Finite element analysis in asymptomatic, symptomatic, and ruptured abdominal aortic aneurysms: in search of new rupture risk predictors

Fracture mechanics modeling of aortic dissection

Aortic dissection, a critical cardiovascular condition with life-threatening implications, is distinguished by the development of a tear and its propagation within the aortic wall. A thorough understanding of the initiation and progression of these tears, or cracks, is essential for accurate diagnosis and effective treatment. This paper undertakes a fracture mechanics approach to delve into the mechanics of tear propagation in aortic dissection. Our objective is to elucidate the impact of geometric and material parameters, providing valuable insights into the determinants of this pivotal cardiovascular event. Through our investigation, we have gained an understanding of how various parameters influence the energy release rate for tear propagation in both longitudinal and circumferential directions, aligning our findings with clinical data.

Aortic Size Index Versus Aortic Diameter in the Prediction of Rupture in Women With Abdominal Aortic Aneurysm

Abdominal aortic aneurysms (AAAs) pose significant challenges in clinical management, particularly in female patients, whose unique anatomical and physiological characteristics influence rupture risk. While aortic diameter (AD) has traditionally been the primary metric for predicting rupture, its limitations, especially in women, have spurred exploration into alternative measures such as the aortic size index (ASI). This review examines the anatomy and physiology of AAAs in women, gender-specific challenges in diagnosis and management, and the comparative effectiveness of ASI versus AD in predicting rupture risk. ASI, calculated as AD divided by body surface area (BSA), offers a more nuanced assessment by adjusting for individual body size differences, potentially mitigating gender disparities in rupture rates. Comparative analyses indicate ASI's superiority in predicting adverse aortic events, particularly in women, thereby advocating for its integration into clinical practice to improve patient outcomes. Additionally, emerging techniques such as 3D volumetric measurements and biomechanical assessments show promise in enhancing rupture risk prediction, heralding a shift toward more personalized and effective management strategies for AAA patients.

Correlation of four-dimensional ultrasound strain analysis with computed tomography angiography wall stress simulations in abdominal aortic aneurysms

Objective

Biomechanical modeling of infrarenal aortic aneurysms seeks to predict ruptures in advance, thereby reducing aneurysm-related deaths. As individual methods focusing on strain and stress analysis lack adequate discretization power, this study aims to explore multifactorial characterization for progressive aneurysmal degeneration. The study's objective is to compare stress- and strain-related parameters in infrarenal aortic aneurysms.

Methods

Twenty-two patients with abdominal aortic aneurysms (AAAs) (mean maximum diameter, 53.2 ± 7.2 mm) were included in the exploratory study, examined by computed tomography angiography (CTA) and three-dimensional real-time speckle tracking ultrasound (4D-US). The conformity of aneurysm anatomy in 4D-US and CTA was determined with the mean point-to-point distance (MPPD). CTA was employed for each AAA to characterize stress-related indices using the semi-automated A4-clinics RE software. Five segmentations from one 4D-US examination were fused into one averaged model for strain analysis using MATLAB and the Abaqus solver.

Results

The mean MPPD between the adjacent points of the 4D-US and CTA-derived geometry was 1.8 ± 0.4 mm. The interclass correlation coefficients for all raters and all measurements for the maximum AAA diameter in 2D, 4D ultrasound, and CTA indicate moderate to good reliability (interclass correlation coefficient1 0.69 with 95% confidence interval [CI], 0.49-0.84; P < .001). The peak wall stress (PWS) correlates fairly with the maximum AAA diameter in 2D-US (r = 0.54; P < .01) and 4D-US (r = 0.53; P < .05) and moderately strongly with the maximum exterior AAA diameter (r = 0.63; P < .01). The peak wall rupture risk index shows a strong correlation with the PWS (ρ > 0.9; P < .001) and is influenced by anatomical parameters with equal strength. Isolated observation of the intraluminal thrombus does not provide significant information in the determination of PWS. The maximum AAA diameter in 2D-US shows a fair negative correlation with the mean circumferential, longitudinal and in-plane shear strain (ρ = -0.46; r = -0.45; ρ = -0.47; P < .05 for all). The circumferential strain ratio as an indicator of wall motion heterogeneity increases with the aneurysm diameter (r = 0.47; P < .05). The direct comparison of wall strain and wall stress indices shows no quantitative correlation.

Conclusions

The strain and stress analyses provide independent biomechanical information of AAAs. At the current stage of development, the two methods are considered complementary and may optimize a more patient-specific rupture risk prediction in the future.

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.

A quarter of a century biomechanical rupture risk assessment of abdominal aortic aneurysms. Achievements, clinical relevance, and ongoing developments

Abdominal aortic aneurysm (AAA) disease, the local enlargement of the infrarenal aorta, is a serious condition that causes many deaths, especially in men exceeding 65 years of age. Over the past quarter of a century, computational biomechanical models have been developed towards the assessment of AAA risk of rupture, technology that is now on the verge of being integrated within the clinical decision-making process. The modeling of AAA requires a holistic understanding of the clinical problem, in order to set appropriate modeling assumptions and to draw sound conclusions from the simulation results. In this article we summarize and critically discuss the proposed modeling approaches and report the outcome of clinical validation studies for a number of biomechanics-based rupture risk indices. Whilst most of the aspects concerning computational mechanics have already been settled, it is the exploration of the failure properties of the AAA wall and the acquisition of robust input data for simulations that has the greatest potential for the further improvement of this technology.

