Narrative Review of Risk Assessment of Abdominal Aortic Aneurysm Rupture Based on Biomechanics-Related Morphology

CLINICAL IMPACT

Studies have shown that the biomechanical indicators based on multi-scale models are more effective in accurately assessing the rupture risk of AAA. To meet the need for clinical monitoring and rapid decision making, the typical morphological parameters associated with AAA rupture and their relationships with the mechanical environment have been summarized, which provide a reference for clinical preoperative risk assessment of AAA.

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

OBJECTIVE

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

DATA SOURCES

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

REVIEW METHODS

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

RESULTS

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

CONCLUSION

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

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.

A quarter of a century biomechanical rupture risk assessment of abdominal aortic aneurysms. Achievements, clinical relevance, and ongoing developments

Abdominal aortic aneurysm (AAA) disease, the local enlargement of the infrarenal aorta, is a serious condition that causes many deaths, especially in men exceeding 65 years of age. Over the past quarter of a century, computational biomechanical models have been developed towards the assessment of AAA risk of rupture, technology that is now on the verge of being integrated within the clinical decision-making process. The modeling of AAA requires a holistic understanding of the clinical problem, in order to set appropriate modeling assumptions and to draw sound conclusions from the simulation results. In this article we summarize and critically discuss the proposed modeling approaches and report the outcome of clinical validation studies for a number of biomechanics-based rupture risk indices. Whilst most of the aspects concerning computational mechanics have already been settled, it is the exploration of the failure properties of the AAA wall and the acquisition of robust input data for simulations that has the greatest potential for the further improvement of this technology.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Prediction of Abdominal Aortic Aneurysm Growth Using Geometric Assessment of Computerized Tomography Images Acquired During the Aneurysm Surveillance Period

OBJECTIVE

We investigated the utility of geometric features for future AAA growth prediction.

BACKGROUND

Novel methods for growth prediction of AAA are recognized as a research priority. Geometric feature have been used to predict cerebral aneurysm rupture, but not examined as predictor of AAA growth.

METHODS

Computerized tomography (CT) scans from patients with infra-renal AAAs were analyzed. Aortic volumes were segmented using an automated pipeline to extract AAA diameter (APD), undulation index (UI), and radius of curvature (RC). Using a prospectively recruited cohort, we first examined the relation between these geometric measurements to patients' demographic features (n = 102). A separate 192 AAA patients with serial CT scans during AAA surveillance were identified from an ongoing clinical database. Multinomial logistic and multiple linear regression models were trained and optimized to predict future AAA growth in these patients.

RESULTS

There was no correlation between the geometric measurements and patients' demographic features. APD (Spearman r = 0.25, P < 0.05), UI (Spearman r = 0.38, P < 0.001) and RC (Spearman r =-0.53, P < 0.001) significantly correlated with annual AAA growth. Using APD, UI, and RC as 3 input variables, the area under receiver operating characteristics curve for predicting slow growth (<2.5 mm/yr) or fast growth (>5 mm/yr) at 12 months are 0.80 and 0.79, respectively. The prediction or growth rate is within 2 mm error in 87% of cases.

CONCLUSIONS

Geometric features of an AAA can predict its future growth. This method can be applied to routine clinical CT scans acquired from patients during their AAA surveillance pathway.

Infrarenal Remains Infrarenal-EVAR Suitability of Small AAA Is Rarely Compromised despite Morphological Changes during Surveillance

