHODS

The geometry of the abdominal aortic aneurysm; was constructed on a 3D scale using computer-aided software SolidWorks (Dassault Systems SolidWorksCorp., Waltham MA). Due to the complex nature of the abdominal aortic aneurysm geometry, the physiological forces and constraints acting on the abdominal aortic aneurysm wall were measured by using a simulation setup using boundary conditions and initial conditions for different studies such as finite element analysis or computational fluid dynamics.

RESULTS

The flow pattern showed an increase velocity at the angular neck, followed by a stagnated flow inside the aneurysm sack. Furthermore, the wall shear stress analysis showed to focalized points of higher stress, the top and bottom of the aneurysm sack, where the flow collides against the wall. An increase of the viscosity showed no significant velocity changed but results in a slight increase in overall pressure and wall shear stress.

CONCLUSIONS

Conducting computational fluid dynamics modeling of the abdominal aortic aneurysm using computer-aided software SolidWorks (Dassault Systems SolidWorksCorp., Waltham MA) proves to be an insightful approach for the clinical setting. The careful consideration of the biomechanics of the abdominal aortic aneurysm may lead to an improved, case-specific prediction of the abdominal aortic aneurysm rupture potential, which could significantly improve the clinical management of these patients.

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.

Statistical techniques for predicting rupture risk in abdominal aortic aneurysms: A contribution based on bootstrap

The morphometry of abdominal aortic aneurysms (AAA) has been recognized as one of the main factors that may predispose them to rupture. The need to quantify the morphometry of AAA on a patient-specific basis constitutes a valuable tool for assisting in rupture risk prediction. Previous results of this research group have determined the correlations between hemodynamic stresses and aneurysm morphometry by means of the Pearson coefficient. The present work aims to find how the AAA morphology correlates with the hemodynamic stresses acting on the arterial wall. To do so, the potential of the bootstrap technique has been explored. Bootstrap works appropriately in applications where few data are available (13 patient-specific AAA models were simulated). The methodology developed can be considered a contribution to predicting the hemodynamic stresses from the size and shape indices. The present work explores the use of a specific statistical technique (the bootstrap technique) to predict, based on morphological correlations, the patient-specific aneurysm rupture risk, provide greater understanding of this complex phenomenon that can bring about improvements in the clinical management of aneurysmatic patients. The results obtained using the bootstrap technique have greater reliability and robustness than those obtained by regression analysis using the Pearson coefficient, thus allowing to obtain more reliable results from the characteristics of the samples used, such as their small size and high variability. Additionally, it could be an indicator that other indices, such as AAA length, deformation rate, saccular index, and asymmetry, are important.

Biomechanical Properties of the Periaortic Abdominal Tissue: It is Not as Fragile as It Seems

BACKGROUND

The perivascular adipose tissue has been studied as a critical element that could influence physiological and disease processes of the vessel covered by it. In terms of anatomy, during the abdominal aorta's dissection, it is possible to identify the periaortic adipose tissue and the periaortic parietal peritoneum lying over it, sealing the retroperitoneal space. They seem to be fragile layers, with apparently no biomechanical role in the abdomen. However, it is well known that most cases of ruptured abdominal aortic aneurysms (AAAs) that reach the emergency department still alive present retroperitoneal bleeding contained by the previously mentioned two-layer combination, eventually allowing time for surgical treatment. In previous studies about aortic wall stress, tension, and AAA rupture prediction, only information concerning the vessel wall itself is highlighted. Therefore, the present work aims to study the biomechanical and histological properties of the periaortic tissue, comparing them to the same variables measured in aortic wall samples described in the medical literature.

MATERIALS AND METHODS

Samples of periaortic tissue were harvested from 27 individuals during necropsy. Smoking status and the presence of AAAs were observed. Biomechanical uniaxial destructive tests were performed up to samples' rupture. Values of failure stress, tension, and strain were obtained. Samples were also harvested for histological analysis.

RESULTS

Periaortic tissue presented less amount of collagen in smokers than in nonsmokers (P = 0.017). The periaortic tissue seems to be more elastic than aortic walls described in the literature (strain: 0.75 ± 0.37). Analyzing periaortic tissue failure stress (56.8 ± 101.26 N/cm2) and tension (7.65 ± 4.99 N/cm), it has at least 52% and 55%, respectively, of the stress and tension described in the medical literature for AAA walls.

