Abdominal Aortic Aneurysm Growth Rate Research Articles

The effect of diabetes on abdominal aortic aneurysm growth - updated systematic review and meta-analysis.

Studies have shown that diabetes mellitus is associated with a reduced prevalence and growth of abdominal aortic aneurysms (AAA). Establishing the factors that influence AAA growth will enable us to risk stratify patients and potentially optimise management. We aimed to provide an updated systematic review and meta-analysis that would inform more targeted screening practices based on patient demographics. MEDLINE, EMBASE, and DARE were searched using the Ovid interface and PubMed search engine. Studies were deemed eligible if they compared the growth rate of AAA between diabetic and non-diabetic populations. The mean difference (MD) and 95% confidence internal (CI) was used for data synthesis. Twenty-four studies from 20 articles with a total of 10,121 participants were included in our meta-analysis. An overall negative effect was shown between AAA growth and diabetes, with an annual mean effect of -0.25 mm/year (95% CI -0.35, -0.15; I2 = 73%). Our meta-analysis, which is larger and scientifically more robust compared to previous analyses, has confirmed that diabetes reduces the growth of AAA by approximately 0.25 mm a year compared to non-diabetic populations. This could have significant implications for AAA screening practices.

Hemoglobin homeostasis in abdominal aortic aneurysm: diagnostic and prognostic potential of hemoglobin/heme and scavenger molecules

BackgroundThere is increasing evidence implicating hemoglobin/heme and their scavengers in oxidative stress-mediated pathologies, but information is limited in abdominal aortic aneurysm (AAA).Methods and resultsIn this case-control study, we assessed heme/heme-related markers in 142 men with AAA and 279 men with a normal aortic diameter consecutively recruited from an ultrasound screening program in Sweden. Enzyme-linked immunosorbent assays (ELISAs) were used to measure heme oxygenase-1 (HO-1) and hemopexin (Hpx) plasma levels, colorimetric assays for cell-free heme and whole blood hemoglobin (Hb) levels, and droplet digital PCR (ddPCR) and real-time PCR to determine haptoglobin (Hp) (pheno)type and genotype, respectively. Hpx and heme plasma levels at baseline were elevated, while HO-1 levels were lower in men with AAA (p < 0.001) and were significantly associated with AAA prevalence independently of potential confounders. A combination of heme and HO-1 showed the best diagnostic potential based on the area under the curve (AUC): 0.76, sensitivity: 80%, specificity: 48%. Additionally, when previously described inflammatory biomarker interleukin-6 (IL-6), was added to our model it significantly improved the diagnostic value (AUC: 0.87, sensitivity: 80%, specificity: 79%) compared to IL-6 alone (AUC: 0.73, sensitivity: 80%, specificity: 49%). Finally, Hb (positively) and Hpx (negatively) levels at baseline were associated with AAA growth rate (mm/year), and their combination showed the best prognostic value for discriminating fast and slow-growing AAA (AUC: 0.76, sensitivity: 80%, specificity: 62%).ConclusionsThis study reports the distinct disruption of heme and related markers in both the development and progression of AAA, underscoring their potential in aiding risk stratification and therapeutic strategies.

624 A Retrospective Review of Blood Pressure Variability (BPV) and Abdominal Aortic Aneurysm (AAA)

Abstract Background Abdominal aortic aneurysms (AAA) rupture risk increases with expansion. Understanding of factors influencing AAA growth are crucial to reduce the risk of rupture. Blood pressure (BP) is considered a contributor to AAA formation, but the association with AAA growth remains unclear. Blood pressure variability (BPV) has emerged as an important cardiovascular risk factor, yet its relationship with AAA growth has not been investigated. Method A retrospective review of 90 patients participating in a multi-centre AAA growth study (NCT05376514) was conducted. Mean growth (mm/yr) was calculated from first and most recent duplex ultrasound scans. Outpatient BP readings between scans were used to calculate BPV defined as the standard deviation (SD) of systolic and diastolic values. Patients were stratified into high and low BPV groups and again into tertiles. Mann-whitney U and unpaired T-tests were used for group comparisons, Kruskall-Wallis to assess for a dose-response relationship between tertiles of BPV. Multiple regression analysis examined variable impact on growth. Results High diastolic BPV was associated with a faster growth rate (2.05 mm/yr [IQR= 1.00 – 3.00]) vs low diastolic BPV (1.44 mm/ yr ([IQR= 0.475-2.00]p=0.036) with a significant dose-response relationship between the lowest and highest BPV tertiles (p= 0.019). DBPV was a significant predictor of AAA growth in the multiple regression model for tertile classification (p=0.016). There was no association between systolic BPV and faster AAA growth rates. Conclusions There was a significant association between higher diastolic blood pressure variability and AAA growth. DBPV may be an important risk stratification tool.

