Wall Stress Analysis in Small Asymptomatic, Symptomatic and Ruptured Abdominal Aortic Aneurysms

An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their clinically-estimated risk of rupture-an event that is the 13th leading cause of death in the US-exceeds the risk associated with repair. Yet the current clinical guideline remains a one-size-fits-all "maximum diameter criterion" whereby AAA exceeding a threshold diameter is thought to make the risk of rupture high enough to warrant intervention. However, between 7 and 23.4% of smaller-sized AAA have been reported to rupture with diameters below the threshold. In this study, we train and assess machine learning models using clinical, biomechanical, and morphological indices from 381 patients to develop an aneurysm prognosis classifier to predict one of three outcomes for a given AAA patient: their AAA will remain stable, their AAA will require repair based as currently indicated from the maximum diameter criterion, or their AAA will rupture. This study represents the largest cohort of AAA patients that utilizes the first available medical image and clinical data to classify patient outcomes. The APC model therefore represents a potential clinical tool to striate specific patient outcomes using machine learning models and patient-specific image-based (biomechanical and morphological) and clinical data as input. Such a tool could greatly assist clinicians in their management decisions for patients with AAA.

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.

How does hemodynamics affect rupture tissue mechanics in abdominal aortic aneurysm: Focus on wall shear stress derived parameters, time-averaged wall shear stress, oscillatory shear index, endothelial cell activation potential, and relative residence time

An abdominal aortic aneurysm (AAA) is a critical health condition with a risk of rupture, where the diameter of the aorta enlarges more than 50% of its normal diameter. The incidence rate of AAA has increased worldwide. Currently, about three out of every 100,000 people have aortic diseases. The diameter and geometry of AAAs influence the hemodynamic forces exerted on the arterial wall. Therefore, a reliable assessment of hemodynamics is crucial for predicting the rupture risk. Wall shear stress (WSS) is an important metric to define the level of the frictional force on the AAA wall. Excessive levels of WSS deteriorate the remodeling mechanism of the arteries and lead to abnormal conditions. At this point, WSS-related hemodynamic parameters, such as time-averaged WSS (TAWSS), oscillatory shear index (OSI), endothelial cell activation potential (ECAP), and relative residence time (RRT) provide important information to evaluate the shear environment on the AAA wall in detail. Calculation of these parameters is not straightforward and requires a physical understanding of what they represent. In addition, computational fluid dynamics (CFD) solvers do not readily calculate these parameters when hemodynamics is simulated. This review aims to explain the WSS-derived parameters focusing on how these represent different characteristics of disturbed hemodynamics. A representative case is presented for spatial and temporal formulation that would be useful for interested researchers for practical calculations. Finally, recent hemodynamics investigations relating WSS-related parameters with AAA rupture risk assessment are presented. This review will be useful to understand the physical representation of WSS-related parameters in cardiovascular flows and how they can be calculated practically for AAA investigations.

An Objective and Repeatable Sac Isolation Technique for Comparing Biomechanical Metrics in Abdominal Aortic Aneurysms

(1) Abdominal aortic aneurysm (AAA) biomechanics-based metrics often reported may be over/under-estimated by including non-aneurysmal regions in the analyses, which is typical, rather than isolating the dilated sac region. We demonstrate the utility of a novel sac-isolation algorithm by comparing peak/mean wall stress (PWS, MWS), with/without sac isolation, for AAA that were categorized as stable or unstable in 245 patient CT image sets. (2) 245 patient computed tomography images were collected, segmented, meshed, and had subsequent finite element analysis performed in preparation of our novel sac isolation technique. Sac isolation was initiated by rotating 3D surfaces incrementally, extracting 2D projections, curve fitting a Fourier series, and taking the local extrema as superior/inferior boundaries for the aneurysmal sac. The PWS/MWS were compared pairwise using the entire aneurysm and the isolated sac alone. (3) MWS, not PWS, was significantly different between the sac alone and the entire aneurysm. We found no statistically significant difference in wall stress measures between stable (n = 222) and unstable (n = 23) groups using the entire aneurysm. However, using sac-isolation, PWS (24.6 ± 7.06 vs. 20.5 ± 8.04 N/cm2; p = 0.003) and MWS (12.0 ± 3.63 vs. 10.5 ± 4.11 N/cm2; p = 0.022) were both significantly higher in unstable vs. stable groups. (4) Our results suggest that evaluating only the AAA sac can influence wall stress metrics and may reveal differences in stable and unstable groups of aneurysms that may not otherwise be detected when the entire aneurysm is used.