CONCLUSIONS

The periaortic tissue presents less collagen fibers in smokers than in nonsmokers. The periaortic tissue seemed very delicate during an autopsy, but the study of its biomechanical properties showed that it presents more than half of the resistance of an AAA wall. This information suggests this tissue might have a mechanical protective role against massive bleeding when it comes to an aortic rupture. Therefore this tissue's biomechanical information should be included in computational models on enlargement and rupture prediction of AAAs.

IFI16 contributes to the pathogenesis of abdominal aortic aneurysm by regulating the caspase-1/IL-1β/MCPIP1 pathway

AIMS

Abdominal aortic aneurysm (AAA) is a multi-factorial progressive vascular disease characterized by chronic inflammatory cell infiltration. We investigated the roles played by IFI16 and ASC inflammasomes in AAA development and progression.

MATERIALS AND METHODS

Western blot and qRT-PCR studies were performed to analyze the expression of relative genes in AAA specimens and mouse vascular smooth muscle cells (VSMCs). The apoptosis rates and ROS levels of VSMCs were assessed by flow cytometry. Transwell assays were performed to analyze the migration ability of VSMCs. The levels of MCP-1, IL-1β, and IL-6 in the supernatants of cultured VSMCs were analyzed by ELISA.

KEY FINDINGS

Increased levels of IFI16 expression were found in AAA specimens and Ang-II-treated VSMCs. IFI16 and ASC silencing suppressed the apoptosis and migration ability of VSMCs undergoing Ang-II treatment, reduced elasticity damage to the aortic wall, and decreased the levels of MMP expression. The effect of IFI16 knockdown in Ang-II-induced VSMCs was reversed by MCPIP1 overexpression.

SIGNIFICANCE

Our data suggest that an up-regulation of IFI16 and ASC expression might promote the apoptosis of VSMCs, enhance the inflammatory response, and impairs vascular wall elasticity via a MCPIP1-related mechanism. The inflammasome components IFI16 and ASC might be involved in AAA progression and serve as target molecules for diagnosing and treating AAA.

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.

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.

Comprehensive Cardiac Rehabilitation as a Therapeutic Strategy for Abdominal Aortic Aneurysm

Abdominal aortic aneurysms (AAA) are referred to as “time bombs”. The only way to prevent AAA rupture is elective repair beforehand using surgical replacement or an endovascular procedure. Non-surgical strategies to prevent AAA expansion are under intense investigation. At each AAA stage, that is, occurrence, expansion, and rupture, the mechanisms and risk factors are different, as discussed in this review. Based on the mechanism and risk factors for AAA expansion, the most effective strategy against AAA expansion need to be identified, but so far none has. Exercise is known to be essential for preventing atherosclerosis related to the coexistence of AAA and CAD, but some doctors are hesitant to prescribe exercise programs to AAA patients given that BP elevation during exercise can cause AAA expansion or rupture. In our retrospective study and prospective study on the safety and effectiveness of exercise for AAA patients, the protective role of mild-moderate exercise against expansion of small AAA was clearly shown. The stability of AAA on exercise might be related to reduced inflammatory activity in the aortic wall, stabilized elevation in BP during exercise, increased aortic blood flow, upregulation of transforming growth factor-β1, moderated BMI and/or fat, or improved endothelial function. Until a revolutionary drug emerges that can regress AAA, cardiac rehabilitation remains the best strategy for preventing AAA expansion and rupture.

Image-Based 3D Characterization of Abdominal Aortic Aneurysm Deformation After Endovascular Aneurysm Repair