Biomechanics and Early Sac Regression after Endovascular Aneurysm Repair of Abdominal Aortic Aneurysm

Background

Sac regression after endovascular aneurysm repair (EVAR) of abdominal aortic aneurysms (AAA) is regarded as a marker of successful response to treatment. Several factors influence sac behavior after EVAR, yet little is known about the value of preoperative biomechanics. The aim of this study was to investigate the difference in aortic biomechanics between patients with and without sac regression.

Methods

Patients treated with standard EVAR for infrarenal AAA at the Karolinska University Hospital between 2009 and 2012 with one preoperative and a minimum of two postoperative computed tomography angiography (CTA) scans were considered for inclusion in this single-center retrospective cohort study. Biomechanical indices such as AAA wall stress and wall stress-strength ratio as well as intraluminal thrombus (ILT) thickness and stress were measured preoperatively in A4ClinicRE (VASCOPS GmbH). AAA diameter and volume were analyzed on preoperative, 30-day, and 1-year CTAs. Patients were dichotomized based on sac regression, defined as a ≥ 5 mm decrease in maximal AAA diameter between the first two postoperative CTA scans. Multivariable logistic regression was used for analysis of factors associated with early sac regression.

Results

Of the 101 patients treated during the inclusion period, 64 were included. Thirty-nine (61%) demonstrated sac regression and 25 (39%) had a stable sac or sac increase. The mean patients age (73 years vs 76 years), male sex (85% vs 96%), and median AAA diameter (58 mm vs 58.5 mm) did not differ between patients with and without sac regression. Although no difference in preoperative biomechanics was seen between the groups, multivariable logistic regression revealed that a larger AAA diameter (odds ratio [OR], 1.27; 95% confidence interval [CI], 1.06-1.51; P = .009) and smoking (OR, 22.1; 95% CI, 2.78-174; P = .003) were positively associated with sac regression. In contrast, the lumen diameter (OR, 0.87; 95% CI, 0.77-0.98; P = .023), ILT thickness (OR, 0.85; 95% CI, 0.75-0.97; P = .013), aspirin or direct-acting oral anticoagulant use (OR, 0.11; 95% CI, 0.02-0.61; P = .012), and mean ILT stress (OR, 0.35; 95% CI, 0.14-0.87; P = .024) showed a negative association. Patients with sac regression had fewer reinterventions (log-rank P = .010) and lower mortality (log-rank P = .012) at the 5-year follow-up.

Conclusions

This study, characterizing preoperative biomechanics in patients with and without sac regression, demonstrated a negative association between mean ILT stress and ILT thickness with a change in sac diameter after EVAR. Given that the ILT is a highly dynamic entity, further studies focusing on the role of the thrombus are needed. Furthermore, patients presenting with early sac regression had improved outcomes after EVAR.

Spatiotemporal Registration of 3-D Multi-perspective Ultrasound Images of Abdominal Aortic Aneurysms

Methods for patient-specific abdominal aortic aneurysm (AAA) progression monitoring and rupture risk assessment are widely investigated. Three-dimensional ultrasound can visualize the AAA's complex geometry and displacement fields. However, ultrasound has a limited field of view and low frame rate (i.e., 3-8 Hz). This article describes an approach to enhance the temporal resolution and the field of view. First, the frame rate was increased for each data set by sequencing multiple blood pulse cycles into one cycle. The sequencing method uses the original frame rate and the estimated pulse wave rate obtained from AAA distension curves. Second, the temporal registration was applied to multi-perspective acquisitions of the same AAA. Third, the field of view was increased through spatial registration and fusion using an image feature-based phase-only correlation method and a wavelet transform, respectively. Temporal sequencing was fully correct in aortic phantoms and was successful in 51 of 62 AAA patients, yielding a factor 5 frame rate increase. Spatial registration of proximal and distal ultrasound acquisitions was successful in 32 of 37 different AAA patients, based on the comparison between the fused ultrasound and computed tomography segmentation (95th percentile Haussdorf distances and similarity indices of 4.2 ± 1.7 mm and 0.92 ± 0.02 mm, respectively). Furthermore, the field of view was enlarged by 9%-49%.

The Detrimental Role of Intraluminal Thrombus Outweighs Protective Advantage in Abdominal Aortic Aneurysm Pathogenesis: The Implications for the Anti-Platelet Therapy

Abdominal aortic aneurysm (AAA) is a common cardiovascular disease resulting in morbidity and mortality in older adults due to rupture. Currently, AAA treatment relies entirely on invasive surgical treatments, including open repair and endovascular, which carry risks for small aneurysms (diameter < 55 mm). There is an increasing need for the development of pharmacological intervention for early AAA. Over the last decade, it has been increasingly recognized that intraluminal thrombus (ILT) is involved in the growth, remodeling, and rupture of AAA. ILT has been described as having both biomechanically protective and biochemically destructive properties. Platelets are the second most abundant cells in blood circulation and play an integral role in the formation, expansion, and proteolytic activity of ILT. However, the role of platelets in the ILT-potentiated AAA progression/rupture remains unclear. Researchers are seeking pharmaceutical treatment strategies (e.g., anti-thrombotic/anti-platelet therapies) to prevent ILT formation or expansion in early AAA. In this review, we mainly focus on the following: (a) the formation/deposition of ILT in the progression of AAA; (b) the dual role of ILT in the progression of AAA (protective or detrimental); (c) the function of platelet activity in ILT formation; (d) the application of anti-platelet drugs in AAA. Herein, we present challenges and future work, which may motivate researchers to better explain the potential role of ILT in the pathogenesis of AAA and develop anti-platelet drugs for early AAA.

