Editor's Choice - Systematic Review and Meta-Analysis of Contemporary Abdominal Aortic Aneurysm Growth Rates

OBJECTIVE

To evaluate the contemporary growth rate of small abdominal aortic aneurysms (AAAs) in view of recent epidemiological changes, such as decreasing smoking rates and establishment of population screening programmes.

DATA SOURCES

MEDLINE, CENTRAL, PsycINFO, Web of Science Core Collection, and OpenGrey databases.

REVIEW METHODS

Systematic review following the PRISMA guidelines. In October 2021, databases were queried for studies reporting on AAA growth rates published from 2015 onwards. The primary outcome was contemporary AAA growth rates in mm/year. Data were pooled in a random effects model meta-analysis, and heterogeneity was assessed through the I2 statistic. GRADE assessment of the findings was performed. The protocol was published in PROSPERO (CRD42022297404).

RESULTS

Of 8 717 titles identified, 43 studies and 28 277 patients were included: 1 241 patients from randomised controlled trials (RCTs), 23 941 from clinical observational studies, and 3 095 from radiological or translational research studies. The mean AAA growth rate was 2.38 mm/year (95% CI 2.16 - 2.60 mm/year; GRADE = low), with meta-regression analysis adjusted for baseline diameter showing an increase of 0.08 mm/year (95% CI 0.024 - 0.137 mm/year; p = .005) for each millimetre of increased baseline diameter. When analysed by study type, the growth rate estimated from RCTs was 1.88 mm/year (95% CI 1.69 - 2.06 mm/year; GRADE = high), while it was 2.31 mm/year (95% CI 1.95 - 2.67 mm/year; GRADE = moderate) from clinical observational studies, and 2.85 mm/year (95% CI 2.44 - 3.26 mm/year; GRADE = low) from translational and radiology based studies (p < .001). Heterogeneity was high, and small study publication bias was present (p = .003), with 27 studies presenting a moderate to high risk of bias. The estimated growth rate from low risk studies was 2.09 mm/year (95% CI 1.87 - 2.32; GRADE = high).

CONCLUSION

This study estimated a contemporaneous AAA growth rate of 2.38 mm/year, being unable to demonstrate any clinically meaningful AAA growth rate reduction concomitant with changed AAA epidemiology. This suggests that the RESCAN recommendations on small AAA surveillance are still valid. However, sub-analysis results from RCTs and high quality study data indicate potential lower AAA growth rates of 1.88 - 2.09 mm/year, findings that should be validated in a high quality prospective registry.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A Deep Learning Approach to Visualize Aortic Aneurysm Morphology Without the Use of Intravenous Contrast Agents

BACKGROUND

Intravenous contrast agents are routinely used in CT imaging to enable the visualization of intravascular pathology, such as with abdominal aortic aneurysms. However, the injection is contraindicated in patients with iodine allergy and is associated with renal complications.

OBJECTIVES

In this study, we investigate if the raw data acquired from a noncontrast CT image contains sufficient information to differentiate blood and other soft tissue components. A deep learning pipeline underpinned by generative adversarial networks was developed to simulate contrast enhanced CTA images using noncontrast CTs.

METHODS AND RESULTS

Two generative models (cycle- and conditional) are trained with paired noncontrast and contrast enhanced CTs from seventy-five patients (total of 11,243 pairs of images) with abdominal aortic aneurysms in a 3-fold cross-validation approach with a training/testing split of 50:25 patients. Subsequently, models were evaluated on an independent validation cohort of 200 patients (total of 29,468 pairs of images). Both deep learning generative models are able to perform this image transformation task with the Cycle-generative adversarial network (GAN) model outperforming the Conditional-GAN model as measured by aneurysm lumen segmentation accuracy (Cycle-GAN: 86.1% ± 12.2% vs Con-GAN: 85.7% ± 10.4%) and thrombus spatial morphology classification accuracy (Cycle-GAN: 93.5% vs Con-GAN: 85.7%).

