Aortic Lumen Area Is Increased in Ruptured Abdominal Aortic Aneurysms and Correlates to Biomechanical Rupture Risk

Early Prediction of Abdominal Aortic Aneurysm Rupture Risk Using Numerical Biomechanical Analysis

Objective: We aimed to predict patient-specific rupture risks and growth behaviors in abdominal aortic aneurysm (AAA) patients using biomechanical evaluation with finite element analysis to establish an additional AAA repair threshold besides diameter and sex. Methods: A total of 1219 patients treated between 2005 and 2024 (conservative and repaired AAAs) were screened for a pseudo-prospective single-center study. A total of 15 ruptured (rAAA) vs. 15 non-ruptured AAAs (control group) were matched for pre-rupture imaging (first rAAA) and the initial post-rupture imaging (second rAAA) with two images in the asymptomatic control group (first and second control). The matching criteria were as follows: aneurysm diameter, sex, and time period between imagings. The biomechanical properties were analyzed with the finite element method (A4clinicsRE, Vascops GmbH, Graz, Austria). Results: Both groups had the same median aortic diameter of 5.5 cm in the first imaging but had significantly different aneurysm progressions with 6.9 cm (5.5-9.4 cm) in the second rAAA vs. 6.0 cm (5.1-7.3 cm) in the second control group (p = 0.006). The first rAAA, compared to the first control, showed significantly a higher peak wall stress (PWS) (211.8 kPa vs. 180.5 kPa, p = 0.029) and luminal diameter (43.5 mm vs. 35.3 mm; p = 0.016). The second rAAA, compared to the matched second control, showed a significantly higher PWS (281.9 kPa vs. 187.4 kPa, p = 0.002), luminal diameter (58.3 mm vs. 39.7 mm; p = 0.007), PWRR (0.78 vs. 0.49, p = 0.014) and RRED (79.8 vs. 56.5, p = 0.014). The rAAA group showed over-proportional averages, over the observation time, and an increase in PWS (nearly 10× faster in rAAA) and luminal diameter (nearly 4× faster in rAAA) per month. Conclusions: The finite element analysis of biomechanical properties could be used for the early prediction of an increased rupture risk in AAA patients. This was confirmed by matched imaging analyses before and after AAA rupture. Further multicenter data are needed to support these findings.

Deep learning-based segmentation of abdominal aortic aneurysms and intraluminal thrombus in 3D ultrasound images

Ultrasound (US)-based patient-specific rupture risk analysis of abdominal aortic aneurysms (AAAs) has shown promising results. Input for these models is the patient-specific geometry of the AAA. However, segmentation of the intraluminal thrombus (ILT) remains challenging in US images due to the low ILT-blood contrast. This study aims to improve AAA and ILT segmentation in time-resolved three-dimensional (3D + t) US images using a deep learning approach. In this study a "no new net" (nnU-Net) model was trained on 3D + t US data using either US-based or (co-registered) computed tomography (CT)-based annotations. The optimal training strategy for this low-contrast data was determined for a limited dataset. The merit of augmentation was investigated, as well as the inclusion of low-contrast areas. Segmentation results were validated with CT-based geometries as the ground truth. The model trained on CT-based masks showed the best performance in terms of DICE index, Hausdorff distance, and diameter differences, covering a larger part of the AAA. With a higher accuracy and less manual input the model outperforms conventional methods, with a mean Hausdorff distance of 4.4 mm for the vessel and 7.8 mm for the lumen. However, visibility of the lumen-ILT interface remains the limiting factor, necessitating improvements in image acquisition to ensure broader patient inclusion and enable rupture risk assessment of AAAs in the future.