Soluble glycoprotein VI predicts abdominal aortic aneurysm growth rate and is a novel therapeutic target

AbstractA common feature in patients with abdominal aortic aneurysms (AAAs) is the formation of a nonocclusive intraluminal thrombus (ILT) in regions of aortic dilation. Platelets are known to maintain hemostasis and propagate thrombosis through several redundant activation mechanisms, yet the role of platelet activation in the pathogenesis of AAA-associated ILT is still poorly understood. Thus, we sought to investigate how platelet activation affects the pathogenesis of AAA. Using RNA sequencing, we identified that the platelet-associated transcripts are significantly enriched in the ILT compared with the adjacent aneurysm wall and healthy control aortas. We found that the platelet-specific receptor glycoprotein VI (GPVI) is among the top enriched genes in AAA ILT and is increased on the platelet surface of patients with AAAs. Examination of a specific indicator of platelet activity, soluble GPVI (sGPVI), in 2 independent cohorts of patients with AAAs is highly predictive of an AAA diagnosis and associates more strongly with aneurysm growth rate than D-dimer in humans. Finally, intervention with the anti-GPVI antibody (JAQ1) in mice with established aneurysms blunted the progression of AAA in 2 independent mouse models. In conclusion, we show that the levels of sGPVI in humans can predict a diagnosis of AAA and AAA growth rate, which may be critical in the identification of high-risk patients. We also identify GPVI as a novel platelet-specific AAA therapeutic target, with minimal risk of adverse bleeding complications, for which none currently exists.

Can Biomarkers and PET Imaging Predict Abdominal Aortic Aneurysm Growth Rate?

Background: Abdominal aortic aneurysm (AAA) is a life-threatening condition due to the risk of aneurysm growth and rupture. Biomarkers linked to AAA pathogenesis are attractive candidates for AAA diagnosis and prognosis. The aim of this study was to assess circulating biomarkers levels relationship with PET imaging positivity and their predictive value in AAA growth rate. Methods: A total of 164 patients with AAA had whole body [18F]FDG PET/CT examination and blood drawn for biomarkers analysis at inclusion. Of these, 121 patients had at least one follow-up imaging assessment for AAA progression. Median (quartiles) imaging follow-up period was 32.8 months (15.2-69.6 months). Results: At baseline, PET was visually positive in 28 (17%) patients. Among PET+ patients, female proportion was higher compared to PET-patients (respectively, n = 6, 21.4% vs. n = 11, 8.1%, p = 0.046). Biomarkers of inflammation (CRP, CCL18), of proteolytic activity (MMP9), of extracellular matrix, and calcification regulation (OPN, OPG) were all significantly increased in PET+ patients (p < 0.05). During follow-up, rapid AAA growth (increase in size ≥ 1 cm per year) was observed in 36 (29.8%) patients and several biomarkers (CRP, MMP9, OPN, and OPG) were increased in those patients compared to patients without rapid growth (p < 0.05). Conclusions: Although PET positivity at baseline was not associated with rapid growth, CRP levels showed a significant association.

Influence of cardiometabolic medications on abdominal aortic aneurysm growth in the UK Aneurysm Growth Study: metformin and angiotensin-converting enzyme inhibitors associated with slower aneurysm growth.

