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Generation of Patient-Specific Structured Hexahedral Mesh of Aortic Aneurysm Wall

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Computational Biomechanics for Medicine (MICCAI 2021)

Abstract

Abdominal aortic aneurysm (AAA) is an enlargement in the lower part of the main artery “Aorta” by 1.5 times its normal diameter. AAA can cause death if rupture occurs. Elective surgeries are recommended to prevent rupture based on measurement of AAA diameter and diameter growth rate. Reliability of these geometric parameters to predict the AAA rupture risk has been questioned, and biomechanical assessment has been proposed to distinguish between patients with high and low risk of AAA rupture. Stress in aneurysm wall is the main variable of interest in such assessment. Most studies use finite element method to compute AAA stress. This requires discretising patient-specific geometry (aneurysm wall and intraluminal thrombus ILT) into finite elements/meshes. Tetrahedral elements are most commonly used as they can be generated in seemingly automated and effortless way. In practice, however, due to complex aneurysm geometry, the process tends to require time-consuming mesh optimisation to ensure sufficiently high quality of tetrahedral elements. Furthermore, ensuring solution convergence requires large number of tetrahedral elements, which leads to relatively long computation times. In this study, we focus on generation of hexahedral meshes as they are known to provide converged solution for smaller number of elements than tetrahedral meshes. We limit our investigation to already existing algorithms and software packages for mesh generation. Generation of hexahedral meshes for continua with complex/irregular geometry, such as aneurysms, requires analyst interaction. We propose a procedure for generating high-quality patient-specific hexahedral discretisation of aneurysm wall using the algorithms available in commercial software package for mesh generation. We demonstrate, for the actual aneurysms, that the procedure facilitates patient-specific mesh generation within timeframe consistent with clinical workflow while requiring only limited input from the analyst.

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Acknowledgements

The authors acknowledge funding of the Australian Government through the National Health and Medical Research Council NHMRC Ideas Grant, Ideas grant no. APP2001689. This research was carried out while the first author F. A. was in receipt of an “Australian Government Research Training Program Scholarship at The University of Western Australia”. The first author acknowledges Ms. Kiara Beinart of the University of Western Australia’s Intelligent System for Medicine Laboratory for her contribution in obtaining the ethics approval and support of Ms. Giuliana D'Aulerio of the University of Western Australia’s Medical School Division of Surgery. Contributions of Christopher Wood and Jane Polce, radiology technicians at Medical Imaging Department, Fiona Stanley Hospital (Western Australia) in patient (abdominal aortic aneurysm) CT image acquisition are gratefully acknowledged. We also thank Fiona Stanley Hospital, Perth, Western Australia, for providing the patient CT images.

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Authors and Affiliations

  1. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia

    Farah Alkhatib, George C. Bourantas, Adam Wittek & Karol Miller

  2. Harvard Medical School, Boston, MA, USA

    Karol Miller

Authors
  1. Farah Alkhatib
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  2. George C. Bourantas
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  3. Adam Wittek
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  4. Karol Miller
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Corresponding author

Correspondence to Farah Alkhatib .

Editor information

Editors and Affiliations

  1. Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

    Martyn P. Nash

  2. Intelligent Systems for Medicine Laboratory, Department of Mechanical Engineering, The University of Western Australia, Perth, WA, Australia

    Adam Wittek

  3. Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

    Poul M. F. Nielsen

  4. Department of Mechanics, Materials and Biomedical Engineering, Wrocław University of Science and Technology, Wrocław, Poland

    Magdalena Kobielarz

  5. Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, Rourkela, India

    Anju R. Babu

  6. Intelligent Systems for Medicine Laboratory, Department of Mechanical Engineering, The University of Western Australia, Perth, WA, Australia

    Karol Miller

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Alkhatib, F., Bourantas, G.C., Wittek, A., Miller, K. (2023). Generation of Patient-Specific Structured Hexahedral Mesh of Aortic Aneurysm Wall. In: Nash, M.P., Wittek, A., Nielsen, P.M.F., Kobielarz, M., Babu, A.R., Miller, K. (eds) Computational Biomechanics for Medicine. MICCAI 2021. Springer, Cham. https://doi.org/10.1007/978-3-031-34906-5_1

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  • DOI: https://doi.org/10.1007/978-3-031-34906-5_1

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