Computational modelling of cardiovascular pathophysiology to risk stratify commercial spaceflight

For more than 60 years, humans have travelled into space. Until now, the majority of astronauts have been professional, government agency astronauts selected, in part, for their superlative physical fitness and the absence of disease. Commercial spaceflight is now becoming accessible to members of the public, many of whom would previously have been excluded owing to unsatisfactory fitness or the presence of cardiorespiratory diseases. While data exist on the effects of gravitational and acceleration (G) forces on human physiology, data on the effects of the aerospace environment in unselected members of the public, and particularly in those with clinically significant pathology, are limited. Although short in duration, these high acceleration forces can potentially either impair the experience or, more seriously, pose a risk to health in some individuals. Rather than expose individuals with existing pathology to G forces to collect data, computational modelling might be useful to predict the nature and severity of cardiovascular diseases that are of sufficient risk to restrict access, require modification, or suggest further investigation or training before flight. In this Review, we explore state-of-the-art, zero-dimensional, compartmentalized models of human cardiovascular pathophysiology that can be used to simulate the effects of acceleration forces, homeostatic regulation and ventilation-perfusion matching, using data generated by long-arm centrifuge facilities of the US National Aeronautics and Space Administration and the European Space Agency to risk stratify individuals and help to improve safety in commercial suborbital spaceflight.

CTA-Based Radiomics and Area Change Rate Predict Infrarenal Abdominal Aortic Aneurysms Patients Events: A Multicenter Study

RATIONALE AND OBJECTIVES

Clinical assessment of abdominal aortic aneurysm (AAA) intervention and rupture risk relies primarily on maximum diameter, but studies have shown that sole dependence on diameter has limitations. CTA-based radiomics, aneurysm and lumen area change rates (AACR, LACR) are measured to predict potential AAA events.

MATERIALS AND METHODS

Between January 2017 and November 2022, 260 AAA patients from four centers who underwent two preoperative CTA examinations were included in this retrospective study. The endpoint event is defined as AAA rupture or repair. Patients were categorized into event and no-event groups based on the occurrence of endpoint event during follow-up. AACR and LACR were assessed using baseline and follow-up CTA, with radiomics features extracted from the baseline images. C-statistics and the Kaplan-Meier analysis were used to evaluate the predictive performance.

RESULTS

A total of 193 eligible infrarenal AAA patients were included, 176 (91.2%) were man and 17 (8.8%) were woman. The median follow-up was 33.4 (14.2, 57.4) months. Seven models were constructed, comprising the aneurysm-based Radscore model, lumen-based Radscore model, intraluminal thrombus (ILT)-based Radscore model, AACR model, LACR model, clinical model (including high-density lipoprotein, D-dimer, and baseline aneurysm diameter), and a merged model. On the external validation set, the C-index of seven models were 0.713 (0.574-0.853), 0.642 (0.499-0.786), 0.727 (0.600-0.854), 0.619 (0.484-0.753), 0.680 (0.530-0.830), 0.690 (0.557-0.824) and 0.760 (0.651-0.869), in that order. In the Kaplan-Meier analysis, the merged model was best-divided patients into high/low-risk groups with Log-rank p < 0.0001. The AARC and LARC between non-event and event groups have significant differences (AACR: 1.4 cm2/y vs. 2.3 cm2/y, p < 0.0001; LACR: 0.3 cm2/y vs. 1.1 cm2/y, p < 0.0001).

CONCLUSION

CTA-based radiomics, AACR and LACR have good predictive value for outcome event in infrarenal AAA patients.

Association between aortic peak wall stress and rupture index with abdominal aortic aneurysm-related events

OBJECTIVE

The aim of this study was to assess whether aortic peak wall stress (PWS) and peak wall rupture index (PWRI) were associated with the risk of abdominal aortic aneurysm (AAA) rupture or repair (defined as AAA events) among participants with small AAAs.

METHODS

PWS and PWRI were estimated from computed tomography angiography (CTA) scans of 210 participants with small AAAs (≥ 30 and  ≤ 50 mm) prospectively recruited between 2002 and 2016 from two existing databases. Participants were followed for a median of 2.0 (inter-quartile range 1.9, 2.8) years to record the incidence of AAA events. The associations between PWS and PWRI with AAA events were assessed using Cox proportional hazard analyses. The ability of PWS and PWRI to reclassify the risk of AAA events compared to the initial AAA diameter was examined using net reclassification index (NRI) and classification and regression tree (CART) analysis.