There is a clinical need for treatments that can slow or prevent the growth of an abdominal aortic aneurysm, not only to reduce the need for surgery, but to provide a means to treat those who cannot undergo surgery. Analysis of the UK Aneurysm Growth Study (UKAGS) prospective cohort was conducted to test for an association between cardiometabolic medications and the growth of an abdominal aortic aneurysm above 30 mm in diameter, using linear mixed-effect models. A total of 3670 male participants with data available on abdominal aortic aneurysm growth, smoking status, co-morbidities, and medication history were included. The mean age at recruitment was 69.5 years, the median number of surveillance scans was 6, and the mean(s.e.) unadjusted abdominal aortic aneurysm growth rate was 1.75(0.03) mm/year. In a multivariate linear mixed-effect model, smoking (mean(s.e.) +0.305(0.07) mm/year, P = 0.00003) and antiplatelet use (mean(s.e.) +0.235(0.06) mm/year, P = 0.00018) were found to be associated with more rapid abdominal aortic aneurysm growth, whilst metformin was strongly associated with slower abdominal aortic aneurysm growth (mean(s.e.) -0.38(0.1) mm/year, P = 0.00019), as were angiotensin-converting enzyme inhibitors (mean(s.e.) -0.243(0.07) mm/year, P = 0.0004), angiotensin II receptor antagonists (mean(s.e.) -0.253(0.08) mm/year, P = 0.00255), and thiazides/related diuretics (mean(s.e.) -0.307(0.09) mm/year, P = 0.00078). The strong association of metformin with slower abdominal aortic aneurysm growth highlights the importance of the ongoing clinical trials assessing the effectiveness of metformin with regard to the prevention of abdominal aortic aneurysm growth and/or rupture. The association of angiotensin-converting enzyme inhibitors, angiotensin II receptor antagonists, and diuretics with slower abdominal aortic aneurysm growth points to the possibility that optimization of cardiovascular risk management as part of abdominal aortic aneurysm surveillance may have the secondary benefit of also reducing abdominal aortic aneurysm growth rates.

Abstract 18814: Glycoprotein VI is Critical for the Detection and Progression of Abdominal Aortic Aneurysms

Objective: Abdominal aortic aneurysms (AAA) frequently feature the formation of a nonocclusive intraluminal thrombus (ILT) along the site of aortic dilation. Platelets are known to maintain hemostasis and propagate thrombosis through several redundant activation mechanisms, yet the role of platelet activation in the pathogenesis of AAA associated ILT is still poorly understand. Thus, we sought to investigate how platelet activation via the glycoprotein VI (GPVI) platelet receptor impacts the pathogenesis of AAA. Methods and Results: RNA sequencing of age-matched control human aortic tissue, AAA aortic tissue, and AAA ILT demonstrates that platelet transcripts comprised 25% of significantly enriched genes AAA thrombus compared to AAA tissue and control aortic wall, with GPVI increased by 9.1 Log2-FC (P = 3.21E -08 ). Examination of soluble GPVI (sGPVI), a specific marker of platelet activity, in 2 independent AAA patient cohorts is predictive of AAA case status, associates strongly with aneurysm growth rate, and better predicts the presence of a fast-growing AAA when compared to D-dimer. To determine if GPVI blockade ameliorates AAA progression, mice were subjected to either the angiotensin II (AngII) infusion or the topical elastase models of aneurysm formation. Following model initiation, aortic diameter was monitored by weekly ultrasounds. After two weeks, mice which developed an aneurysm (defined as an aortic diameter of &gt;1.2mm) were randomized into control (IgG-50μg) or treatment (JAQ1-50μg, monoclonal GPVI antibody) groups. Treatment with JAQ1 blunted GPVI mediated platelet activation, attenuated aneurysm progression, and increased survival in both murine AAA models versus control. Conclusions: The highly specific platelet activation biomarker soluble glycoprotein VI strongly predicts both AAA case status and growth rate with potential use in identifying high risk patients. Specific blockade of GPVI-mediated platelet activation attenuates progression of established aneurysms in two independent murine models. Thus, our work demonstrates that specific targeting of GPVI to blunt platelet activation in AAA could be a potential therapeutic for a pathology with no current pharmacological treatments.

Radiation therapy for cancer is potentially associated with reduced growth of concomitant abdominal aortic aneurysm

PurposeCo-prevalence of abdominal aortic aneurysm (AAA) and cancer poses a unique challenge in medical care since both diseases and their respective therapies might interact. Recently, reduced AAA growth rates were observed in cancer patients that received radiation therapy (RT). The purpose of this study was to perform a fine-grained analysis of the effects of RT on AAA growth with respect to direct (infield) and out-of-field (outfield) radiation exposure, and radiation dose-dependency.MethodsA retrospective single-center analysis identified patients with AAA, cancer, and RT. Clinical data, radiation plans, and aneurysm diameters were analyzed. The total dose of radiation to each aneurysm was computed. AAA growth under infield and outfield exposure was compared to patients with AAA and cancer that did not receive RT (no-RT control) and to an external noncancer AAA reference cohort.ResultsBetween 2003 and 2020, a total of 38 AAA patients who had received well-documented RT for their malignancy were identified. AAA growth was considerably reduced for infield patients (n = 18) compared to outfield patients (n = 20), albeit not significantly (0.8 ± 1.0 vs. 1.3 ± 1.6 mm/year, p = 0.28). Overall, annual AAA growth in RT patients was lower compared to no-RT control patients (1.1 ± 1.5 vs. 1.8 ± 2.2 mm/year, p = 0.06) and significantly reduced compared to the reference cohort (1.1 ± 1.5 vs. 2.7 ± 2.1 mm/year, p < 0.001). The pattern of AAA growth reduction due to RT was corroborated in linear regression analyses correcting for initial AAA diameter. A further investigation with respect to dose-dependency of radiation effects on AAA growth, however, revealed no apparent association.ConclusionIn this study, both infield and outfield radiation exposure were associated with reduced AAA growth. This finding warrants further investigation, both in a larger scale clinical cohort and on a molecular level.

