Comparison of volume and diameter measurement in assessing small abdominal aortic aneurysm expansion examined using computed tomographic angiography

Thoracic Aortic Volume as a Predictor of Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis

BACKGROUND

It is unclear whether thoracic aortic volume (TAV) is useful for cardiovascular (CV) disease prognosis and risk assessment.

PURPOSE

This study evaluated cross-sectional associations of TAV with CV risk factors, and longitudinal association with incident CV events in the multiethnic study of atherosclerosis.

STUDY TYPE

Retrospective cohort analysis of prospective data.

POPULATION

1182 participants (69 ± 9 years, 54% female, 37% Caucasian, 18% Chinese, 31% African American, 14% Hispanic, 60% hypertensive, and 20% diabetic) without prior CV disease.

FIELD STRENGTH AND SEQUENCES

Axial black-blood turbo spin echo or bright blood steady-state free precession images on 1.5T scanners.

ASSESSMENT

TAV was calculated using Simpson's method from axial images, and included the ascending arch and descending segments. Traditional CV risk factors were assessed at the time of MRI. CV outcomes over a 9-year follow-up period were recorded and represented a composite of stroke, stroke death, coronary heart disease (CHD), CHD death, atherosclerotic death, and CVD death.

STATISTICAL TESTS

Multivariable linear regression models adjusted for height and weight were used to determine the relationship (β coefficient) between TAV and CV risk factors. Cox regression models assessed the association of TAV and incident CV events. A P-value of <0.05 was deemed statistically significant.

RESULTS

Mean TAV was = 139 ± 41 mL. In multivariable regression, TAV was directly associated with age (β = 1.6), male gender (β = 23.9), systolic blood pressure (β = 0.1), and hypertension medication use (β = 7.9); and inversely associated with lipid medication use (β = -5.3) and treated diabetes (β = -8.9). Compared to Caucasians, Chinese Americans had higher TAV (β = 11.4), while African Americans had lower TAV (β = -7.0). Higher TAV was independently associated with incident CV events (HR: 1.057 per 10 mL).

CONCLUSION

Greater TAV is associated with incident CV events, increased age, and hypertension in a large multiethnic population while treated diabetes and lipid medication use were associated with lower TAV.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Multicentric clinical evaluation of a computed tomography-based fully automated deep neural network for aortic maximum diameter and volumetric measurements

OBJECTIVE

This study aims to evaluate a fully automatic deep learning-based method (augmented radiology for vascular aneurysm [ARVA]) for aortic segmentation and simultaneous diameter and volume measurements.

METHODS

A clinical validation dataset was constructed from preoperative and postoperative aortic computed tomography angiography (CTA) scans for assessing these functions. The dataset totaled 350 computed tomography angiography scans from 216 patients treated at two different hospitals. ARVA's ability to segment the aorta into seven morphologically based aortic segments and measure maximum outer-to-outer wall transverse diameters and compute volumes for each was compared with the measurements of six experts (ground truth) and thirteen clinicians.

RESULTS

Ground truth (experts') measurements of diameters and volumes were manually performed for all aortic segments. The median absolute diameter difference between ground truth and ARVA was 1.6 mm (95% confidence interval [CI], 1.5-1.7; and 1.6 mm [95% CI, 1.6-1.7]) between ground truth and clinicians. ARVA produced measurements within the clinical acceptable range with a proportion of 85.5% (95% CI, 83.5-86.3) compared with the clinicians' 86.0% (95% CI, 83.9-86.0). The median volume similarity error ranged from 0.93 to 0.95 in the main trunk and achieved 0.88 in the iliac arteries.

CONCLUSIONS

This study demonstrates the reliability of a fully automated artificial intelligence-driven solution capable of quick aortic segmentation and analysis of both diameter and volume for each segment.

Machine learning algorithms for the prognostication of abdominal aortic aneurysm progression: a systematic review

INTRODUCTION

Abdominal aortic aneurysm (AAA), often characterized by an abdominal aortic diameter over 3.0 cm, is managed through screening, surveillance, and surgical intervention. AAA growth can be heterogeneous and rupture carries a high mortality rate, with size and certain risk factors influencing rupture risk. Research is ongoing to accurately predict individual AAA growth rates for personalized management. Machine learning, a subset of artificial intelligence, has shown promise in various medical fields, including endoleak detection post-EVAR. However, its application for predicting AAA growth remains insufficiently explored, thus necessitating further investigation. Subsequently, this paper aims to summarize the current status of machine learning in predicting AAA growth.

EVIDENCE ACQUISITION

A systematic database search of Embase, MEDLINE, Cochrane, PubMed and Google Scholar from inception till December 2022 was conducted of original articles that discussed the use of machine learning in predicting AAA growth using the aforementioned databases.

EVIDENCE SYNTHESIS

Overall, 2742 articles were extracted, of which seven retrospective studies involving 410 patients were included using a predetermined criteria. Six out of seven studies applied a supervised learning approach for their machine learning (ML) models, with considerable diversity observed within specific ML models. The majority of the studies concluded that machine learning models perform better in predicting AAA growth in comparison to reference models. All studies focused on predicting AAA growth over specified durations. Maximal luminal diameter was the most frequently used indicator, with alternative predictors being AAA volume, ILT (intraluminal thrombus) and flow-medicated diameter (FMD).

CONCLUSIONS

The nascent field of applying machine learning (ML) for Abdominal Aortic Aneurysm (AAA) expansion prediction exhibits potential to enhance predictive accuracy across diverse parameters. Future studies must emphasize evidencing clinical utility in a healthcare system context, thereby ensuring patient outcome improvement. This will necessitate addressing key ethical implications in establishing prospective studies related to this topic and collaboration among pivotal stakeholders within the AI field.

The Role of Aortic Volume in the Natural History of Abdominal Aortic Aneurysms and Post-Endovascular Aortic Aneurysm Repair Surveillance

There has been a debate about whether maximum diameter can be solely used to assess the natural history of abdominal aortic aneurysm. The aim of the present review is to collect all the available evidence on the role of abdominal aortic aneurysm (AAA) volume in the natural history of AAAs, including small untreated AAAs and AAAs treated by EVAR. The current literature appears to reinforce the role of volume as a supplementary measure for evaluating the natural history of AAA, in both intact AAAs and after EVAR. The clinical impact of AAA volume measurements remains unclear. Several studies show that volumetric analysis can assess changes in AAAs and predict successful endoluminal exclusion after EVAR more accurately than diameter. However, most studies lack strict standardized measurement criteria and well-defined outcome definitions. It remains unclear whether volumetry could replace diameter assessment in defining the risk of rupture of AAAs and identifying clinically relevant sac growth.