RESULTS

After adjusting for other risk factors, one standard deviation increase in PWS (hazard ratio, HR, 1.56, 95% confidence intervals, CI 1.19, 2.06; p = 0.001) and PWRI (HR 1.74, 95% CI 1.29, 2.34; p < 0.001) were associated with significantly higher risks of AAA events. In the CART analysis, PWRI was identified as the best single predictor of AAA events at a cut-off value of  > 0.562. PWRI, but not PWS, significantly improved the classification of risk of AAA events compared to the initial AAA diameter alone.

CONCLUSION

PWS and PWRI predicted the risk of AAA events but only PWRI significantly improved the risk stratification compared to aortic diameter alone.

KEY POINTS

• Aortic diameter is an imperfect measure of abdominal aortic aneurysm (AAA) rupture risk. • This observational study of 210 participants found that peak wall stress (PWS) and peak wall rupture index (PWRI) predicted the risk of aortic rupture or AAA repair. • PWRI, but not PWS, significantly improved the risk stratification for AAA events compared to aortic diameter alone.

Associations of Tissue and Soluble LOX-1 with Human Abdominal Aortic Aneurysm

Background Indication for prophylactic surgical abdominal aortic aneurysm (AAA) repair depends on the maximal aortic diameter. The lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) is the major receptor for uptake of oxidized low-density lipoprotein cholesterol and is implicated in atherosclerosis. A soluble form of LOX-1 (sLOX-1) has been discussed as a novel biomarker in coronary artery disease and stroke. Herein, we assessed the regulation of aortic LOX-1 as well as the diagnostic and risk stratification potential of sLOX-1 in patients with AAA. Methods and Results Serum sLOX-1 was assessed in a case-control study in AAA (n=104) and peripheral artery disease (n=104). sLOX-1 was not statistically different between AAA and peripheral artery disease but was higher in AAA (β=1.28, P=0.04) after adjusting for age, atherosclerosis, type 2 diabetes, prescription of statins, β-blockers, ACE inhibitors, and therapeutic anticoagulation. sLOX-1 was not associated with the aortic diameter, AAA volume, or the thickness of the intraluminal thrombus. Aortic LOX-1 mRNA expression tended to be higher in AAA when compared with disease, and expression was positively associated with cleaved caspase-3, smooth muscle actin, collagen, and macrophage content. Conclusions In AAA, sLOX-1 was differently affected by age, cardiometabolic diseases, and corresponding medical therapies. Comparison with nonatherosclerotic disease would be beneficial to further elucidate the diagnostic potential of sLOX-1, although it was not useful for risk stratification. Aneurysmal LOX-1 mRNA expression was increased and positively associated with smooth muscle cells and collagen content, suggesting that LOX-1 is eventually not deleterious in human AAA and could counteract AAA rupture.

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

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

Computed Tomography Angiography Markers and Intraluminal Thrombus Morphology as Predictors of Abdominal Aortic Aneurysm Rupture