The aim was to analyze small abdominal aortic aneurysm (AAA) morphology during surveillance with regard to standard endovascular aortic repair (EVAR) suitability. This retrospective single-center study included all patients (n = 52, 48 male, 70 ± 8 years) with asymptomatic AAA ≤ 5.4 cm undergoing ≥2 computed tomography angiography(CTA)/magnetic resonance imaging (MRI) studies (interval: ≥6 months) between 2010 and 2018. Aneurysm diameter, neck quality (shape, length, angulation, thrombus/calcification), aneurysm thrombus, and distal landing zone diameters were compared between first and last CTA/MRI. Resulting treatment plan changes were determined. Neck shortening occurred in 25 AAA (mean rate: 2.0 ± 4.2 mm/year). Neck thrombus, present in 31 patients initially, increased in 16. Average AAA diameters were 47.7 ± 9.3 mm and 56.3 ± 11.6 mm on first and last CTA/MRI, mean aneurysm growth rate was 4.2 mm/year. Aneurysm thrombus was present in 46 patients primarily, increasing in 32. Neck thrombus growth and neck length change, aneurysm thrombus amount and aneurysm growth and aneurysm growth and neck angulation were significantly correlated. A total of 46 (88%) patients underwent open (12/46) or endovascular (34/46) surgery. The planned procedure changed from EVAR to fenestrated EVAR in two patients and from double to triple fenestrated EVAR in one. Thus, standard EVAR suitability was predominantly maintained as the threshold diameter for surgery was reached despite morphological changes. Consecutively, a possibly different pathogenesis of infra- versus suprarenal AAA merits further investigation.

A Finite Element Based Analysis of a Hemodynamics Efficient Flow Stent Suitable for Different Abdominal Aneurysm Shapes

This research aimed to examine the impact of a proposed flow stent (PFS) on different abdominal artery shapes. For that purpose, a finite element-based model using the computational fluid dynamics (CFD) method is developed. The effect of PFS intervention on the hemodynamic efficiency is estimated by all of the significant criteria used for the evaluation of aneurysm occlusion and possible rupture; the flow velocity, pressure, wall shear stress (WSS), and WSS-related indices. Results showed that PFS intervention preserves the effects of high flow rate and decreases irregular flow recirculation in the sac of the aneurysm. The flow velocity decreases inside the aneurysm sac in the range of 55% to 80%. The time-averaged wall shear stress (TAWSS) was reduced from 42% to 53% by FPS deployment. The simulation results implies that PFS could heal an aneurysm efficiently with a mechanism that causes the development of thrombus and ultimately leads to aneurysm resorption.

Structurally abnormal collagen fibrils in abdominal aortic aneurysm resist platelet adhesion

BACKGROUND

Platelet adhesion to the subendothelial collagen fibrils is one of the first steps in hemostasis. Understanding how structural perturbations in the collagen fibril affect platelet adhesion can provide novel insights into disruption of hemostasis in various diseases. We have recently identified the presence of abnormal collagen fibrils with compromised D-periodic banding in the extracellular matrix remodeling present in abdominal aortic aneurysms (AAA).

OBJECTIVE

In this study, we employed multimodal microscopy approaches to characterize how collagen fibril structure impacts platelet adhesion in clinical AAA tissues.

METHODS

Ultrastructural atomic force microscopy (AFM) analysis was performed on tissue sections after staining with fluorescently labeled collagen hybridizing peptide (CHP) to recognize degraded collagen. Second harmonic generation (SHG) microscopy was used on CHP-stained sections to identify regions of intact versus degraded collagen. Finally, platelet adhesion was identified via SHG and indirect immunofluorescence on the same tissue sections.

RESULTS

Our results indicate that ultrastructural features characterizing collagen fibril abnormalities coincide with CHP staining. SHG signal was absent from CHP-positive regions. Additionally, platelet binding was primarily localized to regions with SHG signal. Abnormal collagen fibrils present in AAA (in SHG negative regions) were thus found to inhibit platelet adhesion compared to normal fibrils.

CONCLUSIONS

Our investigations reveal how the collagen fibril structure in the vessel wall can serve as another regulator of platelet-collagen adhesion. These results can be broadly applied to understand the role of collagen fibril structure in regulating thrombosis or bleeding disorders.

