Biomechanical determinants of abdominal aortic aneurysm rupture

Measurement of Abdominal Aortic Aneurysm Strain Using MR Deformable Image Registration: Accuracy and Relationship to Recent Aneurysm Progression

BACKGROUND

Management of asymptomatic abdominal aortic aneurysm (AAA) based on maximum aneurysm diameter and growth rate fails to preempt many ruptures. Assessment of aortic wall biomechanical properties may improve assessment of progression and rupture risk. This study aimed to assess the accuracy of AAA wall strain measured by cine magnetic resonance imaging (MRI) deformable image registration (MR strain) and investigate its relationship with recent AAA progression.

METHODS

The MR strain accuracy was evaluated in silico against ground truth strain in 54 synthetic MRIs generated from a finite element model simulation of an AAA patient's abdomen for different aortic pulse pressures, tissue motions, signal intensity variations, and image noise. Evaluation included bias with 95% confidence interval (CI) and correlation analysis. Association of MR strain with AAA growth rate was assessed in 25 consecutive patients with >6 months of prior surveillance, for whom cine balanced steady-state free-precession imaging was acquired at the level of the AAA as well as the proximal, normal-caliber aorta. Univariate and multivariate regressions were used to associate growth rate with clinical variables, maximum AAA diameter (D max ), and peak circumferential MR strain through the cardiac cycle. The MR strain interoperator variability was assessed using bias with 95% CI, intraclass correlation coefficient, and coefficient of variation.

RESULTS

In silico experiments revealed an MR strain bias of 0.48% ± 0.42% and a slope of correlation to ground truth strain of 0.963. In vivo, AAA MR strain (1.2% ± 0.6%) was highly reproducible (bias ± 95% CI, 0.03% ± 0.31%; intraclass correlation coefficient, 97.8%; coefficient of variation, 7.14%) and was lower than in the nonaneurysmal aorta (2.4% ± 1.7%). D max ( β = 0.087) and MR strain ( β = -1.563) were both associated with AAA growth rate. The MR strain remained an independent factor associated with growth rate ( β = -0.904) after controlling for D max .

CONCLUSIONS

Deformable image registration analysis can accurately measure the circumferential strain of the AAA wall from standard cine MRI and may offer patient-specific insight regarding AAA progression.

An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their clinically-estimated risk of rupture-an event that is the 13th leading cause of death in the US-exceeds the risk associated with repair. Yet the current clinical guideline remains a one-size-fits-all "maximum diameter criterion" whereby AAA exceeding a threshold diameter is thought to make the risk of rupture high enough to warrant intervention. However, between 7 and 23.4% of smaller-sized AAA have been reported to rupture with diameters below the threshold. In this study, we train and assess machine learning models using clinical, biomechanical, and morphological indices from 381 patients to develop an aneurysm prognosis classifier to predict one of three outcomes for a given AAA patient: their AAA will remain stable, their AAA will require repair based as currently indicated from the maximum diameter criterion, or their AAA will rupture. This study represents the largest cohort of AAA patients that utilizes the first available medical image and clinical data to classify patient outcomes. The APC model therefore represents a potential clinical tool to striate specific patient outcomes using machine learning models and patient-specific image-based (biomechanical and morphological) and clinical data as input. Such a tool could greatly assist clinicians in their management decisions for patients with AAA.

Aneurysm Rupture Prediction Based on Strain Energy-CFD Modelling

This paper presents a Patient-Specific Aneurysm Model (PSAM) analyzed using Computational Fluid Dynamics (CFD). The PSAM combines the energy strain function and stress-strain relationship of the dilated vessel wall to predict the rupture of aneurysms. This predictive model is developed by analyzing ultrasound images acquired with a 6-9 MHz Doppler transducer, which provides real-time data on the arterial deformations. The patient-specific cyclic loading on the PSAM is extrapolated from the strain energy function developed using historical stress-strain relationships. Multivariant factors are proposed to locate points of arterial weakening that precede rupture. Biaxial tensile tests are used to calculate the material properties of the artery wall, enabling the observation of the time-dependent material response in wall rupture formation. In this way, correlations between the wall deformation and tissue failure mode can predict the aneurysm's propensity to rupture. This method can be embedded within the ultrasound measures used to diagnose potential AAA ruptures.

Quantitative Magnetic Resonance Imaging to Assess Progression and Rupture Risk of Aortic Aneurysms: A Scoping Review

PURPOSE

In current practice, the diameter of an aortic aneurysm is utilized to estimate the rupture risk and decide upon timing of elective repair, although it is known to be imprecise and not patient-specific. Quantitative magnetic resonance imaging (MRI) enables the visualization of several biomarkers that provide information about processes within the aneurysm and may therefore facilitate patient-specific risk stratification. We performed a scoping review of the literature on quantitative MRI techniques to assess aortic aneurysm progression and rupture risk, summarized these findings, and identified knowledge gaps.

METHODS

Literature concerning primary research was of interest and the medical databases PubMed, Scopus, Embase, and Cochrane were systematically searched. This study used the PRISMA protocol extension for scoping reviews. Articles published between January 2010 and February 2023 involving animals and/or humans were included. Data were extracted by 2 authors using a predefined charting method.

RESULTS

A total of 1641 articles were identified, of which 21 were included in the scoping review. Quantitative MRI-derived biomarkers were categorized into hemodynamic (8 studies), wall (5 studies) and molecular biomarkers (8 studies). Fifteen studies included patients and/or healthy human subjects. Animal models were investigated in the other 6 studies. A cross-sectional study design was the most common, whereas 5 animal studies had a longitudinal component and 2 studies including patients had a prospective design. A promising hemodynamic biomarker is wall shear stress (WSS), which is estimated based on 4D-flow MRI. Molecular biomarkers enable the assessment of inflammatory and wall deterioration processes. The ADAMTS4-specific molecular magnetic resonance (MR) probe showed potential to predict abdominal aortic aneurysm (AAA) formation and rupture in a murine model. Wall biomarkers assessed using dynamic contrast-enhanced (DCE) MRI showed great potential for assessing AAA progression independent of the maximum diameter.

CONCLUSION

This scoping review provides an overview of quantitative MRI techniques studied and the biomarkers derived from them to assess aortic aneurysm progression and rupture risk. Longitudinal studies are needed to validate the causal relationships between the identified biomarkers and aneurysm growth, rupture, or repair. In the future, quantitative MRI could play an important role in the personalized risk assessment of aortic aneurysm rupture.

CLINICAL IMPACT

The currently used maximum aneurysm diameter fails to accurately assess the multifactorial pathology of an aortic aneurysm and precisely predicts rupture in a patient-specific manner. Quantitative magnetic resonance imaging (MRI) enables the detection of various quantitative parameters involved in aneurysm progression and subsequent rupture. This scoping review provides an overview of the studied quantitative MRI techniques, the biomarkers derived from them, and recommendations for future research needed for the implementation of these biomarkers. Ultimately, quantitative MRI could facilitate personalized risk assessment for patients with aortic aneurysms, thereby reducing untimely repairs and improving rupture prevention.

Analyzing the contribution of vasa vasorum in oxygenation of the aneurysmal wall: A computational study

The mechanisms of abdominal aortic aneurysm (AAA) formation and rupture are controversial in the literature. While the intraluminal thrombus (ILT) plays a crucial role in reducing oxygen flux to the tissue and therefore decreasing the aortic wall strength, other physiological parameters such as the vasa vasorum (VV) oxygen flow and its consumption contribute to altered oxygenation responses of the arterial tissue as well. The goal of this research is to analyse the importance of the aforementioned parameters on oxygen delivery to the aneurysmal wall in a patient-specific AAA. Numerical simulations of coupled blood flow and mass transport with varying levels of VV concentration and oxygen reaction rate coefficient are performed. The hypoperfusion of the adventitial VV and high oxygen consumption are observed to have critical effects on reducing aneurysmal tissue oxygen supply and can therefore exacerbate localized oxygen deprivation.

A review on the biomechanical behaviour of the aorta

Large aortic aneurysm and acute and chronic aortic dissection are pathologies of the aorta requiring surgery. Recent advances in medical intervention have improved patient outcomes; however, a clear understanding of the mechanisms leading to aortic failure and, hence, a better understanding of failure risk, is still missing. Biomechanical analysis of the aorta could provide insights into the development and progression of aortic abnormalities, giving clinicians a powerful tool in risk stratification. The complexity of the aortic system presents significant challenges for a biomechanical study and requires various approaches to analyse the aorta. To address this, here we present a holistic review of the biomechanical studies of the aorta by categorising articles into four broad approaches, namely theoretical, in vivo, experimental and combined investigations. Experimental studies that focus on identifying mechanical properties of the aortic tissue are also included. By reviewing the literature and discussing drawbacks, limitations and future challenges in each area, we hope to present a more complete picture of the state-of-the-art of aortic biomechanics to stimulate research on critical topics. Combining experimental modalities and computational approaches could lead to more comprehensive results in risk prediction for the aortic system.