Intermediate pressure-normalized principal wall strain values are associated with increased abdominal aortic aneurysmal growth rates.

Current abdominal aortic aneurysm (AAA) assessment relies on analysis of AAA diameter and growth rate. However, evidence demonstrates that AAA pathology varies among patients and morphometric analysis alone is insufficient to precisely predict individual rupture risk. Biomechanical parameters, such as pressure-normalized AAA principal wall strain (/PP, %/mmHg), can provide useful information for AAA assessment. Therefore, this study utilized a previously validated ultrasound elastography (USE) technique to correlate /PP with the current AAA assessment methods of maximal diameter and growth rate. Our USE algorithm utilizes a finite element mesh, overlaid a 2D cross-sectional view of the user-defined AAA wall, at the location of maximum diameter, to track two-dimensional, frame-to-frame displacements over a full cardiac cycle, using a custom image registration algorithm to produce /PP. This metric was compared between patients with healthy aortas and AAAs (≥3 cm) and compared between small and large AAAs (≥5 cm). AAAs were then separated into terciles based on /PP values to further assess differences in our metric across maximal diameter and prospective growth rate. Non-parametric tests of hypotheses were used to assess statistical significance as appropriate. USE analysis was conducted on 129 patients, 16 healthy aortas and 113 AAAs, of which 86 were classified as small AAAs and 27 as large. Non-aneurysmal aortas showed higher /PP compared to AAAs (0.044 ± 0.015 vs. 0.034 ± 0.017%/mmHg, p = 0.01) indicating AAA walls to be stiffer. Small and large AAAs showed no difference in /PP. When divided into terciles based on /PP cutoffs of 0.0251 and 0.038%/mmHg, there was no difference in AAA diameter. There was a statistically significant difference in prospective growth rate between the intermediate tercile and the outer two terciles (1.46 ± 2.48 vs. 3.59 ± 3.83 vs. 1.78 ± 1.64 mm/yr, p = 0.014). There was no correlation between AAA diameter and /PP, indicating biomechanical markers of AAA pathology are likely independent of diameter. AAAs in the intermediate tercile of /PP values were found to have nearly double the growth rates than the highest or lowest tercile, indicating an intermediate range of /PP values for which patients are at risk for increased AAA expansion, likely necessitating more frequent imaging follow-up.

Intermediate Pressure-Normalized Strain Values Are Associated With Increased Abdominal Aortic Aneurysmal Growth Rates

Current abdominal aortic aneurysm (AAA) assessment methods rely on simple morphometric analysis of the AAA diameter and growth rate. However, evidence has shown that AAA pathology varies among patients, and morphometric analysis alone is insufficient to predict individual risk of growth. Biomechanical parameters, such as pressure-normalized aortic wall strain (εp+/PP), can provide a surrogate to vessel wall stiffness. We aimed to use our novel ultrasound elastography (USE) technique to measure ερ+/PP and correlate ερ+/PP with maximal AAA diameter and growth rate in the largest clinical trial to date. Our USE algorithm uses a finite element mesh overlayed on a 2D axial view of the user-defined AAA wall at the point of maximum diameter to track frame-to-frame displacements over a full cardiac cycle to measure ερ+/PP. ερ+/PP and growth rate were assessed between small and large AAAs based on a diameter of ≥5 cm. Patients with AAA were then separated into terciles based on ερ+/PP values of 0.0251 and 0.038 to assess differences in the AAA diameter and growth rate. Mann-Whitney U and Kruskal-Wallis tests were used to assess differences as appropriate. USE analysis was conducted on 127 patients, 16 normal aortas and 111 AAAs. A total of 79 patients had at least one follow-up clinical scan used to calculate growth rate. Of the 111 aortas, 85 were classified as small and 26 as large. AAAs showed lower ερ+/PP (stiffer) compared with nonaneurysmal aortas (0.034 ± 0.017 vs 0.044 ± 0.015 %/kPa; P = .006). There was no difference in ερ+/PP or growth rate between small and large AAAs. When divided into terciles based on ερ+/PP, there was no difference in the AAA diameter. There was a statistically significant difference in growth rate between the intermediate tercile and the outer terciles (1.46 ± 2.48 vs 3.59 ± 3.83 vs 1.78 ± 1.64 mm/y; P = .014) (Fig). Our validated USE algorithm shows that AAAs are stiffer than nonaneurysmal aortas, similar to previous reports. There was no correlation between AAA diameter and ερ+/PP, indicating that AAA stiffness is independent of diameter, and diameter thresholds alone may not accurately assess future risk of growth. AAAs in the intermediate tercile of ερ+/PP values were found to have greater growth rates than the outer tercile, indicating that an intermediate range of ερ+/PP values, regardless of diameter, place patients at increased risk for AAA growth. These findings also suggest that AAA growth may be related to a failure of collagen remodeling and may be the underlying event that leads to AAA rupture.