Artificial intelligence framework to predict wall stress in abdominal aortic aneurysm

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their risk of rupture - which is the 13th leading cause of death in the US - exceeds the risks associated with repair. Clinical intervention occurs when an aneurysm diameter exceeds 5.5 cm, but this "one-size fits all" criterion is insufficient, as it has been reported thatup to a quarter of AAA smaller than 5.5 cm do rupture. Therefore, there is a need for a more reliable, patient-specific, clinical tool to aide in the management of AAA. Biomechanical assessment of AAA is thought to provide critical physical insights to rupture risk, but clinical translataion of biomechanics-based tools has been limited due to the expertise, time, and computational requirements. It was estimated that through 2015, only 348 individual AAA cases have had biomechanical stress analysis performed, suggesting a deficient sample size to make such analysis relevant in the clinic. Artificial intelligence (AI) algorithms offer the potential to increase the throughput of AAA biomechanical analyses by reducing the overall time required to assess the wall stresses in these complex structures using traditional methods. This can be achieved by automatically segmenting regions of interest from medical images and using machine learning models to predict wall stresses of AAA. In this study, we present an automated AI-based methodology to predict the biomechanical wall stresses for individual AAA. The predictions using this approach were completed in a significantly less amount of time compared to a more traditional approach (~4 hours vs 20 seconds).

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

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.

Neonatal Microsurgical Repair of a Congenital Abdominal Aortic Aneurysm with a Cadaveric Graft

Congenital abdominal aortic aneurysms (AAA) are an extremely rare entity. We present the case of a female fetus diagnosed with an AAA on routine prenatal ultrasound. A postnatal computed tomography angiogram revealed an infrarenal AAA with a narrow proximal neck. Surgery was performed on day of life 14 using a cadaveric femoral artery graft. The proximal anastomosis was performed under the microscope given the severity of the aortic stenosis and the proximity of the renal arteries. The patient's postoperative course was uneventful and she is developing normally 1 year after surgery. The graft remains permeable, albeit with evidence of proximal and distal stenosis and graft calcification on imaging.

Synthetic photoplethysmography (PPG) of the radial artery through parallelized Monte Carlo and its correlation to body mass index (BMI)

Cardiovascular disease is one of the leading causes of death in the United States and obesity significantly increases the risk of cardiovascular disease. The measurement of blood pressure (BP) is critical in monitoring and managing cardiovascular disease hence new wearable devices are being developed to make BP more accessible to physicians and patients. Several wearables utilize photoplethysmography from the wrist vasculature to derive BP assessment although many of these devices are still at the experimental stage. With the ultimate goal of supporting instrument development, we have developed a model of the photoplethysmographic waveform derived from the radial artery at the volar surface of the wrist. To do so we have utilized the relation between vessel biomechanics through Finite Element Method and Monte Carlo light transport model. The model shows similar features to that seen in PPG waveform captured using an off the shelf device. We observe the influence of body mass index on the PPG signal. A degradation the PPG signal of up to 40% in AC to DC signal ratio was thus observed.

Estimating aortic thoracic aneurysm rupture risk using tension-strain data in physiological pressure range: an in vitro study

Previous studies have shown that the rupture properties of an ascending thoracic aortic aneurysm (ATAA) are strongly correlated with the pre-rupture response features. In this work, we present a two-step machine learning method to predict where the rupture is likely to occur in ATAA and what safety reserve the structure may have. The study was carried out using ATAA specimens from 15 patients who underwent surgical intervention. Through inflation test, full-field deformation data and post-rupture images were collected, from which the wall tension and surface strain distributions were computed. The tension-strain data in the pressure range of 9-18 kPa were fitted to a third-order polynomial to characterize the response properties. It is hypothesized that the region where rupture is prone to initiate is associated with a high level of tension buildup. A machine learning method is devised to predict the peak risk region. The predicted regions were found to match the actual rupture sites in 13 samples out of the total 15. In the second step, another machine learning model is utilized to predict the tissue's rupture strength in the peak risk region. Results suggest that the ATAA rupture risk can be reasonably predicted using tension-strain response in the physiological range. This may open a pathway for evaluating the ATAA rupture propensity using information of in vivo response.

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.

A large proportion of patients with small ruptured abdominal aortic aneurysms are women and have chronic obstructive pulmonary disease

Objective

In a population-based cohort of ruptured abdominal aortic aneurysms (rAAAs), our aim was to investigate clinical, morphological and biomechanical features in patients with small rAAAs.

Methods

All patients admitted to an emergency department in Stockholm and Gotland, a region with a population of 2.1 million, between 2009–2013 with a CT-verified rupture (n = 192) were included, and morphological measurements were performed. Patients with small rAAAs, maximal diameter (Dmax) ≤ 60 mm were selected (n = 27), and matched 2:1 by Dmax, sex and age to intact AAA (iAAAs). For these patients, morphology including volume and finite element analysis-derived biomechanics were assessed.