Background: Abdominal aortic aneurysm (AAA) is a complex vascular disease characterized by progressive and irreversible local dilatation of the aortic wall. Currently, the indication for repair is linked to the transverse diameter of the abdominal aorta, using computed tomography angiography imagery, which is one of the most used markers for aneurysmal growth. This study aims to verify the predictive role of imaging markers and underlying risk factors in AAA rupture. Methods: The present study was designed as an observational, analytical, retrospective cohort study and included 220 patients over 18 years of age with a diagnosis of AAA, confirmed by computed tomography angiography (CTA), admitted to Vascular Surgery Clinic of Mures County Emergency Hospital in Targu Mures, Romania, between January 2018 and September 2022. Results: Patients with a ruptured AAA had higher incidences of AH (p = 0.006), IHD (p = 0.001), AF (p < 0.0001), and MI (p < 0.0001), and higher incidences of all risk factors (tobacco (p = 0.001), obesity (p = 0.02), and dyslipidemia (p < 0.0001)). Multivariate analysis showed that a high baseline value of all imaging ratios markers was a strong independent predictor of AAA rupture (for all p < 0.0001). Moreover, a higher baseline value of DAmax (OR:3.91; p = 0.001), SAmax (OR:7.21; p < 0.001), and SLumenmax (OR:34.61; p < 0.001), as well as lower baseline values of DArenal (OR:7.09; p < 0.001), DACT (OR:12.71; p < 0.001), DAfemoral (OR:2.56; p = 0.005), SArenal (OR:4.56; p < 0.001), SACT (OR:3.81; p < 0.001), and SThrombusmax (OR:5.27; p < 0.001) were independent predictors of AAA rupture. In addition, AH (OR:3.33; p = 0.02), MI (OR:3.06; p = 0.002), and PAD (OR:2.71; p = 0.004) were all independent predictors of AAA rupture. In contrast, higher baseline values of SAmax/Lumenmax (OR:0.13; p < 0.001) and ezetimibe (OR:0.45; p = 0.03) were protective factors against AAA rupture. Conclusions: According to our findings, a higher baseline value of all imaging markers ratios at CTA strongly predicts AAA rupture and AH, MI, and PAD highly predicted the risk of rupture in AAA patients. Furthermore, the diameter of the abdominal aorta at different levels has better accuracy and a higher predictive role of rupture than the maximal diameter of AAA.

Reference values of normal abdominal aortic areas in Chinese population measured by contrast-enhanced computed tomography

Objective

To generate reference values of the normal areas of the abdominal aorta at various levels among Chinese people and to explore the factors that may promote the expansion of the abdominal aorta.

Methods

The areas of normal abdominal aortas were gauged at various levels based on inner-to-inner measurements in 1,066 Chinese adult patients (&gt;18 years) without the abdominal aortic disease. The areas of subphrenic abdominal, suprarenal abdominal, infrarenal abdominal, and distal abdominal aortas were measured. The demographic and clinical characteristics were collected into a specifically designed electronic database. Multivariable linear regression was used to analyze the potential risk factors promoting the expansion of the abdominal aorta.

Results

In males, the median areas of the subphrenic abdominal aorta, suprarenal abdominal aorta, infrarenal abdominal aorta, and distal abdominal aorta were 412.1, 308.0, 242.2, and 202.2 mm2, respectively. In females, the median areas of the subphrenic abdominal aorta, suprarenal abdominal aorta, infrarenal abdominal aorta, and distal abdominal aorta were 327.7, 243.4, 185.4, and 159.6 mm2, respectively. The areas of the abdominal aorta at different levels were larger in males than in females and increased with age. Multiple linear stepwise regression analysis showed that the subphrenic abdominal aortic area was significantly related to age (β = 0.544, p &lt; 0.001), sex (β = 0.359, p &lt; 0.001), and hypertension (β = 0.107, p &lt; 0.001). Suprarenal abdominal aortic area was related to age (β = 0.398, p &lt; 0.001), sex (β = 0.383, p &lt; 0.001), history of smoking (β = 0.074, p = 0.005), and hypertension (β = 0.111, p &lt; 0.001). The infrarenal abdominal aortic area was correlated with age (β = 0.420, p &lt; 0.001), sex (β = 0.407, p &lt; 0.001), and history of smoking (β = 0.055, p = 0.036). The distal abdominal aortic area was correlated with age (β = 0.463, p &lt; 0.001), sex (β = 0.253, p &lt; 0.001), and hypertension (β = 0.073, p = 0.013).

Conclusion

The abdominal aortic areas at different levels were larger in males than in females. Aging, hypertension, and smoking prompt the expansion of abdominal aorta.