Status of diagnosis and therapy of abdominal aortic aneurysms

Abdominal aortic aneurysms (AAAs) are characterized by localized dilation of the abdominal aorta. They are associated with several serious consequences, including compression of adjacent abdominal organs, pain, treatment-related financial expenditure. The main complication of AAA is aortic rupture, which is responsible for about 200,000 deaths per year worldwide. An increasing number of researchers are dedicating their efforts to study AAA, resulting in significant progress in this field. Despite the commendable progress made thus far, there remains a lack of established methods to effectively decelerate the dilation of aneurysms. Therefore, further studies are imperative to expand our understanding and enhance our knowledge concerning AAAs. Although numerous factors are known to be associated with the occurrence and progression of AAA, the exact pathway of development remains unclear. While asymptomatic at most times, AAA features a highly unpredictable disease course, which could culminate in the highly deadly rupture of the aneurysmal aorta. Current guidelines recommend watchful waiting and lifestyle adjustment for smaller, slow-growing aneurysms, while elective/prophylactic surgical repairs including open repair and endovascular aneurysm repair are recommended for larger aneurysms that have grown beyond certain thresholds (55 mm for males and 50 mm for females). The latter is a minimally invasive procedure and is widely believed to be suited for patients with a poor general condition. However, several concerns have recently been raised regarding the postoperative complications and possible loss of associated survival benefits on it. In this review, we aimed to highlight the current status of diagnosis and treatment of AAA by an in-depth analysis of the findings from literatures.

Geometry and flow in ascending aortic aneurysms are influenced by left ventricular outflow tract orientation: Detecting increased wall shear stress on the outer curve of proximal aortic aneurysms

BACKGROUND

The geometrical characterization of ascending thoracic aortic aneurysms in clinical practice is limited to diameter measurements. Despite growing interest in hemodynamic assessment, its relationship with ascending thoracic aortic aneurysm pathogenesis is poorly understood. This study examines the relationship between geometry of the ventriculo-aortic junction and blood flow patterns in ascending thoracic aortic aneurysm disease.

METHODS

Thirty-three patients with ascending thoracic aortic aneurysms (exclusions: bicuspid aortic valves, connective tissue disease) underwent 4-dimensional flow magnetic resonance imaging. After image segmentation, geometrical parameters were measured, including aortic curvature, tortuosity, length, and diameter. A unique angular measurement made by the trajectory of the left ventricular outflow tract axis and the proximal aorta was also conducted. Velocity profiles were quantitatively and qualitatively analyzed. In addition, 11 patients (33%) underwent wall shear stress mapping of the ascending thoracic aortic aneurysm region using computational fluid dynamics simulation.

RESULTS

Greater left ventricular outflow tract aortic angles were associated with larger aortic diameters at the levels of the sinus (coefficient = 0.387, P = .014) and ascending aorta (coefficient = 0.284, P = .031). Patients with left ventricular outflow tract aortic angles greater than 60° had marked asymmetric flow acceleration on the outer curvature in the proximal aorta, ascertained from 4-dimensional flow analysis. For patients undergoing computational fluid dynamics assessment, regression analysis found that higher left ventricular outflow tract aortic angles were associated with significantly higher wall shear stress values in the outer curve of the aorta (coefficient 0.07, 95% confidence interval 0.04-0.11, P = .002): Angles greater than 50° yielded time-averaged wall shear stress values greater than 2.5 Pa, exhibiting a linear relationship.

CONCLUSIONS

Our findings strengthen the hypothesis of flow-mediated ascending thoracic aortic aneurysm disease progression and that left ventricular outflow tract aortic angle may be a predictor of disease severity.

Fast strain mapping in abdominal aortic aneurysm wall reveals heterogeneous patterns

Abdominal aortic aneurysm patients are regularly monitored to assess aneurysm development and risk of rupture. A preventive surgical procedure is recommended when the maximum aortic antero-posterior diameter, periodically assessed on two-dimensional abdominal ultrasound scans, reaches 5.5 mm. Although the maximum diameter criterion has limited ability to predict aneurysm rupture, no clinically relevant tool that could complement the current guidelines has emerged so far. In vivo cyclic strains in the aneurysm wall are related to the wall response to blood pressure pulse, and therefore, they can be linked to wall mechanical properties, which in turn contribute to determining the risk of rupture. This work aimed to enable biomechanical estimations in the aneurysm wall by providing a fast and semi-automatic method to post-process dynamic clinical ultrasound sequences and by mapping the cross-sectional strains on the B-mode image. Specifically, the Sparse Demons algorithm was employed to track the wall motion throughout multiple cardiac cycles. Then, the cyclic strains were mapped by means of radial basis function interpolation and differentiation. We applied our method to two-dimensional sequences from eight patients. The automatic part of the analysis took under 1.5 min per cardiac cycle. The tracking method was validated against simulated ultrasound sequences, and a maximum root mean square error of 0.22 mm was found. The strain was calculated both with our method and with the established finite-element method, and a very good agreement was found, with mean differences of one order of magnitude smaller than the image spatial resolution. Most patients exhibited a strain pattern that suggests interaction with the spine. To conclude, our method is a promising tool for investigating abdominal aortic aneurysm wall biomechanics as it can provide a fast and accurate measurement of the cyclic wall strains from clinical ultrasound sequences.

Quantification of patient-specific coronary material properties and their correlations with plaque morphological characteristics: An in vivo IVUS study

BACKGROUND

A method using in vivo Cine IVUS and VH-IVUS data has been proposed to quantify material properties of coronary plaques. However, correlations between plaque morphological characteristics and mechanical properties have not been studied in vivo.

METHOD

In vivo Cine IVUS and VH-IVUS data were acquired at 32 plaque cross-sections from 19 patients. Six morphological factors were extracted for each plaque. These samples were categorized into healthy vessel, fibrous plaque, lipid-rich plaque and calcified plaque for comparisons. Three-dimensional thin-slice models were constructed using VH-IVUS data to quantify in vivo plaque material properties following a finite element updating approach by matching Cine IVUS data. Effective Young's moduli were calculated to represent plaque stiffness for easy comparison. Spearman's rank correlation analysis was performed to identify correlations between plaque stiffness and morphological factor. Kruskal-Wallis test with Bonferroni correction was used to determine whether significant differences in plaque stiffness exist among four plaque groups.

RESULT

Our results show that lumen circumference change has a significantly negative correlation with plaque stiffness (r = -0.7807, p = 0.0001). Plaque burden and calcification percent also had significant positive correlations with plaque stiffness (r = 0.5105, p < 0.0272 and r = 0.5312, p < 0.0193) respectively. Among the four categorized groups, calcified plaques had highest stiffness while healthy segments had the lowest.

CONCLUSION

There is a close link between plaque morphological characteristics and mechanical properties in vivo. Plaque stiffness tends to be higher as coronary atherosclerosis advances, indicating the potential to assess plaque mechanical properties in vivo based on plaque compositions.

LOX-1 deficiency increases ruptured abdominal aortic aneurysm via thinning of adventitial collagen

Lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) is a key mediator of inflammation and plays an important role in the pathogenesis of atherosclerosis. Conversely, LOX-1 deficiency has been shown to decrease inflammation and atherosclerosis, both of which have been proposed to contribute to abdominal aortic aneurysm (AAA) pathogenesis. However, the role of LOX-1 in AAA pathogenesis remains unknown. Here, we investigated the effects of Olr1 (which encodes LOX-1) deletion on angiotensin II (Ang II)-induced AAA in apolipoprotein E knockout (ApoE KO) mice to determine whether LOX-1 deficiency mitigates AAA development. To accomplish this, we used serial, non-invasive ultrasound assessment, which revealed that the incidence and expansion rate of AAA were similar regardless of Olr1 deletion. However, Olr1 deletion significantly increased severe AAAs, including ruptured AAAs resulting in death. Oil Red O staining of the harvested aortas showed that the extent of atheroma burden localized in aneurysmal lesions did not differ between LOX-1-deficient and control mice, suggesting that Olr1 deletion did not decrease atheroma burden in the aneurysmal wall. Further histopathological analysis revealed that aneurysmal lesions in LOX-1-deficient mice had fewer fibroblasts and myofibroblasts, as well as thinner adventitial collagen, although the degree of elastin fragmentation or disruption was similar between LOX-1-deficient and control mice. An in vitro study confirmed that the proliferation of adventitial fibroblasts collected from LOX-1-deficient mice was significantly attenuated despite Ang II stimulation. In conclusion, Olr1 deletion may not mitigate aneurysm development but rather increases the vulnerability of rupture by suppressing adventitial fibroblast proliferation and collagen synthesis.

Abdominal Aortic Thrombus Segmentation in Postoperative Computed Tomography Angiography Images Using Bi-Directional Convolutional Long Short-Term Memory Architecture

Abdominal aortic aneurysm (AAA) is a fatal clinical condition with high mortality. Computed tomography angiography (CTA) imaging is the preferred minimally invasive modality for the long-term postoperative observation of AAA. Accurate segmentation of the thrombus region of interest (ROI) in a postoperative CTA image volume is essential for quantitative assessment and rapid clinical decision making by clinicians. Few investigators have proposed the adoption of convolutional neural networks (CNN). Although these methods demonstrated the potential of CNN architectures by automating the thrombus ROI segmentation, the segmentation performance can be further improved. The existing methods performed the segmentation process independently per 2D image and were incapable of using adjacent images, which could be useful for the robust segmentation of thrombus ROIs. In this work, we propose a thrombus ROI segmentation method to utilize not only the spatial features of a target image, but also the volumetric coherence available from adjacent images. We newly adopted a recurrent neural network, bi-directional convolutional long short-term memory (Bi-CLSTM) architecture, which can learn coherence between a sequence of data. This coherence learning capability can be useful for challenging situations, for example, when the target image exhibits inherent postoperative artifacts and noises, the inclusion of adjacent images would facilitate learning more robust features for thrombus ROI segmentation. We demonstrate the segmentation capability of our Bi-CLSTM-based method with a comparison of the existing 2D-based thrombus ROI segmentation counterpart as well as other established 2D- and 3D-based alternatives. Our comparison is based on a large-scale clinical dataset of 60 patient studies (i.e., 60 CTA image volumes). The results suggest the superior segmentation performance of our Bi-CLSTM-based method by achieving the highest scores of the evaluation metrics, e.g., our Bi-CLSTM results were 0.0331 higher on total overlap and 0.0331 lower on false negative when compared to 2D U-net++ as the second-best.

