Mesh-morphing algorithms for specimen-specific finite element modeling

• Published in: Journal of biomechanics Vol. 41; no. 7; pp. 1381 - 1389
• Main Authors: Sigal, Ian A, Hardisty, Michael R, Whyne, Cari M
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01-01-2008; Elsevier Limited
• Subjects: Algorithms; Animation; Automation; Biomechanics; Finite Element Analysis; Finite element modeling; Geometry; Imaging, Three-Dimensional - methods; Medical imaging; Methods; Models, Theoretical; Morphing; Physical Medicine and Rehabilitation; Studies; Vertebra; Biomechanics; Vertebra; Finite element modeling; Morphing
• ISSN: 0021-9290; 1873-2380
• DOI: 10.1016/j.jbiomech.2008.02.019

Abstract Despite recent advances in software for meshing specimen-specific geometries, considerable effort is still often required to produce and analyze specimen-specific models suitable for biomechanical analysis through finite element modeling. We hypothesize that it is possible to obtain accurate models by adapting a pre-existing geometry to represent a target specimen using morphing techniques. Here we present two algorithms for morphing, automated wrapping (AW) and manual landmarks (ML), and demonstrate their use to prepare specimen-specific models of caudal rat vertebrae. We evaluate the algorithms by measuring the distance between target and morphed geometries and by comparing response to axial loading simulated with finite element (FE) methods. First a traditional reconstruction process based on μCT was used to obtain two natural specimen-specific FE models. Next, the two morphing algorithms were used to compute mappings from the surface of one model, the source , to the other, the target , and to use this mapping to morph the source mesh to produce a target mesh. The μCT images were then used to assign element-specific material properties. In AW the mappings were obtained by wrapping the source and target surfaces with an auxiliary triangulated surface. In ML, landmarks were manually placed on corresponding locations on the surfaces of both source and target. Both morphing algorithms were successful in reproducing the shape of the target vertebra with a median distance between natural and morphed models of 18.8 and 32.2 μm, respectively, for AW and ML. Whereas AW–morphing produced a surface more closely resembling that of the target, ML guaranteed correspondence of the landmark locations between source and target. Morphing preserved the quality of the mesh producing models suitable for FE simulation. Moreover, there were only minor differences between natural and morphed models in predictions of deformation, strain and stress. We therefore conclude that it is possible to use mesh-morphing techniques to produce accurate specimen-specific FE models of caudal rat vertebrae. Mesh morphing techniques provide advantages over conventional specimen-specific finite element modeling by reducing the effort required to generate multiple target specimen models, facilitating intermodel comparisons through correspondence of nodes and maintenance of connectivity, and lends itself to parametric evaluation of “artificial” geometries with a focus on optimizing reconstruction.