On strain-based rupture criterion for ascending aortic aneurysm: the role of fiber waviness

We propose a new approach for constructing strain-based rupture criterion for ascending thoracic aortic aneurysm. The rupture metric is formulated using an effective strain, which is a measure of net strain that the collagen bundles experience after fiber uncrimping. The effective strain is a function of the total strain and the waviness properties of the collagen fibers. In the present work, the waviness properties are obtained from fitting biaxial response data to constitutive models that explicitly consider the collagen waviness and fiber recruitment. Inflation test data from 10 ascending thoracic aortic aneurysm specimens are analyzed. For each specimen, tension-strain data at ∼2300 material points are garnered. The effective strain fields in the configuration immediately before rupture are computed. It is found that the hotspots of the effective strain match the rupture sites very well in all 10 samples. More importantly, the values of effective strain at the hotsopts are closely clustered around 0.1, in contrast to a much wider distribution of the total strain. The study underscores the importance of considering the fiber recruitment in formulating strain-based rupture metric, and suggests that ϵ¯≈0.1, where ϵ¯ is the effective strain metric defined in this work, can be considered as a criterion for assessing the imminent rupture risk of ascending aortic aneurysms.

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.

Comparison of peak wall stress and peak wall rupture index in ruptured and asymptomatic intact abdominal aortic aneurysms

BACKGROUND

Previous studies have suggested that finite element analysis (FEA) can estimate the rupture risk of an abdominal aortic aneurysm (AAA); however, the value of biomechanical estimates over measurement of AAA diameter alone remains unclear. This study aimed to compare peak wall stress (PWS) and peak wall rupture index (PWRI) in participants with ruptured and asymptomatic intact AAAs.

METHODS

The reproducibility of semiautomated methods for estimating aortic PWS and PWRI from CT images was assessed. PWS and PWRI were estimated in people with ruptured AAAs and those with asymptomatic intact AAAs matched by orthogonal diameter on a 1 : 2 basis. Spearman's correlation coefficient was used to assess the association between PWS or PWRI and AAA diameter. Independent associations between PWS or PWRI and AAA rupture were identified by means of logistic regression analyses.

RESULTS

Twenty individuals were included in the analysis of reproducibility. The main analysis included 50 patients with an intact AAA and 25 with a ruptured AAA. Median orthogonal diameter was similar in ruptured and intact AAAs (82·3 (i.q.r. 73·5-92·0) versus 81·0 (73·2-92·4) mm respectively; P = 0·906). Median PWS values were 286·8 (220·2-329·6) and 245·8 (215·2-302·3) kPa respectively (P = 0·192). There was no significant difference in PWRI between the two groups (P = 0·982). PWS and PWRI correlated positively with orthogonal diameter (both P < 0·001). Participants with high PWS, but not PWRI, were more likely to have a ruptured AAA after adjusting for potential confounders (odds ratio 5·84, 95 per cent c.i. 1·22 to 27·95; P = 0·027). This association was not maintained in all sensitivity analyses.

CONCLUSION

High aortic PWS had an inconsistent association with greater odds of aneurysm rupture in patients with a large AAA.

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.

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.

Mathematical model of atherosclerotic aneurysm

Atherosclerosis is a major cause of abdominal aortic aneurysm (AAA) and up to 80% of AAA patients have atherosclerosis. Therefore it is critical to understand the relationship and interactions between atherosclerosis and AAA to treat atherosclerotic aneurysm patients more effectively. In this paper, we develop a mathematical model to mimic the progression of atherosclerotic aneurysms by including both the multi-layer structured arterial wall and the pathophysiology of atherosclerotic aneurysms. The model is given by a system of partial differential equations with free boundaries. Our results reveal a 2D biomarker, the cholesterol ratio and DDR1 level, assessing the risk of atherosclerotic aneurysms. The efficacy of different treatment plans is also explored via our model and suggests that the dosage of anti-cholesterol drugs is significant to slow down the progression of atherosclerotic aneurysms while the additional anti-DDR1 injection can further reduce the risk.

Prediction of local strength of ascending thoracic aortic aneurysms

Knowledges of both local stress and strength are needed for a reliable evaluation of the rupture risk for ascending thoracic aortic aneurysm (ATAA). In this study, machine learning is applied to predict the local strength of ATAA tissues based on tension-strain data collected through in vitro inflation tests on tissue samples. Inputs to machine learning models are tension, strain, slope, and curvature values at two points on the low strain region of the tension-strain curve. The models are trained using data from locations where the tissue ruptured, and subsequently applied to data from intact sites to predict the local rupture strength. The predicted strengths are compared with the known strength at rupture sites as well as the highest tension the tissues experienced at the intact sites. A local rupture index, which is the ratio of the end tension to the predicted rupture strength, is computed. The 'hot spots' of the rupture index are found to match the rupture sites better than those of the peak tension. The study suggests that the strength of ATAA tissue could be reliably predicted from early phase response features defined in this work.

Predictors of Abdominal Aortic Aneurysm Risks

Computational biomechanics via finite element analysis (FEA) has long promised a means of assessing patient-specific abdominal aortic aneurysm (AAA) rupture risk with greater efficacy than current clinically used size-based criteria. The pursuit stems from the notion that AAA rupture occurs when wall stress exceeds wall strength. Quantification of peak (maximum) wall stress (PWS) has been at the cornerstone of this research, with numerous studies having demonstrated that PWS better differentiates ruptured AAAs from non-ruptured AAAs. In contrast to wall stress models, which have become progressively more sophisticated, there has been relatively little progress in estimating patient-specific wall strength. This is because wall strength cannot be inferred non-invasively, and measurements from excised patient tissues show a large spectrum of wall strength values. In this review, we highlight studies that investigated the relationship between biomechanics and AAA rupture risk. We conclude that combining wall stress and wall strength approximations should provide better estimations of AAA rupture risk. However, before personalized biomechanical AAA risk assessment can become a reality, better methods for estimating patient-specific wall properties or surrogate markers of aortic wall degradation are needed. Artificial intelligence methods can be key in stratifying patients, leading to personalized AAA risk assessment.

