Use of Regional Mechanical Properties of Abdominal Aortic Aneurysms to Advance Finite Element Modeling of Rupture Risk

On the Material Constitutive Behavior of the Aortic Root in Patients with Transcatheter Aortic Valve Implantation

BACKGROUND

Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure used to treat patients with severe aortic valve stenosis. However, there is limited knowledge on the material properties of the aortic root in TAVI patients, and this can impact the credibility of computer simulations. This study aimed to develop a non-invasive inverse approach for estimating reliable material constituents for the aortic root and calcified valve leaflets in patients undergoing TAVI.

METHODS

The identification of material parameters is based on the simultaneous minimization of two cost functions, which define the difference between model predictions and cardiac-gated CT measurements of the aortic wall and valve orifice area. Validation of the inverse analysis output was performed comparing the numerical predictions with actual CT shapes and post-TAVI measures of implanted device diameter.

RESULTS

A good agreement of the peak systolic shape of the aortic wall was found between simulations and imaging, with similarity index in the range in the range of 83.7% to 91.5% for n.20 patients. Not any statistical difference was observed between predictions and CT measures of orifice area for the stenotic aortic valve. After TAVI simulations, the measurements of SAPIEN 3 Ultra (S3) device diameter were in agreement with those from post-TAVI angio-CT imaging. A sensitivity analysis demonstrated a modest impact on the S3 diameters when altering the elastic material property of the aortic wall in the range of inverse analysis solution.

CONCLUSIONS

Overall, this study demonstrates the feasibility and potential benefits of using non-invasive imaging techniques and computational modeling to estimate material properties in patients undergoing TAVI.

Artificial intelligence framework to predict wall stress in abdominal aortic aneurysm

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their risk of rupture - which is the 13th leading cause of death in the US - exceeds the risks associated with repair. Clinical intervention occurs when an aneurysm diameter exceeds 5.5 cm, but this "one-size fits all" criterion is insufficient, as it has been reported thatup to a quarter of AAA smaller than 5.5 cm do rupture. Therefore, there is a need for a more reliable, patient-specific, clinical tool to aide in the management of AAA. Biomechanical assessment of AAA is thought to provide critical physical insights to rupture risk, but clinical translataion of biomechanics-based tools has been limited due to the expertise, time, and computational requirements. It was estimated that through 2015, only 348 individual AAA cases have had biomechanical stress analysis performed, suggesting a deficient sample size to make such analysis relevant in the clinic. Artificial intelligence (AI) algorithms offer the potential to increase the throughput of AAA biomechanical analyses by reducing the overall time required to assess the wall stresses in these complex structures using traditional methods. This can be achieved by automatically segmenting regions of interest from medical images and using machine learning models to predict wall stresses of AAA. In this study, we present an automated AI-based methodology to predict the biomechanical wall stresses for individual AAA. The predictions using this approach were completed in a significantly less amount of time compared to a more traditional approach (~4 hours vs 20 seconds).

Assessment of the regional distribution of normalized circumferential strain in the thoracic and abdominal aorta using DENSE cardiovascular magnetic resonance

BACKGROUND

Displacement Encoding with Stimulated Echoes (DENSE) cardiovascular magnetic resonance (CMR) of the aortic wall offers the potential to improve patient-specific diagnostics and prognostics of diverse aortopathies by quantifying regionally heterogeneous aortic wall strain in vivo. However, before regional mapping of strain can be used to clinically assess aortic pathology, an evaluation of the natural variation of normal regional aortic kinematics is required.

METHOD

Aortic spiral cine DENSE CMR was performed at 3 T in 30 healthy adult subjects (range 18 to 65 years) at one or more axial locations that are at high risk for aortic aneurysm or dissection: the infrarenal abdominal aorta (IAA, n = 11), mid-descending thoracic aorta (DTA, n = 17), and/or distal aortic arch (DAA, n = 11). After implementing custom noise-reduction techniques, regional circumferential Green strain of the aortic wall was calculated across 16 sectors around the aortic circumference at each location and normalized by the mean circumferential strain for comparison between individuals.