Image-Based Finite Element Modeling Approach for Characterizing In Vivo Mechanical Properties of Human Arteries

Mechanical properties of the arterial walls could provide meaningful information for the diagnosis, management and treatment of cardiovascular diseases. Classically, various experimental approaches were conducted on dissected arterial tissues to obtain their stress-stretch relationship, which has limited value clinically. Therefore, there is a pressing need to obtain biomechanical behaviors of these vascular tissues in vivo for personalized treatment. This paper reviews the methods to quantify arterial mechanical properties in vivo. Among these methods, we emphasize a novel approach using image-based finite element models to iteratively determine the material properties of the arterial tissues. This approach has been successfully applied to arterial walls in various vascular beds. The mechanical properties obtained from the in vivo approach were compared to those from ex vivo experimental studies to investigate whether any discrepancy in material properties exists for both approaches. Arterial tissue stiffness values from in vivo studies generally were in the same magnitude as those from ex vivo studies, but with lower average values. Some methodological issues, including solution uniqueness and robustness; method validation; and model assumptions and limitations were discussed. Clinical applications of this approach were also addressed to highlight their potential in translation from research tools to cardiovascular disease management.

MR Elastography of Abdominal Aortic Aneurysms: Relationship to Aneurysm Events

Background Abdominal aortic aneurysm (AAA) diameter remains the standard clinical parameter to predict growth and rupture. Studies suggest that using solely AAA diameter for risk stratification is insufficient. Purpose To evaluate the use of aortic MR elastography (MRE)-derived AAA stiffness and stiffness ratio at baseline to identify the potential for future aneurysm rupture or need for surgical repair. Materials and Methods Between August 2013 and March 2019, 72 participants with AAA and 56 healthy participants were enrolled in this prospective study. MRE examinations were performed to estimate AAA stiffness and the stiffness ratio between AAA and its adjacent remote normal aorta. Two Cox proportional hazards models were used to assess AAA stiffness and stiffness ratio for predicting aneurysmal events (subsequent repair, rupture, or diameter >5.0 cm). Log-rank tests were performed to determine a critical stiffness ratio suggesting high-risk AAAs. Baseline AAA stiffness and stiffness ratio were studied using Wilcoxon rank-sum tests between participants with and without aneurysmal events. Spearman correlation was used to investigate the relationship between stiffness and other potential imaging markers. Results Seventy-two participants with AAA (mean age, 71 years ± 9 [SD]; 56 men and 16 women) and 56 healthy participants (mean age, 42 years ± 16; 27 men and 29 women) were evaluated. In healthy participants, aortic stiffness positively correlated with age (ρ = 0.44; P < .001). AAA stiffness (event group [n = 21], 50.3 kPa ± 26.5 [SD]; no-event group [n = 21], 86.9 kPa ± 52.6; P = .01) and the stiffness ratio (event group, 0.7 ± 0.4; no-event group, 2.0 ± 1.4; P < .001) were lower in the event group than the no-event group at a mean follow-up of 449 days. AAA stiffness did not correlate with diameter in the event group (ρ = -0.06; P = .68) or the no-event group (ρ = -0.13; P = .32). AAA stiffness was inversely correlated with intraluminal thrombus area (ρ = -0.50; P = .01). Conclusion Lower abdominal aortic aneurysm stiffness and stiffness ratio measured with use of MR elastography was associated with aneurysmal events at a 15-month follow-up. © RSNA, 2022 See also the editorial by Sakuma in this issue.

Interaction of the Blood Components with Ascending Thoracic Aortic Aneurysm Wall: Biomechanical and Fluid Analyses

Background: Ascending thoracic aortic aneurysm (ATAA) is an asymptomatic localized dilation of the aorta that is prone to rupture with a high rate of mortality. While diameter is the main risk factor for rupture assessment, it has been shown that the peak wall stress from finite element (FE) simulations may contribute to refinement of clinical decisions. In FE simulations, the intraluminal boundary condition is a single-phase blood flow that interacts with the thoracic aorta (TA). However, the blood is consisted of red blood cells (RBCs), white blood cells (WBCs), and plasma that interacts with the TA wall, so it may affect the resultant stresses and strains in the TA, as well as hemodynamics of the blood. Methods: In this study, discrete elements were distributed in the TA lumen to represent the blood components and mechanically coupled using fluid–structure interaction (FSI). Healthy and aneurysmal human TA tissues were subjected to axial and circumferential tensile loadings, and the hyperelastic mechanical properties were assigned to the TA and ATAA FE models. Results: The ATAA showed larger tensile and shear stresses but smaller fluid velocity compared to the ATA. The blood components experienced smaller shear stress in interaction with the ATAA wall compared to TA. The computational fluid dynamics showed smaller blood velocity and wall shear stress compared to the FSI. Conclusions: This study is a first proof of concept, and future investigations will aim at validating the novel methodology to derive a more reliable ATAA rupture risk assessment considering the interaction of the blood components with the TA wall.

The Effects of Geometric Features of Intraluminal Thrombus on the Vessel Wall Oxygen Deprivation

The objective of this paper is to analyze the association of intraluminal thrombus (ILT) presence and morphology with oxygen transport in abdominal aortic aneurysms (AAA) and local hypoxia. The biomechanical role of the ILT layer in the evolution of the aneurysm is still not fully understood. ILT has been shown to create an inflammatory environment by reducing oxygen flux to the arterial wall and therefore decreasing its strength. It has been also hypothesized that the geometry of the ILT may further affect AAA rupture. However, no previous research has attempted to explore the effect of morphological features of ILT on oxygen distributions within the AAA, in a systematic manner. In this study, we perform a comprehensive analysis to investigate how physiologically meaningful variations in ILT geometric characteristics affect oxygen transport within an AAA. We simulate twenty-seven AAA models with variable ILT dimensions and investigate the extent to which ILT attenuates oxygen concentration in the arterial wall. Geometric variations studied include ILT thickness and ILT length, as well as the bulge diameter of the aneurysm which is related to ILT curvature. Computer simulations of coupled fluid flow-mass transport between arterial wall, ILT, and blood are solved and spatial variations of oxygen concentrations within the ILT and wall are obtained. The comparison of the results for all twenty-seven simulations supports the hypothesis that the presence of ILT in AAA correlates to significantly impaired oxygen transport to the aneurysmal wall. Mainly, we observed that ILT thickness and length are the parameters that influence decreased oxygen flow and concentration values the most, and thick thrombi exacerbate hypoxic conditions in the arterial wall, which may contribute to increased tissue degradation. Conversely, we observed that the arterial wall oxygen concentration is nearly independent of the AAA bulge diameter. This confirms that consideration of ILT size and anatomy is crucial in the analysis of AAA development.

Micromechanical and Ultrastructural Properties of Abdominal Aortic Aneurysms

Abdominal aortic aneurysms are a common condition of uncertain pathogenesis that can rupture if left untreated. Current recommended thresholds for planned repair are empirical and based entirely on diameter. It has been observed that some aneurysms rupture before reaching the threshold for repair whilst other larger aneurysms do not rupture. It is likely that geometry is not the only factor influencing rupture risk. Biomechanical indices aiming to improve and personalise rupture risk prediction require, amongst other things, knowledge of the material properties of the tissue and realistic constitutive models. These depend on the composition and organisation of the vessel wall which has been shown to undergo drastic changes with aneurysmal degeneration, with loss of elastin, smooth muscle cells, and an accumulation of isotropically arranged collagen. Most aneurysms are lined with intraluminal thrombus, which has an uncertain effect on the underlying vessel wall, with some authors demonstrating a reduction in wall stress and others a reduction in wall strength. The majority of studies investigating biomechanical properties of ex vivo abdominal aortic aneurysm tissues have used low-resolution techniques, such as tensile testing, able to measure the global material properties at the macroscale. High-resolution engineering techniques such as nanoindentation and atomic force microscopy have been modified for use in soft biological tissues and applied to vascular tissues with promising results. These techniques have the potential to advance the understanding and improve the management of abdominal aortic aneurysmal disease.