Role of Common Antihypertensives in the Growth of Abdominal Aortic Aneurysm at the Presurgical Stage

Background: Whether drug therapy slows the growth of abdominal aortic aneurysms (AAAs) in the Japanese population remains unknown. Methods and Results: In a multicenter prospective open-label study, patients with AAA at the presurgical stage (mean [±SD] AAA diameter 3.27±0.58 cm) were randomly assigned to treatment with candesartan (CAN; n=67) or amlodipine (AML; n=64) considering confounding factors (statin use, smoking, age, sex, renal function), with effects of blood pressure control minimized setting a target control level. The primary endpoint was percentage change in AAA diameter over 24 months. Secondary endpoints were changes in circulating biomarkers (high-sensitivity C-reactive protein [hs-CRP], malondialdehyde-low-density lipoprotein, tissue-specific inhibitor of metalloproteinase-1, matrix metalloproteinase [MMP] 2, MMP9, transforming growth factor-β1, plasma renin activity [PRA], angiotensin II, aldosterone). At 24 months, percentage changes in AAA diameter were comparable between the CAN and AML groups (8.4% [95% CI 6.23-10.59%] and 6.5% [95% CI 3.65-9.43%], respectively; P=0.23]. In subanalyses, AML attenuated AAA growth in patients with comorbid chronic kidney disease (CKD; P=0.04) or systolic blood pressure (SBP) <130 mmHg (P=0.003). AML exhibited a definite trend for slowing AAA growth exclusively in never-smokers (P=0.06). Among circulating surrogate candidates for AAA growth, PRA (P=0.02) and hs-CRP (P=0.001) were lower in the AML group. Conclusions: AML may prevent AAA growth in patients with CKD or lower SBP, associated with a decline in PRA and circulating hs-CRP.

Using averaged models from 4D ultrasound strain imaging allows to significantly differentiate local wall strains in calcified regions of abdominal aortic aneurysms

Abdominal aortic aneurysms are a degenerative disease of the aorta associated with high mortality. To date, in vivo information to characterize the individual elastic properties of the aneurysm wall in terms of rupture risk is lacking. We have used time-resolved 3D ultrasound strain imaging to calculate spatially resolved in-plane strain distributions characterized by mean and local maximum strains, as well as indices of local variations in strains. Likewise, we here present a method to generate averaged models from multiple segmentations. Strains were then calculated for single segmentations and averaged models. After registration with aneurysm geometries based on CT-A imaging, local strains were divided into two groups with and without calcifications and compared. Geometry comparison from both imaging modalities showed good agreement with a root mean squared error of 1.22 ± 0.15 mm and Hausdorff Distance of 5.45 ± 1.56 mm (mean ± sd, respectively). Using averaged models, circumferential strains in areas with calcifications were 23.2 ± 11.7% (mean ± sd) smaller and significantly distinguishable at the 5% level from areas without calcifications. For single segmentations, this was possible only in 50% of cases. The areas without calcifications showed greater heterogeneity, larger maximum strains, and smaller strain ratios when computed by use of the averaged models. Using these averaged models, reliable conclusions can be made about the local elastic properties of individual aneurysm (and long-term observations of their change), rather than just group comparisons. This is an important prerequisite for clinical application and provides qualitatively new information about the change of an abdominal aortic aneurysm in the course of disease progression compared to the diameter criterion.

Comparing maximum diameter and volume when assessing the growth of small abdominal aortic aneurysms using longitudinal CTA data: cohort study

BACKGROUND

Monitoring of abdominal aortic aneurysms (AAAs) is currently based on serial measurements of maximum aortic diameter. Additional assessment of aneurysm volume has previously been proposed to possibly improve growth prediction and treatment decisions. To evaluate the use of supplementing volume measurements, the authors aimed to characterise the growth distribution of AAA volume and to compare the growth rates of the maximum diameter and volume at the patient level.

METHODS

Maximum diameter and volume were monitored every 6 months in 84 patients with small AAAs, with a total of 331 computed tomographic angiographies (with initial maximum diameters of 30-68 mm). A previously developed statistical growth model for AAAs was applied to assess the growth distribution of volume and to compare individual growth rates for volume and for maximum diameter.

RESULTS

The median (25-75% quantile) expansion in volume was 13.4 (6.5-24.7) % per year. Cube root transformed volume and maximum diameter showed a closely linear association with a within-subject correlation of 0.77. At the surgery threshold maximum diameter of 55 mm, the median (25-75% quantile) volume was 132 (103-167) ml. In 39% of subjects, growth rates for volume and maximum diameter were equivalent, in 33% growth was faster in volume and in 27% growth was faster in maximum diameter.

CONCLUSION

At the population level, volume and maximum diameter show a substantial association such that the average volume is approximately proportional to the average maximum diameter raised to a power of three. At the individual level, however, in the majority of patient's AAAs grow at different pace in different dimensions. Hence, closer monitoring of aneurysms with sub-critical diameter but suspicious morphology may benefit from complementing maximum diameter by volume or related measurements.

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.

Hemodynamic parameters impact the stability of distal stent graft-induced new entry

Stent graft-induced new entry tear (SINE) is a serious complication in aortic dissection patients caused by the stent-graft itself after thoracic endovascular aortic repair (TEVAR). The stability of SINE is a key indicator for the need and timing of reinterventions. This study aimed to understand the role of hemodynamics in SINE stability by means of computational fluid dynamics (CFD) analysis based on patient-specific anatomical information. Four patients treated with TEVAR who developed a distal SINE (dSINE) were included; two patients had a stable dSINE and two patients experienced expansion of the dSINE upon follow-up examinations. CFD simulations were performed on geometries reconstructed from computed tomography scans acquired upon early detection of dSINE in these patients. Computational results showed that stable dSINEs presented larger regions with low time-averaged wall shear stress (TAWSS) and high relative residence time (RRT), and partial thrombosis was observed at subsequent follow-ups. Furthermore, significant systolic antegrade flow was observed in the unstable dSINE which also had a larger retrograde flow fraction (RFF) on the SINE plane. In conclusion, this pilot study suggested that high RRT and low TAWSS may indicate stable dSINE by promoting thrombosis, whereas larger RFF and antegrade flows inside dSINE might be associated with its expansion.

Ascending Aortic Volume: A Feasible Indicator for Ascending Aortic Aneurysm Elective Surgery?

Diameter-based criterion have been widely adopted for preventive surgery of ascending thoracic aortic aneurysm (ATAA). However, recent and growing evidence has shown that diameter-based methods may not be sufficient for identifying patients who are at risk of an ATAA. In this study, fluid-structure interaction (FSI) analysis was performed on one-hundred ATAA geometries reconstructed from clinical data to examine the relationship between hemodynamic conditions, ascending aortic volume (AAV), ascending aortic curvature, and aortic ratios measured from the reconstructed 3D models. The simulated hemodynamic and biomechanical parameters were compared among different groups of ATAA geometries classified based on AAV. The ATAAs with enlarged AAV showed significantly compromised hemodynamic conditions and higher mechanical wall stress. The maximum oscillatory shear index (OSI), particle residence time (PRT) and wall stress (WS) were significantly higher in enlarged ATAAs compared with controls (0.498 [0.497, 0.499] vs 0.499 [0.498, 0.499], p = 0.002, 312.847 [207.445, 519.391] vs 996.047 [640.644, 1573.140], p < 0.001, 769.680 [668.745, 879.795] vs 1072.000 [873.060, 1280.000] kPa, p < 0.001, respectively). Values were reported as median with interquartile range (IQR). AAV was also found to be more strongly correlated with these parameters compared to maximum diameter. The correlation coefficient between AAV and average WS was as high as 0.92 (p < 0.004), suggesting that AAV might be a feasible risk identifier for ATAAs. STATEMENT OF SIGNIFICANCE: Ascending thoracic aortic aneurysm is associated with the risk of dissection or rupture, creating life-threatening conditions. Current surgical intervention guidelines are purely diameter based. Recently, many studies proposed to incorporate other morphological parameters into the current clinical guidelines to better prevent severe adverse aortic events like rupture or dissection. The purpose of this study is to gain a better understanding of the relationship between morphological parameters and hemodynamic parameters in ascending aortic aneurysms using fluid-solid-interaction analysis on patient-specific geometries. Our results suggest that ascending aortic volume may be a better indicator for surgical intervention as it shows a stronger association with pathogenic hemodynamic conditions.