CONCLUSION

This pipeline implements deep learning methods to generate CTAs from noncontrast images, without the need of contrast injection, that bear strong concordance to the ground truth and enable the assessment ofimportant clinical metrics. Our pipeline is poised to disrupt clinical pathways requiring intravenous contrast.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Synthetic Post-Contrast Imaging through Artificial Intelligence: Clinical Applications of Virtual and Augmented Contrast Media

Contrast media are widely diffused in biomedical imaging, due to their relevance in the diagnosis of numerous disorders. However, the risk of adverse reactions, the concern of potential damage to sensitive organs, and the recently described brain deposition of gadolinium salts, limit the use of contrast media in clinical practice. In recent years, the application of artificial intelligence (AI) techniques to biomedical imaging has led to the development of 'virtual' and 'augmented' contrasts. The idea behind these applications is to generate synthetic post-contrast images through AI computational modeling starting from the information available on other images acquired during the same scan. In these AI models, non-contrast images (virtual contrast) or low-dose post-contrast images (augmented contrast) are used as input data to generate synthetic post-contrast images, which are often undistinguishable from the native ones. In this review, we discuss the most recent advances of AI applications to biomedical imaging relative to synthetic contrast media.

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.

Prediction of abdominal aortic aneurysm growth by artificial intelligence taking into account clinical, biologic, morphologic, and biomechanical variables

OBJECTIVES

To develop a prediction model that could risk stratify abdominal aortic aneurysms (AAAs) into high and low growth rate groups, using machine learning algorithms based on variables from different pathophysiological fields.

METHODS

A cohort of 40 patients with small AAAs (maximum diameter 32-53 mm) who had at least an initial and a follow-up CT scan (median follow-up 12 months, range 3-36 months) were included. 29 input variables from clinical, biological, morphometric, and biomechanical pathophysiological aspects extracted for predictive modeling. Collected data were used to build two supervised machine learning models. A gradient boosting (XGboost) and a support vector machines (SVM) algorithm were trained with 60% and tested with 40% of the data to predict which AAA would achieve a growth rate higher than the median of our study cohort. Receiver operating characteristics (ROC) curves and areas under the curve (AUC) were used for the evaluation of the developed algorithms.

RESULTS

XGboost achieved the highest AUC in predicting high compared to low AAA growth rate with an AUC of 81.2% (95% CI from 61.1 to 100%). SVM achieved the second highest performance with an AUC of 68.8% (95% CI from 46.5 to 91%). Based on the best performing algorithm, variable importance was estimated. Diameter-diameter ratio (maximum diameter/neck diameter), Tortuosity from Renal arteries to aortic bifurcation, and maximum thickness of the intraluminal thrombus were found to be the most important factors for model predictions. Other factors were also found to play a significant but less important role.

CONCLUSIONS

A prediction model that can risk stratify AAAs into high and low growth rate groups could be developed by analyzing several factors implicated in the multifactorial pathophysiology of this disease, with the use of machine learning algorithms. Future studies including larger patient cohorts and implementing additional risk markers may aid in the establishment of such methodology during AAA rupture risk estimation.

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.

Mechanical role of intraluminal thrombus in aneurysm growth: A computational study

Models that seek to improve our current understanding of biochemical processes and predict disease progression have been increasingly in use over the last decades. Recently, we proposed a finite element implementation of arterial wall growth and remodeling with application to abdominal aortic aneurysms (AAAs). The study focused on changes within the aortic wall and did not include the complex role of intraluminal thrombus (ILT) during the AAA evolution. Thus, in this work, we extend the model with a gradual deposition of ILT and its mechanical influence on AAA growth. Despite neglecting the increased biochemical activity due to the presence of a proteolytically active luminal layer of ILT, and thus underestimating rupture risk potential, we show that ILT helps to slow down the growth of the aneurysm in the axial direction by redirecting blood pressure loading from the axial-radial plane to predominately radial direction. This very likely lowers rupture potential. We also show that the ratio of ILT volume to volume sac is an important factor in AAA stabilization and that fully thrombosed aneurysms could stabilize quicker and at smaller maximum diameters compared to partially thrombosed ones. Furthermore, we show that ILT formation and the associated mural stress decrease negatively impact the wall constituent production and thickness. Although further studies that include increased biochemical degradation of the wall after the formation of ILT and ILT deposition based on hemodynamics are needed, the present findings highlight the dual role an ILT plays during AAA progression.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