Hyperuricemia exacerbates abdominal aortic aneurysm formation through the URAT1/ERK/MMP-9 signaling pathway

ObjectivePrevious studies have revealed associations between hyperuricemia and microvascular diseases, but the association between hyperuricemia and abdominal aortic aneurysm (AAA) remains unclear. The aim of this study was to elucidate the pathogenesis and prove the relationship between AAA and hyperuricemia.MethodsA retrospective study was performed to validate the growth rates of AAA in humans with different serum uric acid levels. A murine model of angiotensin II-induced AAA was used to assess the effects of hyperuricemia on AAA growth in vivo, and human aortic smooth muscle cells (HASMCs) were used to study the pathways involved in these effects in vitro.ResultsWe analyzed data from 107 AAA patients and found that patients with serum uric acid levels above 9 mg/dl had higher AAA growth rates than patients with serum uric acid levels between 4 and 7.9 mg/dl. In vivo, induction of hyperuricemia increased the incidence of AAA formation and the abdominal aortic diameter in mice. The hyperuricemic mice exhibited higher levels of urate transporter 1 (URAT1) expression, phospho-extracellular signal-regulated kinase (p-ERK)1/2 expression, reactive oxygen species (ROS) levels and matrix metalloproteinase (MMP)-9 expression in the abdominal aorta than the control mice. Soluble uric acid increased the expression of URAT1, p-ERK1/2, and MMP-9 and the levels of ROS in HASMCs in vitro.ConclusionsWe have provided human evidence that hyperuricemia exacerbates AAA formation. In addition, our murine experimental evidence suggests that hyperuricemia exacerbates AAA formation and reveals that the URAT1/ERK1/2/ROS/MMP-9 pathway is among the pathways activated by uric acid in HASMCs.

Abdominal aortic aneurysm growth rates are not correlated to body surface area in screened men.

Screening for abdominal aortic aneurysm (AAA) in 65-year-old males reduces aneurysm related mortality. Infrarenal aortic diameter (IAD) has been shown to correlate to body surface area (BSA) which could influence diagnostic criteria for AAA. This study investigates whether AAA growth rates are also dependent on BSA, as that might have potential effects on surveillance of small AAAs. We conducted a retrospective, single center cohort study of 301 men with screening detected AAA between 2010-2017 with surveillance to 2021. AAA growth rates were analyzed in relation to the subject's BSA, smoking habits, and diabetic disease using a linear mixed-effects model. All men were offered smoking cessation program, optimized medical treatment, and advice on physical activity. The screening program included 28,784 men. Of the 22,819 (79%) attending the examinations, 374 men (1.6%) were found to have an AAA out of which 301 men had undergone two or more examinations during surveillance and were included with a median follow-up of 1846 days (IQR: 1 399). Mean unadjusted AAA growth rate was 1.60 mm/year (95% CI: 1.41-1.80). Diabetes mellitus had a statistically significant negative impact, smoking had a statistically significant positive impact on AAA growth rates whereas no correlation between AAA growth rate and BSA could be found. Body surface area could not be found to have a statistically significant correlation to AAA growth rates. The impact of smoking and diabetes on AAA growth rates remains similar to previously reported.