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.

Abdominal aortic aneurysm volume and relative intraluminal thrombus volume might be auxiliary predictors of rupture-an observational cross-sectional study

Objectives

The study aimed to identify differences and compare anatomical and biomechanical features between elective and ruptured abdominal aortic aneurysms (AAAs).

Methods

Data (clinical, anatomical, and biomechanical) of 98 patients with AAA, 75 (76.53%) asymptomatic (Group aAAA) and 23 (23.46%) ruptured AAA (Group rAAA), were prospectively collected and analyzed. Anatomical, morphological, and biomechanical imaging markers like peak wall stress (PWS) and rupture risk equivalent diameter (RRED), comorbid conditions, and demographics were compared between the groups. Biomechanical features were assessed by analysis of Digital Imaging and Communication in Medicine images by A4clinics (Vascops), and anatomical features were assessed by 3Surgery (Trimensio). Binary and multiple logistic regression analysis were used and adjusted for confounders. Accuracy was assessed using receiving operative characteristic (ROC) curve analysis.

Results

In a multivariable model, including gender and age as confounder variables, maximal aneurysm diameter [MAD, odds ratio (OR) = 1.063], relative intraluminal thrombus (rILT, OR = 1.039), and total aneurysm volume (TAV, OR = 1.006) continued to be significant predictors of AAA rupture with PWS (OR = 1.010) and RRED (OR = 1.031). Area under the ROC curve values and correct classification (cc) for the same parameters and the model that combines MAD, TAV, and rILT were measured: MAD (0.790, cc = 75%), PWS (0.713, cc = 73%), RRED (0.717, cc = 55%), TAV (0.756, cc = 79%), rILT (0.656, cc = 60%), and MAD + TAV + rILT (0.797, cc = 82%).

Conclusion

Based on our results, in addition to MAD, other important predictors of rupture that might be used during aneurysm surveillance are TAV and rILT. Biomechanical parameters (PWS, RRED) as valuable predictors should be assessed in prospective clinical trials. Similar studies on AAA smaller than 55 mm in diameter, even difficult to organize, would be of even greater clinical value.

Abdominal Aortic Aneurysm Diameter versus Volume: A Systematic Review

Recently, AAA volume measurement has been proposed as a potentially valuable surveillance method in situations when diameter measurement might fail.

OBJECTIVE

The aim of this systematic review was to analyze the results of previous studies comparing AAA diameter and volume measurements.

METHODS

A systematic search in PubMed, Cochrane, and EMBASE databases was performed to identify studies investigating the use of diameter and volume measurements in AAA diagnosis and prognosis in English, German, and Russian, published until December 2022. The manuscripts were reviewed by three researchers and scored on the quality of the research using MINORS criteria.

RESULTS

After screening 752 manuscripts, 19 studies (n = 1690) were included. The majority (n = 17) of the manuscripts appeared to favor volume. It is, however, important to highlight the heterogeneity of methodologies and lack of standardized protocol for measuring both volume and diameter in the included studies, which hindered the interpretation of the results.

CONCLUSIONS

The clinical relevance of abdominal aortic aneurysm volume measurement is still unclear, although studies show favorable and promising results for volumetric changes in AAA, especially in follow-up after EVAR.

One-year volume growth of abdominal aortic aneurysms measured by extended field-of-view ultrasound

BACKGROUND

Measurement of volume has the potential to detect subtle growth not recognized in the current surveillance paradigm of abdominal aortic aneurysms (AAAs). Currently available three-dimensional ultrasound allows for estimation of AAA volume, but for most patients, the AAA extends beyond the ultrasound field-of-view and only allows visualization of a partial AAA volume. A new extended field-of-view three-dimensional ultrasound protocol (XFoV US) has been found to improve the proportion of patients with visualization of the full AAA volume.

METHODS

To investigate the applicability of the XFoV US protocol in estimating AAA volume growth in follow-up, 86 patients with AAAs were recruited from the surveillance program at a university hospital. All were imaged by XFoV US at baseline and at one-year follow-up.

RESULTS

Assessment of full volume, based on visualization of the AAA neck and bifurcation at both baseline and one-year follow-up, was achieved in 67/86 (78%) of patients. One-year mean growth in maximum diameter was 2.8 mm (6%/year), in centerline length 2.9 mm (4%/year), and in volume 15.9 mL (19%/year). In 17/67 (25%) of patients, volume growth was detected in diameter-stable AAAs. Baseline XFoV US volume was associated with one-year AAA volume growth, while, conversely, maximum baseline diameter was not associated with one-year AAA diameter growth.

CONCLUSIONS

This study concludes that the XFoV US protocol provides a safe and repeatable modality for assessing AAA volume growth, and that AAA volume is a promising predictive measure of AAA growth.

3D Ultrasound Measurements Are Highly Sensitive to Monitor Formation and Progression of Abdominal Aortic Aneurysms in Mouse Models

Background

Available mouse models for abdominal aortic aneurysms (AAAs) differ substantially in the applied triggers, associated pathomechanisms and rate of vessel expansion. While maximum aortic diameter (determined after aneurysm excision or by 2D ultrasound) is commonly applied to document aneurysm development, we evaluated the sensitivity and reproducibility of 3D ultrasound to monitor aneurysm growth in four distinct mouse models of AAA.

Methods

The models included angiotensin-II infusion in ApoE deficient mice, topical elastase application on aortas in C57BL/6J mice (with or without oral administration of β-aminoproprionitrile) and intraluminal elastase perfusion in C57BL/6J mice. AAA development was monitored using semi-automated 3D ultrasound for aortic volume calculation over 12 mm length and assessment of maximum aortic diameter.

Results

While the models differed substantially in the time course of aneurysm development, 3D ultrasound measurements (volume and diameter) proved highly reproducible with concordance correlation coefficients > 0.93 and variations below 9% between two independent observers. Except for the elastase perfusion model where aorta expansion was lowest and best detected by diameter increase, all other models showed high sensitivity of absolute volume and diameter measurements in monitoring AAA formation and progression by 3D ultrasound. When compared to standard 2D ultrasound, the 3D derived parameters generally reached the highest effect size.

Conclusion

This study has yielded novel information on the robustness and limitations of semi-automated 3D ultrasound analysis and provided the first direct comparison of aortic volume increase over time in four widely applied mouse models of AAA. While 3D ultrasound generally proved highly sensitive in detecting early AAA formation, the 3D based volume analysis was found inferior to maximum diameter assessment in the elastase perfusion model where the extent of inflicted local injury is determined by individual anatomical features.