Microscopic multifrequency magnetic resonance elastography of ex vivo abdominal aortic aneurysms for extracellular matrix imaging in a mouse model

An abdominal aortic aneurysm (AAA) is a permanent dilatation of the abdominal aorta, usually accompanied by thrombus formation. The current clinical imaging modalities cannot reliably visualize the thrombus composition. Remodeling of the extracellular matrix (ECM) during AAA development leads to stiffness changes, providing a potential imaging marker. 14 apolipoprotein E-deficient mice underwent surgery for angiotensin II-loaded osmotic minipump implantation. 4 weeks post-op, 5 animals developed an AAA. The aneurysm was imaged ex vivo by microscopic multifrequency magnetic resonance elastography (µMMRE) with an in-plane resolution of 40 microns. Experiments were performed on a 7-Tesla preclinical magnetic resonance imaging scanner with drive frequencies between 1000 Hz and 1400 Hz. Shear wave speed (SWS) maps indicating stiffness were computed based on tomoelastography multifrequency inversion. As control, the aortas of 5 C57BL/6J mice were examined with the same imaging protocol. The regional variation of SWS in the thrombus ranging from 0.44 ± 0.07 to 1.20 ± 0.31 m/s was correlated fairly strong with regional histology-quantified ECM accumulation (R² = 0.79). Our results suggest that stiffness changes in aneurysmal thrombus reflect ECM remodeling, which is critical for AAA risk assessment. In the future, µMMRE could be used for a mechanics-based clinical characterization of AAAs in patients. STATEMENT OF SIGNIFICANCE: To our knowledge, this is the first study mapping the stiffness of abdominal aortic aneurysms with microscopic resolution of 40 µm. Our work revealed that stiffness critically changes due to extracellular matrix (ECM) remodeling in the aneurysmal thrombus. We were able to image various levels of ECM remodeling in the aneurysm reflected in distinct shear wave speed patterns with a strong correlation to regional histology-quantified ECM accumulation. The generated results are significant for the application of microscopic multifrequency magnetic resonance elastography for quantification of pathological remodeling of the ECM and may be of great interest for detailed characterization of AAAs in patients.

The risk of rupture and abdominal aortic aneurysm morphology: A computational study

Prediction of rupture and optimal timing for abdominal aortic aneurysm (AAA) surgical intervention remain wanting even after decades of clinical, histological, and numerical research. Although studies estimating rupture from AAA geometrical features from CT imaging showed some promising results, they are still not being used in practice. Patient-specific numerical stress analysis introduced too many assumptions about wall structure for the related rupture potential index (RPI) to be considered reliable. Growth and remodeling (G&R) numerical models eliminate some of these assumptions and thus might have the most potential to calculate mural stresses and RPI and increase our understanding of rupture. To recognize numerical models as trustworthy, it is necessary to validate the computed results with results derived from imaging. Elastin degradation function is one of the main factors that determine idealized aneurysm sac shape. Using a hundred different combinations of variables defining AAA geometry or influences AAA stability (elastin degradation function parameters, collagen mechanics, and initial healthy aortic diameters), we investigated the relationship between AAA morphology and RPI and compared numerical results with clinical findings. Good agreement of numerical results with clinical expectations from the literature gives us confidence in the validity of the numerical model. We show that aneurysm morphology significantly influences the stability of aneurysms. Additionally, we propose new parameters, geometrical rupture potential index (GRPI) and normalized aneurysm length (NAL), that might predict rupture of aneurysms without thrombus better than currently used criteria (i.e., maximum diameter and growth rate). These parameters can be computed quickly, without the tedious processing of CT images.

On stress in abdominal aortic aneurysm: Linear versus non-linear analysis and aneurysm rupture risk

We present comprehensive biomechanical analyses of abdominal aortic aneurysms (AAA) for 43 patients. We compare stress magnitudes and stress distributions within arterial walls of abdominal aortic aneurysms (AAA) obtained using two simulation and modelling methods: (a) Fully automated and computationally very efficient linear method embedded in the software platform Biomechanics based Prediction of Aneurysm Rupture Risk (BioPARR), freely available from https://bioparr.mech.uwa.edu.au/; (b) More complex and much more computationally demanding Non-Linear Iterative Stress Analysis (Non-LISA) that uses a non-linear inverse iterative approach and strongly non-linear material model. Both methods predicted localised high stress zones with over 90% of AAA model volume fraction subjected to stress below 20% of the 99th percentile maximum principal stress. However, for the non-linear iterative method, the peak maximum principal stress (and 99th percentile maximum principal stress) was higher and the stress magnitude in the low stress area lower than for the automated linear method embedded in BioPARR. Differences between the stress distributions obtained using the two methods tended to be particularly pronounced in the areas where the AAA curvature was large. Performance of the selected characteristic features of the stress fields (we used 99th percentile maximum principal stress) obtained using BioPARR and Non-LISA in distinguishing between the AAAs that would rupture and remain intact was for practical purposes the same for both methods.

Microstructural and mechanical characterization of the layers of human descending thoracic aortas

The mechanical properties of human aortas are linked to the layered tissue and its microstructure at different length scales. Each layer has specific mechanical and structural properties. While the ground substance and the elastin play an important role in tissue stiffness at small strain, collagen fibers carry most of the load at larger strains, which corresponds to the physiological conditions of the aorta at maximum pulsatile blood pressure. In fact, collagen fibers are crimped in the unloaded state. Collagen fibers show different orientation distributions when they are observed in a plane that is tangent to the aortic wall (in-plane section) or along a direction orthogonal to it (out-of-plane section). This was systematically investigated using large images (2500 × 2500 µm) with high resolution obtained by second harmonic generation (SHG) in order to homogenize tissue heterogeneity after a convergence analysis, which is a main goal of the study. In addition, collagen fibers show lateral interactions due to entanglements and the presence of transverse elastin fibers, observed on varying length scales using atomic force microscopy and a three-dimensional rendering obtained by stacking a sequence of SHG and two-photon fluorescence images; this is another important contribution. Human descending thoracic aortas from 13 heartbeat donors aged 28 to 66 years were examined. Uniaxial tensile tests were carried out on the longitudinal and circumferential strips of the aortic wall and the three separated layers (intima, media and adventitia). A structurally-motivated material model with (i) a term to describe the combined response of ground substance and elastin and (ii) terms to consider four families of collagen fibers with different directions was applied. The exclusion of compressed fibers was implemented in the fitting process of the experimental data, which was optimized by a genetic algorithm. The results show that a single fiber family with directional and dispersion parameters measured from SHG images can describe the mechanical response of all 39 layers (3 layers for each of the 13 aortas) with very good accuracy when a second (auxiliary) family of aligned fibers is introduced in the orthogonal direction to account for lateral fiber interaction. Indeed, all observed distributions of collagen directions can be accurately fitted by a single bivariate von Mises distribution. Statistical analysis of in-plane and out-of-plane dispersion of fiber orientations reveals structural differences between the three layers and a change of collagen dispersion parameters with age. STATEMENT OF SIGNIFICANCE: The stiffness of healthy young aortas is adjusted so that a diameter expansion of about 10 % is possible during the heartbeat. This creates the Windkessel effect, which smooths out the pulsating nature of blood flow and benefits organ perfusion. The specific elastic properties of the aorta that are required to achieve this effect are related to the microstructure of the aortic tissue at different length scales. An increase in the aortic stiffness, in addition to reducing cyclic expansion and worsening perfusion, is a risk factor for clinical hypertension. The present study relates the microstructure of healthy human aortas to the mechanical response and examines the changes in microstructural parameters with age, which is a key factor in increasing stiffness.

Design considerations for engineering 3D models to study vascular pathologies in vitro

Many cardiovascular diseases (CVD) are driven by pathological remodelling of blood vessels, which can lead to aneurysms, myocardial infarction, ischaemia and strokes. Aberrant remodelling is driven by changes in vascular cell behaviours combined with degradation, modification, or abnormal deposition of extracellular matrix (ECM) proteins. The underlying mechanisms that drive the pathological remodelling of blood vessels are multifaceted and disease specific; however, unravelling them may be key to developing therapies. Reductionist models of blood vessels created in vitro that combine cells with biomaterial scaffolds may serve as useful analogues to study vascular disease progression in a controlled environment. This review presents the main considerations for developing such in vitro models. We discuss how the design of blood vessel models impacts experimental readouts, with a particular focus on the maintenance of normal cellular phenotypes, strategies that mimic normal cell-ECM interactions, and approaches that foster intercellular communication between vascular cell types. We also highlight how choice of biomaterials, cellular arrangements and the inclusion of mechanical stimulation using fluidic devices together impact the ability of blood vessel models to mimic in vivo conditions. In the future, by combining advances in materials science, cell biology, fluidics and modelling, it may be possible to create blood vessel models that are patient-specific and can be used to develop and test therapies. STATEMENT OF SIGNIFICANCE: Simplified models of blood vessels created in vitro are powerful tools for studying cardiovascular diseases and understanding the mechanisms driving their progression. Here, we highlight the key structural and cellular components of effective models and discuss how including mechanical stimuli allows researchers to mimic native vessel behaviour in health and disease. We discuss the primary methods used to form blood vessel models and their limitations and conclude with an outlook on how blood vessel models that incorporate patient-specific cells and flows can be used in the future for personalised disease modelling.

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.

Arterial Stiffness Assessed by Cardio-Ankle Vascular Index in Patients With Abdominal Aortic Aneurysm and Its Alterations After Treatment

PURPOSE

The aim of the present study was to investigate a potential difference on the arterial stiffness among aneurysm patients and non-aneurysm controls, as well as to explore potential changes between patients treated either with endovascular or open repair.

MATERIALS AND METHODS

A 110 patients with an infrarenal AAA were prospectively enrolled in this study. Fifty-six patients received an EVAR, whereas 54 patients received an open surgical repair. Moreover, 103 gender and age-matched subjects without AAA served as controls. The cardio-ankle vascular index (CAVI) was applied for measurement of the arterial stiffness.