Results

The mean Dmax for all rAAAs was 80.8 mm (SD = 18.9 mm), women had smaller Dmax at rupture (73.4 ± 18.4 mm vs 83.1 ± 18.5 mm, p = 0.003), and smaller neck and iliac diameters compared to men. Aortic size index (ASI) was similar between men and women (4.1 ± 3.1 cm/m² vs 3.8 ± 1.0 cm/m²). Fourteen percent of all patients ruptured at Dmax ≤ 60 mm, and a higher proportion of women compared to men ruptured at Dmax ≤ 60 mm: 27% (12/45) vs. 10% (15/147), p = 0.005. Also, a higher proportion of patients with a chronic obstructive pulmonary disease ruptured at Dmax ≤ 60 mm (34.6% vs 14.6%, p = 0.026). Supra-renal aortic size index (14.0, IQR 13.3–15.3 vs 12.8, IQR = 11.4–14.0) and peak wall rupture index (PWRI, 0.35 ± 0.08 vs 0.43 ± 0.11, p = 0.016) were higher for small rAAAs compared to matched iAAAs. Aortic size index, peak wall stress and aneurysm volume did not differ.

Conclusion

More than one tenth of ruptures occur at smaller diameters, women continuously suffer an even higher risk of presenting with smaller diameters, and this must be considered in surveillance programs. The increased supra-renal aortic size index and PWRI are potential markers for rupture risk, and patients under surveillance with these markers may benefit from increased attention, and potentially from timely repair.

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.

Navigation and visualisation with HoloLens in endovascular aortic repair

Introduction

Endovascular aortic repair (EVAR) is a minimal-invasive technique that prevents life-threatening rupture in patients with aortic pathologies by implantation of an endoluminal stent graft. During the endovascular procedure, device navigation is currently performed by fluoroscopy in combination with digital subtraction angiography. This study presents the current iterative process of biomedical engineering within the disruptive interdisciplinary project Nav EVAR, which includes advanced navigation, image techniques and augmented reality with the aim of reducing side effects (namely radiation exposure and contrast agent administration) and optimising visualisation during EVAR procedures. This article describes the current prototype developed in this project and the experiments conducted to evaluate it.

Methods

The current approach of the Nav EVAR project is guiding EVAR interventions in real-time with an electromagnetic tracking system after attaching a sensor on the catheter tip and displaying this information on Microsoft HoloLens glasses. This augmented reality technology enables the visualisation of virtual objects superimposed on the real environment. These virtual objects include three-dimensional (3D) objects (namely 3D models of the skin and vascular structures) and two-dimensional (2D) objects [namely orthogonal views of computed tomography (CT) angiograms, 2D images of 3D vascular models, and 2D images of a new virtual angioscopy whose appearance of the vessel wall follows that shown in ex vivo and in vivo angioscopies]. Specific external markers were designed to be used as landmarks in the registration process to map the tracking data and radiological data into a common space. In addition, the use of real-time 3D ultrasound (US) is also under evaluation in the Nav EVAR project for guiding endovascular tools and updating navigation with intraoperative imaging. US volumes are streamed from the US system to HoloLens and visualised at a certain distance from the probe by tracking augmented reality markers. A human model torso that includes a 3D printed patient-specific aortic model was built to provide a realistic test environment for evaluation of technical components in the Nav EVAR project. The solutions presented in this study were tested by using an US training model and the aortic-aneurysm phantom.

Results

During the navigation of the catheter tip in the US training model, the 3D models of the phantom surface and vessels were visualised on HoloLens. In addition, a virtual angioscopy was also built from a CT scan of the aortic-aneurysm phantom. The external markers designed for this study were visible in the CT scan and the electromagnetically tracked pointer fitted in each marker hole. US volumes of the US training model were sent from the US system to HoloLens in order to display them, showing a latency of 259±86 ms (mean±standard deviation).

Conclusion

The Nav EVAR project tackles the problem of radiation exposure and contrast agent administration during EVAR interventions by using a multidisciplinary approach to guide the endovascular tools. Its current state presents several limitations such as the rigid alignment between preoperative data and the simulated patient. Nevertheless, the techniques shown in this study in combination with fibre Bragg gratings and optical coherence tomography are a promising approach to overcome the problems of EVAR interventions.

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.

Hostility of proximal aortic neck anatomy in relation to abdominal aortic aneurysm size and its impact on the outcome of endovascular repair with the new generation endografts

BACKGROUND

To assess the relation of abdominal aortic aneurysm (AAA) diameter with the proximal neck anatomy (PNA) hostility and to evaluate its impact on the endovascular aneurysm repair (EVAR) outcomes with the use of newer generation endografts.

METHODS

Retrospective analysis of single institution's recorded data from February 2009 to April 2016. Patients' characteristics, comorbidities, aortic morphology, perioperative characteristics and outcomes were analyzed. In relation to AAA diameter 2 groups were identified: group A (50-55 mm) and group B (>55 mm). Hostile PNA was defined based on: neck diameter >28 mm, length <15 mm, angulation >60o, and circumferential thrombus and/or calcification >50%. The aortic neck scoring system was calculated. Multiple logistic regression analysis with a forward likelihood ratio method adjusted for age and gender was undertaken.