Hemostatic Biomarkers and Volumetry Help to Identify High-Risk Abdominal Aortic Aneurysms

Predicting the progression of small aneurysms is a main challenge in abdominal aortic aneurysm (AAA) management. The combination of circulating biomarkers and image techniques might provide an alternative for risk stratification. We evaluated the association of plasma TAT complexes (TAT) and D-dimer with AAA severity in 3 groups of patients: group 1, without AAA (n = 52), group 2, AAA 40−50 mm (n = 51) and group 3, AAA > 50 mm (n = 50). TAT (p < 0.001) and D-dimer (p < 0.001) were increased in patients with AAA (groups 2 and 3) vs. group 1. To assess the association between baseline TAT and D-dimer concentrations, and AAA growth, aortic diameter and volume (volumetry) were measured by computed tomography angiography (CTA) in group 2 at recruitment (baseline) and 1-year after inclusion. Baseline D-dimer and TAT levels were associated with AAA diameter and volume variations at 1-year independently of confounding factors (p ≤ 0.044). Additionally, surgery incidence, recorded during a 4-year follow-up in group 2, was associated with larger aneurysms, assessed by aortic diameter and volumetry (p ≤ 0.036), and with elevated TAT levels (sub-hazard ratio 1.3, p ≤ 0.029), while no association was found for D-dimer. The combination of hemostatic parameters and image techniques might provide valuable tools to evaluate AAA growth and worse evolution.

Fully automatic volume segmentation using deep learning approaches to assess aneurysmal sac evolution after infra-renal endovascular aortic repair

OBJECTIVE

Endovascular aortic repair (EVAR) surveillance relies on serial measurements of maximal diameter despite significant inter- and intra-observer variability. Volumetric measurements are more sensitive but general use is hampered by the time required for their implementation. An innovative fully automated software (PRAEVAorta® from Nurea), using artificial intelligence (AI), previously demonstrated fast and robust detection of infra-renal abdominal aortic aneurysm's (AAA) characteristics on pre-operative imaging. This study aimed to assess the robustness of these data on post-EVAR computed tomography (CT) scans.

METHODS

Comparison was made between fully automatic and semi-automatic segmentation manually corrected by a senior surgeon on a dataset of 48 patients (48 early post-EVAR CT scans with 6466 slices, and a total of 101 follow-up CT scans with 13708 slices).

RESULTS

The analyses confirmed an excellent correlation of post-EVAR volumes and surfaces, as well as, proximal neck and maximum aneurysm diameters measured with the fully automatic and manually corrected segmentation methods (Pearson's coefficient correlation >.99, p<.0001). Comparison between the fully automatic and manually corrected segmentation method revealed a mean Dice Similarity Coefficient of 0.950±0.015, Jaccard index of 0.906±0.028, Sensitivity of 0.929±0.028, Specificity of 0.965±0.016, Volumetric Similarity (VS) of 0.973±0.018 and mean Hausdorff Distance/slice of 8.7±10.8mm. The mean VS reached 0.873±0.100 for the lumen and 0.903±0.091 for the thrombus. The segmentation time was 9 times faster with the fully automatic method (2.5 vs 22 min/patient with the manually corrected method; p<.0001). Preliminary analysis also demonstrated that a diameter increase of 2mm can actually represent >5% volume increase.

CONCLUSION

PRAEVAorta® enables a fast, reproducible, and fully automated analysis of post-EVAR AAA sac and neck characteristics, with comparison between different time points. It could become a crucial adjunct for EVAR follow-up through early detection of sac evolution, which may reduce the risk of secondary rupture.

Fully automatic segmentation of abdominal aortic thrombus in pre-operative CTA images using deep convolutional neural networks

BACKGROUND

Endovascular aortic aneurysm repair (EVAR) is currently established as the first-line treatment for anatomically suitable abdominal aortic aneurysm (AAA).

OBJECTIVE

To establish a deep convolutional neural networks (DCNN) model for fully automatic segmentation intraluminal thrombosis (ILT) of abdominal aortic aneurysm (AAA) in pre-operative computed tomography angiography (CTA) images.

METHODS

We retrospectively reviewed 340 patients of AAA with ILT at our single center. The software ITKSNAP was used to draw AAA and ILT region of interests (ROIs), respectively. Image preprocessing and DCNN model build using MATLAB. Randomly divided, 80% of patients was classified as training set, 20% of patients was classified as test set. Accuracy, intersection over union (IOU), Boundary F1 (BF) Score were used to evaluate the predictive effect of the model.

RESULTS

By training in 34760-35652 CTA images (n= 204) and validation in 6968-7860 CTA images (n=68), the DCNN model achieved encouraging predictive performance in test set (n= 68, 6898 slices): Global accuracy 0.9988 ± 5.7735E-05, mean accuracy 0.9546 ± 0.0054, ILT IOU 0.8650 ± 0.0033, aortic lumen IOU 0.8595 ± 0.0085, ILT weighted IOU 0.9976 ± 0.0001, mean IOU 0.9078 ± 0.0029, mean BF Score 0.9829 ± 0.0011. Our DCNN model achieved a mean IOU of more than 90.78% for segmentation of ILT and aortic lumen. It provides a mean relative volume difference between automatic segmentation and ground truth (P> 0.05).

CONCLUSION

An end-to-end DCNN model could be used as an efficient and adjunctive tool for fully automatic segmentation of abdominal aortic thrombus in pre-operative CTA image.

Full-Volume Assessment of Abdominal Aortic Aneurysm by Improved-Field-of-View 3-D Ultrasound Performs Comparably to Computed Tomographic Angiography

Three-dimensional ultrasound (US) of abdominal aortic aneurysms (AAAs) is limited by the field-of-view of the 3D-US transducer. To obtain an extended field-of-view (XFoV), two transducer navigation system-assisted US protocols have been developed: XFoV-2D and XFoV-3D. In this study, the XFoV US protocols were compared with the currently available 3D-US protocol with standard field-of-view (FoV-st) and the established gold standard, computed tomography angiography (CTA). A total of 65 patients with AAA were included, and AAA imaging was processed offline with prototype software. The novel XFoV-2D and XFoV-3D protocols allowed for assessment of full AAA volume in significantly more patients (45/65 [69%] and 43/65 [66%], respectively), compared with the current 3D-US standard, FoV-st (30/65 [46%] patients). The mean difference in AAA volume estimation between each XFoV US protocol and 3-D CTA differed significantly (XFoV-2D: 16.9 mL, XFoV-3D: 7.6 mL, p = 0.002), indicating that XFoV-3D agreed best with 3D-CTA. No significant difference was found in the variance of full AAA volume quantification between each XFoV US protocol and CTA (p = 0.49). It is concluded that the XFoV US protocols improved the generation of full AAA volumes compared with the currently available 3D-US technology, with AAA volume estimates comparable to CTA estimates.

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.

Protocol for the Metformin Aneurysm Trial (MAT): a placebo-controlled randomised trial testing whether metformin reduces the risk of serious complications of abdominal aortic aneurysm

Background

Multiple observational studies have associated metformin prescription with reduced progression of abdominal aortic aneurysm (AAA). The Metformin Aneurysm Trial (MAT) will test whether metformin reduces the risk of AAA rupture-related mortality or requirement for AAA surgery (AAA events) in people with asymptomatic aneurysms.

Methods

MAT is an international, multi-centre, prospective, parallel-group, randomised, placebo-controlled trial. Participants must have an asymptomatic AAA measuring at least 35 mm in maximum diameter, no diabetes, no contraindication to metformin and no current plans for surgical repair. The double-blind period is preceded by a 6-week, single-blind, active run-in phase in which all potential participants receive metformin. Only patients tolerating metformin by taking at least 80% of allocated medication will enter the trial and be randomised to 1500 mg of metformin XR or an identical placebo. The primary outcome is the proportion of AAA events defined as rupture-related mortality or need for surgical repair. Secondary outcomes include AAA growth, major adverse cardiovascular events and health-related quality of life. In order to test if metformin reduced the risk of AAA events by at least 25%, 616 primary outcome events will be required (power 90%, alpha 0.05).

