Finite element analysis in asymptomatic, symptomatic, and ruptured abdominal aortic aneurysms: in search of new rupture risk predictors.

OBJECTIVES To compare biomechanical rupture risk parameters of asymptomatic, symptomatic and ruptured abdominal aortic aneurysms (AAA) using finite element analysis (FEA). STUDY DESIGN Retrospective biomechanical single center analysis of asymptomatic, symptomatic, and ruptured AAAs. Comparison of biomechanical parameters from FEA. MATERIALS AND METHODS From 2011 to 2013 computed tomography angiography (CTA) data from 30 asymptomatic, 15 symptomatic, and 15 ruptured AAAs were collected consecutively. FEA was performed according to the successive steps of AAA vessel reconstruction, segmentation and finite element computation. Biomechanical parameters Peak Wall Rupture Risk Index (PWRI), Peak Wall Stress (PWS), and Rupture Risk Equivalent Diameter (RRED) were compared among the three subgroups. RESULTS PWRI differentiated between asymptomatic and symptomatic AAAs (p < .0004) better than PWS (p < .1453). PWRI-dependent RRED was higher in the symptomatic subgroup compared with the asymptomatic subgroup (p < .0004). Maximum AAA external diameters were comparable between the two groups (p < .1355). Ruptured AAAs showed the highest values for external diameter, total intraluminal thrombus volume, PWS, RRED, and PWRI compared with asymptomatic and symptomatic AAAs. In contrast with symptomatic and ruptured AAAs, none of the asymptomatic patients had a PWRI value >1.0. This threshold value might identify patients at imminent risk of rupture. CONCLUSIONS From different FEA derived parameters, PWRI distinguishes most precisely between asymptomatic and symptomatic AAAs. If elevated, this value may represent a negative prognostic factor for asymptomatic AAAs.

Influence of Smoothing on Voxel-Based Mesh Accuracy in Micro-Finite Element

The interest in automatic volume meshing for finite element analysis (FEA) has grown more since the appearance of microfocus CT (μCT), due to its high resolution, which allows for the assessment of mechanical behaviour at a high precision. Nevertheless, the basic meshing approach of generating one hexahedron per voxel produces jagged edges. To prevent this effect, smoothing algorithms have been introduced to enhance the topology of the mesh. However, whether smoothing also improves the accuracy of voxel-based meshes in clinical applications is still under question. There is a trade-off between smoothing and quality of elements in the mesh. Distorted elements may be produced by excessive smoothing and reduce accuracy of the mesh. In the present work, influence of smoothing on the accuracy of voxel-based meshes in micro-FE was assessed. An accurate 3D model of a trabecular structure with known apparent mechanical properties was used as a reference model. Virtual CT scans of this reference model (with resolutions of 16, 32 and 64 μm) were then created and used to build voxel-based meshes of the microarchitecture. Effects of smoothing on the apparent mechanical properties of the voxel-based meshes as compared to the reference model were evaluated. Apparent Young’s moduli of the smooth voxel-based mesh were significantly closer to those of the reference model for the 16 and 32 μm resolutions. Improvements were not significant for the 64 μm, due to loss of trabecular connectivity in the model. This study shows that smoothing offers a real benefit to voxel-based meshes used in micro-FE. It might also broaden voxel-based meshing to other biomechanical domains where it was not used previously due to lack of accuracy. As an example, this work will be used in the framework of the European project ContraCancrum, which aims at providing a patient-specific simulation of tumour development in brain and lungs for oncologists. For this type of clinical application, such a fast, automatic, and accurate generation of the mesh is of great benefit.