New predictors of aneurysm sac behavior after endovascular aortic aneurysm repair

OBJECTIVES

This study aimed to identify new predictors of sac behavior after endovascular aortic aneurysm repair (EVAR) and to investigate whether sac behavior is associated with long-term clinical outcomes.

METHODS

A total of 168 patients undergoing successful EVAR for abdominal aortic aneurysms with CTA follow-up of at least 1 year were included. Predictors of aneurysm sac behavior and its impact on long-term clinical outcomes were retrospectively analyzed.

RESULTS

According to sac behavior, eligible patients were stratified into the sac regression group (n = 79, 47.0%) and the sac non-regression group (n = 89, 53.0%). Patients in the regression group were younger (p = 0.036) and more likely to take sarpogrelate hydrochloride postoperatively (p = 0.011) than those in the non-regression group. The incidence of postimplantation syndrome (PIS) was significantly higher in the regression group (p = 0.005). On multivariate analysis, sac regression was more likely to occur in those with PIS (hazard ratio [HR], 1.68; 95% confidence interval [CI], 1.07-2.64; p = 0.023) and less likely to occur in those with transient type II endoleaks (HR, 0.43; 95% CI, 0.20-0.95; p = 0.037) and higher thrombus density within the sac on follow-up CTA (HR, 0.97; 95% CI, 0.95-0.99; p = 0.013). Non-regression of the sac was associated with significantly higher rates of re-intervention during the follow-up period (p = 0.001).

CONCLUSIONS

In addition to type II endoleaks, PIS and thrombus density are new predictors of aneurysm sac behavior, and sac regression is significantly associated with lower rates of re-intervention.

KEY POINTS

• After endovascular aortic aneurysm repair (EVAR), patients with sac regression were younger and more likely to take sarpogrelate hydrochloride postoperatively than those with sac non-regression. • The incidence of postimplantation syndrome (PIS) was significantly higher in patients with sac regression. • In our analysis, PIS and thrombus density within the sac were newly identified predictors of aneurysm sac behavior after EVAR.

Spatial Distribution of Abdominal Aortic Aneurysm Surface Expansion and Correlation With Maximum Diameter and Volume Growth

BACKGROUND

Abdominal aortic aneurysm (AAA) growth rate, measured as maximum diameter (Dmax) change over time, is used as a surrogate marker of rupture risk. However, AAA expansion presents significant spatial variability. We aim to record the spatial distribution of regional wall surface expansion.

METHODS

Thirty AAAs were retrospectively studied. Each AAA had one baseline and at least one follow-up computed tomography scan. Three-dimensional AAA models were reconstructed, and change in Dmax and total aneurysm volume was recorded to calculate annual growth rates. Regional surface growth was quantified using the VascForm algorithm, which is based on nonrigid point cloud registration and iterative closest point analysis. Maximum and average surface growths were calculated and correlated with the diameter/volume growth rates. Furthermore, to identify potential correlation between maximum thrombus (intraluminal thrombus) thickness and maximum surface growth, as well as between peak wall stress (PWS) and surface growth, their colocalization was examined.

RESULTS

The median average annual surface growth was 6% (0%-28%), and the maximum surface growth 24% (11%-238%). There was strong evidence of a moderate correlation between Dmax and average as well as maximum surface growth. Regarding volumes, there was strong evidence of a very strong association with average surface growth rate and a moderate association with maximum surface growth rate (rho: 0.91, P < 0.001; rho: 0.7, P < 0.001, respectively). In 51.6% of the follow-ups, maximum surface growth occurred away from Dmax site. Sixteen cases presented maximum surface growth away and fifteen at the region of maximum initial intraluminal thrombus thickness. AAAs in the former group had significantly thinner initial intraluminal thrombus thickness (11.3 vs 19.5 mm, P < 0.001) than those in the latter. Apart from a single case, maximum surface growth did not occur at the PWS region.