Discussion

Currently, there is no drug therapy for AAA. Past trials have found no convincing evidence of the benefit of multiple blood pressure lowering, antibiotics, a mast cell inhibitor, an anti-platelet drug and a lipid-lowering medication on AAA growth. MAT is one of a number of trials now ongoing testing metformin for AAA. MAT, unlike these other trials, is designed to test the effect of metformin on AAA events. The international collaboration needed for MAT will be challenging to achieve given the current COVID-19 pandemic. If this challenge can be overcome, MAT will represent a trial unique within the AAA field in its large size and design.

Trial registration

Australian Clinical Trials ACTRN12618001707257. Registered on 16 October 2018

Automatic measurement of maximal diameter of abdominal aortic aneurysm on computed tomography angiography using artificial intelligence

INTRODUCTION

The treatment of abdominal aortic aneurysm (AAA) relies on surgical repair and the indication mainly depends on its size evaluated by the maximal diameter (Dmax). The aim of this study was to evaluate a new automatic method based on artificial intelligence (AI) to measure the Dmax on computed tomography angiography (CTA).

METHODS

A fully automatic segmentation of the vascular system was performed using a hybrid method combining expert system with supervised deep learning (DL). The aorta centreline was extracted from the segmented aorta and the aortic diameters were automatically calculated. Results were compared to manual segmentation performed by two human operators.

RESULTS

The median absolute error between the two human operators was 1.2 mm (IQR 0.5- 1.9). The automatic method using the DL algorithm demonstrated correlation with the human segmentation, with a median absolute error of 0.8 (0.5- 4.2) mm and a coefficient correlation of 0.91 (p<0.001).

CONCLUSION

Although validation in larger cohorts is required, this method brings perspectives to develop new tools to standardize and automate the measurement of AAA Dmax in order to help clinicians in the decision-making process.

Profiling abdominal aortic aneurysm growth with three-dimensional ultrasound

BACKGROUND

"Profiling" is a new method based on three-dimensional ultrasound (3D-US) allowing for direct comparison of baseline and follow-up diameters along the AAA length. This study aimed to evaluate the feasibility of profiling to visualize AAA changes at sub-maximum diameters, and to categorize the growth profiles.

METHODS

Retrospective analysis of prospectively and consecutively included patients under AAA surveillance at a tertiary referral centre. 3D-US images of AAAs at baseline and at one-year follow-up were segmented, generating a centerline and a mesh of the aneurysm geometry. The mesh was processed to illustrate diameter changes of a given AAA. Three growth profiles were identified: A) Peak Growth: the largest, significant (≥3.6 mm) diameter difference occurred within a 10 mm margin to either side of the maximum baseline diameter; B) Edge Growth: at least one significant diameter difference and the criteria for Peak Growth did not apply; C) No Growth: all diameter differences were nonsignificant. A centerline length of ≥60 mm was assumed to capture a comparable segment of the wall geometry at baseline and follow-up. Cohen's kappa and Kaplan Meier analysis were used to analyze data.

RESULTS

In total, 186 patients had growth profiles generated. Of these, 28 (15%) were discarded, mainly based on inadequate centerline lengths (n= 21, 11.3%). The remaining patients were categorized into Edge Growth (n=83, 52%), No Growth (n=47, 30%), and Peak Growth (n=28, 18%).

CONCLUSIONS

Profiling interprets AAA growth at sub-maximum diameters. Half of the cohort had Edge Growth. These AAAs risk being classified as stable.

Role of volume in small abdominal aortic aneurysm surveillance

OBJECTIVE

Current management of small abdominal aortic aneurysms (AAAs) primarily involves serial imaging surveillance of maximum transverse diameter (MTD) to estimate rupture risk. Other measurements, such as volume and tortuosity, are less well-studied and may help characterize and predict AAA progression. This study evaluated predictors of AAA volume growth and discusses the role of volume in clinical practice.

METHODS

Subjects from the Non-invasive Treatment of Abdominal Aortic Aneurysm Clinical Trial (baseline AAA MTD, 3.5-5.0 cm) with ≥2 computed tomography scans were included in this study (n = 250). Computed tomography scans were conducted approximately every 6 months over 2 years. MTD, volume, and tortuosity were used to model growth. Univariable and multivariable backwards elimination least squares regressions assessed associations with volume growth.

RESULTS

Baseline MTD accounted for 43% of baseline volume variance (P < .0001). Mean volume growth rate was 10.4 cm³/year (standard deviation, 8.8 cm³/year) (mean volume change +10.4%). Baseline volume accounted for 30% of volume growth variance; MTD accounted for 13% of volume growth variance. More tortuous aneurysms at baseline had significantly larger volume growth rates (difference, 32.8 cm³/year; P < .0001). Univariable analysis identified angiotensin II receptor blocker use (difference, -3.4 cm³/year; P = .02) and history of diabetes mellitus (difference, -2.8 cm³/year; P = .04) to be associated with lower rates of volume growth. Baseline volume, tortuosity index, current tobacco use, and absence of diabetes mellitus remained significantly associated with volume growth in multivariable analysis. AAAs that reached the MTD threshold for repair had a wide range of volumes: 102 cm³ to 142 cm³ in female patients (n = 5) and 105 cm³ to 229 cm³ in male patients (n = 20).

CONCLUSIONS

Baseline AAA volume and MTD were found to be moderately correlated. On average, AAA volume grows about 10% annually. Baseline volume, tortuosity, MTD, current tobacco use, angiotensin II receptor blocker use, and history of diabetes mellitus were predictive of volume growth over time.

Three-dimensional Ultrasound Volume and Conventional Ultrasound Diameter Changes are Equally Good Markers of Endoleak in Follow-up after Endovascular Aneurysm Repair

INTRODUCTION

The main disadvantages of computed tomography angiography in follow-up after endovascular aneurysm repair are the risks of contrast-induced renal impairment and radiation-induced cancer. Three-dimensional ultrasound is a new technique for volume estimation of the aneurysm sac. Some studies have reported promising results. The aim of this study was to evaluate the accuracy and precision of three-dimensional ultrasound aneurysm sac-volume estimates, and to explore whether volume and/or diameter changes on ultrasound can be used as markers of endoleak.

METHODS

A single-center diagnostic accuracy study was performed. 92 Patients planned for endovascular aneurysm repair were prospectively and consecutively enrolled (2013-2016). Aneurysm sac diameter and volume were measured using computed tomography angiography, conventional ultrasound, and three-dimensional ultrasound preoperatively and 1, 6, 12, and 24 months postoperatively. Three-dimensional ultrasound was performed with a commercially available electromechanical transducer. Patients with endoleak were observed 5 years after endovascular aneurysm repair.

RESULTS

79 men and 13 women were included. Mean age was 74 years (57-92). Median follow-up was 24 months. Endoleak cases were observed for up to 55 months. Diameter measurements on conventional ultrasound correlated well with CT diameters (r = 0.9, P < 0.05, n = 347), and Bland-Altman analyses showed an upper limit of agreement of +0.5 cm and a lower limit of agreement of -0.8 cm. The mean difference was -0.13 cm ± 0.36 cm. Three-dimensional ultrasound volumes had a correlation with computed tomography angiography diameters of r = 0.8 (P < 0.05, n = 347) and with three-dimensional computed tomography volumes of r = 0.8 (P < 0.05, n = 155). Receiver operating characteristic analyses showed that the diameter and volume changes which led to reintervention were most accurate at 24-month follow-up, with area-under-the-curve percentage changes of 0.98 (two-dimensional ultrasound), 0.97 (three-dimensional ultrasound), and 0.97 (two-dimensional computed tomography).