Platelet protects angiotensin II-driven abdominal aortic aneurysm formation through inhibition of inflammation

BACKGROUND

Inflammation is the primary cause of abdominal aortic aneurysm (AAA) formation and development. It has been reported that platelets protect against septic shock by inhibiting inflammation. However, it is unclear whether platelets protect AAA progress via suppressing inflammation.

METHODS

A mouse model of AAA was established by a daily administration of angiotensin II (Ang II, 1000 ng/kg/min) for 28-day. The AAA mice received 1 × 10⁹ platelets transfusion in normal saline every 3rd day for 1 month. Hematoxylin and eosin, Masson's trichrome, and elastic van Gieson staining techniques were used to analyze the morphology of the abdominal aorta. Immunohistochemistry was used to detect any infiltration of inflammatory cells, inflammatory factors, and matrix metalloproteins (MMPs) in the aortic tissue. Western blot and enzyme-linked immunosorbent assay (ELISA) were used to examine the inflammatory factor proteins levels in the aortic wall and peripheral blood, respectively.

RESULTS

Platelets infusion significantly suppressed the Ang II-driven elevation of aortic diameter, AAA formation (52.38% decrease, P < 0.05), aortic expansion, elastic lamina destruction, and inflammatory response. In addition, MMP-2 and MMP-9 production were also reduced by platelets transfusion.

CONCLUSIONS

For the first time, our study reported the beneficial effect of platelet transfusion in suppressing the Ang II-driven AAA progress in mice through the inhibition of inflammation.

Experimental aortic aneurysm severity and growth depend on topical elastase concentration and lysyl oxidase inhibition

Abdominal aortic aneurysm (AAA) formation and expansion is highly complex and multifactorial, and the improvement of animal models is an important step to enhance our understanding of AAA pathophysiology. In this study, we explore our ability to influence aneurysm growth in a topical elastase plus β-Aminopropionitrile (BAPN) mouse model by varying elastase concentration and by altering the cross-linking capability of the tissue. To do so, we assess both chronic and acute effects of elastase concentration using volumetric ultrasound. Our results suggest that the applied elastase concentration affects initial elastin degradation, as well as long-term vessel expansion. Additionally, we assessed the effects of BAPN by (1) removing it to restore the cross-linking capability of tissue after aneurysm formation and (2) adding it to animals with stable aneurysms to interrupt cross-linking. These results demonstrate that, even after aneurysm formation, lysyl oxidase inhibition remains necessary for continued expansion. Removing BAPN reduces the aneurysm growth rate to near zero, resulting in a stable aneurysm. In contrast, adding BAPN causes a stable aneurysm to expand. Altogether, these results demonstrate the ability of elastase concentration and BAPN to modulate aneurysm growth rate and severity. The findings open several new areas of investigation in a murine model that mimics many aspects of human AAA.

A Predictive Analysis of Wall Stress in Abdominal Aortic Aneurysms Using a Neural Network Model