Was the Devonian placoderm Titanichthys a suspension feeder?

Large nektonic suspension feeders have evolved multiple times. The apparent trend among apex predators for some evolving into feeding on small zooplankton is of interest for understanding the associated shifts in anatomy and behaviour, while the spatial and temporal distribution gives clues to an inherent relationship with ocean primary productivity and how past and future perturbations to these may impact on the different tiers of the food web. The evolution of large nektonic suspension feeders-'gentle giants'-occurred four times among chondrichthyan fishes (e.g. whale sharks, basking sharks and manta rays), as well as in baleen whales (mysticetes), the Mesozoic pachycormid fishes and at least twice in radiodontan stem group arthropods (Anomalocaridids) during the Cambrian explosion. The Late Devonian placoderm Titanichthys has tentatively been considered to have been a megaplanktivore, primarily due to its gigantic size and narrow, edentulous jaws while no suspension-feeding apparatus have ever been reported. Here, the potential for microphagy and other feeding behaviours in Titanichthys is assessed via a comparative study of jaw mechanics in Titanichthys and other placoderms with presumably differing feeding habits (macrophagy and durophagy). Finite-element models of the lower jaws of Titanichthys termieri in comparison to Dunkleosteus terrelli and Tafilalichthys lavocati reveal considerably less resistance to von Mises stress in this taxon. Comparisons with a selection of large-bodied extant taxa of similar ecological diversity reveal similar disparities in jaw stress resistance. Our results, therefore, conform to the hypothesis that Titanichthys was a suspension feeder with jaws ill-suited for biting and crushing but well suited for gaping ram feeding.

Abdominal aortic calcification: from ancient friend to modern foe

Background

Abdominal aortic calcifications were already ubiquitous in ancient populations from all continents. Although nowadays generally considered as an innocent end stage of stabilised atherosclerotic plaques, increasing evidence suggests that arterial calcifications contribute to cardiovascular risk. In this review we address abdominal aortic calcification from an evolutionary perspective and review the literature on histology, prevalence, risk factors, clinical outcomes and pharmacological interventions of abdominal aortic calcification.

Design

The design of this study was based on a literature review.

Methods

Pubmed and Embase were systematically searched for articles on abdominal aortic calcification and its synonyms without language restrictions. Articles with data on histology, prevalence, risk factors clinical outcomes and/or pharmacological interventions were selected.

Results

Abdominal aortic calcification is highly prevalent in the general population and prevalence and extent increase with age. Prevalence and risk factors differ between males and females and different ethnicities. Risk factors include traditional cardiovascular risk factors and decreased bone mineral density. Abdominal aortic calcification is shown to contribute to arterial stiffness and is a strong predictor of cardiovascular events and mortality. Several therapies to inhibit arterial calcification have been developed and investigated in small clinical trials.

Conclusions

Abdominal aortic calcification is from all eras and increasingly acknowledged as an independent contributor to cardiovascular disease. Large studies with long follow-up must be carried out to show whether inhibition of abdominal aortic calcification will further reduce cardiovascular risk.

Combining Volumetric and Wall Shear Stress Analysis from CT to Assess Risk of Abdominal Aortic Aneurysm Progression

Background Despite known limitations, the decision to operate on abdominal aortic aneurysm (AAA) is primarily on the basis of measurement of maximal aneurysm diameter. Purpose To identify volumetric and computational fluid dynamics parameters to predict AAAs that are likely to progress in size. Materials and Methods This study, part of a multicenter prospective registry (NCT01599533), included 126 patients with AAA. Patients were sorted into stable (≤10-mL increase in aneurysm volume) and progression (>10-mL increase in aneurysm volume) groups. Initial AAA characteristics of the derivation cohort were analyzed (maximal diameter and surface, thrombus and lumen volumes, maximal wall pressure, and wall shear stress [WSS]) to identify relevant parameters for a logistic regression model. Model and maximal diameter diagnostic performances were assessed in both cohorts and for AAAs smaller than 50 mm by using area under the receiver operating characteristic curve (AUC). Results Eighty-one patients were included (mean age, 73 years ± 7 years [standard deviation]; 78 men). The derivation and validation cohorts included, respectively, 50 and 31 participants. In the derivation cohort, there was higher mean lumen volume and lower mean WSS in the progression group compared with the stable group (60 mL ± 14 vs 46 mL ± 18 [P = .005] and 66% ± 6 vs 53% ± 9 [P = .02], respectively). Mean lumen volume and mean WSS at baseline were correlated to total volume growth (r = 0.47 [P = .002] and -0.42 [P = .006], respectively). In the derivation cohort, a regression model including lumen volume and WSS to predict aneurysm enlargement was superior to maximal diameter alone (AUC, 0.78 vs 0.52, respectively; P = .003); although no difference was found in the validation cohort (AUC, 0.79 vs 0.71, respectively; P = .51). For AAAs smaller than 50 mm, a regression model that included both baseline WSS and lumen volume performed better than maximal diameter (AUC, 0.79 vs 0.53, respectively; P = .01). Conclusion Combined analysis of lumen volume and wall shear stress was associated with enlargement of abdominal aortic aneurysms at 1 year, particularly in aneurysms smaller than 50 mm in diameter. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Mitsouras and Leach in this issue.

