3D-Ultrasound Based Mechanical and Geometrical Analysis of Abdominal Aortic Aneurysms and Relationship to Growth

The heterogeneity of progression of abdominal aortic aneurysms (AAAs) is not well understood. This study investigates which geometrical and mechanical factors, determined using time-resolved 3D ultrasound (3D + t US), correlate with increased growth of the aneurysm. The AAA diameter, volume, wall curvature, distensibility, and compliance in the maximal diameter region were determined automatically from 3D + t echograms of 167 patients. Due to limitations in the field-of-view and visibility of aortic pulsation, measurements of the volume, compliance of a 60 mm long region and the distensibility were possible for 78, 67, and 122 patients, respectively. Validation of the geometrical parameters with CT showed high similarity, with a median similarity index of 0.92 and root-mean-square error (RMSE) of diameters of 3.5 mm. Investigation of Spearman correlation between parameters showed that the elasticity of the aneurysms decreases slightly with diameter (p = 0.034) and decreases significantly with mean arterial pressure (p < 0.0001). The growth of a AAA is significantly related to its diameter, volume, compliance, and surface curvature (p < 0.002). Investigation of a linear growth model showed that compliance is the best predictor for upcoming AAA growth (RMSE 1.70 mm/year). To conclude, mechanical and geometrical parameters of the maximally dilated region of AAAs can automatically and accurately be determined from 3D + t echograms. With this, a prediction can be made about the upcoming AAA growth. This is a step towards more patient-specific characterization of AAAs, leading to better predictability of the progression of the disease and, eventually, improved clinical decision making about the treatment of AAAs.

Structural numerical analysis of a branched modular stent-graft for aneurysms encompassing all zones of the aortic arch

The development of stent-grafts for the total repair of aneurysms in the aortic arch is still a technical challenge due mainly to the anatomical complexity of this region. Research performed here structurally evaluated a modular branched stent-graft for aneurysms encompassing all zones of the aortic arch by means of numerical simulations using fluid-structure interaction. The geometric domain obtained by means of computed tomography was subjected to physiological boundary conditions. The blood was modelled as non-Newtonian by the Carreau model, and the arterial wall was modelled as anisotropic hyperelastic by the Holzapfel model. The material adopted for the stents was Nitinol, and expanded polytetrafluoroethylene (ePTFE) was used for the graft. A comparison of the structural behaviour of the aneurysmal aortic arch before and after stent-graft implantation was performed. The numerical flow model was experimentally verified in vitro on a representative test bench of blood flow in the aortic arch. The stent-graft was shown to minimally modify arterial wall dynamics and was not susceptible to migration and endoleak. Peak stresses and strains were found in the stents and graft, respectively, while the stresses in the aneurysm sac were significantly reduced, of the order of 97.5%, due to the isolation of the arterial wall by the stent-graft.

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.

Comparative study between 1-way and 2-way coupled fluid-structure interaction in numerical simulation of aortic arch aneurysms

Hemodynamic forces are related to pathological variations of the cardiovascular system, and numerical simulations for fluid-structure interaction have been systematically used to analyze the behavior of blood flow and the arterial wall in aortic aneurysms. This paper proposes a comparative analysis of 1-way and 2-way coupled fluid-structure interaction for aortic arch aneurysm. The coupling models of fluid-structure interaction were conducted using 3D geometry of the thoracic aorta from computed tomography. Hyperelastic anisotropic properties were estimated for the Holzapfel arterial wall model. The rheological behavior of the blood was modeled by the Carreau-Yasuda model. The results showed that the 1-way approach tends to underestimate von Mises stress, displacement, and strain over the entire cardiac cycle, compared to the 2-way approach. In contrast, the behavior of the variables of flow field, velocity, wall shear stress, and Reynolds number when coupled by the 1-way model was overestimated at the systolic moment and tends to be equal at the diastolic moment. The quantitative differences found, especially during the systole, suggest the use of 2-way coupling in numerical simulations of aortic arch aneurysms due to the hyperelastic nature of the arterial wall, which leads to a strong iteration between the fluid and the arterial wall.

Engineering analysis of aortic wall stress and root dilatation in the V-shape surgery for treatment of ascending aortic aneurysms

OBJECTIVES

The study objective was to evaluate the aortic wall stress and root dilatation before and after the novel V-shape surgery for the treatment of ascending aortic aneurysms and root ectasia.

METHODS

Clinical cardiac computed tomography images were obtained for 14 patients [median age, 65 years (range, 33-78); 10 (71%) males] who underwent the V-shape surgery. For 10 of the 14 patients, the computed tomography images of the whole aorta pre- and post-surgery were available, and finite element simulations were performed to obtain the stress distributions of the aortic wall at pre- and post-surgery states. For 6 of the 14 patients, the computed tomography images of the aortic root were available at 2 follow-up time points post-surgery (Post 1, within 4 months after surgery and Post 2, about 20-52 months from Post 1). We analysed the root dilatation post-surgery using change of the effective diameter of the root at the two time points and investigated the relationship between root wall stress and root dilatation.