RESULTS

Three hundred seventeen patients (96% males, mean age 72.4±9 years, 80% elective) were follow-up for a mean of 23.4 months (range, 3-86 months). No differences were observed in demographics and co-morbidities between the two groups (group A: 134, 42% vs. group B: 183, 58%). Hostile PNA was present in 147/317 (46%) patients and significantly more likely to be present in group B (P<0.001). In group B the aortic neck score was higher (P<0.001), the likelihood for having hostile PNA increased for neck diameter by 2.2-fold (OR 2.2, P=0.013, 95% CI: 1.18-4.03), length by 2.3-fold (OR 2.3, P=0.012, 95% CI: 1.20-4.51), angle by 4.8-fold (OR 4.8, P=0.002, 95% CI: 1.79-13.24) and presence of thrombus by 1.5-fold (OR 1.5, P=0.037, 95% CI: 1.45-10.34). No association existed for neck calcification (P=0.071). Technical success, adjunctive procedures, perioperative characteristics and outcomes were comparable in friendly and hostile PNAs.

CONCLUSIONS

PNA hostility is more likely in AAA with diameter >55 mm but with the use of newer generation endografts this did not influence the short- and mid-term EVAR outcomes. Longer follow-up is needed for a more definite conclusion.

Biomechanical changes during abdominal aortic aneurysm growth

The biomechanics-based Abdominal Aortic Aneurysm (AAA) rupture risk assessment has gained considerable scientific and clinical momentum. However, such studies have mainly focused on information at a single time point, and little is known about how AAA properties change over time. Consequently, the present study explored how geometry, wall stress-related and blood flow-related biomechanical properties change during AAA expansion. Four patients with a total of 23 Computed Tomography-Angiography (CT-A) scans at different time points were analyzed. At each time point, patient-specific properties were extracted from (i) the reconstructed geometry, (ii) the computed wall stress at Mean Arterial Pressure (MAP), and (iii) the computed blood flow velocity at standardized inflow and outflow conditions. Testing correlations between these parameters identified several nonintuitive dependencies. Most interestingly, the Peak Wall Rupture Index (PWRI) and the maximum Wall Shear Stress (WSS) independently predicted AAA volume growth. Similarly, Intra-luminal Thrombus (ILT) volume growth depended on both the maximum WSS and the ILT volume itself. In addition, ILT volume, ILT volume growth, and maximum ILT layer thickness correlated with PWRI as well as AAA volume growth. Consequently, a large ILT volume as well as fast increase of ILT volume over time may be a risk factor for AAA rupture. However, tailored clinical studies would be required to test this hypothesis and to clarify whether monitoring ILT development has any clinical benefit.

Effects of anatomical characteristics as factors in abdominal aortic aneurysm rupture: CT aortography analysis

The aim of this study was to analyze the anatomical characteristics of patients with ruptured abdominal aortic aneurysms (AAAs) using computed tomography (CT) aortography in order to determine the risk factors for rupture.We retrospectively reviewed the CT aortography findings and medical records of patients with ruptured AAAs who underwent CT aortography between February 2002 and December 2014. Age, sex, blood pressure at the time of rupture, treatment methods used for the ruptured AAAs, and treatment outcomes were analyzed. Statistical analyses were performed to determine the association between the maximum aneurysm diameter, which is considered the standard predictor of aneurysm rupture, and anatomical characteristics such as proximal neck diameter, angle between the suprarenal aorta and the aneurysm neck (α angle), angle between the aneurysm neck and aneurysm sac (β angle), and angles between the abdominal aorta and both iliac arteries.Data were reviewed for a total of 36 patients. The mean maximum diameter of AAAs was 76.84 ± 21.08 mm. Multivariate analysis adjusted for age and sex indicated statistical correlations between the α and β angles and maximum aneurysm diameter and between the β angle and iliac artery involvement.Our results suggest that the tortuosity of the aorta tends to be associated with the diameter of AAAs and iliac artery involvement. Investigation of the anatomical characteristics of individual patients using CT aortography is expected to aid in predicting the risk of AAA rupture.

Abdominal Pain in the Presence of Small Abdominal Aortic Aneurysms: If in Doubt, Cut It Out!

Although small (<5 cm) abdominal aortic aneurysms (AAA) have been associated with symptoms and indication for intervention scarcely, the clinicians should never exclude such potential association especially in the absence of other overt pathological findings. In such cases, a surgical exploration with consequent intervention, if feasible, should be justified to prevent a detrimental evolution in a dubious scenario. In this article, we present 2 cases of patients with small AAA presenting with severe abdominal pain. In the absence of other solid clinical and radiological pathological findings, both patients underwent laparotomy where an inflammatory small AAA was identified and subjected either to resection and restoration with a tube graft or secondary endovascular repair because the periaortic fibrosis precluded the open repair. The characteristics and rationale of treatment modalities are exemplified and discussed.