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

Prediction of abdominal aortic aneurysm (AAA) growth is of essential importance for the early treatment and surgical intervention of AAA. Capturing key features of vascular growth, such as blood flow and intraluminal thrombus (ILT) accumulation play a crucial role in uncovering the intricated mechanism of vascular adaptation, which can ultimately enhance AAA growth prediction capabilities. However, local correlations between hemodynamic metrics, biological and morphological characteristics, and AAA growth rates present high inter-patient variability that results in that the temporal-spatial biochemical and mechanical processes are still not fully understood. Hence, this study aims to integrate the physics-based knowledge with deep learning with a patch-based convolutional neural network (CNN) approach by incorporating important multiphysical features relating to its pathogenesis for validating its impact on AAA growth prediction. For this task, we observe that the unstructured multiphysical features cannot be directly employed in the kernel-based CNN. To tackle this issue, we propose a parameterization of features to leverage the spatio-temporal relations between multiphysical features. The proposed architecture was tested on different combinations of four features including radius, intraluminal thrombus thickness, time-average wall shear stress, and growth rate from 54 patients with 5-fold cross-validation with two metrics, a root mean squared error (RMSE) and relative error (RE). We conduct extensive experiments on AAA patients, the results show the effect of leveraging multiphysical features and demonstrate the superiority of the presented architecture to previous state-of-the-art methods in AAA growth prediction.

Double-edged sword of diabetes mellitus for abdominal aortic aneurysm.

Diabetes mellitus (DM) has been proved to contribute to multiple comorbidities that are risk factors for abdominal aortic aneurysm (AAA). Remarkably, evidences from epidemiologic studies have demonstrated a negative association between the two disease states. On the other hand, hyperglycemic state was linked to post-operative morbidities following AAA repair. This review aims to provide a thorough picture on the double-edged nature of DM and major hypoglycemic medications on prevalence, growth rate and rupture of AAA, as well as DM-associated prognosis post AAA repair. We performed a comprehensive search in electronic databases to look for literatures demonstrating the association between DM and AAA. The primary focus of the literature search was on the impact of DM on the morbidity, enlargement and rupture rate, as well as post-operative complications of AAA. The role of antidiabetic medications was also explored. Retrospective epidemiological studies and large database researches associated the presence of DM with decreased prevalence, slower expansion and limited rupture rate of AAA. Major hypoglycemic drugs exert similar protective effect as DM against AAA by targeting pathological hallmarks involved in AAA formation and progression, which were demonstrated predominantly by animal studies. Nevertheless, presence of DM or postoperative hyperglycemia was linked to poorer short-term and long-term prognosis, primarily due to greater risk of infection, longer duration of hospital stays and death. While DM is a positive factor in the formation and progression of AAA, it is also associated with higher risk of negative outcomes following AAA repair. Concomitant use of antidiabetic medications may contribute to the protective mechanism of DM in AAA, but further studies are still warranted to explore their role following AAA repair.

Rupture risk parameters upon biomechanical analysis independently change from vessel geometry during abdominal aortic aneurysm growth

ObjectiveThe indication for abdominal aortic aneurysm (AAA) repair is based on a diameter threshold. However, mechanical properties, such as peak wall stress (PWS) and peak wall rupture index (PWRI), influence the individual rupture risk. This study aims to correlate biomechanical and geometrical AAA characteristics during aneurysm growth applying a new linear transformation-based comparison of sequential imaging. MethodsPatients with AAA with two sequential computed tomography angiographies (CTA) were identified from a single-center aortic database. Patient characteristics included age, gender, and comorbidities. Semiautomated segmentation of CTAs was performed using Endosize (Therenva) for geometric variables (diameter, neck configuration, α/β angle, and vessel tortuosity) and for finite element method A4 Clinics Research Edition (Vascops) for additional variables (intraluminal thrombus [ILT]), vessel volume, PWS, PWRI). Maximum point coordinates from at least one CTA 6 to 24 months before their final were predicted for the final preoperative CTA using linear transformation along fix and validation points to estimate spatial motion. Pearson’s correlation and the t test were used for comparison. ResultsThirty-two eligible patients (median age, 70 years) were included. The annual AAA growth rate was 3.7 mm (interquartile range [IQR], 2.25-5.44; P < .001) between CTs. AAA (+17%; P < .001) and ILT (+43%; P < .001) volume, maximum ILT thickness (+35%; P < .001), β angle (+1.96°; P = .017) and iliac tortuosity (+0.009; P = .012) increased significantly. PWS (+12%; P = .0029) and PWRI (+16%; P < .001) differed significantly between both CTAs. Both mechanical parameters correlated most significantly with the AAA volume increase (r = 0.68 [P < .001] and r = 0.6 [P < .001]). Changes in PWS correlated best with the aneurysm neck configuration. The spatial motion of maximum ILT thickness was 14.4 mm (IQR, 7.3-37.2), for PWS 8.4 mm (IQR, 3.8-17.3), and 11.5 mm (IQR, 5.9-31.9) for PWRI. Here, no significant correlation with any of the aforementioned parameters, patient age, or time interval between CTs were observed. ConclusionsPWS correlates highly significant with vessel volume and aneurysm neck configuration. Spatial motion of maximum ILT thickness, PWS, and PWRI is detectable and predictable and might expose different aneurysm wall segments to maximum stress throughout aneurysm growth. Linear transformation could thus add to patient-specific rupture risk analysis. Clinical RelevanceAbdominal aortic aneurysm rupture risk assessment is a key feature in future individualized therapy approaches for patients, since more and more data are obtained concluding a heterogeneous disease entity that might not be addressed ideally looking only at diameter enlargement. The approach presented in this pilot study demonstrates the feasibility and importance of measuring peak wall stress and rupture risk indices based on predicted and actual position of maximum stress points including intraluminal thrombus.