RESULTS

CAVI values were statistically higher in the AAA patients when compared with control subjects. Although at 48 hours postoperatively the CAVI values were increased in both groups when compared to baseline values, the difference in CAVI had a tendency to be higher in the open group compared to the endovascular group. At 6 months of follow up the CAVI values returned to the baseline for the patients of the open repair group. However, in the endovascular group CAVI values remained higher when compared with the baseline values.

CONCLUSION

Patients with AAAs demonstrated a higher value of CAVI compared to healthy controls. A significant increase of arterial stiffness in both groups during the immediate postoperative period was documented. The increase in arterial stiffness remained significant at 6 months in EVAR patients. Further studies are needed to elucidate the impact of a decreased aortic compliance after stentgraft implantation on the cardiac function of patients with AAA.

The Contribution of Glycosaminoglycans/Proteoglycans to Aortic Mechanics in Health and Disease: A Critical Review

While elastin and collagen have received a lot of attention as major contributors to aortic biomechanics, glycosaminoglycans (GAGs) and proteoglycans (PGs) recently emerged as additional key players whose roles must be better elucidated if one hopes to predict aortic ruptures caused by aneurysms and dissections more reliably. GAGs are highly negatively charged polysaccharide molecules that exist in the extracellular matrix (ECM) of the arterial wall. In this critical review, we summarize the current understanding of the contributions of GAGs/PGs to the biomechanics of the normal aortic wall, as well as in the case of aortic diseases such as aneurysms and dissections. Specifically, we describe the fundamental swelling behavior of GAGs/PGs and discuss their contributions to residual stresses and aortic stiffness, thereby highlighting the importance of taking these polyanionic molecules into account in mathematical and numerical models of the aorta. We suggest specific lines of investigation to further the acquisition of experimental data to complement simulations and solidify our current understanding. We underscore different potential roles of GAGs/PGs in thoracic aortic aneurysm (TAAD) and abdominal aortic aneurysm (AAA). Namely, we report findings according to which the accumulation of GAGs/PGs in TAAD causes stress concentrations which may be sufficient to initiate and propagate delamination. On the other hand, there seems to be no clear indication of a relationship between the marked reduction in GAG/PG content and the stiffening and weakening of the aortic wall in AAA.

In Vivo Aortic Magnetic Resonance Elastography in Abdominal Aortic Aneurysm: A Validation in an Animal Model

OBJECTIVES

Using maximum diameter of an abdominal aortic aneurysm (AAA) alone for management can lead to delayed interventions or unnecessary urgent repairs. Abdominal aortic aneurysm stiffness plays an important role in its expansion and rupture. In vivo aortic magnetic resonance elastography (MRE) was developed to spatially measure AAA stiffness in previous pilot studies and has not been thoroughly validated and evaluated for its potential clinical value. This study aims to evaluate noninvasive in vivo aortic MRE-derived stiffness in an AAA porcine model and investigate the relationships between MRE-derived AAA stiffness and (1) histopathology, (2) uniaxial tensile test, and (3) burst testing for assessing MRE's potential in evaluating AAA rupture risk.

MATERIALS AND METHODS

Abdominal aortic aneurysm was induced in 31 Yorkshire pigs (n = 226 stiffness measurements). Animals were randomly divided into 3 cohorts: 2-week, 4-week, and 4-week-burst. Aortic MRE was sequentially performed. Histopathologic analyses were performed to quantify elastin, collagen, and mineral densities. Uniaxial tensile test and burst testing were conducted to measure peak stress and burst pressure for assessing the ultimate wall strength.

RESULTS

Magnetic resonance elastography-derived AAA stiffness was significantly higher than the normal aorta. Significant reduction in elastin and collagen densities as well as increased mineralization was observed in AAAs. Uniaxial tensile test and burst testing revealed reduced ultimate wall strength. Magnetic resonance elastography-derived aortic stiffness correlated to elastin density (ρ = -0.68; P < 0.0001; n = 60) and mineralization (ρ = 0.59; P < 0.0001; n = 60). Inverse correlations were observed between aortic stiffness and peak stress (ρ = -0.32; P = 0.0495; n = 38) as well as burst pressure (ρ = -0.55; P = 0.0116; n = 20).

CONCLUSIONS

Noninvasive in vivo aortic MRE successfully detected aortic wall stiffening, confirming the extracellular matrix remodeling observed in the histopathologic analyses. These mural changes diminished wall strength. Inverse correlation between MRE-derived aortic stiffness and aortic wall strength suggests that MRE-derived stiffness can be a potential biomarker for clinically assessing AAA wall status and rupture potential.

Imaging Biological Pathways in Abdominal Aortic Aneurysms Using Positron Emission Tomography

[Figure: see text].

Design, Development, and Temporal Evaluation of a Magnetic Resonance Imaging-Compatible In Vitro Circulation Model Using a Compliant Abdominal Aortic Aneurysm Phantom

Biomechanical characterization of abdominal aortic aneurysms (AAAs) has become commonplace in rupture risk assessment studies. However, its translation to the clinic has been greatly limited due to the complexity associated with its tools and their implementation. The unattainability of patient-specific tissue properties leads to the use of generalized population-averaged material models in finite element analyses, which adds a degree of uncertainty to the wall mechanics quantification. In addition, computational fluid dynamics modeling of AAA typically lacks the patient-specific inflow and outflow boundary conditions that should be obtained by nonstandard of care clinical imaging. An alternative approach for analyzing AAA flow and sac volume changes is to conduct in vitro experiments in a controlled laboratory environment. In this study, we designed, built, and characterized quantitatively a benchtop flow loop using a deformable AAA silicone phantom representative of a patient-specific geometry. The impedance modules, which are essential components of the flow loop, were fine-tuned to ensure typical intraluminal pressure conditions within the AAA sac. The phantom was imaged with a magnetic resonance imaging (MRI) scanner to acquire time-resolved images of the moving wall and the velocity field inside the sac. Temporal AAA sac volume changes lead to a corresponding variation in compliance throughout the cardiac cycle. The primary outcome of this work was the design optimization of the impedance elements, the quantitative characterization of the resistive and capacitive attributes of a compliant AAA phantom, and the exemplary use of MRI for flow visualization and quantification of the deformed AAA geometry.

Mathematical model of atherosclerotic aneurysm

Atherosclerosis is a major cause of abdominal aortic aneurysm (AAA) and up to 80% of AAA patients have atherosclerosis. Therefore it is critical to understand the relationship and interactions between atherosclerosis and AAA to treat atherosclerotic aneurysm patients more effectively. In this paper, we develop a mathematical model to mimic the progression of atherosclerotic aneurysms by including both the multi-layer structured arterial wall and the pathophysiology of atherosclerotic aneurysms. The model is given by a system of partial differential equations with free boundaries. Our results reveal a 2D biomarker, the cholesterol ratio and DDR1 level, assessing the risk of atherosclerotic aneurysms. The efficacy of different treatment plans is also explored via our model and suggests that the dosage of anti-cholesterol drugs is significant to slow down the progression of atherosclerotic aneurysms while the additional anti-DDR1 injection can further reduce the risk.

Magnetic resonance elastography for estimating in vivo stiffness of the abdominal aorta using cardiac-gated spin-echo echo-planar imaging: a feasibility study

INTRODUCTION

Magnetic resonance elastography (MRE)-derived aortic stiffness is a potential biomarker for multiple cardiovascular diseases. Currently, gradient-recalled echo (GRE) MRE is a widely accepted technique to estimate aortic stiffness. However, multi-slice GRE MRE requires multiple breath-holds (BHs), which can be challenging for patients who cannot consistently hold their breath. The aim of this study was to investigate the feasibility of a multi-slice spin-echo echo-planar imaging (SE-EPI) MRE sequence for quantifying in vivo aortic stiffness using a free-breathing (FB) protocol and a single-BH protocol.

METHOD

On Scanner 1, 25 healthy subjects participated in the validation of FB SE-EPI against FB GRE. On Scanner 2, another 15 healthy subjects were recruited to compare FB SE-EPI with single-BH SE-EPI. Among all volunteers, five participants were studied on both scanners to investigate the inter-scanner reproducibility of FB SE-EPI aortic MRE. Bland-Altman analysis, Lin's concordance correlation coefficient (LCCC) and coefficient of variation (COV) were evaluated. The phase-difference signal-to-noise ratios (PD SNR) were compared.

RESULTS

Aortic MRE using FB SE-EPI and FB GRE yielded similar stiffnesses (paired t-test, P = 0.19), with LCCC = 0.97. The FB SE-EPI measurements were reproducible (intra-scanner LCCC = 0.96) and highly repeatable (LCCC = 0.99). The FB SE-EPI MRE was also reproducible across different scanners (inter-scanner LCCC = 0.96). Single-BH SE-EPI scans yielded similar stiffness to FB SE-EPI scans (LCCC = 0.99) and demonstrated a low COV of 2.67% across five repeated measurements.

CONCLUSION

Multi-slice SE-EPI aortic MRE using an FB protocol or a single-BH protocol is reproducible and repeatable with advantage over multi-slice FB GRE in reducing acquisition time. Additionally, FB SE-EPI MRE provides a potential alternative to BH scans for patients who have challenges in holding their breath.