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.

A Methodology for the Derivation of Unloaded Abdominal Aortic Aneurysm Geometry With Experimental Validation

In this work, we present a novel method for the derivation of the unloaded geometry of an abdominal aortic aneurysm (AAA) from a pressurized geometry in turn obtained by 3D reconstruction of computed tomography (CT) images. The approach was experimentally validated with an aneurysm phantom loaded with gauge pressures of 80, 120, and 140 mm Hg. The unloaded phantom geometries estimated from these pressurized states were compared to the actual unloaded phantom geometry, resulting in mean nodal surface distances of up to 3.9% of the maximum aneurysm diameter. An in-silico verification was also performed using a patient-specific AAA mesh, resulting in maximum nodal surface distances of 8 μm after running the algorithm for eight iterations. The methodology was then applied to 12 patient-specific AAA for which their corresponding unloaded geometries were generated in 5-8 iterations. The wall mechanics resulting from finite element analysis of the pressurized (CT image-based) and unloaded geometries were compared to quantify the relative importance of using an unloaded geometry for AAA biomechanics. The pressurized AAA models underestimate peak wall stress (quantified by the first principal stress component) on average by 15% compared to the unloaded AAA models. The validation and application of the method, readily compatible with any finite element solver, underscores the importance of generating the unloaded AAA volume mesh prior to using wall stress as a biomechanical marker for rupture risk assessment.

Biomechanical Imaging Markers as Predictors of Abdominal Aortic Aneurysm Growth or Rupture: A Systematic Review

OBJECTIVES

Biomechanical characteristics, such as wall stress, are important in the pathogenesis of abdominal aortic aneurysms (AAA) and can be visualised and quantified using imaging techniques. This systematic review aims to present an overview of all biomechanical imaging markers that have been studied in relation to AAA growth and rupture.

METHODS

This systematic review followed the PRISMA guidelines. A search in Medline, Embase, and the Cochrane Library identified 1503 potentially relevant articles. Studies were included if they assessed biomechanical imaging markers and their potential association with growth or rupture.

RESULTS

Twenty-seven articles comprising 1730 patients met the inclusion criteria. Eighteen studies performed wall stress analysis using finite element analysis (FEA), 13 of which used peak wall stress (PWS) to quantify wall stress. Ten of 13 case control FEA studies reported a significantly higher PWS for symptomatic or ruptured AAAs than for intact AAAs. However, in some studies there was confounding bias because of baseline differences in aneurysm diameter between groups. Clinical heterogeneity in methodology obstructed a meaningful meta-analysis of PWS. Three of five FEA studies reported a significant positive association between several wall stress markers, such as PWS and 99th percentile stress, and growth. One study reported a significant negative association and one other study reported no significant association. Studies assessing wall compliance, the augmentation index and wall stress analysis using Laplace's law, computational fluid dynamics and fluid structure interaction were also included in this systematic review.

CONCLUSIONS

Although PWS is significantly higher in symptomatic or ruptured AAAs in most FEA studies, confounding bias, clinical heterogeneity, and lack of standardisation limit the interpretation and generalisability of the results. Also, there is conflicting evidence on whether increased wall stress is associated with growth.

Biomechanical Rupture Risk Assessment: A Consistent and Objective Decision-Making Tool for Abdominal Aortic Aneurysm Patients

Abdominal aortic aneurysm (AAA) rupture is a local event in the aneurysm wall that naturally demands tools to assess the risk for local wall rupture. Consequently, global parameters like the maximum diameter and its expansion over time can only give very rough risk indications; therefore, they frequently fail to predict individual risk for AAA rupture. In contrast, the Biomechanical Rupture Risk Assessment (BRRA) method investigates the wall's risk for local rupture by quantitatively integrating many known AAA rupture risk factors like female sex, large relative expansion, intraluminal thrombus-related wall weakening, and high blood pressure. The BRRA method is almost 20 years old and has progressed considerably in recent years, it can now potentially enrich the diameter indication for AAA repair. The present paper reviews the current state of the BRRA method by summarizing its key underlying concepts (i.e., geometry modeling, biomechanical simulation, and result interpretation). Specifically, the validity of the underlying model assumptions is critically disused in relation to the intended simulation objective (i.e., a clinical AAA rupture risk assessment). Next, reported clinical BRRA validation studies are summarized, and their clinical relevance is reviewed. The BRRA method is a generic, biomechanics-based approach that provides several interfaces to incorporate information from different research disciplines. As an example, the final section of this review suggests integrating growth aspects to (potentially) further improve BRRA sensitivity and specificity. Despite the fact that no prospective validation studies are reported, a significant and still growing body of validation evidence suggests integrating the BRRA method into the clinical decision-making process (i.e., enriching diameter-based decision-making in AAA patient treatment).