RESULTS

The distribution of normalized circumferential strain (NCS) was heterogeneous for all locations evaluated. Despite large differences in mean strain between subjects, comparisons of NCS revealed consistent patterns of strain distribution for similar groupings of patients by axial location, age, and/or mean displacement angle. NCS at local systole was greatest in the lateral/posterolateral walls in the IAAs (1.47 ± 0.27), medial wall in anteriorly displacing DTAs (1.28 ± 0.20), lateral wall in posteriorly displacing DTAs (1.29 ± 0.29), superior curvature in DAAs < 50 years-old (1.93 ± 0.22), and medial wall in DAAs > 50 years (2.29 ± 0.58). The distribution of strain was strongly influenced by the location of the vertebra and other surrounding structures unique to each location.

CONCLUSIONS

Regional in vivo circumferential strain in the adult aorta is unique to each axial location and heterogeneous around its circumference, but can be grouped into consistent patterns defined by basic patient-specific metrics following normalization. The heterogeneous strain distributions unique to each group may be due to local peri-aortic constraints (particularly at the aorto-vertebral interface), heterogeneous material properties, and/or heterogeneous flow patterns. These results must be carefully considered in future studies seeking to clinically interpret or computationally model patient-specific aortic kinematics.

Demonstration of circumferential heterogeneity in displacement and strain in the abdominal aortic wall by spiral cine DENSE MRI

BACKGROUND

Knowledge of tissue properties of the abdominal aorta can improve understanding of vascular disease and guide interventional approaches. Existing MRI methods to quantify aortic wall displacement and strain are unable to discern circumferential heterogeneity.

PURPOSE

To assess regional variation in abdominal aortic wall displacement and strain as a function of circumferential position using spiral cine displacement encoding with stimulated echoes (DENSE).

STUDY TYPE

Prospective.

POPULATION

Cardiovascular disease-free men (n = 8) and women (n = 9) ages 30-42.

SEQUENCES

Prospective electrocardiogram (ECG)-gated and navigator echo-gated spiral, cine 2D DENSE and retrospective ECG-gated phase contrast MR (PCMR) sequences at 3T.

ASSESSMENT

In-plane displacement values of the aortic wall acquired with DENSE were used to determine radial and circumferential aortic wall motion. A quadrilateral-based 2D strain calculation method was implemented to determine strain from the displacement field. Peak displacement and its radial and circumferential contributions as well as peak circumferential strain were compared among eight circumferential wall segments. Distensibility was calculated using PCMR and compared with homogenized circumferential strain.

STATISTICAL TESTS

To account for repeated measurements in volunteers, linear mixed models for mean sector values were created for displacement magnitude, circumferential displacement, radial displacement, and circumferential strain. Comparisons were made between sectors. Calculated distensibility and homogenized circumferential strain were compared using Bland-Altman analysis. Statistical significance was defined as P < 0.05.

RESULTS

Displacement was highest in the anterior wall (1.5 ± 0.7 mm) and was primarily in the radial as compared with circumferential direction (1.04 ± 0.05 mm vs. 0.81 ± 0.42 mm). Circumferential strain was highest in the lateral walls (left 0.16 ± 0.05 and right 0.21 ± 0.12) with homogenized circumferential strain of 0.14 ± 0.05.

DATA CONCLUSION

DENSE imaging in the abdominal aortic wall demonstrated that the anterior aortic wall exhibits the greatest displacement, while the lateral wall experiences the largest circumferential strain.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:731-743.

Additional value of biomechanical indices based on CTa for rupture risk assessment of abdominal aortic aneurysms

OBJECTIVE

Biomechanics for rupture risk prediction in abdominal aortic aneurysms (AAA) are gaining popularity. However, their clinical applicability is still doubtful as there is lack of standardization. This study evaluates the added value of biomechanical indices in rupture risk assessment.

METHODS

This study included 175 asymptomatic, 11 sAAA and 45 ruptured aneurysms. 3D-geometries were reconstructed using computer tomography angiographies. Subsequently, finite element models were made to calculate peak wall stress (PWS), peak wall rupture index (PWRI) and the rupture risk equivalent diameter (RRED). The indices were determined with a dedicated software to facilitate standardization.

RESULTS

SAAAs showed a trend towards higher PWS, PWRI and RRED compared to asymptomatic AAAs, but PWS (22.0±5.8 vs. 33.4±15.8 N/cm2), PWRI (0.52±0.2 vs. 1.01±0.64), and RRED (65±60 vs. 98±51 mm) were significantly (p = 0.001) higher in ruptured. However, after diameter-matching no significant differences were seen. The ROC-curves for the maximum diameter and all biomechanical indices were similar but it slightly increased when diameter and biomechanical indices were combined.