Abdominal Aortic Aneurysm Morphology as an Essential Criterion for Stratifying the Risk of Aneurysm Rupture

The current stratification model of aneurysm rupture seems to be insufficient in some clinical cases. In our study, we determined the differences in wall structure between ruptured and unruptured aneurysms. We obtained computed tomography angiograms and categorized them into the following three groups, consisting of 49 patients each: the group with ruptured abdominal aortic aneurysms (rAAA), symptomatic (sAAA), and asymptomatic (aAAA). The three-dimensional AAA anatomy was digitally reconstructed for each patient through semi-automatically obtained segmentation, and each aneurysm was distinguished by the following three parameters: AFL (aneurysm flow lumen), ILT (intraluminal thrombus), and calcifications. The AFL volume was greater in rAAA compared with aAAA (p = 0.004), the ILT volume was greater in aAAA than in rAAA (p = 0.013), and the AFL/ILT surface ratio was bigger in rAAA than in aAAA (p < 0.001), sAAA than in aAAA (p = 0.033), and rAAA than in sAAA (p = 0.016). AFL/ILT surface*100 was defined as an independent predictive factor of rAAA to aAAA (OR 1.187; 95% CI 1.099–1.281), to sAAA (OR 1.045; 95% CI 1.004–1.087), and in sAAA vs. aAAA (OR 1.067; 95% CI 1.017–1.119). Consequently, the wall of rAAA differs significantly from unruptured aneurysms. The AFL/ILT surface ratio might indicate an increased risk of aneurysm rupture and the occurrence of symptoms in AAA.

Local aortic aneurysm wall expansion measured with automated image analysis

Background

Assessment of regional aortic wall deformation (RAWD) might better predict for abdominal aortic aneurysm (AAA) rupture than the maximal aortic diameter or growth rate. Using sequential computed tomography angiograms (CTAs), we developed a streamlined, semiautomated method of computing RAWD using deformable image registration (dirRAWD).

Methods

Paired sequential CTAs performed 1 to 2 years apart of 15 patients with AAAs of various shapes and sizes were selected. Using each patient’s initial CTA, the luminal and aortic wall surfaces were segmented both manually and semiautomatically. Next, the same patient’s follow-up CTA was aligned with the first using automated rigid image registration. Deformable image registration was then used to calculate the local aneurysm wall expansion between the sequential scans (dirRAWD). To measure technique accuracy, the deformable registration results were compared with the local displacement of anatomic landmarks (fiducial markers), such as the origin of the inferior mesenteric artery and/or aortic wall calcifications. Additionally, for each patient, the maximal RAWD was manually measured for each aneurysm and was compared with the dirRAWD at the same location.

Results

The technique was successful in all patients. The mean landmark displacement error was 0.59 ± 0.93 mm with no difference between true landmark displacement and deformable registration landmark displacement by Wilcoxon rank sum test (P = .39). The absolute difference between the manually measured maximal RAWD and dirRAWD was 0.27 ± 0.23 mm, with a relative difference of 7.9% and no difference using the Wilcoxon rank sum test (P = .69). No differences were found in the maximal dirRAWD when derived using a purely manual AAA segmentation compared with using semiautomated AAA segmentation (P = .55).

Conclusions

We found accurate and automated RAWD measurements were feasible with clinically insignificant errors. Using semiautomated AAA segmentations for deformable image registration methods did not alter maximal dirRAWD accuracy compared with using manual AAA segmentations. Future work will compare dirRAWD with finite element analysis–derived regional wall stress and determine whether dirRAWD might serve as an independent predictor of rupture risk.

Current abdominal aortic aneurysm (AAA) surveillance methods are limited to assessments of the maximal diameter, which cannot accurately predict for AAA expansion and rupture risk. Automated assessment of AAA expansion across the entire three-dimensional geometry of the aneurysm could better describe aneurysm growth and could substantially inform management decisions, including the indications for repair. We have developed an accurate and streamlined approach to assessing local three-dimensional AAA expansion with submillimeter accuracy using computed tomography imaging obtained during routine aneurysm surveillance. This novel process does not require significant user expertise nor computer processing power and can be performed using open-source software readily accessible to both scientists and clinicians.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Anatomical Differences Between Intact and Ruptured Large Abdominal Aortic Aneurysms

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