Rupture risk assessment of abdominal aortic aneurysms (AAAs) by means of quantifying wall stress is a common biomechanical strategy. However, the clinical translation of this approach has been greatly limited due to the complexity associated with the computational tools required for its implementation. Thus, being able to estimate wall stress using nonbiomechanical markers that can be quantified as a direct outcome of clinical image segmentation would be advantageous in improving the potential implementation of said strategy. In the present work, we investigated the use of geometric indices to predict patient-specific AAA wall stress by means of a novel neural network (NN) modeling approach. We conducted a retrospective review of existing clinical images of two patient groups: 98 asymptomatic and 50 symptomatic AAAs. The images were subject to a protocol consisting of image segmentation, processing, volume meshing, finite element modeling, and geometry quantification, from which 53 geometric indices and the spatially averaged wall stress (SAWS) were calculated. SAWS estimated from finite element analysis was considered the gold standard for the predictions. We developed feed-forward NN models composed of an input layer, two dense layers, and an output layer using Keras, a deep learning library in python. The NN models were trained, tested, and validated independently for both AAA groups using all geometric indices, as well as a reduced set of indices resulting from a variable reduction procedure. We compared the performance of the NN models with two standard machine learning algorithms (MARS: multivariate adaptive regression splines and GAM: generalized additive model) and a linear regression model (GLM: generalized linear model). With the reduced sets of indices, the NN-based approach exhibited the highest mean goodness-of-fit (for the symptomatic group 0.71 and for the asymptomatic group 0.79) and lowest mean relative error (17% for both groups). In contrast, MARS yielded a mean goodness-of-fit of 0.59 for the symptomatic group and 0.77 for the asymptomatic group, with relative errors of 17% for the symptomatic group and 22% for the asymptomatic group. GAM had a mean goodness-of-fit of 0.70 for the symptomatic group and 0.80 for the asymptomatic group, with relative errors of 16% for the symptomatic group and 20% for the asymptomatic group. GLM did not perform as well as the other algorithms, with a mean goodness-of-fit of 0.53 for the symptomatic group and 0.70 for the asymptomatic group, with relative errors of 19% for the symptomatic group and 23% for the asymptomatic group. Nevertheless, the NN models required a reduced set of 15 and 13 geometric indices to predict SAWS for the symptomatic and asymptomatic AAA groups, respectively. This was in contrast to the reduced set of nine and eight geometric indices required to predict SAWS with the MARS and GAM algorithms for each AAA group, respectively. The use of NN modeling represents a promising alternative methodology for the estimation of AAA wall stress using geometric indices as surrogates, in lieu of finite element modeling. The performance metrics of NN models are expected to improve with significantly larger group sizes, given the suitability of NN modeling for "big data" applications.

Multidimensional Analysis of Descending Aortic Growth After Acute Type A Aortic Dissection

BACKGROUND

After repair of acute type A aortic dissection, typical geometric variables of conventional aortic surveillance focus on maximum diameter and its rate of growth, potentially missing important geometric changes elsewhere. We determined additional information provided by a semiautomated, 3-dimensional (3D), nonlinear growth model of the descending thoracic aorta after repair of type A aortic dissection.

METHODS

Computed tomographic angiography data were retrospectively collected after hemiarch repair of type A aortic dissection. The descending aorta was systematically reconstructed to generate a 3D model made up of individual segments. The baseline and follow-up diameters were measured semiautomatically for each segment, and the nonlinear interval growth was determined.

RESULTS

The fastest growing segment expanded at a rate of 3.8 mm/y (interquartile range, 2.2 to 5.4 mm/y) vs 0.6 mm/y (interquartile range, -0.3 to 1.7 mm/y) when measured at the original site of maximum diameter (P < .01). The maximum baseline diameter was a poor predictor of location with fastest growth (r = 0.10, P > .1). Using the society recommended growth limits, a greater proportion of patients would be considered "at risk" when assessed by our method vs conventional surveillance measures.

CONCLUSIONS

Our model identifies areas of rapid aortic growth after repair of type A dissection that would likely be missed using current surveillance techniques. The increased precision, resolution, and reproducibility provided by our technique may improve on limitations of current surveillance techniques, provide novel geometric data on aortic remodeling, and contribute to the pursuit of a comprehensive patient-specific approach to aortic risk stratification.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Evaluation of the distribution and progression of intraluminal thrombus in abdominal aortic aneurysms using high-resolution MRI

BACKGROUND

Intraluminal thrombus (ILT) signal intensity on MRI has been studied as a potential marker of abdominal aortic aneurysm (AAA) progression.

PURPOSE

1) To characterize the relationship between ILT signal intensity and AAA diameter; 2) to evaluate ILT change over time; and 3) to assess the relationship between ILT features and AAA growth.

STUDY TYPE

Prospective.

SUBJECTS

Eighty AAA patients were imaged, and a subset (n = 41) were followed with repeated MRI for 16 ± 9 months.