CONCLUSIONS

This study showed no added value for biomechanical indices in AAA rupture risk assessment. Additionally, the difficulty of such an assessment increases. However, as symptomatic aneurysms show a trend towards higher biomechanical indices with similar diameters the indices may provide information about aneurysm growth and development.

In vivo quantification of regional circumferential Green strain in the thoracic and abdominal aorta by 2D spiral cine DENSE MRI

INTRODUCTION

Regional tissue mechanics play a fundamental role in patient-specific cardiovascular function. Nevertheless, regional assessments of aortic kinematics remain lacking due to the challenge of imaging the thin aortic wall. Herein, we present a novel application of DENSE (Displacement Encoding with Stimulated Echoes) MRI to quantify the circumferential Green strain of the thoracic and abdominal aorta.

METHODS

2D spiral cine DENSE and steady-state free procession (SSFP) cine images were acquired at 3T at the infrarenal aorta (IAA), descending thoracic aorta (DTA), or distal aortic arch (DAA) in a pilot study of 6 healthy volunteers. DENSE data was processed with multiple custom noise-reduction techniques to calculate circumferential Green strain across 16 equispaced sectors around the aorta. Each volunteer was scanned twice to evaluate interstudy repeatability.

RESULTS

Circumferential strain was heterogeneously distributed in all volunteers and locations. Spatial heterogeneity index by location was 0.37 (IAA), 0.28 (DTA), and 0.59 (DAA). Mean peak strain by DENSE for each cross-section was consistent with the homogenized linearized strain estimated from SSFP cine. The mean difference in peak strain across all sectors following repeat imaging was -0.1±2.2%, with a mean absolute difference of 1.7%.

CONCLUSIONS

Aortic cine DENSE MRI is a viable non-invasive technique for quantifying heterogeneous regional aortic wall strain and has significant potential to improve patient-specific clinical assessments of numerous aortopathies, as well as to provide the lacking spatiotemporal data required to refine computational models of aortic growth and remodeling.

Toward modeling the effects of regional material properties on the wall stress distribution of abdominal aortic aneurysms

The overall geometry and different biomechanical parameters of an abdominal aortic aneurysm (AAA), contribute to its severity and risk of rupture, therefore they could be used to track its progression. Previous and ongoing research efforts have resorted to using uniform material properties to model the behavior of AAA. However, it has been recently illustrated that different regions of the AAA wall exhibit different behavior due to the effect of the biological activities in the metalloproteinase matrix that makes up the wall at the aneurysm site. In this work, we introduce a non-invasive patient-specific regional material property model to help us better understand and investigate the AAA wall stress distribution, peak wall stress (PWS) severity, and potential rupture risk. Our results indicate that the PWS and the overall wall stress distribution predicted using the proposed regional material property model, are higher than those predicted using the traditional homogeneous, hyper-elastic model (p <1.43E-07). Our results also show that to investigate AAA, the overall geometry, presence of intra-luminal thrombus (ILT), and loading condition in a patient specific manner may be critical for capturing the biomechanical complexity of AAAs.

Histology and Biaxial Mechanical Behavior of Abdominal Aortic Aneurysm Tissue Samples

Abdominal aortic aneurysms (AAAs) represent permanent, localized dilations of the abdominal aorta that can be life-threatening if progressing to rupture. Evaluation of risk of rupture depends on understanding the mechanical behavior of patient AAA walls. In this project, a series of patient AAA wall tissue samples have been evaluated through a combined anamnestic, mechanical, and histopathologic approach. Mechanical properties of the samples have been characterized using a novel, strain-controlled, planar biaxial testing protocol emulating the in vivo deformation of the aorta. Histologically, the tissue ultrastructure was highly disrupted. All samples showed pronounced mechanical stiffening with stretch and were notably anisotropic, with greater stiffness in the circumferential than the axial direction. However, there were significant intrapatient variations in wall stiffness and stress. In biaxial tests in which the longitudinal stretch was held constant at 1.1 as the circumferential stretch was extended to 1.1, the maximum average circumferential stress was 330 ± 70 kPa, while the maximum average axial stress was 190 ± 30 kPa. A constitutive model considering the wall as anisotropic with two preferred directions fit the measured data well. No statistically significant differences in tissue mechanical properties were found based on patient gender, age, maximum bulge diameter, height, weight, body mass index, or smoking history. Although a larger patient cohort is merited to confirm these conclusions, the project provides new insight into the relationships between patient natural history, histopathology, and mechanical behavior that may be useful in the development of accurate methods for rupture risk evaluation.