Abstract 12087: Improving Characterization of Abdominal Aortic Aneurysms by Modeling Thrombosis

Introduction: In seniors, the prevalence of abdominal aortic aneurysms (AAA) is high (9-10%). We aim to characterize AAA growth rates (slow vs. rapid) to help inform management strategies, including individualized imaging surveillance frequency. Hypothesis: Modeling thrombosis may improve the characterization of AAAs' growth status. Methods: 3D geometrical AAA models with and without thrombosis (vessel lumen only) were generated for 70 human subjects using available contrast-enhanced CTA data. AAA growth rates were categorized as slow (&lt; 5 mm/year) or rapid (≥ 5 mm/year) based on serial imaging. Python scripts were used to calculate geometrical parameters (83) with and without thrombosis. Patient-specific relevant health information was retrieved through a review of medical records. Support vector machine (SVM), a well-established machine learning method, was run with 10-fold cross-validation (100 iterations) to assess the predictive accuracy. Results: Among 70 AAAs studied, the ratio between rapidly-growing and slowly-growing was nearly 1:2. The combination of antihypertensive medication, coronary artery disease, juxta-aneurysm aortic size, and five geometrical parameters quantifying the extent of thrombosis provided the best accuracy for AAA's growth status. The area under receiving operating curve (AUROC) was 0.85, and total accuracy was 0.81, with 57% and 93% of rapidly- and slowly-growing AAAs correctly identified, respectively. Excluding patients with aneurysm thrombus, the AUROC and accuracy in predicting rapidly-growing AAAs decreased to 0.82 and 48%, respectively. Conclusions: machine-learning-based predictive modeling appears feasible for characterizing AAA's growth rate status. Manual aortic image segmentation, required for data analytics, is labor-intensive (on average, 1 hour). Leveraging artificial intelligence-based segmentation methodology may provide an automated solution to improve workflow and feasibility.

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

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. A cohort of 40patients with small AAAs (maximum diameter 32-53mm) who had at least an initial and a follow-up CT scan (median follow-up 12months, range 3-36months) 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. 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. 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.

Aneurysm Geometry Analyzed by the Novel Three-Dimensional Tomographic Ultrasound Relates to Abdominal Aortic Aneurysm Growth

Abdominal aortic aneurysms (AAAs) are increasingly screen-detected and many small aneurysms enter surveillance. Computed tomography identifies characteristics that can predict subsequent AAA growth but ionizing radiation and nephrotoxic contrast disadvantage its use in surveillance. We investigated whether duplex and 3-dimensional tomographic ultrasound identified features associated with AAA growth in patients on AAA surveillance. Duplex and three-dimensional tomographic ultrasound imaging was performed independently by 2 vascular scientists in 128 AAA surveillance patients who all had AAA growth measured over at least 2 years. Diameter, cross-sectional area, length, volume, wall thickness/volume, and intraluminal thrombus were measured. Pulsatility using maximum systolic and minimum diastolic diameters corrected for diameter and distensibility (consisting of strain and stiffness) were also calculated. AAA growth rate correlated with AAA diameter (r 0.43), volume (r 0.46), and cross-sectional area (r 0.42) (P < 0.01). Measuring wall thickness was inaccurate, but wall volume (corrected for AAA volume) inversely related to growth rate (r -0.43, P < 0.01). On a multivariate analysis, diameter and wall volume (r2adjusted 0.22, P < 0.01) improved prediction of growth rate compared with diameter alone (r2adjusted 0.18, P<0.01). Intraluminal thrombus volume, strain distensibility, and elastic distensibility were not significantly associated with AAA growth. AAA growth most strongly related to AAA volume and inversely to wall volume. AAA volume and wall volume may prove useful in the prediction of AAA growth rates.