The Association Between Curvature and Rupture in a Murine Model of Abdominal Aortic Aneurysm and Dissection

BACKGROUND

Mouse models of abdominal aortic aneurysm (AAA) and dissection have proven to be invaluable in the advancement of diagnostics and therapeutics by providing a platform to decipher response variables that are elusive in human populations. One such model involves systemic Angiotensin II (Ang-II) infusion into low density-lipoprotein receptor-deficient (LDLr-/-) mice leading to intramural thrombus formation, inflammation, matrix degradation, dilation, and dissection. Despite its effectiveness, considerable experimental variability has been observed in AAAs taken from our Ang-II infused LDLr-/- mice (n=12) with obvious dissection occurring in 3 samples, outer bulge radii ranging from 0.73 to 2.12 mm, burst pressures ranging from 155 to 540 mmHg, and rupture location occurring 0.05 to 2.53 mm from the peak bulge location.

OBJECTIVE

We hypothesized that surface curvature, a fundamental measure of shape, could serve as a useful predictor of AAA failure at supra-physiological inflation pressures.

METHODS

To test this hypothesis, we fit well-known biquadratic surface patches to 360° micro-mechanical test data and used Spearman's rank correlation (rho) to identify relationships between failure metrics and curvature indices.

RESULTS

We found the strongest associations between burst pressure and the maximum value of the first principal curvature (rho=-0.591, p-val=0.061), the maximum value of Mean curvature (rho=-0.545, p-val=0.087), and local values of Mean curvature at the burst location (rho=-0.864, p-val=0.001) with only the latter significant after Bonferroni correction. Additionally, the surface profile at failure was predominantly convex and hyperbolic (saddle-shaped) as indicated by a negative sign in the Gaussian curvature. Findings reiterate the importance of shape in experimental models of AAA.

Scannographic Study of Risk Factors of Abdominal Aortic Aneurysm Rupture

BACKGROUND

Current decision about when to operate abdominal aortic aneurysms (AAAs) is based only on the maximum aneurysm diameter (MAD). However, small aneurysms still rupture and we can observe very large AAA without any symptom. A simple morphologic analysis could be a tool to assess the risk of rupture. The main objective of this study was to assess the relevance of ratios between MAD and healthy aorta on computed tomography (CT) as a risk factor of AAA rupture. The secondary objective was to evaluate CT signs as risk factors of AAA rupture.

METHODS

Retrospective observational bicentric study comparing CT scans of a ruptured AAA group and a control group treated electively was conducted. Appariement 1:1 based on MAD was applied. Ratios between healthy aorta diameters at several levels, celiac trunk (CTR), superior mesenteric artery (SMA), highest renal artery (RA), and the MAD were calculated. The presence of blebs, crescent signs, ruptures of calcifications of the aneurysm sack, and draped aorta were notified.

RESULTS

From 2010 to 2016, 38 ruptured AAA and 38 controls were included. Ratios were superior in the rupture group, respectively: MAD/CTR [2.77 (±0.5) versus 2.58 (±0.4) P < 0.095], MAD/SMA [2.92 (±0.7) versus 2.74 (±0.5) P < 0.194], and MAD/RA [3.02 (±0.70) versus 2.76 (±0.5) P < 0.054] but not significatively. Receiver operating characteristic curve analysis demonstrated optimal threshold to detect rupture at 2.8 for the ratio MAD/CTR (area under the curve (AUC) 0.593, sensitivity 47.4%, specificity 78.9%), at 3.3 for the ratio MAD/SMA (AUC 0.564, sensitivity 31.6%, specificity 92.1%), and at 3.3 for the ratio MAD/RA (AUC 0.591, sensitivity 31.6%, specificity 94.7%). Bivariate analysis for rupture risk factor showed significance for the three ratios (MAD/CTR > 2.8 [OR = 11 (1.42; 85.20) P < 0.0217], MAD/SMA > 3.3 [OR = 10 (1.28; 78.12) P < 0.0281], and MAD/RA >3.3 [OR = 11.00 (1.42; 85.20) P < 0.0217]). One scannographic sign was more present in the rupture group: crescent sign 36.8% versus 5.3%, P = 0.0007, as well in bivariate analysis [OR = 7 (1.59; 30.80) P < 0.0326].

CONCLUSIONS

In our experience, specific ratios when they exceed calculated threshold, seem to be more prone to rupture. We could consider that these measures, easy to apply in clinical practice, would be complementary keys for rupture risk individual assessment.

Investigation of Pathophysiological Aspects of Aortic Growth, Remodeling, and Failure Using a Discrete-Fiber Microstructural Model

Aortic aneurysms are inherently unpredictable. One can never be sure whether any given aneurysm may rupture or dissect. Clinically, the criteria for surgical intervention are based on size and growth rate, but it remains difficult to identify a high-risk aneurysm, which may require intervention before the cutoff criteria, versus an aneurysm than can be treated safely by more conservative measures. In this work, we created a computational microstructural model of a medial lamellar unit (MLU) incorporating (1) growth and remodeling laws applied directly to discrete, individual fibers, (2) separate but interacting fiber networks for collagen, elastin, and smooth muscle, (3) active and passive smooth-muscle cell mechanics, and (4) failure mechanics for all three fiber types. The MLU model was then used to study different pathologies and microstructural anomalies that may play a role in vascular growth and failure. Our model recapitulated many aspects of arterial remodeling under hypertension with no underlying genetic syndrome including remodeling dynamics, tissue mechanics, and failure. Syndromic effects (smooth muscle cell (SMC) dysfunction or elastin fragmentation) drastically changed the simulated remodeling process, tissue behavior, and tissue strength. Different underlying pathologies were able to produce similarly dilatated vessels with different failure properties, providing a partial explanation for the imperfect nature of aneurysm size as a predictor of outcome.

A REVIEW OF THE MECHANICAL STRESSES PREDISPOSING ABDOMINAL AORTIC ANEURYSMAL RUPTURE: UNIAXIAL EXPERIMENTAL APPROACH

In this paper, problems concerning the uniaxial experimental investigation of the human abdominal aortic aneurysm (AAA) biomechanical characteristics, concomitant values of the associated Cauchy stress, failure (ultimate) stress in AAA, and the constitutive modeling of AAA are considered. The aim of this paper is to review and compare the disposable experimental data, to reveal the reasons for the high dissipation of the results between studies, and to propound some unification criteria. We examined 22 literature sources published between 1994 and 2017 and compared their results, including our own results. The experiments in the reviewed literature have been designed to obtain the stress–strain characteristics and the failure (ultimate) stress and strain of the aneurysmal tissue. A variety of forms of the strain–energy function (SEF) have been applied in the considered studies to model the biomechanical behavior of the aneurysmal wall. The specimen condition and physical parameters, the experimental protocols, the failure stress and strain, and SEFs differ between studies, contributing to the differences between the final results. We propound some criteria and suggestions for the unification of the experiments leading to the comparable results.

Minor aortic injury may be at risk of progression from uncontrolled shear stress: An in-vitro model demonstrates aortic lesion expansion

Background

Non-operative management is considered appropriate treatment for minor aortic injury, while blood pressure and anti-impulse therapy are routinely utilized to prevent higher grade aortic injury progression. However, a universal medical regimen for low grade intimal injuries has not been adopted and risks of low-grade injury progression not well described. The purpose of this study is to determine the fracture response of minimally damaged aortic tissue to the various applied forces. Our hypothesis is that internal circumferential shear within the aortic wall is a primary fracture mode. This knowledge may help guide clinical management to minimize risk of injury progression, including instituting standard medical regimens with anti-impulse therapy and β-blockade for such minor injuries.

Methods

Human ascending aortic tissue was obtained after aneurysm repair or heart transplant, stored at 4°C and tested within 48 hours. Minor injury was modeled with a small radial notch on the luminal aspect of aortic rings, circumferentially expanded under video acquisition and analyzed to determine lesion propagation.

Results

15 rings were obtained from 8 aneurysmal and 4 healthy aortas. All specimens demonstrated circumferential crack propagation. Propagation was longer (8.02 ± 5.92 mm vs 2.70 ± 1.23 mm) and initiation of crack propagation earlier in aneurysmal tissue (1.54 ± 0.17 versus 1.90 ± 0.17 times initial diameter).

Conclusions

Dilation of minimally injured aortic rings is associated with lesion expansion and injury progression in all specimens including healthy and aneurysmal tissue. This propagation illustrates the mechanical response to increased levels of internal shear, compromising structural integrity and increasing risk of aortic rupture in all injured aortas. Shear forces are routinely generated through normal circumferential aortic expansion with each pulsation, the magnitude of these forces determined by pulse and blood pressure. This suggests minor aortic injuries are not trivial and strategies to reduce shear stress be implemented in all such patients without contraindications to β- blockers.

Assessment of cardio-ankle vascular index in patients with abdominal aortic aneurysm: An observational study

OBJECTIVES

Arterial stiffness is associated with major adverse cardiovascular events. The aim of this study is to investigate arterial stiffness by cardio-ankle vascular index (CAVI) in patients with abdominal aortic aneurysm (AAA).

METHODS

This observational and cross-sectional study involved 59 subjects with AAA and 32 healthy subjects. All subjects underwent ultrasonography examination. CAVI was measured by VaSera-1000 CAVI instrument.