Piecewise Pulse Wave Imaging (pPWI) for Detection and Monitoring of Focal Vascular Disease in Murine Aortas and Carotids In Vivo

Atherosclerosis and Abdominal Aortic Aneurysms (AAAs) are two common vascular diseases associated with mechanical changes in the arterial wall. Pulse Wave Imaging (PWI), a technique developed by our group to assess and quantify the mechanical properties of the aortic wall in vivo, may provide valuable diagnostic information. This work implements piecewise PWI (pPWI), an enhanced version of PWI designed for focal vascular diseases. Localized, sub-regional PWVs and PWI moduli ( EPWI ) were estimated within 2-4 mm wall segments of murine normal, atherosclerotic and aneurysmal arteries. Overall, stiffness was found to increase in the atherosclerotic cases. The mean sub-regional PWV was found to be 2.57±0.18 m/s for the normal aortas (n = 7) with a corresponding mean EPWI of 43.82±5.86 kPa. A significant increase ( (p ≤ 0.001)) in the group means of the sub-regional PWVs was found between the normal aortas and the aortas of mice on high-fat diet for 20 ( 3.30±0.36 m/s) and 30 weeks ( 3.56±0.29 m/s). The mean of the sub-regional PWVs ( 1.57±0.78 m/s) and EPWI values ( 19.23±15.47 kPa) decreased significantly in the aneurysmal aortas (p ≤ 0.05) . Furthermore, the mean coefficient of determination (r(2)) of the normal aortas was significantly higher (p ≤ 0.05) than those of the aneurysmal and atherosclerotic cases. These findings demonstrated that pPWI may be able to provide useful biomarkers for monitoring focal vascular diseases.

Multilayer flow modulator stent technology: a treatment revolution for US patients?

Thoracoabdominal aortic repair is a high-risk procedure in most experienced centers, not only because of anatomical complexity but also due to the fragility of the patients in whom these aneurysms occur. Such repairs are complex, time-consuming and impose a systemic injury upon the patients, regardless of whether the repair is performed by open surgery or via a fenestrated/branched technique. The substantive risks associated with such repairs include death, dialysis and paralysis. The multilayer flow modulator (MFM) is a disruptive technology which promises a minimally invasive reproducible treatment option, with clinical results demonstrating physiological modulation of the aortic sac with abolition of spinal injury. The mode of action of MFM forces us to completely rethink aneurysm pathogenesis and, consequently, it has been met with much cynicism. We aim to uncloak some of the mystery surrounding the MFM, clarify its mode of action and explore the truth behind its clinical effectiveness.

Diagnosis and treatment of congenital abdominal aortic aneurysm: a systematic review of reported cases

Background

Congenital abdominal aortic aneurysm (AAA) is distinctly rare in infants and children and carries a high mortality rate. Our objective was to summarize the experience of the diagnosis and treatment in patients with congenital AAA.

Methods

Reported cases of congenital AAA published prior to November 8, 2014, were identified through PubMed, EMBASE, Web of Science, and reference lists. All selected cases were evaluated for main clinical characteristics.

Results

Twenty-six cases of congenital AAA were identified in the English language literature. Congenital AAA occurred primarily in children under three years old, but it was also found in young adults and fetuses. With regards to the localization, the great majority of congenital AAA was infrarenal AAA. The majority of the AAA patients lacked specific symptoms, and a painless pulsatile abdominal mass was the most common clinical presentation. The diagnosis of AAA was based on ultrasound scanning in twenty-five cases, multi-slice spiral computed tomography angiography (MSCTA) in sixteen cases, and magnetic resonance angiography (MRA) in nine cases. Histopathological analyses were available in seven cases. Seven patients received conservative management. Surgical treatment was performed in seventeen cases, and open repair with an artificial graft was the main surgical intervention. The mortality associated with congenital AAA was high (30.76%). Ruptured aneurysm and renal failure were the main causes of death.

Conclusions

Good outcomes can be achieved in children with early identification of congenital AAA and individualized surgical repair with grafts.

Biomechanical analysis of an aortic aneurysm model and its clinical application to thoracic aortic aneurysms for defining "saccular" aneurysms

Background

We aimed to develop a simple structural model of aortic aneurysms using computer‐assisted drafting (CAD) in order to create a basis of definition for saccular aortic aneurysms.