DISCUSSION

Both diameter and volume changes can be used as markers for endoleak with excellent areas under the curve on receiver operating characteristic analyses. However, three-dimensional ultrasound volumes did not add any further diagnostic information. Conventional 2D diameter measurements were as accurate as volume changes as markers of endoleak.

CONCLUSION

Type II endoleaks can safely be followed up using a simple diameter measurement on conventional ultrasound.

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.

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement

Imaging-based measurements form the basis of surgical decision making in patients with aortic aneurysm. Unfortunately, manual measurement suffer from suboptimal temporal reproducibility, which can lead to delayed or unnecessary intervention. We tested the hypothesis that deep learning could improve upon the temporal reproducibility of CT angiography-derived thoracic aortic measurements in the setting of imperfect ground-truth training data. To this end, we trained a standard deep learning segmentation model from which measurements of aortic volume and diameter could be extracted. First, three blinded cardiothoracic radiologists visually confirmed non-inferiority of deep learning segmentation maps with respect to manual segmentation on a 50-patient hold-out test cohort, demonstrating a slight preference for the deep learning method (p < 1e-5). Next, reproducibility was assessed by evaluating measured change (coefficient of reproducibility and standard deviation) in volume and diameter values extracted from segmentation maps in patients for whom multiple scans were available and whose aortas had been deemed stable over time by visual assessment (n = 57 patients, 206 scans). Deep learning temporal reproducibility was superior for measures of both volume (p < 0.008) and diameter (p < 1e-5) and reproducibility metrics compared favorably with previously reported values of manual inter-rater variability. Our work motivates future efforts to apply deep learning to aortic evaluation.

Vascular Deformation Mapping of Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a complex disease that requires regular imaging surveillance to monitor for aneurysm stability. Current imaging surveillance techniques use maximum diameter, often assessed by computed tomography angiography (CTA), to assess risk of rupture and determine candidacy for operative repair. However, maximum diameter measurements can be variable, do not reliably predict rupture risk and future AAA growth, and may be an oversimplification of complex AAA anatomy. Vascular deformation mapping (VDM) is a recently described technique that uses deformable image registration to quantify three-dimensional changes in aortic wall geometry, which has been previously used to quantify three-dimensional (3D) growth in thoracic aortic aneurysms, but the feasibility of the VDM technique for measuring 3D growth in AAA has not yet been studied. Seven patients with infra-renal AAAs were identified and VDM was used to identify three-dimensional maps of AAA growth. In the present study, we demonstrate that VDM is able to successfully identify and quantify 3D growth (and the lack thereof) in AAAs that is not apparent from maximum diameter. Furthermore, VDM can be used to quantify growth of the excluded aneurysm sac after endovascular aneurysm repair (EVAR). VDM may be a useful adjunct for surgical planning and appears to be a sensitive modality for detecting regional growth of AAAs.

Comparison of diametric and volumetric changes in Stanford type B aortic dissection patients in assessing aortic remodeling post-stent graft treatment

Background

The study aims to analyze the correlation between the maximal diameter (both axial and orthogonal) and volume changes in the true (TL) and false lumens (FL) after stent-grafting for Stanford type B aortic dissection.

Method

Computed tomography angiography was performed on 13 type B aortic dissection patients before and after procedure, and at 6 and 12 months follow-up. The lumens were divided into three regions: the stented area (Region 1), distal to the stent graft to the celiac artery (Region 2), and between the celiac artery and the iliac bifurcation (Region 3). Changes in aortic morphology were quantified by the increase or decrease of diametric and volumetric percentages from baseline measurements.

Results

At Region 1, the TL diameter and volume increased (pre-treatment: volume =51.4±41.9 mL, maximal axial diameter =22.4±6.8 mm, maximal orthogonal diameter =21.6±7.2 mm; follow-up: volume =130.7±69.2 mL, maximal axial diameter =40.1±8.1 mm, maximal orthogonal diameter =31.9+2.6 mm, P<0.05 for all comparisons), while FL decreased (pre-treatment: volume =129.6±150.5 mL; maximal axial diameter =43.0±15.8 mm; maximal orthogonal diameter =28.3±12.6 mm; follow-up: volume =66.6±95.0 mL, maximal axial diameter =24.5±19.9 mm, maximal orthogonal diameter =16.9±13.7, P<0.05 for all comparisons). Due to the uniformity in size throughout the vessel, high concordance was observed between diametric and volumetric measurements in the stented region with 93% and 92% between maximal axial diameter and volume for the true/false lumens, and 90% and 92% between maximal orthogonal diameter and volume for the true/false lumens. Large discrepancies were observed between the different measurement methods at regions distal to the stent graft, with up to 46% differences between maximal orthogonal diameter and volume.

Conclusions

Volume measurement was shown to be a much more sensitive indicator in identifying lumen expansion/shrinkage at the distal stented region.

Efficacy of Telmisartan to Slow Growth of Small Abdominal Aortic Aneurysms: A Randomized Clinical Trial

Importance

Currently there is no drug therapy for abdominal aortic aneurysm (AAA).

Objective

To test the efficacy of the angiotensin receptor blocker telmisartan in slowing AAA growth in the Telmisartan in the Management of Abdominal Aortic Aneurysm (TEDY) trial.

Design, Setting, and Participants

A randomized, double-blind, placebo-controlled trial recruited participants between September 6, 2011, and October 5, 2016, to evaluate the efficacy of telmisartan treatment in patients with AAA. Participants with 35- to 49-mm AAAs recruited from Australia, the Netherlands, and the US were randomized 1:1 to receive telmisartan, 40 mg, or identical placebo. Analyses were conducted according to intention-to-treat principles. Final follow-up was conducted on October 11, 2018, and data analysis was performed between June and November 2019.

Intervention

Telmisartan, 40 mg, or identical placebo.

Main Outcomes and Measures

The primary outcome of the difference in AAA growth, assessed on core imaging laboratory-read ultrasonographic scanning, was tested with linear mixed-effects models. Other outcomes included effects on blood pressure, computed tomographic (CT)-measured AAA diameter and volume, time to AAA-related events (AAA repair or mortality due to AAA rupture), and health-related quality of life.

Results

Of 300 intended participants, 210 were enrolled and randomized to receive telmisartan (n = 107) or placebo (n = 103). Of patients included in the intention-to-treat analysis (telmisartan: n = 106, placebo: n = 101), 183 were men (88%); mean (SD) age was 73.5 (7.9) years. At 1 year, participants receiving telmisartan had mean lower systolic (8.9; 95% CI, 4.1-13.8 mm Hg; P < .001) and diastolic (7.0; 4.3-9.8 mm Hg; P < .001) blood pressure levels compared with participants receiving placebo. A total of 188 participants (91%) received at least 2 ultrasonographic scans and 133 participants (64%) had at least 2 CT scans. There was no significant difference in ultrasonographic-assessed AAA growth rates among those assigned telmisartan (1.68 mm/y) or placebo (1.78 mm/y): mean difference, -0.11 mm/y (95% CI, -0.60 to 0.38 mm/y; P = .66). Telmisartan had no significant effects on AAA growth assessed by CT-measured AAA diameter (mean difference, -0.01 mm/y; 95% CI, -0.02 to 0.01 mm/y; P = .23) or volume (mean difference, -0.02 cm3/y; 95% CI, -0.04 to 0.00 cm3/y; P = .11), AAA-related events (relative risk, 1.35; 95% CI, 0.54-3.35; P = .52), or health-related quality of life (mean difference in physical component score at 24 months, 0.4; 95% CI, 0.4-0.4; P = .80). Hypotensive symptoms (eg, syncope) were twice as common among participants receiving telmisartan compared with placebo (28 [26%] vs 13 [13%]; P = .02), but overall adverse event rates were otherwise similar for both groups.