On the Relative Impact of Intraluminal Thrombus Heterogeneity on Abdominal Aortic Aneurysm Mechanics

Intraluminal thrombus (ILT) is present in the majority of abdominal aortic aneurysms (AAA) of a size warranting consideration for surgical or endovascular intervention. The rupture risk of AAAs is thought to be related to the balance of vessel wall strength and the mechanical stress caused by systemic blood pressure. Previous finite element analyses of AAAs have shown that ILT can reduce and homogenize aneurysm wall stress. These works have largely considered ILT to be homogeneous in mechanical character or have idealized a stiffness distribution through the thrombus thickness. In this work, we use magnetic resonance imaging (MRI) to delineate the heterogeneous composition of ILT in 7 AAAs and perform patient-specific finite element analysis under multiple conditions of ILT layer stiffness disparity. We find that explicit incorporation of ILT heterogeneity in the finite element analysis is unlikely to substantially alter major stress analysis predictions regarding aneurysm rupture risk in comparison to models assuming a homogenous thrombus, provided that the maximal ILT stiffness is the same between models. Our results also show that under a homogeneous ILT assumption, the choice of ILT stiffness from values common in the literature can result in significantly larger variations in stress predictions compared to the effects of thrombus heterogeneity.

Role of intraluminal thrombus in abdominal aortic aneurysm ruptures: A hemodynamic point of view

PURPOSE

Intraluminal thrombus (ILTs) are found in most abdominal aortic aneurysms (AAAs) of clinically relevant size; however, the role of ILTs in AAA ruptures remains unclear. This study investigated the role of the presence and thickness of ILTs in AAA ruptures by analyzing the hemodynamic environment in ruptured AAAs (RAAAs).

METHODS

Three-dimensional reconstructions from computed tomography scans were performed, and 13 RAAA cases were categorized into a no-ILT group, a thin-layered ILT group (thickness < 3 mm), and a thick-layered ILT group. The hemodynamic features of the RAAAs were assessed using computational fluid dynamics simulation.

RESULTS

The thin- and thick-layered ILT groups showed significant differences in aneurysm diameters (P < 0.05). The three types of AAAs ruptured at different flow regions, with different hemodynamic features: (a) the no-ILT AAAs ruptured at regions of flow recirculation where velocity and wall shear stresses (WSSs) were close to zero; (b) the thin-layered ILT AAAs ruptured at sites at which the dominant flow impinged the wall; and (c) the thick-layered ILT AAAs ruptured at the border of the dominant flow channel and recirculation zone where the flow velocity and pressure changed dramatically.

CONCLUSIONS

Hemodynamic characteristics influence the rupture mechanisms of particular AAAs differently on the basis of the presence and thickness of ILTs. Recirculation flows and low WSSs may have negative effects by inducing local rupture or positive effects by promoting the formation of thin-layered ILTs. However, eccentrically located thick-layered ILTs may increase the rupture risk of small AAAs because of their location in the sac lumen, which results in chaotic flow patterns and rapid increases in flow resistance.

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.

COMPARISON OF TWO METHODS FOR ESTIMATING THE UNLOADED STATE FOR ABDOMINAL AORTIC ANEURYSM STRESS CALCULATIONS

Biomechanical analyses can be used to better understand the rupture risk of abdominal aortic aneurysms (AAAs) on a patient-specific basis using vascular geometries obtained from medical imaging. Methodologies of varying complexity are used to estimate the unloaded state of the imaged vessel to provide a reference configuration for finite element simulations. In this work, we compare the implementation and results of two of these methods, one based on geometric scaling and the other using an iterative determination of unloaded vessel geometry. We find that the two methods result in significantly different stress predictions, and that the iterative method offers superior geometric accuracy. Our findings lend context to the variation in finite element results presented in the AAA stress analysis literature.

Finite element analysis in symptomatic and asymptomatic abdominal aortic aneurysms for aortic disease risk stratification

BACKGROUND

Advanced biomechanical models can provide additional information concerning rupture risk in abdominal aortic aneurysms (AAA). Here we evaluated the predictive value of finite element analysis (FEA) to assess AAA rupture risk.

METHODS

In a case-control study, we compared FEA parameters in a group of symptomatic AAA (sAAA) patients, considered as a high risk of rupture group, with FEA parameters in asymptomatic AAA patients (aAAA).

RESULTS

We included 15 sAAA and 28 aAAA patients matched for age- and maximum diameter diagnosed with infrarenal non-ruptured AAA at our center between 2009 and 2013. Mean age was 75±69 years and mean maximum diameter was 77±17 mm. Peak wall stress (PWS) was significantly higher in sAAA patients than in aAAA patients (354.3±139.6 kPa vs. 248.6±81.9 kPa; P=0.001). The C statistic for the ROC curve based on PWS was 0.748 (95% CI: 0.592-0.903; P=0.008). CART analysis classified patients into high and low PWS groups. The high-PWS group (>305.15 kPa; N.=15) had a higher incidence of sAAA (33.3% aAAA, 66.7% sAAA) than the low-PWS-group (≤305.15 kPa; N.=28. 82.1% aAAA, 17.9% sAAA).

CONCLUSIONS

In conclusion, PWS was significantly higher in sAAA patients. Measuring PWS may help estimate the individual rupture risk in patients with AAA, but larger studies are needed to confirm our results.

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.

Systematic Review of Circulating, Biomechanical, and Genetic Markers for the Prediction of Abdominal Aortic Aneurysm Growth and Rupture

BACKGROUND

The natural course of abdominal aortic aneurysms (AAA) is growth and rupture if left untreated. Numerous markers have been investigated; however, none are broadly acknowledged. Our aim was to identify potential prognostic markers for AAA growth and rupture.