[Contribution of mathematical models and biomechanical properties in predicting the risk of abdominal aortic aneurysm rupture]

INTRODUCTION

Rupture is the worst outcome of abdominal aortic aneurysm (AAA). The decision to operate should include counterbalancing the risk of aneurysm rupture against the risk of aneurysm repair, within the context of a patient's overall life expectancy. Current surgical guidelines are based on population studies, and important variables are missed in predicting individual risk of rupture.

METHODS

In this literature review, we focused on the contribution of biomechanical and mathematical models in predicting risk of AAA rupture.

RESULTS

Anatomical features as diameter asymmetry and lack of tortuosity are shown to be anatomical risk factors of rupture. Wall stiffness (due to modifications of elastin and collagen composition) and increased inflammatory response are also factors that affect the structural integrity of the AAA wall. Biomechanical studies showed that wall strength is lower in ruptured than non-ruptured AAA. Intra-luminal thrombus also has a big role to play in the occurrence of rupture. Current mathematical models allow more variables to be included in predicting individual risk of rupture.

CONCLUSION

Moving away from using maximal transverse diameter of the AAA as a unique predictive factor and instead including biological, structural and biomechanical variables in predicting individual risk of rupture will be essential in the future and will help gain precision and accuracy in surgical indications.

Progression of abdominal aortic aneurysm towards rupture: refining clinical risk assessment using a fully coupled fluid-structure interaction method

Rupture of abdominal aortic aneurysm (AAA) is associated with high mortality rates. Risk of rupture is multi-factorial involving AAA geometric configuration, vessel tortuosity, and the presence of intraluminal pathology. Fluid structure interaction (FSI) simulations were conducted in patient based computed tomography scans reconstructed geometries in order to monitor aneurysmal disease progression from normal aortas to non-ruptured and contained ruptured AAA (rAAA), and the AAA risk of rupture was assessed. Three groups of 8 subjects each were studied: 8 normal and 16 pathological (8 non-ruptured and 8 rAAA). The AAA anatomical structures segmented included the blood lumen, intraluminal thrombus (ILT), vessel wall, and embedded calcifications. The vessel wall was described with anisotropic material model that was matched to experimental measurements of AAA tissue specimens. A statistical model for estimating the local wall strength distribution was employed to generate a map of a rupture potential index (RPI), representing the ratio between the local stress and local strength distribution. The FSI simulations followed a clear trend of increasing wall stresses from normal to pathological cases. The maximal stresses were observed in the areas where the ILT was not present, indicating a potential protective effect of the ILT. Statistically significant differences were observed between the peak systolic stress and the peak stress at the mean arterial pressure between the three groups. For the ruptured aneurysms, where the geometry of intact aneurysm was reconstructed, results of the FSI simulations clearly depicted maximum wall stress at the a priori known location of rupture. The RPI mapping indicated several distinct regions of high RPI coinciding with the actual location of rupture. The FSI methodology demonstrates that the aneurysmal disease can be described by numerical simulations, as indicated by a clear trend of increasing aortic wall stresses in the studied groups, (normal aortas, AAAs and rAAAs). Ultimately, the results demonstrate that FSI wall stress mapping and RPI can be used as a tool for predicting the potential rupture of an AAA by predicting the actual rupture location, complementing current clinical practice by offering a predictive diagnostic tool for deciding whether to intervene surgically or spare the patient from an unnecessary risky operation.

Imaging and finite element analysis: a methodology for non-invasive characterization of aortic tissue

Characterization of the mechanical properties of arterial tissues usually involves an invasive procedure requiring tissue removal. In this work we propose a non-invasive method to perform a biomechanical analysis of cardiovascular aortic tissue. This method is based on combining medical imaging and finite element analysis (FEA). Magnetic resonance imaging (MRI) was chosen since it presents relatively low risks for human health. A finite element model was created from the MRI images and loaded with systolic physiological pressures. By means of an optimization routine, the structural material properties were changed until average strains matched those measured by MRI. The method outlined in this work produced an estimate of the in situ properties of cardiovascular tissue based on non-invasive image datasets and finite element analysis.