Abdominal aortic aneurysm growth rates in patients undergoing local ultrasound surveillance.

Abdominal aortic aneurysm ultrasound surveillance varies between hospitals in the United Kingdom. University Hospitals Bristol and Weston adopt a 6-monthly surveillance interval for 4.5-4.9 cm abdominal aortic aneurysm, which is a deviation from nationally recommended 3-monthly intervals. Assessment of abdominal aortic aneurysm growth rate, and the concurrent impact of abdominal aortic aneurysm risk factors and medications prescribed for risk factors, may inform whether this change in surveillance intervals is safe and appropriate. This analysis was conducted retrospectively. A total of 1312 abdominal aortic aneurysm ultrasound scans from 315 patients between January 2015 and March 2020 were split into 0.5 cm groups, ranging from 3.0 to 5.5 cm. Abdominal aortic aneurysm growth rate was assessed with one-way analysis of variance. The impact of risk factors and risk factor medication on abdominal aortic aneurysm growth rate was analysed using multivariate and univariate linear regression and Kruskal-Wallis tests. Patient cause of death among surveillance patients was recorded. Abdominal aortic aneurysm growth rate was significantly associated with increased abdominal aortic aneurysm diameter (p < 0.001). There was a significant whole-group reduction in growth rate from 0.29 to 0.19 cm/year in diabetics compared to non-diabetics (p = 0.02), supported by univariate linear regression (p = 0.04). In addition, gliclazide patients had lower growth rate compared to patients not on the medication (p = 0.04). One abdominal aortic aneurysm rupture occurred <5.5 cm resulting in death. Abdominal aortic aneurysm measuring 4.5-4.9 cm had a mean growth rate of 0.3 cm/year (± 0.18 cm/year). Therefore, mean growth rate and variability suggest patients are unlikely to surpass surgical threshold of 5.5 cm between the 6-monthly surveillance scans, supported by low rupture rates. This suggests the surveillance interval for 4.5-4.9 cm abdominal aortic aneurysm is a safe and appropriate deviation from national guidance. In addition, it may be pertinent to consider diabetic status when designing surveillance intervals.

Influencing Factors of Diabetes Mellitus on Abdominal Aortic Aneurysm Diameter and Biochemical Parameters

Objective To investigate the effect of diabetes mellitus and hypoglycemic treatment on the diameter and biochemical parameters of abdominal aortic aneurysm (AAA).Methods A case-control study was conducted to retrospectively analyze the clinical data of AAA patients in Peking Union Medical College Hospital from 2015 to 2021.The AAA patients were classified into a group with diabetes mellitus (n=53) and a group without diabetes mellitus (n=104),and the biochemical parameters and aneurysm diameter were compared between the two groups.According to the aneurysm diameter,they were further classified into a small and medium abdominal aortic aneurysm group (SMAAA group,n=85) and a large abdominal aortic aneurysm group (LAAA group,n=72),and the biochemical parameters between the two groups were compared.Results Among the 157 cases with AAA,the incidence of hypertension in the group without diabetes mellitus was higher than that in the group with diabetes mellitus (χ2=8.147,P=0.004).The aneurysm diameter,homocysteine,and D-dimer in the group with diabetes mellitus were lower than those in the group without diabetes mellitus (t=-3.148,P=0.002;U=-1.503,P=0.013;U=-3.002,P=0.003).The aneurysm diameter and D-dimer in the SMAAA group were lower than those in the LAAA group (t=-14.406,P<0.001;U=-0.388,P<0.001).Multivariate Logistic regression analysis showed that diabetes mellitus (OR=0.477,95%CI=0.238-0.955,P=0.037) and hypoglycemic treatment (OR=0.477,95%CI=0.238-0.955,P=0.037) did not increase the risk of AAA enlargement.Conclusion Diabetes mellitus and hypoglycemic therapy may affect the growth rate of AAA by lowering D-dimer and inflammatory indexes.