Conclusions and Relevance

This underpowered study did not show a treatment effect for telmisartan on small AAA growth. Future trials will need to ensure adequate sample size and duration of follow-up.

Trial Registrations

anzctr.org.au Identifier: ACTRN12611000931976; ClinicalTrials.gov Identifier: NCT01683084.

Full-Volume Assessment of Abdominal Aortic Aneurysms by 3-D Ultrasound and Magnetic Tracking

Volume assessment of abdominal aortic aneurysms (AAAs) using 3-D ultrasound (US) is an innovative technique reporting good agreement with computed tomography angiography. One major limitation of the current 3-D US technique is a limited field of view, allowing full AAA acquisition in only 60% of patients. This study presents two new US acquisition protocols using magnetic field tracking, providing an "extended field of view" (XFoV-2-D and XFoV-3-D) with the aim of including both the aortic bifurcation and neck for full-volume assessment, and compares these methods with the current standard 3-D US protocol and with computed tomography angiography. A total of 20 AAA patients were included and underwent the current standard 3-D US protocol and the two novel 3-D US "extended field of view" protocols. Four patients were excluded from further analysis because of low image quality, leaving 16 patients eligible for analysis. Full AAA volume was achieved in 8 patients (50%) using the standard 3-D US protocol, in 11 patients (69%) with the XFoV-2-D protocol and in 13 patients (81%) with the XFoV-3-D protocol. In conclusion, this article describes two new and feasible US protocols applicable for full-AAA-volume estimation in most patients and should initiate further research into the added value of full volume in AAA surveillance.

Effect of blood pressure lowering drugs and antibiotics on abdominal aortic aneurysm growth: a systematic review and meta-analysis

OBJECTIVE

There is currently no medical treatment proven to limit abdominal aortic aneurysm (AAA) progression. The aim of this systematic review and meta-analysis was to pool data from previous randomised controlled trials assessing the efficacy of blood pressure-lowering and antibiotic medications in limiting AAA growth and AAA-related events, that is, rupture or repair.

METHODS

A systematic literature search was performed to identify randomised controlled trials that examined the efficacy of blood pressure-lowering medications or antibiotics in reducing AAA growth and AAA-related events. AAA growth (mm/year) was measured by ultrasound or computed tomography imaging. Meta-analyses were performed using random effects models. A subanalysis was conducted including trials that investigated tetracycline or macrolide antibiotics.

RESULTS

Ten randomised controlled trials including 2045 participants with an asymptomatic AAA were included. Follow-up was between 18 and 63 months. Neither blood pressure-lowering medications (mean growth±SD 2.0±2.4 vs 2.3±2.7 mm/year; standardised mean difference (SMD) -0.07, 95% CI -0.19 to 0.06; p=0.288) or antibiotics (mean growth±SD 2.6±2.1 vs 2.6±2.5 mm/year; SMD -0.11, 95% CI -0.38 to 0.16; p=0.418) reduced AAA growth or AAA-related events (blood pressure-lowering medications: 92 vs 95 events; risk ratio (RR) 0.86, 95% CI 0.66 to 1.11; p=0.244; and antibiotics: 69 vs 73 events; RR 0.93, 95% CI 0.69 to 1.25; p=0.614). The subanalysis of antibiotics showed similar results.

CONCLUSIONS

This meta-analysis suggests that neither blood pressure-lowering medications or antibiotics limit growth or clinically relevant events in people with AAAs.

The effect of ticagrelor on growth of small abdominal aortic aneurysms-a randomized controlled trial

AIMS

To evaluate if ticagrelor, an effective platelet inhibitor without known non-responders, could inhibit growth of small abdominal aortic aneurysms (AAAs).

METHODS AND RESULTS

In this multi-centre randomized controlled trial, double-blinded for ticagrelor and placebo, acetylic salicylic acid naïve patients with AAA and with a maximum aortic diameter 35-49 mm were included. The primary outcome was mean reduction in log-transformed AAA volume growth rate (%) measured with magnetic resonance imaging (MRI) at 12 months compared with baseline. Secondary outcomes include AAA-diameter growth rate and intraluminal thrombus (ILT) volume enlargement rate. A total of 144 patients from eight Swedish centres were randomized (72 in each group). MRI AAA volume increase was 9.1% for the ticagrelor group and 7.5% for the placebo group (P = 0.205) based on intention-to-treat analysis, and 8.5% vs. 7.4% in a per-protocol analysis (P = 0.372). MRI diameter change was 2.5 mm vs. 1.8 mm (P = 0.113), US diameter change 2.3 mm vs. 2.2 mm (P = 0.778), and ILT volume change 12.9% vs. 10.4% (P = 0.590).

CONCLUSION

In this RCT, platelet inhibition with ticagrelor did not reduce growth of small AAAs. Whether the ILT has an important pathophysiological role for AAA growth cannot be determined based on this study due to the observed lack of thrombus modulating effect of ticagrelor.

TRIAL REGISTRATION

The TicAAA trial is registered at the US National Institutes of Health (ClinicalTrials.gov) #NCT02070653.

Lack of an effective drug therapy for abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) rupture is a common cause of death in adults. Current AAA treatment is by open surgical or endovascular aneurysm repair. Rodent model and human epidemiology, and genetic and observational studies over the last few decades have highlighted the potential of a number of drug therapies, including medications that lower blood pressure, correct dyslipidaemia, or inhibit thrombosis, inflammation or matrix remodelling, as approaches to managing small AAA. This review summarizes prior AAA pathogenesis data from animal and human studies aimed at identifying targets for the development of drug therapies. The review also systematically assesses past randomized placebo-controlled drug trials in patients with small AAAs. Eleven previously published randomized-controlled clinical trials testing different drug therapies aimed at slowing AAA progression were identified. Five of the trials tested antibiotics and three trials assessed medications that lower blood pressure. Meta-analyses of these trials suggested that neither of these approaches limit AAA growth. Allocation to blood pressure-lowering medication was associated with a small reduction in AAA rupture or repair, compared to placebo (relative risk 0.94, 95% confidence intervals 0.89, 1.00, P = 0.047). Three further trials assessed the effect of a mast cell inhibitor, fibrate or platelet aggregation inhibition and reported no effect on AAA growth or clinical events. Past trials were noted to have a number of design issues, particularly small sample sizes and limited follow-up. Much larger trials are needed to properly test potential therapeutic approaches if a convincingly effective medical therapy for AAA is to be identified.