METHODS AND RESULTS

Potential circulating, biomechanical, and genetic markers were studied. A comprehensive search was conducted in PubMed, Embase, and Cochrane Library in February 2017, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Study selection, data extraction, and methodological quality assessment were conducted by 2 independent researchers. Plausibility of markers was based on the amount of publications regarding the marker (more than 3), pooled sample size (more than 100), bias risk and statistical significance of the studies. Eighty-two studies were included, which examined circulating (n=40), biomechanical (n=27), and genetic markers (n=7) and combinations of markers (n=8). Factors with an increased expansion risk included: AAA diameter (9 studies; n=1938; low bias risk), chlamydophila pneumonia (4 studies; n=311; medium bias risk), S-elastin peptides (3 studies; n=205; medium bias risk), fluorodeoxyglucose uptake (3 studies; n=104; medium bias risk), and intraluminal thrombus size (5 studies; n=758; medium bias risk). Factors with an increased rupture risk rupture included: peak wall stress (9 studies; n=579; medium bias risk) and AAA diameter (8 studies; n=354; medium bias risk). No meta-analysis was conducted because of clinical and methodological heterogeneity.

CONCLUSIONS

We identified 5 potential markers with a prognostic value for AAA growth and 2 for rupture. While interpreting these data, one must realize that conclusions are based on small sample sizes and clinical and methodological heterogeneity. Prospective and methodological consonant studies are strongly urged to further study these potential markers.

Machine learning-aided exploration of relationship between strength and elastic properties in ascending thoracic aneurysm

Machine learning was applied to classify tension-strain curves harvested from inflation tests on ascending thoracic aneurysm samples. The curves were classified into rupture and nonrupture groups using prerupture response features. Two groups of features were used as the basis for classification. The first was the constitutive parameters fitted from the tension-strain data, and the second was geometric parameters extracted from the tension-strain curve. Based on the importance scores provided by the machine learning, implications of some features were interrogated. It was found that (1) the value of a constitutive parameter is nearly the same for all members in the rupture group and (2) the strength correlates strongly with a tension in the early phase of response as well as with the end stiffness. The study suggests that the strength, which is not available without rupturing the tissue, may be indirectly inferred from prerupture response features.

The impact of personalized probabilistic wall thickness models on peak wall stress in abdominal aortic aneurysms

If computational models are ever to be used in high-stakes decision making in clinical practice, the use of personalized models and predictive simulation techniques is a must. This entails rigorous quantification of uncertainties as well as harnessing available patient-specific data to the greatest extent possible. Although researchers are beginning to realize that taking uncertainty in model input parameters into account is a necessity, the predominantly used probabilistic description for these uncertain parameters is based on elementary random variable models. In this work, we set out for a comparison of different probabilistic models for uncertain input parameters using the example of an uncertain wall thickness in finite element models of abdominal aortic aneurysms. We provide the first comparison between a random variable and a random field model for the aortic wall and investigate the impact on the probability distribution of the computed peak wall stress. Moreover, we show that the uncertainty about the prevailing peak wall stress can be reduced if noninvasively available, patient-specific data are harnessed for the construction of the probabilistic wall thickness model.

The Obsolete Maximum Diameter Criterion, the Evident Role of Biomechanical (Pressure) Indices, the New Role of Hemodynamic (Flow) Indices, and the Multi-Modal Approach to the Rupture Risk Assessment of Abdominal Aortic Aneurysms

Although the therapeutic management of abdominal aortic aneurysms (AAAs) is currently based on the maximum diameter criterion, this has often proved inaccurate and misleading. Conversely, the biomechanical approach, which takes into account the pressure-induced wall stress exerted at every point throughout the aneurysmal surface, has been proven superior in predicting the rupture risk of AAAs, and its value is being increasingly recognized among physicians. More recently, hemodynamic indices, such as flow-induced wall shear stresses, have been indicated as potentially significant determinants of AAA natural history. Ultimately, a statistical model that takes into account all these factors may be relevant for making a sound prediction of the rupture risk of aneurysms and optimizing the management of these patients.

Applicability of simplified computational models in prediction of peak wall stress in abdominal aortic aneurysms

In the paper impact of different material models on the calculated peak wall stress (PWS) and peak wall rupture risk (PWRR) in abdominal aortic aneurysms (AAAs) is assessed. Computational finite element models of 70 patient-specific AAAs were created using two different material models - a realistic one based on mean population results of uniaxial tests of AAA wall considered as reference, and a 100 times stiffer artificial model. The calculated results of PWS and PWRR were tested to evaluate statistical significance of differences caused by the non-realistic material model. It was shown that for majority of AAAs the differences are insignificant but for some 10% of them their relative differences exceed 20% which may lead to incorrect decisions on their surgical treatment. This percentage of failures favours application of realistic material models in clinical practise although they are much more time-consuming.

Increased Peak Wall Stress, but Not Maximum Diameter, Is Associated with Symptomatic Abdominal Aortic Aneurysm

OBJECTIVE

Maximum diameter (MD) is the established rupture predictor for abdominal aortic aneurysm (AAA). However, biomechanical markers from finite element analysis (FEA) could be more accurate predictors for these patients. In this study, the association between peak wall stress (PWS) and MD with symptoms of AAA was evaluated.

METHODS

Patients diagnosed with infrarenal non-ruptured AAA at the centre between 2009 and 2015 were included. Clinical data, morphological variables (including MD), and the biomechanical variables PWS and diameter normalised PWS (dnPWS) in symptomatic (sAAA) and asymptomatic AAA patients (aAAA) were included.

