From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs
IntroductionBiomechanical simulations can enhance our understanding of spinal disorders. Applied to large cohorts, they can reveal complex mechanisms beyond conventional imaging. Therefore, automating the patient-specific modeling process is essential.MethodsWe developed an automated and robust pipe...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1485115/full |
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| author | Kati Nispel Kati Nispel Tanja Lerchl Gabriel Gruber Hendrik Moeller Robert Graf Veit Senner Jan S. Kirschke Jan S. Kirschke |
| author_facet | Kati Nispel Kati Nispel Tanja Lerchl Gabriel Gruber Hendrik Moeller Robert Graf Veit Senner Jan S. Kirschke Jan S. Kirschke |
| author_sort | Kati Nispel |
| collection | DOAJ |
| description | IntroductionBiomechanical simulations can enhance our understanding of spinal disorders. Applied to large cohorts, they can reveal complex mechanisms beyond conventional imaging. Therefore, automating the patient-specific modeling process is essential.MethodsWe developed an automated and robust pipeline that generates and simulates biofidelic vertebrae and intervertebral disc finite element method (FEM) models based on automated magnetic resonance imaging (MRI) segmentations. In a first step, anatomically-constrained smoothing approaches were implemented to ensure seamless contact surfaces between vertebrae and discs with shared nodes. Subsequently, surface meshes were filled isotropically with tetrahedral elements. Lastly, simulations were executed. The performance of our pipeline was evaluated using a set of 30 patients from an in-house dataset that comprised an overall of 637 vertebrae and 600 intervertebral discs. We rated mesh quality metrics and processing times.ResultsWith an average number of 21 vertebrae and 20 IVDs per subject, the average processing time was 4.4 min for a vertebra and 31 s for an IVD. The average percentage of poor quality elements stayed below 2% in all generated FEM models, measured by their aspect ratio. Ten vertebra and seven IVD FE simulations failed to converge.DiscussionThe main goal of our work was to automate the modeling and FEM simulation of both patient-specific vertebrae and intervertebral discs with shared-node surfaces directly from MRI segmentations. The biofidelity, robustness and time-efficacy of our pipeline marks an important step towards investigating large patient cohorts for statistically relevant, biomechanical insight. |
| format | Article |
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| institution | Kabale University |
| issn | 2296-4185 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj-art-cc34faea653e4842acae27fa786ce5442025-01-03T11:35:56ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852025-01-011210.3389/fbioe.2024.14851151485115From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discsKati Nispel0Kati Nispel1Tanja Lerchl2Gabriel Gruber3Hendrik Moeller4Robert Graf5Veit Senner6Jan S. Kirschke7Jan S. Kirschke8Institute for Neuroradiology, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, GermanyAssociate Professorship of Sport Equipment and Sport Materials, School of Engineering and Design, Technical University of Munich, Garching, GermanyInstitute for Neuroradiology, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, GermanyInstitute for Neuroradiology, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, GermanyInstitute for Neuroradiology, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, GermanyInstitute for Neuroradiology, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, GermanyAssociate Professorship of Sport Equipment and Sport Materials, School of Engineering and Design, Technical University of Munich, Garching, GermanyInstitute for Neuroradiology, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, GermanyBonescreen GmbH, Munich, GermanyIntroductionBiomechanical simulations can enhance our understanding of spinal disorders. Applied to large cohorts, they can reveal complex mechanisms beyond conventional imaging. Therefore, automating the patient-specific modeling process is essential.MethodsWe developed an automated and robust pipeline that generates and simulates biofidelic vertebrae and intervertebral disc finite element method (FEM) models based on automated magnetic resonance imaging (MRI) segmentations. In a first step, anatomically-constrained smoothing approaches were implemented to ensure seamless contact surfaces between vertebrae and discs with shared nodes. Subsequently, surface meshes were filled isotropically with tetrahedral elements. Lastly, simulations were executed. The performance of our pipeline was evaluated using a set of 30 patients from an in-house dataset that comprised an overall of 637 vertebrae and 600 intervertebral discs. We rated mesh quality metrics and processing times.ResultsWith an average number of 21 vertebrae and 20 IVDs per subject, the average processing time was 4.4 min for a vertebra and 31 s for an IVD. The average percentage of poor quality elements stayed below 2% in all generated FEM models, measured by their aspect ratio. Ten vertebra and seven IVD FE simulations failed to converge.DiscussionThe main goal of our work was to automate the modeling and FEM simulation of both patient-specific vertebrae and intervertebral discs with shared-node surfaces directly from MRI segmentations. The biofidelity, robustness and time-efficacy of our pipeline marks an important step towards investigating large patient cohorts for statistically relevant, biomechanical insight.https://www.frontiersin.org/articles/10.3389/fbioe.2024.1485115/fullpatient-specificMRIFEMautomatedspinevertebra |
| spellingShingle | Kati Nispel Kati Nispel Tanja Lerchl Gabriel Gruber Hendrik Moeller Robert Graf Veit Senner Jan S. Kirschke Jan S. Kirschke From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs Frontiers in Bioengineering and Biotechnology patient-specific MRI FEM automated spine vertebra |
| title | From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs |
| title_full | From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs |
| title_fullStr | From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs |
| title_full_unstemmed | From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs |
| title_short | From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs |
| title_sort | from mri to fem an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs |
| topic | patient-specific MRI FEM automated spine vertebra |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1485115/full |
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