Contemporary Role of Computational Analysis in Endovascular Treatment for Thoracic Aortic Disease

In the past decade, thoracic endovascular aortic repair (TEVAR) has become the primary treatment option in descending aneurysm and dissection. The clinical outcome of this minimally invasive technique is strictly related to an appropriate patient/stent graft selection, hemodynamic interactions, and operator skills. In this context, a quantitative assessment of the biomechanical stress induced in the aortic wall due to the stent graft may support the planning of the procedure. Different techniques of medical imaging, like computed tomography or magnetic resonance imaging, can be used to evaluate dynamics in the thoracic aorta. Such information can also be combined with dedicated patient-specific computer-based simulations, to provide a further insight into the biomechanical aspects. In clinical practice, computational analysis might show the development of aortic disease, such as the aortic wall segments which experience higher stress in places where rupture and dissection may occur. In aortic dissections, the intimal tear is usually located at the level of the sino-tubular junction and/or at the origin of the left subclavian artery. Besides, computational models may potentially be used preoperatively to predict stent graft behavior, virtually testing the optimal stent graft sizing, deployment, and conformability, in order to provide the best endovascular treatment. The present study reviews the current literature regarding the use of computational tools for TEVAR biomechanics, highlighting their potential clinical applications.

The role of geometric and biomechanical factors in abdominal aortic aneurysm rupture risk assessment

The current clinical management of abdominal aortic aneurysm (AAA) disease is based to a great extent on measuring the aneurysm maximum diameter to decide when timely intervention is required. Decades of clinical evidence show that aneurysm diameter is positively associated with the risk of rupture, but other parameters may also play a role in causing or predisposing the AAA to rupture. Geometric factors such as vessel tortuosity, intraluminal thrombus volume, and wall surface area are implicated in the differentiation of ruptured and unruptured AAAs. Biomechanical factors identified by means of computational modeling techniques, such as peak wall stress, have been positively correlated with rupture risk with a higher accuracy and sensitivity than maximum diameter alone. The objective of this review is to examine these factors, which are found to influence AAA disease progression, clinical management and rupture potential, as well as to highlight on-going research by our group in aneurysm modeling and rupture risk assessment.

New Insights Into Aortic Diseases: A Report From the Third International Meeting on Aortic Diseases (IMAD3)

The current state of research and treatment on aortic diseases was discussed in the "3rd International Meeting on Aortic Diseases" (IMAD3) held on October 4-6, 2012, in Liège, Belgium. The 3-day meeting covered a wide range of topics related to thoracic aortic aneurysms and dissections, abdominal aortic aneurysms, and valvular diseases. It brought together clinicians and basic scientists and provided an excellent opportunity to discuss future collaborative research projects for genetic, genomics, and biomarker studies, as well as clinical trials. Although great progress has been made in the past few years, there are still a large number of unsolved questions about aortic diseases. Obtaining answers to the key questions will require innovative, interdisciplinary approaches that integrate information from epidemiological, genetic, molecular biology, and bioengineering studies on humans and animal models. It is more evident than ever that multicenter collaborations are needed to accomplish these goals.

Patient-specific aortic endografting simulation: from diagnosis to prediction

Traditional surgical repair of ascending aortic pseudoaneurysm is complex, technically challenging, and associated with significant mortality. Although new minimally invasive procedures are rapidly arising thanks to the innovations in catheter-based technologies, the endovascular repair of the ascending aorta is still limited because of the related anatomical challenges. In this context, the integration of the clinical considerations with dedicated bioengineering analysis, combining the vascular features and the prosthesis design, might be helpful to plan the procedure and predict its outcome. Moving from such considerations, in the present study we describe the use of a custom-made stent-graft to perform a fully endovascular repair of an asymptomatic ascending aortic pseudoaneurysm in a patient, who was a poor candidate for open surgery. We also discuss the possible contribution of a dedicated medical images analysis and patient-specific simulation as support to procedure planning. In particular, we have compared the simulation prediction based on pre-operative images with post-operative outcomes. The agreement between the computer-based analysis and reality encourages the use of the proposed approach for a careful planning of the treatment strategy and for an appropriate patient selection, aimed at achieving successful outcomes for endovascular treatment of ascending aortic pseudoaneurysms as well as other aortic diseases.