RESULTS

A total of 170 patients were analysed, 153 aAAA and 17 sAAA. MD was significantly greater in sAAA patients than in aAAA patients (70.4 mm, 95% CI 66.4-86.0 vs. 59.1 mm, 95% CI 53.7-67.8, respectively; p = .002). PWS was also significantly higher in the sAAA group (324.6 kPa, 95% CI 217.4-399.5 vs. 199.2 kPa, 95% CI 165.6-239.5; p < .01). No differences in MD were found in patients with an AAA ≥ 65 mm (43 aAAA and 14 sAAA); however, both PWS (327.4 kPa, 95% CI 239.0-473.3 vs. 229.4 kPa, 95% CI 210.0 to 289.4; p = .020) and dnPWS (4.3, 95% CI 3.17-4.67 vs. 3.03, 95% CI 2.8-3.49; p = .004) were higher in sAAA than in aAAA.

CONCLUSIONS

This study suggests that MD and the biomechanical parameters obtained by finite element analysis are greater in sAAA than in aAAA. However, considering patients with MD ≥ 65 mm alone, only PWS, and particularly dnPWS, were able to differentiate sAAA from aAAA.

A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm

Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused on relationship between intuitive geometric features (e.g., diameter and curvature) and wall stress. This work investigates the feasibility of a machine learning approach to establish the linkages between shape features and FEA-predicted AsAA rupture risk, and it may serve as a faster surrogate for FEA associated with long simulation time and numerical convergence issues. This method consists of four main steps: (1) constructing a statistical shape model (SSM) from clinical 3D CT images of AsAA patients; (2) generating a dataset of representative aneurysm shapes and obtaining FEA-predicted risk scores defined as systolic pressure divided by rupture pressure (rupture is determined by a threshold criterion); (3) establishing relationship between shape features and risk by using classifiers and regressors; and (4) evaluating such relationship in cross-validation. The results show that SSM parameters can be used as strong shape features to make predictions of risk scores consistent with FEA, which lead to an average risk classification accuracy of 95.58% by using support vector machine and an average regression error of 0.0332 by using support vector regression, while intuitive geometric features have relatively weak performance. Compared to FEA, this machine learning approach is magnitudes faster. In our future studies, material properties and inhomogeneous thickness will be incorporated into the models and learning algorithms, which may lead to a practical system for clinical applications.

Gene Expression Profiling in Abdominal Aortic Aneurysms After Finite Element Rupture Risk Assessment

PURPOSE

To investigate the association between local biomechanical rupture risk calculations from finite element analysis (FEA) and whole-genome profiling of the abdominal aortic aneurysm (AAA) wall to determine if AAA wall regions with highest and lowest estimated rupture risk show different gene expression patterns.

METHODS

Six patients (mean age 74 years; all men) scheduled for open surgery to treat asymptomatic AAAs (mean diameter 55.2±3.5 mm) were recruited for the study. Rupture risk profiles were estimated by FEA from preoperative computed tomography angiography data. During surgery, AAA wall samples of ~10 mm² were extracted from the lowest and highest rupture risk locations identified by the FEA. Twelve samples were processed for RNA extraction and subsequent whole genome expression profiling. Expression of single genes and of predefined gene groups were compared between vessel wall areas with highest and lowest predicted rupture risk.

RESULTS

Normalized datasets comprised 15,079 gene transcripts with expression above background. In biopsies with high rupture risk, upregulation of 18 and downregulation of 18 genes was detected when compared to the low-risk counterpart. Global analysis of predefined gene groups revealed expression differences in genes associated with extracellular matrix (ECM) degradation (p<0.001), matrix metalloproteinase activity (p<0.001), and chemokine signaling (p<0.001).

CONCLUSION

Increased expression of genes involved in degrading ECM components was present in AAA wall regions with highest biomechanical stress, supporting the thesis of mechanotransduction. More experimental studies with cooperation of multicenter vascular biobanks are necessary to understand AAA etiologies and identify further parameters of FEA model complementation.

BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms

An abdominal aortic aneurysm (AAA) is a permanent and irreversible dilation of the lower region of the aorta. It is a symptomless condition that, if left untreated, can expand until rupture. Despite ongoing efforts, an efficient tool for accurate estimation of AAA rupture risk is still not available. Furthermore, a lack of standardisation across current approaches and specific obstacles within computational workflows limit the translation of existing methods to the clinic. This paper presents BioPARR (Biomechanics based Prediction of Aneurysm Rupture Risk), a software system to facilitate the analysis of AAA using a finite element analysis based approach. Except semi-automatic segmentation of the AAA and intraluminal thrombus (ILT) from medical images, the entire analysis is performed automatically. The system is modular and easily expandable, allows the extraction of information from images of different modalities (e.g. CT and MRI) and the simulation of different modelling scenarios (e.g. with/without thrombus). The software uses contemporary methods that eliminate the need for patient-specific material properties, overcoming perhaps the key limitation to all previous patient-specific analysis methods. The software system is robust, free, and will allow researchers to perform comparative evaluation of AAA using a standardised approach. We report preliminary data from 48 cases.

Gender, smoking, body size, and aneurysm geometry influence the biomechanical rupture risk of abdominal aortic aneurysms as estimated by finite element analysis

OBJECTIVE

Finite element analysis (FEA) has been suggested to be superior to maximal diameter measurements in predicting rupture of abdominal aortic aneurysms (AAAs). Our objective was to investigate to what extent previously described rupture risk factors were associated with FEA-estimated rupture risk.