FIELD STRENGTH/SEQUENCE

3D black-blood fast-spin-echo sequence at 3 T.

ASSESSMENT

ILT was designated as "bright" if the signal was greater than 1.2 times that of adjacent psoas muscle. AAAs were divided into three groups based on ILT: Type 1: bright ILT; Type 2: isointense ILT; Type 3: no ILT. During follow-up, an active ILT change was defined as new ILT formation or an increase in ILT signal intensity to bright; stable ILT was defined as no change in ILT type or ILT became isointense from bright previously.

STATISTICAL TESTS

Shapiro-Wilk test; Mann-Whitney U-test; Fisher's exact test; Kruskal-Wallis test; Spearman's r; intraclass correlation coefficient (ICC), Cohen's kappa.

RESULTS

AAAs with Type 1 ILT were larger than those with Types 2 and 3 ILT (5.1 ± 1.1 cm, 4.4 ± 0.9 cm, 4.2 ± 0.8 cm, P = 0.008). The growth rate of AAAs with Type 1 ILT was significantly greater than that of AAAs with Types 2 and 3 ILT (2.6 ± 2.5, 0.6 ± 1.3, 1.5 ± 0.6 mm/year, P = 0.01). During follow-up, AAAs with active ILT changes had a 3-fold increased growth rate compared with AAAs with stable ILT (3.6 ± 3.0 mm/year vs. 1.2 ± 1.5 mm/year, P = 0.008).

DATA CONCLUSION

AAAs with bright ILT are larger in diameter and grow faster. Active ILT change is associated with faster AAA growth. Black-blood MRI can characterize ILT features and monitor their change over time, which may provide new insights into AAA risk assessment.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019;50:994-1001.

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

PURPOSE

To investigate how 2-dimensional geometric parameters differ between ruptured and asymptomatic abdominal aortic aneurysms (AAAs) and provide a biomechanical explanation for the findings.

METHODS

The computed tomography angiography (CTA) scans of 30 patients (mean age 77±10 years; 23 men) with ruptured AAAs and 60 patients (mean age 76±8 years; 46 men) with asymptomatic AAAs were used to measure maximum sac diameter along the center lumen line, the cross-sectional lumen area, the total vessel area, the intraluminal thrombus (ILT) area, and corresponding volumes. The CTA data were segmented to create 3-dimensional patient-specific models for finite element analysis to compute peak wall stress (PWS) and the peak wall rupture index (PWRI). To reduce confounding from the maximum diameter, 2 diameter-matched groups were selected from the initial patient cohorts: 28 ruptured AAAs and another with 15 intact AAAs (diameters 74±12 vs 73±11, p=0.67). A multivariate model including the maximum diameter, the lumen area, and the ILT area of the 60 intact aneurysms was employed to predict biomechanical rupture risk parameters.

RESULTS

In the diameter-matched subgroup comparison, ruptured AAAs had a significantly larger cross-sectional lumen area (1954±1254 vs 1120±623 mm², p=0.023) and lower ILT area ratio (55±24 vs 68±24, p=0.037). The ILT area (2836±1462 vs 2385±1364 mm², p=0.282) and the total vessel area (3956±1170 vs 4338±1388 mm², p=0.384) did not differ statistically between ruptured and intact aneurysms. The PWRI was increased in ruptured AAAs (0.80 vs 0.48, p<0.001), but the PWS was similar (249 vs 284 kPa, p=0.194). In multivariate regression analysis, lumen area was significantly positively associated with both PWS (p<0.001) and PWRI (p<0.01). The ILT area was also significantly positively associated with PWS (p<0.001) but only weakly with PWRI (p<0.01). The lumen area conferred a higher risk increase in both PWS and PWRI when compared with the ILT area.

CONCLUSION

The lumen area is increased in ruptured AAAs compared to diameter-matched asymptomatic AAAs. Furthermore, this finding may in part be explained by a relationship with biomechanical rupture risk parameters, in which lumen area, irrespective of maximum diameter, increases PWS and PWRI. These observations thus suggest a possible method to improve prediction of rupture risk in AAAs by measuring the lumen area without the use of computational modeling.