RESULTS

Mean abdominal aortic diameter of AAA patients and controls were 43.88 ± 9.28 mm and 20.43 ± 3.14 mm, consecutively. Baseline clinical characteristics of the patients and controls were similar for age, presence of hypertension, diabetes, dyslipidemia, coronary artery disease and smoking. Left ventricle ejection fraction and Left ventricle mass index (LVMI) were similar between groups. CAVI was significantly higher in patients with AAA than controls (9.74 ± 1.50 vs. 7.60 ± 1.07, p < 0.001). CAVI was positively correlated with AAA diameter (r = 0.461, p < 0.001) and negatively correlated with left ventricle ejection fraction (r= -0.254, p = 0.015). CAVI >8.3 had a sensitivity 89.8% and a specificity of 78.1% for predicting the presence of AAA in ROC analysis (area under curve = 0.897, 95%CI = 0.816-0.951, p < 0.001).

CONCLUSION

CAVI is increased in patients with AAA. Increased arterial stiffness may be a mechanical link between AAA, coronary artery disease and peripheral artery disease or a common mechanism effects the arterial stiffness, coronary artery disease, peripheral artery disease and AAA. Therefore, CAVI may be used as a valuable marker for risk stratification for the development of AAA in susceptible patients.

GSK2593074A blocks progression of existing abdominal aortic dilation

Objective

Receptor interacting proteins kinase 1 and 3 (RIPK1 and RIPK3) have been shown to play essential roles in the pathogenesis of abdominal aortic aneurysms (AAAs) by mediating necroptosis and inflammation. We previously discovered a small molecular inhibitor GSK2593074A (GSK’074) that binds to both RIPK1 and RIPK3 with high affinity and prevents AAA formation in mice. In this study, we evaluated whether GSK’074 can attenuate progression of existing AAA in the calcium phosphate model.

Methods

C57BL6/J mice were subjected to the calcium phosphate model of aortic aneurysm generation. Mice were treated with either GSK’074 (4.65 mg/kg/day) or dimethylsulfoxide (DMSO) controls starting 7 days after aneurysm induction. Aneurysm growth was monitored via ultrasound imaging every 7 days until harvest on day 28. Harvested aortas were examined via immunohistochemistry. The impact of GSK’074 on vascular smooth muscle cells and macrophages were evaluated via flow cytometry and transwell migration assay.

Results

At the onset of treatment, mice in both the control (DMSO) and GSK’074 groups showed similar degree of aneurysmal expansion. The weekly ultrasound imaging showed a steady aneurysm growth in DMSO-treated mice. The aneurysm growth was attenuated by GSK’074 treatment. At humane killing, GSK’074-treated mice had significantly reduced progression in aortic diameter from baseline as compared with the DMSO-treated mice (83.2% ± 13.1% [standard error of the mean] vs 157.2% ± 32.0% [standard error of the mean]; P < .01). In addition, the GSK’074-treated group demonstrated reduced macrophages (F4/80, CD206, MHCII), less gelatinase activity, a higher level of smooth muscle cell-specific myosin heavy chain, and better organized elastin fibers within the aortic walls compared with DMSO controls. In vitro, GSK’074 inhibited necroptosis in mouse aortic smooth muscle cells; whereas, it was able to prevent macrophage migration without affecting Il1b and Tnf expression.

Conclusions

GSK’074 is able to attenuate aneurysm progression in the calcium phosphate model. The ability to inhibit both vascular smooth muscle cell necroptosis and macrophage migration makes GSK’074 an attractive drug candidate for pharmaceutical treatment of aortic aneurysms.

Previous clinical trials evaluating pharmaceutical treatments in blocking aneurysm progression have failed. However, most agents used in those trials focused on inhibiting only one mechanism that contributes to aneurysm pathogenesis. In this study, we found GSK’074 is able to attenuate aneurysm progression in the calcium phosphate model by inhibiting both vascular smooth muscle cell necroptosis and macrophage migration, which are both key processes in the pathogenesis of aneurysm progression. The ability of GSK’0474 to inhibit multiple key pathologic mechanisms makes it an attractive therapeutic candidate for aneurysm progression.

Factor Xa Inhibition by Rivaroxaban Modified Mitochondrial-Associated Proteins in Human Abdominal Aortic Aneurysms

BACKGROUND

The presence of intraluminal thrombus and mitochondrial dysfunction in human abdominal aortic aneurysms (AAAs) have been associated with aneurysmal growth and rupture. The objective of the study was to study if endogenous factor Xa (FXa) may modulate mitochondrial functionality and expression of proteins associated with mitophagy in human AAAs.

METHODS

AAA sites with intraluminal thrombus were obtained from 6 patients undergoing elective AAA surgery repair. Control samples were collected from 6 organ donors. The effect of FXa was analyzed by in vitro incubation of AAA with 50 nmol/L rivaroxaban, an oral FXa inhibitor.

RESULTS

The enzymatic activities of citrate synthase, a biomarker of mitochondrial density, and cytochrome C oxidase, a biomarker of mitochondrial respiratory chain functionality, were significantly reduced in the AAA sites with respect to the healthy aorta (citrate synthase activity in μU/min/μg protein: control: 3.51 ± 0.22 vs. AAA: 0.37 ± 0.15.; P < 0.01; cytochrome C oxidase activity in μOD/min/μg protein: control: 8.05 ± 1.57 vs. AAA: 3.29 ± 1.05; P < 0.05). The addition of rivaroxaban to AAA reverted the activity of both citrate synthase and cytochrome C oxidase to similar values to control. Mitochondrial Drp-1 expression was higher in AAA sites than in either control aortas or rivaroxaban-incubated AAA sites. Cytosolic content of Drp-1 phosphorylated at Ser637, mitochondrial Parkin, and mitochondrial PINK1-Parkin interaction were significantly reduced in the AAA sites with respect to control aortas. For all these parameters, rivaroxaban-incubated AAA showed similar values compared with control aortas.

CONCLUSIONS

In human AAA, rivaroxaban improved mitochondrial functionality that was associated with changes in proteins related to mitophagy. Its opens possible new effects of endogenous FXa on the mitochondria in the human AAA site.

Caloric Restriction Exacerbates Angiotensin II-Induced Abdominal Aortic Aneurysm in the Absence of p53

p53-dependent vascular smooth muscle cell senescence is a key pathological process of abdominal aortic aneurysm (AAA). Caloric restriction (CR) is a nonpharmacological intervention that prevents AAA formation. However, whether p53 is indispensable to the protective role of CR remains unknown. In this study, we investigated the necessity of p53 in the beneficial role of CR in AAA formation and the underlying mechanisms. We subjected p53^+/+ and p53^-/- mice to 12 weeks of CR and then examined the incidence of Ang II (angiotensin II)-induced AAA formation. We found that both CR and p53 knockout reduced Ang II-induced AAA formation; however, CR markedly increased the incidence of AAA formation and exacerbated aortic elastin degradation in p53^-/- mice, accompanied by increased vascular senescence, reactive oxygen species generation, and reduced energy production. Analysis of mitochondrial respiratory activity revealed that dysfunctional complex IV accounts for the abnormal mitochondrial respiration in p53^-/- vascular smooth muscle cells treated by CR serum. Mechanistically, ablation of p53 almost totally blocked the protective role of CR by inhibiting SCO2 (cytochrome C oxidase assembly protein 2)-dependent mitochondrial complex IV activity. Overexpression of SCO2 restored the beneficial effect of CR on antagonizing Ang II-induced expression of AAA-related molecules and reactive oxygen species generation in p53^-/- vascular smooth muscle cells. Together, our findings demonstrate that the existence of p53 in vascular smooth muscle cells is critical to the protective role of CR in Ang II-induced AAA formation by maintaining an appropriate mitochondrial function.

The Effect of Pentagalloyl Glucose on the Wall Mechanics and Inflammatory Activity of Rat Abdominal Aortic Aneurysms

An abdominal aortic aneurysm (AAA) is a permanent localized expansion of the abdominal aorta with mortality rate of up to 90% after rupture. AAA growth is a process of vascular degeneration accompanied by a reduction in wall strength and an increase in inflammatory activity. It is unclear whether this process can be intervened to attenuate AAA growth, and hence, it is of great clinical interest to develop a technique that can stabilize the AAA. The objective of this work is to develop a protocol for future studies to evaluate the effects of drug-based therapies on the mechanics and inflammation in rodent models of AAA. The scope of the study is limited to the use of pentagalloyl glucose (PGG) for aneurysm treatment in the calcium chloride rat AAA model. Peak wall stress (PWS) and matrix metalloproteinase (MMP) activity, which are the biomechanical and biological markers of AAA growth and rupture, were evaluated over 4 weeks in untreated and treated (with PGG) groups. The AAA specimens were mechanically characterized by planar biaxial tensile testing and the data fitted to a five-parameter nonlinear, hyperelastic, anisotropic Holzapfel–Gasser–Ogden (HGO) material model, which was used to perform finite element analysis (FEA) to evaluate PWS. Our results demonstrated that there was a reduction in PWS between pre- and post-AAA induction FEA models in the treatment group compared to the untreated group using either animal-specific or average material properties. However, this reduction was not statistically significant. Conversely, there was a statistically significant reduction in MMP-activated fluorescent signal between pre- and post-AAA induction models in the treated group compared to the untreated group. Therefore, the primary contribution of this work is the quantification of the stabilizing effects of PGG using biomechanical and biological markers of AAA, thus indicating that PGG could be part of a new clinical treatment strategy that will require further investigation.