METHODS

One hundred forty-six patients with an asymptomatic AAA of a 40- to 60-mm diameter were retrospectively identified and consecutively included. The patients' computed tomography angiograms were analyzed by FEA without (neutral) and with (specific) input of patient-specific mean arterial pressure (MAP), gender, family history, and age. The maximal wall stress/wall strength ratio was described as a rupture risk equivalent diameter (RRED), which translated this ratio into an average aneurysm diameter of corresponding rupture risk.

RESULTS

In multivariate linear regression, RRED_neutral increased with female gender (3.7 mm; 95% confidence interval [CI], 0.13-7.3) and correlated with patient height (0.27 mm/cm; 95% CI, 0.11-0.43) and body surface area (BSA, 16 mm/m²; 95% CI, 8.3-24) and inversely with body mass index (BMI, -0.40 mm/kg m^-2; 95% CI, -0.75 to -0.054) in a wall stress-dependent manner. Wall stress-adjusted RRED_neutral was raised if the patient was currently smoking (1.1 mm; 95% CI, 0.21-1.9). Age, MAP, family history, and patient weight were unrelated to RRED_neutral. In specific FEA, RRED_specific increased with female gender, MAP, family history positive for AAA, height, and BSA, whereas it was inversely related to BMI. All results were independent of aneurysm diameter. Peak wall stress and RRED correlated with aneurysm diameter and lumen volume.

CONCLUSIONS

Female gender, current smoking, increased patient height and BSA, and low BMI were found to increase the mechanical rupture risk of AAAs. Previously described rupture risk factors may in part be explained by patient characteristic-dependent variations in aneurysm biomechanics.

High Structural Stress and Presence of Intraluminal Thrombus Predict Abdominal Aortic Aneurysm 18F-FDG Uptake: Insights From Biomechanics

Supplemental Digital Content is available in the text.

Background—

Abdominal aortic aneurysm (AAA) wall inflammation and mechanical structural stress may influence AAA expansion and lead to rupture. We hypothesized a positive correlation between structural stress and fluorine-18-labeled 2-deoxy-2-fluoro-d-glucose (¹⁸F-FDG) positron emission tomography–defined inflammation. We also explored the influence of computed tomography–derived aneurysm morphology and composition, including intraluminal thrombus, on both variables.

Methods and Results—

Twenty-one patients (19 males) with AAAs below surgical threshold (AAA size was 4.10±0.54 cm) underwent ¹⁸F-FDG positron emission tomography and contrast-enhanced computed tomography imaging. Structural stresses were calculated using finite element analysis. The relationship between maximum aneurysm ¹⁸F-FDG standardized uptake value within aortic wall and wall structural stress, patient clinical characteristics, aneurysm morphology, and compositions was explored using a hierarchical linear mixed-effects model. On univariate analysis, local aneurysm diameter, thrombus burden, extent of calcification, and structural stress were all associated with ¹⁸F-FDG uptake (P<0.05). AAA structural stress correlated with ¹⁸F-FDG maximum standardized uptake value (slope estimate, 0.552; P<0.0001). Multivariate linear mixed-effects analysis revealed an important interaction between structural stress and intraluminal thrombus in relation to maximum standardized uptake value (fixed effect coefficient, 1.68 [SE, 0.10]; P<0.0001). Compared with other factors, structural stress was the best predictor of inflammation (receiver-operating characteristic curve area under the curve =0.59), with higher accuracy seen in regions with high thrombus burden (area under the curve =0.80). Regions with both high thrombus burden and high structural stress had higher ¹⁸F-FDG maximum standardized uptake value compared with regions with high thrombus burdens but low stress (median [interquartile range], 1.93 [1.60–2.14] versus 1.14 [0.90–1.53]; P<0.0001).

Conclusions—

Increased aortic wall inflammation, demonstrated by ¹⁸F-FDG positron emission tomography, was observed in AAA regions with thick intraluminal thrombus subjected to high mechanical stress, suggesting a potential mechanistic link underlying aneurysm inflammation.

Biomechanical Indices for Rupture Risk Estimation in Abdominal Aortic Aneurysms

PURPOSE

To review the use of biomechanical indices for the estimation of abdominal aortic aneurysm (AAA) rupture risk, emphasizing their potential use in a clinical setting.

METHODS

A search of the PubMed, Embase, Scopus, and Compendex databases was made up to June 2015 to identify articles involving biomechanical analysis of AAA rupture risk. Outcome variables [aneurysm diameter, peak wall stress (PWS), peak wall shear stress (PWSS), wall strain, peak wall rupture index (PWRI), and wall stiffness] were compared for asymptomatic intact AAAs vs symptomatic or ruptured AAAs. For quantitative analysis of the pooled data, a random effects model was used to calculate the standard mean differences (SMDs) with the 95% confidence interval (CI) for the biomechanical indices.

RESULTS

The initial database searches yielded 1894 independent articles of which 19 were included in the analysis. The PWS was significantly higher in the symptomatic/ruptured group, with a SMD of 1.11 (95% CI 0.93 to 1.26, p<0.001). Likewise, the PWRI was significantly higher in the ruptured or symptomatic group, with a SMD of 1.15 (95% CI 0.30 to 2.01, p=0.008). After adjustment for the aneurysm diameter, the PWS remained higher in the ruptured or symptomatic group, with a SMD of 0.85 (95% CI 0.46 to 1.23, p<0.001). Less is known of the wall shear stress and wall strain indices, as too few studies were available for analysis.

CONCLUSION

Biomechanical indices are a promising tool in the assessment of AAA rupture risk as they incorporate several factors, including geometry, tissue properties, and patient-specific risk factors. However, clinical implementation of biomechanical AAA assessment remains a challenge owing to a lack of standardization.