Methods and Results

We constructed a simple aortic aneurysm model with 2 components: a tube similar to an aorta and an ellipse analogous to a bulging aneurysm. Three parameters, including the vertical and horizontal diameters of the ellipse and the fillet radius, were altered in the model. Using structural analysis with the finite element method, we visualized the distribution of the maximum principal stress (MPS) in the aortic wall and identified the area(s) of prominent stress. We then selected patients with thoracic aortic aneurysms in whom the aneurysm expansion rates were followed up and applied the theoretical results to the raw imaging data. The maximum MPS drastically increased at areas where the aspect ratio (vertical/horizontal) was <1, indicating that “horizontally long” hypothetical ellipses should be defined as “saccular” aneurysms. The aneurysm expansion rate for the patients with thoracic aneurysms conforming to these parameters was significantly high. Further, “vertically long” ellipses with a small fillet might be candidates for saccular aneurysms; however, the clinical data did not support this.

Conclusions

Based on the biomechanical analysis of a simple aneurysm model and the clinical data of the thoracic aortic aneurysms, we defined “horizontally long” aortic aneurysms with an aspect ratio of <1 as “saccular” aneurysms.

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

OBJECTIVES

To compare biomechanical rupture risk parameters of asymptomatic, symptomatic and ruptured abdominal aortic aneurysms (AAA) using finite element analysis (FEA).

STUDY DESIGN

Retrospective biomechanical single center analysis of asymptomatic, symptomatic, and ruptured AAAs. Comparison of biomechanical parameters from FEA.

MATERIALS AND METHODS

From 2011 to 2013 computed tomography angiography (CTA) data from 30 asymptomatic, 15 symptomatic, and 15 ruptured AAAs were collected consecutively. FEA was performed according to the successive steps of AAA vessel reconstruction, segmentation and finite element computation. Biomechanical parameters Peak Wall Rupture Risk Index (PWRI), Peak Wall Stress (PWS), and Rupture Risk Equivalent Diameter (RRED) were compared among the three subgroups.

RESULTS

PWRI differentiated between asymptomatic and symptomatic AAAs (p < .0004) better than PWS (p < .1453). PWRI-dependent RRED was higher in the symptomatic subgroup compared with the asymptomatic subgroup (p < .0004). Maximum AAA external diameters were comparable between the two groups (p < .1355). Ruptured AAAs showed the highest values for external diameter, total intraluminal thrombus volume, PWS, RRED, and PWRI compared with asymptomatic and symptomatic AAAs. In contrast with symptomatic and ruptured AAAs, none of the asymptomatic patients had a PWRI value >1.0. This threshold value might identify patients at imminent risk of rupture.

CONCLUSIONS

From different FEA derived parameters, PWRI distinguishes most precisely between asymptomatic and symptomatic AAAs. If elevated, this value may represent a negative prognostic factor for asymptomatic AAAs.

Progression of abdominal aortic aneurysm towards rupture: refining clinical risk assessment using a fully coupled fluid-structure interaction method

Rupture of abdominal aortic aneurysm (AAA) is associated with high mortality rates. Risk of rupture is multi-factorial involving AAA geometric configuration, vessel tortuosity, and the presence of intraluminal pathology. Fluid structure interaction (FSI) simulations were conducted in patient based computed tomography scans reconstructed geometries in order to monitor aneurysmal disease progression from normal aortas to non-ruptured and contained ruptured AAA (rAAA), and the AAA risk of rupture was assessed. Three groups of 8 subjects each were studied: 8 normal and 16 pathological (8 non-ruptured and 8 rAAA). The AAA anatomical structures segmented included the blood lumen, intraluminal thrombus (ILT), vessel wall, and embedded calcifications. The vessel wall was described with anisotropic material model that was matched to experimental measurements of AAA tissue specimens. A statistical model for estimating the local wall strength distribution was employed to generate a map of a rupture potential index (RPI), representing the ratio between the local stress and local strength distribution. The FSI simulations followed a clear trend of increasing wall stresses from normal to pathological cases. The maximal stresses were observed in the areas where the ILT was not present, indicating a potential protective effect of the ILT. Statistically significant differences were observed between the peak systolic stress and the peak stress at the mean arterial pressure between the three groups. For the ruptured aneurysms, where the geometry of intact aneurysm was reconstructed, results of the FSI simulations clearly depicted maximum wall stress at the a priori known location of rupture. The RPI mapping indicated several distinct regions of high RPI coinciding with the actual location of rupture. The FSI methodology demonstrates that the aneurysmal disease can be described by numerical simulations, as indicated by a clear trend of increasing aortic wall stresses in the studied groups, (normal aortas, AAAs and rAAAs). Ultimately, the results demonstrate that FSI wall stress mapping and RPI can be used as a tool for predicting the potential rupture of an AAA by predicting the actual rupture location, complementing current clinical practice by offering a predictive diagnostic tool for deciding whether to intervene surgically or spare the patient from an unnecessary risky operation.

Meta-analysis of peak wall stress in ruptured, symptomatic and intact abdominal aortic aneurysms

BACKGROUND

Abdominal aortic aneurysm (AAA) is an important cause of sudden death; however, there are currently incomplete means to predict the risk of AAA rupture. AAA peak wall stress (PWS) can be estimated using finite element analysis (FEA) methods from computed tomography (CT) scans. The question is whether AAA PWS can predict AAA rupture. The aim of this systematic review was to compare PWS in patients with ruptured and intact AAA.