Sensitivity of Arterial Hyperelastic Models to Uncertainties in Stress-Free Measurements

Despite major advances made in modeling vascular tissue biomechanics, the predictive power of constitutive models is still limited by uncertainty of the input data. Specifically, key measurements, like the geometry of the stress-free (SF) state, involve a definite, sometimes non-negligible, degree of uncertainty. Here, we introduce a new approach for sensitivity analysis of vascular hyperelastic constitutive models to uncertainty in SF measurements. We have considered two vascular hyperelastic models: the phenomenological Fung model and the structure-motivated Holzapfel-Gasser-Ogden (HGO) model. Our results indicate up to 160% errors in the identified constitutive parameters for a 5% measurement uncertainty in the SF data. Relative margins of errors of up to 30% in the luminal pressure, 36% in the axial force, and over 200% in the stress predictions were recorded for 10% uncertainties. These findings are relevant to the large body of studies involving experimentally based modeling and analysis of vascular tissues. The impact of uncertainties on calibrated constitutive parameters is significant in context of studies that use constitutive parameters to draw conclusions about the underlying microstructure of vascular tissues, their growth and remodeling processes, and aging and disease states. The propagation of uncertainties into the predictions of biophysical parameters, e.g., force, luminal pressure, and wall stresses, is of practical importance in the design and execution of clinical devices and interventions. Furthermore, insights provided by the present findings may lead to more robust parameters identification techniques, and serve as selection criteria in the trade-off between model complexity and sensitivity.

Automatic Segmentation, Detection, and Diagnosis of Abdominal Aortic Aneurysm (AAA) Using Convolutional Neural Networks and Hough Circles Algorithm

PURPOSE

An abdominal aortic aneurysm (AAA) is known as a cardiovascular disease involving localized deformation (swelling or enlargement) of aorta occurring between the renal and iliac arteries. AAA would jeopardize patients' lives due to its rupturing risk, so prompt recognition and diagnosis of this disorder is vital. Although computed tomography angiography (CTA) is the preferred imaging modality used by radiologist for diagnosing AAA, computed tomography (CT) images can be used too. In the recent decade, there has been several methods suggested by experts in order to find a precise automated way to diagnose AAA without human intervention base on CT and CTA images. Despite great approaches in some methods, most of them need human intervention and they are not fully automated. Also, the error rate needs to decrease in other methods. Therefore, finding a novel fully automated with lower error rate algorithm using CTA and CT images for Abdominal region segmentation, AAA detection, and disease severity classification is the main goal of this paper.

METHODS

The proposed method in this article will be performed in three steps: (1) designing a classifier based on Convolutional Neural Network (CNN) for classifying different parts of abdominal into four different classes such as: abdominal inside region, aorta, body border, and bone. (2) After correct aorta detection, defining its edge and measuring its diameter with the use of Hough Circle Algorithm (which is an algorithm for finding an arbitrary shape in images and measuring its diameter in pixel) is the second step. (3) Ultimately, the detected aorta, depending on its diameter, will be categorized in one of these groups: (a) there is no risk of AAA, (b) there is a medium risk of AAA, and (c) there is a high risk of AAA.

RESULTS

The designed CNN classifier classifies different parts of abdominal into four different classes such as: abdominal inside region, aorta, body border, and bone with the accuracy, precision, and sensitivity of 97.93, 97.94, and 97.93% respectively. The accuracy of the proposed classifier for aorta region detection is 98.62% and Hough Circles algorithm can classify 120 aorta patches according to their diameter with accuracy of 98.33%.

CONCLUSIONS

As a whole, a classifier using Convolutional Neural Network is designed and applied in order to detect AAA region among other abdominal regions. Then Hough Circles algorithm is applied to aorta patches for finding aorta border and measuring its diameter. Ultimately, the detected aortas will be categorized according to their diameters. All steps meet the expected results.

The role of tissue remodeling in mechanics and pathogenesis of abdominal aortic aneurysms

Arterial walls can be regarded as composite materials consisting of collagen fibers embedded in an elastic matrix and smooth muscle cells. Remodeling of the structural proteins has been shown to play a significant role in the mechanical behavior of walls during pathogenesis of abdominal aortic aneurysms (AAA). In this study, we systematically studied the change in the microstructure, histology and mechanics to link them to AAA disease progression. We performed biaxial extension tests, second-harmonic generation imaging and histology on 15 samples from the anterior part of AAA walls harvested during open aneurysm surgery. Structural data were gained by fitting to a bivariate von Mises distribution and yielded the mean fiber direction and in- and out-of-plane fiber dispersions of collagen. Mechanical and structural data were fitted to a recently proposed material model. Additionally, the mechanical data were used to derive collagen recruitment points in the obtained stress-stretch curves. We derived 14 parameters from histology such as smooth muscle cell-, elastin-, and abluminal adipocyte content. In total, 22 parameters were obtained and statistically evaluated. Based on the collagen recruitment points we were able to define three different stages of disease progression. Significant differences in elastin content, collagen orientation and adipocyte contents were discovered. Nerves entrapped inside AAA walls pointed towards a significant deposition of newly formed collagen abluminally, which we propose as neo-adventitia formation. We were able to discriminate two types of remodeled walls with a high collagen content - potentially safe and possibly vulnerable walls with a high adipocyte content inside the wall and significant amounts of inflammation. The study yielded a hypothesis for disease progression, derived from the systematic comparison of mechanical, microstructural and histological changes in AAAs. STATEMENT OF SIGNIFICANCE: Remodeling of the structural proteins plays an important role in the mechanical behavior of walls during pathogenesis of abdominal aortic aneurysms (AAA). We analyzed changes in the microstructure, histology and biomechanics of 15 samples from the anterior part of AAA walls and, for the first time, linked the results to three different stages of disease progression. We identified significant differences in elastin content, collagen orientation, adipocyte contents, and also a deposition of newly formed collagen forming a neoadventitia. We could discriminate two types of remodeled walls: (i) potentially safe and (ii) possibly vulnerable associated with inflammation and a high amount of adipocytes.

Effect of Local Neck Anatomy on Localized One-Dimensional Measurements of Arterial Stiffness: A Finite-Element Model Study

Cardiovascular diseases (CVD) are the most prevalent cause of death in the Western World, and their prevalence is only expected to rise. Several screening modalities aim at detecting CVD at the early stages. A common target for early screening is common carotid artery (CCA) stiffness, as reflected in the pulse wave velocity (PWV). For assessing the CCA stiffness using ultrasound (US), one-dimensional (1D) measurements along the CCA axis are typically used, ignoring possible boundary conditions of neck anatomy and the US probe itself. In this study, the effect of stresses and deformations induced by the US probe, and the effect of anatomy surrounding CCA on a simulated 1D stiffness measurement (PWVus) is compared with the ground truth stiffness (PWVgt) in 60 finite-element models (FEM) derived from anatomical computed tomography (CT) scans of ten healthy male volunteers. Based on prior knowledge from the literature, and from results in this study, we conclude that it is safe to approximate arterial stiffness using 1D measurements of compliance or pulse wave velocity, regardless of boundary conditions emerging from the anatomy or from the measurement procedure.

Role of Noncoding RNAs in the Pathogenesis of Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a local dilatation of the abdominal aortic vessel wall and is among the most challenging cardiovascular diseases as without urgent surgical intervention, ruptured AAA has a mortality rate of >80%. Most patients present acutely after aneurysm rupture or dissection from a previously asymptomatic condition and are managed by either surgery or endovascular repair. Patients usually are old and have other concurrent diseases and conditions, such as diabetes mellitus, obesity, and hypercholesterolemia making surgical intervention more difficult. Collectively, these issues have driven the search for alternative methods of diagnosing, monitoring, and treating AAA using therapeutics and less invasive approaches. Noncoding RNAs-short noncoding RNAs (microRNAs) and long-noncoding RNAs-are emerging as new fundamental regulators of gene expression. Researchers and clinicians are aiming at targeting these microRNAs and long noncoding RNAs and exploit their potential as clinical biomarkers and new therapeutic targets for AAAs. While the role of miRNAs in AAA is established, studies on long-noncoding RNAs are only beginning to emerge, suggesting their important yet unexplored role in vascular physiology and disease. Here, we review the role of noncoding RNAs and their target genes focusing on their role in AAA. We also discuss the animal models used for mechanistic understanding of AAA. Furthermore, we discuss the potential role of microRNAs and long noncoding RNAs as clinical biomarkers and therapeutics.

Cardiovascular magnetic resonance elastography: A review

Cardiovascular diseases are the leading cause of death worldwide. These cardiovascular diseases are associated with mechanical changes in the myocardium and aorta. It is known that stiffness is altered in many diseases, including the spectrum of ischemia, diastolic dysfunction, hypertension and hypertrophic cardiomyopathy. In addition, the stiffness of the aortic wall is altered in multiple diseases, including hypertension, coronary artery disease and aortic aneurysm formation. For example, in diastolic dysfunction in which the ejection fraction is preserved, stiffness can potentially be an important biomarker. Similarly, in aortic aneurysms, stiffness can provide valuable information with regard to rupture potential. A number of studies have addressed invasive and non-invasive approaches to test and measure the mechanical properties of the myocardium and aorta. One of the non-invasive approaches is magnetic resonance elastography (MRE). MRE is a phase-contrast magnetic resonance imaging technique that measures tissue stiffness non-invasively. This review article highlights the technical details and application of MRE in the quantification of myocardial and aortic stiffness in different disease states.