Case Study: Intra-Patient Heterogeneity of Aneurysmal Tissue Properties

Introduction: Current recommendations for surgical treatment of abdominal aortic aneurysms (AAAs) rely on the assessment of aortic diameter as a marker for risk of rupture. The use of aortic size alone may overlook the role that vessel heterogeneity plays in aneurysmal progression and rupture risk. The aim of the current study was to investigate intra-patient heterogeneity of mechanical and fluid mechanical stresses on the aortic wall and wall tissue histopathology from tissue collected at the time of surgical repair. Methods: Finite element analysis (FEA) and computational fluid dynamics (CFD) simulations were used to predict the mechanical wall stress and the wall shear stress fields for a non-ruptured aneurysm 2 weeks prior to scheduled surgery. During open repair surgery one specimen partitioned into different regions was collected from the patient's diseased aorta according to a pre-operative map. Histological analysis and mechanical testing were performed on the aortic samples and the results were compared with the predicted stresses. Results: The preoperative simulations highlighted the presence of altered local hemodynamics particularly at the proximal segment of the left anterior area of the aneurysm. Results from the post-operative assessment on the surgical samples revealed a considerable heterogeneity throughout the aortic wall. There was a positive correlation between elastin fragmentation and collagen content in the media. The tensile tests demonstrated a good prediction of the locally varying constitutive model properties predicted using geometrical variables, i.e., wall thickness and thrombus thickness. Conclusions: The observed large regional differences highlight the local response of the tissue to both mechanical and biological factors. Aortic size alone appears to be insufficient to characterize the large degree of heterogeneity in the aneurysmal wall. Local assessment of wall vulnerability may provide better risk of rupture predictions.

The Obsolete Maximum Diameter Criterion, the Evident Role of Biomechanical (Pressure) Indices, the New Role of Hemodynamic (Flow) Indices, and the Multi-Modal Approach to the Rupture Risk Assessment of Abdominal Aortic Aneurysms

Although the therapeutic management of abdominal aortic aneurysms (AAAs) is currently based on the maximum diameter criterion, this has often proved inaccurate and misleading. Conversely, the biomechanical approach, which takes into account the pressure-induced wall stress exerted at every point throughout the aneurysmal surface, has been proven superior in predicting the rupture risk of AAAs, and its value is being increasingly recognized among physicians. More recently, hemodynamic indices, such as flow-induced wall shear stresses, have been indicated as potentially significant determinants of AAA natural history. Ultimately, a statistical model that takes into account all these factors may be relevant for making a sound prediction of the rupture risk of aneurysms and optimizing the management of these patients.

Biomechanical changes during abdominal aortic aneurysm growth

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

Use of Synchrotron Radiation to Accurately Assess Cross-Sectional Area Reduction of the Aortic Branch Ostia Caused by Suprarenal Stent Wires

PURPOSE

To compare in vivo the use of synchrotron radiation to computed tomography angiography (CTA) for the measurement of cross-sectional area (CSA) reduction of the aortic branch ostia caused by suprarenal stent-graft wires.

METHODS

This study was performed with a Zenith stent-graft placed in a phantom of the human aorta to simulate treatment of abdominal aortic aneurysm. Synchrotron radiation scans were performed using beam energies between 40 and 100 keV and spatial resolution of 19.88 μm per pixel. CSA reduction of the aortic branch ostia by suprarenal stent wires was calculated based on these exposure factors and compared with measurements from CTA images acquired on a 64-row scanner with slice thicknesses of 1.0, 1.5, and 2.0 mm.