CONCLUSIONS

More than half of the lesions display maximum growth away from Dmax, suggesting that a more accurate method of analyzing AAA growth needs to be established in clinical practice that will take into account local surface growth.

Intraluminal Thrombus Deposition Is Reduced in Ruptured Compared to Diameter-matched Intact Abdominal Aortic Aneurysms

BACKGROUND

The aim of this study is to compare the pattern of intraluminal thrombus (ILT) deposition in diameter-matched ruptured and nonruptured abdominal aortic aneurysms (AAAs).

METHODS

We performed a single-center, retrospective study. Ruptured AAAs were collected during 24 months. Diameter-matched intact lesions were randomly selected in a 2:1 ratio and served as controls. ILT cross-sectional area, relative area, maximum thickness, and asymmetric distribution were recorded at the site of maximum aneurysm size and compared between groups. Moreover, additional comparisons were performed inside the group of ruptured AAAs, between the site of maximum size and the site of rupture.

RESULTS

Fifteen ruptured cases were compared with 30 nonruptured cases. ILT relative area (37.5% vs. 73.5%, P = 0.004) and maximum thickness (14.5 vs. 28 mm, P= 0.0017) were significantly reduced among ruptured compared to intact AAAs. The latter group presented mostly an anterior eccentric ILT deposition, while the former presented a more symmetrical pattern. The site of rupture was located at the site of maximum size in only 2 cases. In general, ILT was reduced at the site of rupture compared to the site of maximum aneurysm size in ruptured cases but differences did not reach statistical significance.

CONCLUSIONS

In similar sized AAAs, ILT is reduced in ruptured compared to nonruptured cases.

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.

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.

A novel approach for local abdominal aortic aneurysm growth quantification

Although aneurysm size still remains the most accepted predictor of rupture risk, abdominal aortic aneurysms (AAAs) with maximum diameter smaller than 5 cm may also rupture. Growth rate is an additional marker for rupture risk as it potentially reflects an undesirable wall remodeling that leads to fast regional growth. Currently, an indication for surgery is an expansion rate >10 mm/year, measured as change in maximum diameter over time. However, as AAA expansion is non-uniform, it is questionable whether measurement of maximum diameter change over time can capture increased localized remodeling activity. A method for estimating AAA surface area growth is introduced, providing a better measure of local wall deformation. The proposed approach is based on the non-rigid iterative closest point algorithm. Optimization and validation is performed using 12 patient-specific AAA geometries artificially deformed to produce a target surface with known nodal displacements. Mesh density sensitivity, range of uncertainty, and method limitations are discussed. Application to ten AAA patient-specific follow-ups suggested that maximum diameter growth does not correlate strongly with the maximum surface growth (R ² = 0.614), which is not always colocated with maximum diameter, or uniformly distributed. Surface growth quantification could reinforce the quality of aneurysm surveillance programs.

Non-contrast 3D black blood MRI for abdominal aortic aneurysm surveillance: comparison with CT angiography

OBJECTIVES

Management of abdominal aortic aneurysms (AAAs) is based on diameter. CT angiography (CTA) is commonly used, but requires radiation and iodinated contrast. Non-contrast MRI is an appealing alternative that may allow better characterization of intraluminal thrombus (ILT). This study aims to 1) validate non-contrast MRI for measuring AAA diameter, and 2) to assess ILT with CTA and MRI.

METHOD

28 patients with AAAs (diameter 50.7 ± 12.3 mm) underwent CTA and non-contrast MRI. MRI was acquired at 3 T using 1) a conventional 3D gradient echo (GRE) sequence and 2) a 3D T₁-weighted black blood fast-spin-echo sequence. Two radiologists independently measured the AAA diameter. The ratio of signal of ILT and adjacent psoas muscle (ILT_r = signal_ILT/signal_Muscle) was quantified.

