A Framework for the Automatic Generation of Surface Topologies for Abdominal Aortic Aneurysm Models

Abstract

Patient-specific abdominal aortic aneurysms (AAAs) are characterized by local curvature changes, which we assess using a feature-based approach on topologies representative of the AAA outer wall surface. The application of image segmentation methods yields 3D reconstructed surface polygons that contain low-quality elements, unrealistic sharp corners, and surface irregularities. To optimize the quality of the surface topology, an iterative algorithm was developed to perform interpolation of the AAA geometry, topology refinement, and smoothing. Triangular surface topologies are generated based on a Delaunay triangulation algorithm, which is adapted for AAA segmented masks. The boundary of the AAA wall is represented using a signed distance function prior to triangulation. The irregularities on the surface are minimized by an interpolation scheme and the initial coarse triangulation is refined by forcing nodes into equilibrium positions. A surface smoothing algorithm based on a low-pass filter is applied to remove sharp corners. The optimal number of iterations needed for polygon refinement and smoothing is determined by imposing a minimum average element quality index with no significant AAA sac volume change. This framework automatically generates high-quality triangular surface topologies that can be used to characterize local curvature changes of the AAA wall.

The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

“…[15], which is the only resource, to our knowledge, with the capability to assess thickness at 72 points on each CT image with low relative errors with respect to reference standards. With the segmentation capabilities of VESSEG, noninvasive quantification of AAA geometry was made possible [14,16,26], as well as the wall mechanics assessment with regional distributions of wall thickness, as described herein. …”

A content-based 3D shape retrieval system for Abdominal Aortic Aneurysm rupture risk prediction

“…This algorithm for image segmentation is capable of identifying the extent of the relevant aneurysm regions: lumen, intraluminal thrombus and vascular wall. We have previously applied the algorithm for segmentation of unruptured and ruptured AAA data sets that were used in a feature-based approach for quantification of size, shape and wall thickness features [6][7][8]. For the purpose of this investigation, a "ruptured" shape is obtained from the last CTA scan available up to 1 month prior to the patient undergoing emergent AAA repair.…”

A Relation Between Near-Wall Particle-Hemodynamics and Onset of Thrombus Formation in Abdominal Aortic Aneurysms

“…22 and Shum et al . 35,36 for geometric analysis and risk stratification of AAA population subsets. The 3D anatomical geometry was obtained via reconstruction of the segmented images with subsequent surface meshing, using Simpleware (Simpleware Ltd., Exeter, UK).…”