An abdominal aortic aneurysm (AAA) is a focal dilation of the abdominal aorta, that if not treated, tends to grow and may rupture. The most common treatment for AAAs is the endovascular aneurysm repair (EVAR), which requires that patients undergo Computed Tomography Angiography (CTA)-based post-operative lifelong surveillance due to the possible appearance of complications. These complications may again lead to AAA dilation and rupture. However, there is a lack of advanced quantitative image-analysis tools to support the clinicians in the follow-up. Currently, the approach is to evaluate AAA diameter changes along time to infer the progress of the patient and the post-operative risk of AAA rupture. An increased AAA diameter is usually associated with a higher rupture risk, but there are some small AAAs that rupture, whereas other larger aneurysms remain stable. This means that the diameter-based rupture risk assessment is not suitable for all the cases, and there is increasing evidence that the biomechanical behavior of the AAA may provide additional valuable information regarding the progression of the disease and the risk of rupture. Hence, we propose a promising methodology for post-operative CTA time-series registration and subsequent aneurysm biomechanical strain analysis. From these strains, quantitative image-based descriptors are extracted using a principal component analysis of the tensile and compressive strain fields. Evaluated on 22 patients, our approach yields a mean area under the curve of 88.6% when correlating the strain-based quantitative descriptors with the long-term patient prognosis. This suggests that the strain information directly extracted from the CTA images is able to capture the biomechanical behavior of the aneurysm without relying on finite element modeling and simulation. Furthermore, the extracted descriptors set the basis for possible future imaging biomarkers that may be used in clinical practice. Apart from the diameter, these biomarkers may be used to assess patient prognosis and to enable informed decision making after an EVAR intervention, especially in difficult uncertain cases.

Metformin represses the pathophysiology of AAA by suppressing the activation of PI3K/AKT/mTOR/autophagy pathway in ApoE-/- mice

Background

The protective effect of metformin (MET) on abdominal aortic aneurysm (AAA) has been reported. However, the related mechanism is still poor understood. In this study, we deeply investigated the role of metformin in AAA pathophysiology.

Methods

Angiotensin II (Ang-II) was used to construct the AAA model in ApoE^−/− mice. The related mechanism was explored using Western blot and quantitative real time PCR (qRT-PCR). We also observed the morphological changes in the abdominal aorta and the influence of metformin on biological behaviors of rat abdominal aortic VSMCs.

Results

The PI3K/AKT/mTOR pathway was activated in aneurysmal wall tissues of AAA patients and rat model. Treatment with metformin inhibited the breakage and preserved the elastin structure of the aorta, the loss of collagen, and the apoptosis of aortic cells. In addition, metformin significantly suppressed the activation of the PI3K/AKT/mToR pathway and decreased the mRNA and protein levels of LC3B and Beclin1, which were induced by Ang-II. Moreover, PI3K inhibitors enhanced the effect of metformin while PI3K agonists largely reversed this effect. Interestingly, the cell proliferation, apoptosis, migration and autophagy of vascular smooth muscle cells (VSMCs) induced by Ang-II were also decreased following metformin treatment. PI3K inhibitors and agonists strengthened and weakened the effects of metformin in VSMCs, respectively.

Conclusions

Metformin represses the pathophysiology of AAA by inhibiting the activation of PI3K/AKT/mTOR/autophagy pathway. This repression may be useful as a new therapeutic strategy for AAA.

(PEAK) WALL STRESS AS AN INDICATOR OF ABDOMINAL AORTIC ANEURYSM SEVERITY

Abdominal aortic aneurysms, which consist of dilatations of the infra-renal aorta by at least 1.5 times of its normal diameter, are becoming a leading cause of death worldwide. Rupture often occurs unexpectedly, before a repair procedure is conducted. The AAA maximum diameter has been used as a clinical criterion to monitor AAA severity. However, assessment of AAA rupture risk requires knowledge of wall stress and wall strength at the potential rupture location. We conducted a study on 37 patient specific CT datasets to investigate the benefits of using peak wall stress instead of D_max for AAA rupture severity. Correlation between PWS and 24 geometric indices and biomechanical factors was studied where eleven of them showed a statistically significant correlation with PWS. A Finite Element Analysis Rupture Index was used to conclude that the use of D _max as a single predictor of AAA behavior and severity may be insufficient based on our patient population with a D_max smaller than the 5.5 cm, clinically recommended repair threshold.

