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Towards Automating Patient-Specific Finite Element Model Development

Towards Automating Patient-Specific Finite Element Model Development. Finite Element Method. Invaluable tool in musculoskeletal research Demands associated with modeling the geometrically complex structures of the human body often limit its utility – restricting analyses to baseline models

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Towards Automating Patient-Specific Finite Element Model Development

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  1. Towards Automating Patient-Specific Finite Element Model Development

  2. Finite Element Method • Invaluable tool in musculoskeletal research • Demands associated with modeling the geometrically complex structures of the human body often limit its utility – restricting analyses to baseline models • Conventional meshing techniques often prove inadequate

  3. Patient Specific Models • In order to bring FE to the “bedside” for guiding surgical procedures the technique must be unencumbered from the image segmentation and mesh generation process • Overcome the limitations associated with individualized, or patient-specific models

  4. FE Model Development Acquire Medical Imaging Data Surface Generation Mesh Generation Segment Regions of Interest Apply Boundary/Load Conditions and Material Properties Finite Element Analysis

  5. Objective • Automate the generation of high quality hexahedral meshes • Projection method • Mapped Meshing • Inclusion of soft tissues such as cartilage • Automated Segmentation • Neural network • Level set • EM Segmentation • Validation • Segmentation using surface scanning • FE analysis using physical testing

  6. Bones of Interest Why initiate with the bones of the hand? • Long bones and cuboidal bones • Number of bones per cadaveric specimen • Readily extended to the other bones of the body

  7. Bones of Interest Extend to irregular bones such as the vertebrae

  8. Segmentation of ROIs • Manual Segmentation • Establish manual rater reliability and validity • Automated segmentation • Neural network algorithm • EM Segmentation • Level Set Segmentation

  9. Regions of Interest

  10. Segmentation Validation • Cadeveric specimens dissected and scanned using a 3D laser scanner • Physical scan surface co-registered with CT surface representation using ICP registration • Distance between manual and automated definitions compared to physical scans

  11. Surface Distance Measurement Tool

  12. Projection Method Carpal Bone Bounding Box with Assigned Mesh Seeding Projected Mesh Initial Bounding Box

  13. Projection Method Example – Proximal Phalanx Bone

  14. Extending Projection Method • A single bounding box coupled with the projection technique may not always prove sufficient • Method has been extended to add multiple boxes and/or subdivide existing boxes

  15. Projection Method Multiple Boxes

  16. Multiple Bounding Boxes Spine

  17. Subject Surface Overlap After Registration Template Mesh Initial Overlap Mapped Meshing • Map a template mesh to a new subject • Use FE framework in ITK • Apply forces based on distance from mesh surface to surface representation ITK FEM Registration

  18. Solid Mesh Smoothing • Projection of initial mesh onto the surface oftentimes yields distorted elements • Need to smooth resulting mesh – Iterative Laplacian smoothing for solid mesh • Method • Apply Laplacian smoothing to surface nodes holding interior nodes fixed • Project nodes back onto the original surface • Smooth interior nodes with surface nodes held fixed • Iterate for specified number of iterations or until convergence threshold is reached

  19. Results of Mesh Smoothing Unsmoothed Smoothed Unsmoothed Smoothed

  20. Mesh Quality Check • Aspect Ratio: Excess of 100 to 1 • Distorted Isoparametric Elements: • Angle between isoparametric lines • < 45 degrees or > 135 degrees

  21. Acknowledgements • Grant funding • R21 (NIBIB - EB001501) • R01 (NIBIB - EB005973) • Steve Pieper, Simon Warfield, Curt Lisle • Kiran H. Shivanna, Nicole Kallemeyn, Nicole DeVries, Esther Gassman, Ritesh Bafna, Srinivas Tadepalli, Dr. Brian Adams

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