RESULTS

The mean and peak max-principal stresses of the aortic root exhibit a significant reduction, P=0.002 between pre- and post-surgery for both root mean stress (median among the 10 patients presurgery, 285.46 kPa; post-surgery, 199.46 kPa) and root peak stress (median presurgery, 466.66 kPa; post-surgery, 342.40 kPa). The mean and peak max-principal stresses of the ascending aorta also decrease significantly from pre- to post-surgery, with P=0.004 for the mean value (median presurgery, 296.48 kPa; post-surgery, 183.87 kPa), and P=0.002 for the peak value (median presurgery, 449.73 kPa; post-surgery, 282.89 kPa), respectively. The aortic root diameter after the surgery has an average dilatation of 5.01% in total and 2.15%/year. Larger root stress results in larger root dilatation.

CONCLUSIONS

This study marks the first biomechanical analysis of the novel V-shape surgery. The study has demonstrated significant reduction in wall stress of the aortic root repaired by the surgery. The root was able to dilate mildly post-surgery. Wall stress could be a critical factor for the dilatation since larger root stress results in larger root dilatation. The dilated aortic root within 4 years after surgery is still much smaller than that of presurgery.

Predictors of Abdominal Aortic Aneurysm Risks

Computational biomechanics via finite element analysis (FEA) has long promised a means of assessing patient-specific abdominal aortic aneurysm (AAA) rupture risk with greater efficacy than current clinically used size-based criteria. The pursuit stems from the notion that AAA rupture occurs when wall stress exceeds wall strength. Quantification of peak (maximum) wall stress (PWS) has been at the cornerstone of this research, with numerous studies having demonstrated that PWS better differentiates ruptured AAAs from non-ruptured AAAs. In contrast to wall stress models, which have become progressively more sophisticated, there has been relatively little progress in estimating patient-specific wall strength. This is because wall strength cannot be inferred non-invasively, and measurements from excised patient tissues show a large spectrum of wall strength values. In this review, we highlight studies that investigated the relationship between biomechanics and AAA rupture risk. We conclude that combining wall stress and wall strength approximations should provide better estimations of AAA rupture risk. However, before personalized biomechanical AAA risk assessment can become a reality, better methods for estimating patient-specific wall properties or surrogate markers of aortic wall degradation are needed. Artificial intelligence methods can be key in stratifying patients, leading to personalized AAA risk assessment.

Automated Quantification of Diseased Thoracic Aortic Longitudinal Centerline and Surface Curvatures

Precise description of vascular morphometry is crucial to support medical device manufacturers and clinicians for improving device development and interventional outcomes. A compact and intuitive method is presented to automatically characterize the surface geometry of tubular anatomic structures and quantify surface curvatures starting from generic stereolithographic (STL) surfaces. The method was validated with software phantoms and used to quantify the longitudinal surface curvatures of 37 human thoracic aortas with aneurysm or dissection. The quantification of surface curvatures showed good agreement with analytic solutions from the software phantoms, and demonstrated better agreement as compared to estimation methods using only centerline geometry and cross-sectional radii. For the human thoracic aortas, longitudinal inner surface curvature was significantly higher than centerline curvature (0.33 ± 0.06 versus 0.16 ± 0.02 cm-1 for mean; 1.38 ± 0.48 versus 0.45 ± 0.11 cm-1 for peak; both p < 0.001). These findings show the importance of quantifying surface curvatures in order to better describe the geometry and biomechanical behavior of the thoracic aorta, which can assist in treatment planning and supplying device manufactures with more precise boundary conditions for mechanical evaluation.

Decal-Lenses: Interactive Lenses on Surfaces for Multivariate Visualization

We present decal-lenses, a new interaction technique that extends the concept of magic lenses to augment and manage multivariate visualizations on arbitrary surfaces. Our object-space lenses follow the surface geometry and allow the user to change the point of view during data exploration while maintaining a spatial reference to positions where one or more lenses were placed. Each lens delimits specific regions of the surface where one or more attributes can be selected or combined. Similar to 2D lenses, the user interacts with our lenses in real-time, switching between different attributes within the lens context. The user can also visualize the surface data representations from the point of view of each lens by using local cameras. To place lenses on surfaces of intricate geometry, such as the human brain, we introduce the concept of support surfaces for designing interaction techniques. Support surfaces provide a way to place and interact with the lenses while avoiding holes and occluded regions during data exploration. We further extend decal-lenses to arbitrary regions using brushing and lassoing operations. We discuss the applicability of our technique and present several examples where our lenses can be useful to create a customized exploration of multivariate data on surfaces.