RESULTS

Images acquired with synchrotron radiation showed <10% of the CSA occupied by stent wires when a single wire crossed a renal artery ostium and <20% for 2 wires crossing a renovisceral branch ostium. The corresponding areas ranged from 24% to 25% for a single wire and from 40% to 48% for double wires crossing the branch ostia when measured on CT images. The stent wire was accurately assessed on synchrotron radiation with a diameter between 0.38±0.01 and 0.53±0.03 mm, which is close to the actual size of 0.47±0.01 mm. The wire diameter measured on CT images was greatly overestimated (1.15±0.01 to 1.57±0.02 mm).

CONCLUSION

CTA has inferior spatial resolution that hinders accurate assessment of CSA reduction. This experiment demonstrated the superiority of synchrotron radiation over CTA for more accurate assessment of aortic stent wires and CSA reduction of the aortic branch ostia.

Growth Description for Vessel Wall Adaptation: A Thick-Walled Mixture Model of Abdominal Aortic Aneurysm Evolution

(1) Background: Vascular tissue seems to adapt towards stable homeostatic mechanical conditions, however, failure of reaching homeostasis may result in pathologies. Current vascular tissue adaptation models use many ad hoc assumptions, the implications of which are far from being fully understood; (2) Methods: The present study investigates the plausibility of different growth kinematics in modeling Abdominal Aortic Aneurysm (AAA) evolution in time. A structurally motivated constitutive description for the vessel wall is coupled to multi-constituent tissue growth descriptions; Constituent deposition preserved either the constituent’s density or its volume, and Isotropic Volume Growth (IVG), in-Plane Volume Growth (PVG), in-Thickness Volume Growth (TVG) and No Volume Growth (NVG) describe the kinematics of the growing vessel wall. The sensitivity of key modeling parameters is explored, and predictions are assessed for their plausibility; (3) Results: AAA development based on TVG and NVG kinematics provided not only quantitatively, but also qualitatively different results compared to IVG and PVG kinematics. Specifically, for IVG and PVG kinematics, increasing collagen mass production accelerated AAA expansion which seems counterintuitive. In addition, TVG and NVG kinematics showed less sensitivity to the initial constituent volume fractions, than predictions based on IVG and PVG; (4) Conclusions: The choice of tissue growth kinematics is of crucial importance when modeling AAA growth. Much more interdisciplinary experimental work is required to develop and validate vascular tissue adaption models, before such models can be of any practical use.

How Precise Are Preinterventional Measurements Using Centerline Analysis Applications? Objective Ground Truth Evaluation Reveals Software-Specific Centerline Characteristics

PURPOSE

To evaluate different centerline analysis applications using objective ground truth from realistic aortic aneurysm phantoms with precisely defined geometry and centerlines to overcome the lack of unknown true dimensions in previously published in vivo validation studies.

METHODS

Three aortic phantoms were created using computer-aided design (CAD) software and a 3-dimensional (3D) printer. Computed tomography angiograms (CTAs) of phantoms and 3 patients were analyzed with 3 clinically approved and 1 research software application. The 3D centerline coordinates, intraluminal diameters, and lengths were validated against CAD ground truth using a dedicated evaluation software platform.

RESULTS

The 3D centerline position mean error ranged from 0.7±0.8 to 2.9±2.5 mm between tested applications. All applications calculated centerlines significantly different from ground truth. Diameter mean errors varied from 0.5±1.2 to 1.1±1.0 mm among 3 applications, but exceeded 8.0±11.0 mm with one application due to an unsteady distortion of luminal dimensions along the centerline. All tested commercially available software tools systematically underestimated centerline total lengths by -4.6±0.9 mm to -10.4±4.3 mm (maximum error -14.6 mm). Applications with the highest 3D centerline accuracy yielded the most precise diameter and length measurements.

CONCLUSION

One clinically approved application did not provide reproducible centerline-based analysis results, while another approved application showed length errors that might influence stent-graft choice and procedure success. The variety and specific characteristics of endovascular aneurysm repair planning software tools require scientific evaluation and user awareness.

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

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