RESULTS

Strong agreement between CTA and non-contrast MRI was shown for AAA diameter (intra-class coefficient > 0.99). Both approaches had excellent inter-observer reproducibility (ICC > 0.99). ILT appeared homogenous on CTA, whereas MRI revealed compositional variations. Patients with AAAs ≥5.5 cm and <5.5 cm had a variety of distributions of old/fresh ILT types.

CONCLUSIONS

Non-contrast 3D black blood MRI provides accurate and reproducible AAA diameter measurements as validated by CTA. It also provides unique information about ILT composition, which may be linked with elevated risk for disease progression.

KEY POINTS

• Non-contrast MRI is an appealing alternative to CTA for AAA management. • Non-contrast MRI can accurately measure AAA diameters compared to CTA. • MRI affords unique characterization of intraluminal thrombus composition.

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.

Volumetry and biomechanical parameters detected by 3D and 2D ultrasound in patients with and without an abdominal aortic aneurysm

The objective was to demonstrate the ability of ultrasound (US) with 3D properties to evaluate volumetry and biomechanical parameters of the aorta in patients with and without abdominal aortic aneurysm (AAA). Thirty-one patients with normal aortas (group 1), 46 patients with AAA measuring 3.0–5.5 cm (group 2) and 31 patients with AAA ⩾ 5.5 cm (group 3) underwent a 2D/3D-US examination of the infra-renal aorta, and the images were post-processed prior to being analyzed. In the maximum diameter, the global circumferential strain and the global maximum rotation assessed by 2D speckle-tracking algorithms were compared among the three groups. The volumetry data obtained using 3D-US from 40 AAA patients were compared with the volumetry data obtained by a contemporary computed tomography (CT) scan. The median global circumferential strain was 2.0% (interquartile range (IR): 1.0–3.0), 1.0% (IR: 1.0–2.0) and 1.0% (IR: 1.0–1.75) in groups 1, 2 and 3, respectively ( p < 0.001). The median global maximum rotation decreased progressively from group 1 to group 3 (1.38º (IR: 0.77–2.13), 0.80º (IR: 0.57–1.0) and 0.50º (IR: 0.31–0.75), p < 0.001). AAA volume estimations by 3D-US correlated well with CT ( R2 = 0.76). In conclusion, US with 3D properties is non-invasive and has the potential to evaluate volumetry and biomechanical characteristics of AAA.

The - Not So - Solid 5.5 cm Threshold for Abdominal Aortic Aneurysm Repair: Facts, Misinterpretations, and Future Directions

Abdominal aortic aneurysms (AAAs) represent a focal dilation of the aorta exceeding 1.5 times its normal diameter. It is reported that 4-8% of men and 0.5-1% of women above 50 years of age bear an AAA. Rupture represents the most disastrous complication of aneurysmal disease that is accompanied by an overall mortality of 80%. Autopsy data have shown that nearly 13% of AAAs with a maximum diameter ≤5 cm were ruptured and 60% of the AAAs >5 cm in diameter never ruptured. It is therefore obvious that the "maximum diameter criterion," as a single parameter that fits all patients, is obsolete. Investigators have begun a search for more reliable rupture risk markers for AAA expansion, such as the level and change of peak wall stress or AAA geometry. Furthermore, it is becoming more and more evident that intraluminal thrombus (ILT), which is present in 75% of all AAAs, affects AAA features and promotes their expansion. Though these hemodynamic properties of AAAs are significant and seem to better describe rupture risk, they are in need of specialized equipment and software and demand time for processing making them difficult in use and unattractive to clinicians in everyday practice. In the search for the addition of other risk factors or user-friendly tools, which may predict AAA expansion and rupture, the use of the asymmetrical ILT deposition index seems appealing since it has been reported to identify AAAs that may have an increased or decreased growth rate.