Feasibility and accuracy of a novel automated three-dimensional ultrasonographic analysis system for abdominal aortic aneurysm: comparison with two-dimensional ultrasonography and computed tomography

Background

Accurate measurement of the maximum aortic diameter (Dmax) is crucial for patients with abdominal aortic aneurysm (AAA). Aortic computed tomography (CT) provides accurate Dmax values by three-dimensional (3-D) reconstruction but may cause nephrotoxicity because of contrast use and radiation hazard. We aimed to evaluate the accuracy of a novel semi-automated 3-D ultrasonography (3-D US) system compared with that of CT as a reference.

Methods

Patients with AAA (n = 59) or individuals with normal aorta (n = 18) were prospectively recruited in an outpatient setting. Two-dimensional ultrasonography (2-D US) and 3-D US images were acquired with a single-sweep volumetric transducer. The analysis was performed offline with a software. Dmax and the vessel area of the Dmax slice were measured with 2-D US, 3-D US, and CT. The lumen and thrombus areas of the Dmax slice were also measured in 40 patients with intraluminal thrombus. Vessel and thrombus volumes were measured using 3-D US and CT.

Results

The Dmax values from 3-D US demonstrated better agreement (R² = 0.984) with the CT values than with the 2-D US values (R² = 0.938). Overall, 2-D US underestimated Dmax compared with 3-D US (32.3 ± 12.1 mm vs. 35.1 ± 12.0 mm). The Bland-Altman analysis of the 3-D US values, revealed better agreement with the CT values (2 standard deviations [SD], 2.9 mm) than with the 2-D US values (2 SD, 5.4 mm). The vessel, lumen, and thrombus areas all demonstrated better agreement with CT than with 2-D US (R² = 0.986 vs. 0.960 for the vessel, R² = 0.891 vs. 0.837 for the lumen, and R² = 0.977 vs. 0.872 for the thrombus). The thrombus volume assessed with 3-D US showed good correlation with the CT value (R² = 0.981 and 2 SD in the Bland-Altman analysis: 13.6 cm³).

Conclusions

Our novel semi-automated 3-D US analysis system provides more accurate Dmax values than 2-D US and provides precise volumetric data, which were not evaluable with 2-D US. The application of the semi-automated 3-D US analysis system in abdominal aorta assessment is easy and accurate.

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

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

Plasma D-dimer as a predictor of intraluminal thrombus burden and progression of abdominal aortic aneurysm

AIM

Intraluminal thrombus (ILT) is presented in most abdominal aortic aneurysms (AAAs) and is suggested to promote AAA expansion. D-dimer, a breakdown product in the thrombus remodeling, may have prognostic value for AAA. This study investigated the interrelation between plasma D-dimer level, ILT volume, AAA size and progression.

MAIN METHODS

This was a retrospective observational study that involved 181 patients with infra-renal AAA. They were divided into small and large AAA groups according to AAA diameter. 24 of them had repeated abdominal computed tomography angiography (CTA) scan and were divided into slow-growing and fast-growing AAA groups according to the median value of AAA growth rate. Baseline and follow-up plasma D-dimer level, maximum diameter of AAA, total infra-renal aortic volume and ILT volume were analyzed.

KEY FINDINGS

Plasma D-dimer level was positively correlated with ILT volume (R = 0.382, P < 0.001) and maximum diameter of AAA (R = 0.442, P < 0.001). Increasing value of plasma D-dimer was positively associated with the accelerated growth rate of AAA (R = 0.720, P < 0.01). ILT volume showed positive correlation with maximum diameter (R = 0.859, P < 0.001) and growth rate of AAA (R = 0.490, P < 0.05). After adjusting the baseline ILT volume, the positive correlations remained to be statistically significant between plasma D-dimer level and AAA size (R = 0.200, P < 0.05), as well as increasing value of plasma D-dimer and growth rate of AAA (R = 0.642, P < 0.05).

SIGNIFICANCE

Plasma D-dimer level reflected ILT burden in AAAs. Plasma D-dimer level and ILT volume were positively correlated with AAA size. Increasing value of plasma D-dimer and baseline ILT volume could be predictors of AAA progression.

Aortic sac enlargement after endovascular aneurysm repair: volume-related changes and the impact of intraluminal thrombus

Purpose

Abdominal aortic aneurysm (AAA) growth after endovascular aneurysm repair (EVAR) is still unpredictable. The issue of optimal frequency of computed tomography angiography for surveillance and its measurement method accuracy remain unclear. We aimed to assess the value of abdominal aneurysm sac volume measurement for detecting expansions and the association of preprocedural intraluminal thrombus (ILT) volume with aneurysm sac growth following EVAR.

Material and methods

A total of 107 patients underwent elective EVAR. Inclusion criteria provided a cohort of 39 patients. Changes of postoperative maximum aneurysm sac diameter and AAA volume were calculated. Volumetric AAA changes and demographic data of the cases with clinically irrelevant AAA diameter enlargement were evaluated. Preoperative ILT volumes were collected. ILT and AAA sac volume ratio was calculated. Statistical data analysis was performed using standard methods.

Results

The mean changes of maximum AAA diameter and volume in percentage after EVAR were –5.08 ± 8.20 mm and –13.39 ± 23.32%, respectively. A moderate positive linear correlation between those changes was found (R² = 0.731; p < 0.0001). The mean relative AAA volume increase in cases without clinically relevant diameter enlargement was 11.50 ± 8.27%. The means of ILT and AAA sac ratios were 0.59 ± 0.17 and 0.52 ± 1.8 in growing AAA sac and in stable or shrinking AAA sac groups, respectively (p = 0.308).

Conclusions

Volumetric AAA measurement may be useful as an additional method to diameter measurement after EVAR to identify clinically relevant sac growth. Preoperative volume of ILT may not significantly affect the growth rate of AAA after EVAR.

Clinical Validation of a Semi-Automated Software for Maximal Diameter Measurements for Endovascular Repair Follow-up

PURPOSE

To compare automated measurements of maximal diameter (D_max) of abdominal aortic aneurysm (AAA) orthogonal to luminal or outer wall envelope centerline for endovascular repair (EVAR) follow-up.

MATERIAL AND METHODS

Eighty-three consecutive patients with AAA treated by EVAR who had at least 1 computed tomography (CT) scan before and 2 CT scans after EVAR with at least 5 months' interval were included. Three-dimensional reconstruction of the AAA was achieved with dedicated segmentation software. Performances of automated calculation algorithms of D_max perpendicular to lumen or outer wall envelope centerlines were then compared to manual measurement of D_max on double-oblique multiplanar reconstruction (gold standard). Accuracy of automated D_max measurements at baseline, follow-up, and progression over time was evaluated by calculation of mean error, Bland-Altman plot, and regression models.

RESULTS

Disagreement in D_max measurements between outer wall envelope algorithm and manual method was insignificant (mean error: baseline, -0.07 ± 1.66 mm, P = .7; first follow-up, 0.24 ± 1.69 mm, P = .2; last follow-up, -0.41 ± 2.74 mm, P = .17); whereas significant discrepancies were found between the luminal algorithm and the manual method (mean error: baseline, -1.24 ± 2.01 mm, P < .01; first follow-up, -1.49 ± 3.30 mm, P < .01; last follow-up, -1.78 ± 3.60 mm, P < .01). D_max progression results were more accurate with AAA outer wall envelope algorithm compared to luminal method (P = .2).

CONCLUSIONS

AAA outer wall envelope segmentation is recommended to enable automated calculation of D_max perpendicular to its centerline during EVAR follow-up.