Co-localization of microstructural damage and excessive mechanical strain at aortic branches in angiotensin-II-infused mice

Animal models of aortic aneurysm and dissection can enhance our limited understanding of the etiology of these lethal conditions particularly because early-stage longitudinal data are scant in humans. Yet, the pathogenesis of often-studied mouse models and the potential contribution of aortic biomechanics therein remain elusive. In this work, we combined micro-CT and synchrotron-based imaging with computational biomechanics to estimate in vivo aortic strains in the abdominal aorta of angiotensin-II-infused ApoE-deficient mice, which were compared with mouse-specific aortic microstructural damage inferred from histopathology. Targeted histology showed that the 3D distribution of micro-CT contrast agent that had been injected in vivo co-localized with precursor vascular damage in the aortic wall at 3 days of hypertension, with damage predominantly near the ostia of the celiac and superior mesenteric arteries. Computations similarly revealed higher mechanical strain in branching relative to non-branching regions, thus resulting in a positive correlation between high strain and vascular damage in branching segments that included the celiac, superior mesenteric, and right renal arteries. These results suggest a mechanically driven initiation of damage at these locations, which was supported by 3D synchrotron imaging of load-induced ex vivo delaminations of angiotensin-II-infused suprarenal abdominal aortas. That is, the major intramural delamination plane in the ex vivo tested aortas was also near side branches and specifically around the celiac artery. Our findings thus support the hypothesis of an early mechanically mediated formation of microstructural defects at aortic branching sites that subsequently propagate into a macroscopic medial tear, giving rise to aortic dissection in angiotensin-II-infused mice.

Estimation of Abdominal Aortic Aneurysm Rupture Risk with Biomechanical Imaging Markers

PURPOSE

To evaluate whether the biomechanical marker known as rupture risk equivalent diameter (RRED) was superior to the actual abdominal aortic aneurysm (AAA) diameter in estimating future rupture risk in patients who had undergone pre-rupture computed tomography (CT) angiography.

MATERIALS AND METHODS

A retrospective study was conducted in 13 patients with ruptured AAAs who had undergone CT angiography before and after rupture between 2001 and 2015. The median time between the 2 scans was 731 days. Biomechanical and geometrical markers such as maximal AAA diameter, peak wall stress (PWS), and RRED were calculated with AAA-dedicated software. The main analyses determined whether RRED was higher than the actual diameter and the threshold diameter for elective surgery (55 mm for men, 50 mm for women) in AAAs before and after rupture. Differences between diameter and biomechanical markers before and after rupture were tested with appropriate statistical tests.

RESULTS

RRED before and after rupture was smaller than the actual diameter in 7 of 13 cases. Post-rupture RRED was estimated to be smaller than the threshold diameter for elective repair in 4 cases, again suggesting a low rupture risk. The median PWS before and after rupture was 181.7 kPa (interquartile range [IQR], 152.1-244.2 kPa) and 274.1 kPa (IQR, 172.2-377.2 kPa), respectively.

CONCLUSIONS

RRED was smaller than the actual diameter in more than half of pre-rupture AAAs, suggesting a lower rupture risk than estimated with the actual diameter. The results suggest that the currently available biomechanical imaging markers might not be ready for use in clinical practice.

Additional value of biomechanical indices based on CTa for rupture risk assessment of abdominal aortic aneurysms

OBJECTIVE

Biomechanics for rupture risk prediction in abdominal aortic aneurysms (AAA) are gaining popularity. However, their clinical applicability is still doubtful as there is lack of standardization. This study evaluates the added value of biomechanical indices in rupture risk assessment.

METHODS

This study included 175 asymptomatic, 11 sAAA and 45 ruptured aneurysms. 3D-geometries were reconstructed using computer tomography angiographies. Subsequently, finite element models were made to calculate peak wall stress (PWS), peak wall rupture index (PWRI) and the rupture risk equivalent diameter (RRED). The indices were determined with a dedicated software to facilitate standardization.

RESULTS

SAAAs showed a trend towards higher PWS, PWRI and RRED compared to asymptomatic AAAs, but PWS (22.0±5.8 vs. 33.4±15.8 N/cm2), PWRI (0.52±0.2 vs. 1.01±0.64), and RRED (65±60 vs. 98±51 mm) were significantly (p = 0.001) higher in ruptured. However, after diameter-matching no significant differences were seen. The ROC-curves for the maximum diameter and all biomechanical indices were similar but it slightly increased when diameter and biomechanical indices were combined.

CONCLUSIONS

This study showed no added value for biomechanical indices in AAA rupture risk assessment. Additionally, the difficulty of such an assessment increases. However, as symptomatic aneurysms show a trend towards higher biomechanical indices with similar diameters the indices may provide information about aneurysm growth and development.