METHODS

The MEDLINE database was searched on 25 May 2013. Case-control studies assessing PWS in asymptomatic intact, and acutely symptomatic or ruptured AAA from CT scans using FEA were included. Data were extracted independently. A random-effects model was used to calculate standard mean differences (SMDs) for PWS measurements.

RESULTS

Nine studies assessing 348 individuals were identified and used in the meta-analysis. Results from 204 asymptomatic intact and 144 symptomatic or ruptured AAAs showed that PWS was significantly greater in the symptomatic/ ruptured AAAs compared with the asymptomatic intact AAAs (SMD 0·95, 95 per cent confidence interval 0·71 to 1·18; P < 0·001). The findings remained significant after adjustment for mean systolic blood pressure, standardized at 120 mmHg (SMD 0·68, 0·39 to 0·96; P < 0·001). Minimal heterogeneity between studies was noted (I(2)  = 0 per cent).

CONCLUSION

This study suggests that PWS is greater in symptomatic or ruptured AAA than in asymptomatic intact AAA.

Clopidogrel, a platelet P2Y12 receptor inhibitor, reduces vascular inflammation and angiotensin II induced-abdominal aortic aneurysm progression

Medial degeneration and inflammation are features of abdominal aortic aneurysms (AAAs). However, the early inflammatory event initiating aneurysm formation remains to be identified. Activated platelets release abundant proinflammatory cytokines and are involved in initial inflammation in various vascular diseases. We investigated the role of platelets in progression of AAA in vivo and in vitro. Histological studies of tissues of patients with AAA revealed that the number of platelets was increased in aneurysm sites along with the increased infiltration of T lymphocytes and augmented angiogenesis. In a murine model of AAA, apolipoprotein E-knockout mice infused with 1,000 ng/kg/min angiotensin II, treatment with clopidogrel, an inhibitor of platelets, significantly suppressed aneurysm formation (47% decrease, P<0.05). The clopidogrel also suppressed changes in aortic expansion, elastic lamina degradation and inflammatory cytokine expression. Moreover, the infiltration of macrophages and production of matrix metalloproteinases (MMPs) were also significantly reduced by clopidogrel treatment. In vitro incubation of macrophages with isolated platelets stimulated MMP activity by 45%. These results demonstrate a critical role for platelets in vascular inflammation and AAA progression.

A pull-back algorithm to determine the unloaded vascular geometry in anisotropic hyperelastic AAA passive mechanics

Biomechanical studies on abdominal aortic aneurysms (AAA) seek to provide for better decision criteria to undergo surgical intervention for AAA repair. More accurate results can be obtained by using appropriate material models for the tissues along with accurate geometric models and more realistic boundary conditions for the lesion. However, patient-specific AAA models are generated from gated medical images in which the artery is under pressure. Therefore, identification of the AAA zero pressure geometry would allow for a more realistic estimate of the aneurysmal wall mechanics. This study proposes a novel iterative algorithm to find the zero pressure geometry of patient-specific AAA models. The methodology allows considering the anisotropic hyperelastic behavior of the aortic wall, its thickness and accounts for the presence of the intraluminal thrombus. Results on 12 patient-specific AAA geometric models indicate that the procedure is computational tractable and efficient, and preserves the global volume of the model. In addition, a comparison of the peak wall stress computed with the zero pressure and CT-based geometries during systole indicates that computations using CT-based geometric models underestimate the peak wall stress by 59 ± 64 and 47 ± 64 kPa for the isotropic and anisotropic material models of the arterial wall, respectively.

ACR Appropriateness Criteria® pulsatile abdominal mass, suspected abdominal aortic aneurysm

Clinical palpation of a pulsating abdominal mass alerts the clinician to the presence of a possible abdominal aortic aneurysm (AAA). Generally an arterial aneurysm is defined as a localized arterial dilatation ≥50% greater than the normal diameter. Imaging studies are important in diagnosing the cause of a pulsatile abdominal mass and, if an AAA is found, in determining its size and involvement of abdominal branches. Ultrasound (US) is the initial imaging modality of choice when a pulsatile abdominal mass is present. Noncontrast computed tomography (CT) may be substituted in patients for whom US is not suitable. When aneurysms have reached the size threshold for intervention or are clinically symptomatic, contrast-enhanced multidetector CT angiography (CTA) is the best diagnostic and preintervention planning study, accurately delineating the location, size, and extent of aneurysm and the involvement of branch vessels. Magnetic resonance angiography (MRA) may be substituted if CT cannot be performed. Catheter arteriography has some utility in patients with significant contraindications to both CTA and MRA. The American College of Radiology Appropriateness Criteria(®) are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.