Development of a Semi-automatic Finite Element Modeling Workflow for the Evaluation of Cranial Suture-Bone Complex Temporal Strain Evolution During Growth.
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| Title: | Development of a Semi-automatic Finite Element Modeling Workflow for the Evaluation of Cranial Suture-Bone Complex Temporal Strain Evolution During Growth. |
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| Authors: | Khurelbaatar, Tsolmonbaatar1 (AUTHOR), Sadati, Mahzad1 (AUTHOR), Schultz, Rachel1 (AUTHOR), Fisher, Leah1 (AUTHOR), Robertson, Emilie2 (AUTHOR), Budden, Curtis2 (AUTHOR), Popowics, Tracy3 (AUTHOR), Doschak, Michael R.4 (AUTHOR), Dennison, Christopher R.5 (AUTHOR), Westover, Lindsey1,6 (AUTHOR), Romanyk, Dan L.1,6,7 (AUTHOR) dromanyk@ualberta.ca |
| Source: | Annals of Biomedical Engineering. Jun2025, Vol. 53 Issue 6, p1370-1384. 15p. |
| Subjects: | Cranial sutures, Strains & stresses (Mechanics), Finite element method, Image segmentation, Workflow, Bone mechanics |
| Abstract: | Purpose: This study aimed to develop a semi-automatic workflow for medical image segmentation and finite element (FE) modeling. The workflow was subsequently used to investigate the temporal evolution of the localized mechanical strain in the rat coronal suture during normal growth. Methods: The subject-specific FE models were created based on in vivo longitudinal micro-computed tomography images acquired from n = 4 rats (AUP00003759, 11/04/2021). The FE models were created through a semi-automatic workflow that consisted of a semi-automatic segmentation of the rat cranial sutures, a simplified full skull model, and the detailed coronal suture model. Simulated intracranial pressure loading was implemented, and the localized equivalent, maximum principal, and minimum principal strains were estimated at volumes of interest (VOIs) selected along the suture-bone interface. Results: The semi-automatic segmentations were consistent among operators with a coefficient of variation of 1.8% and showed good agreement compared to the manual segmentation, with maximum differences of 4.1% and 2.0% in terms of suture volume and surface area, respectively. The estimated strains evolved with a trend increasing from 7 to 9 week and 9 to 11 week time intervals and decreasing from 11 to 16 week time interval for all VOIs. The results showed that strains at VOIs significantly changed (p < 0.05) over time. The concave regions of the suture experienced the highest magnitude of strains. Conclusion: The presented research has developed an appropriate semi-automatic FE workflow capable of evaluating temporal changes in mechanical strain of cranial sutures during growth, and was utilized to demonstrate transient and location-specific changes in the rat coronal suture. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 185134750 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Development of a Semi-automatic Finite Element Modeling Workflow for the Evaluation of Cranial Suture-Bone Complex Temporal Strain Evolution During Growth. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Khurelbaatar%2C+Tsolmonbaatar%22">Khurelbaatar, Tsolmonbaatar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sadati%2C+Mahzad%22">Sadati, Mahzad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schultz%2C+Rachel%22">Schultz, Rachel</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fisher%2C+Leah%22">Fisher, Leah</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Robertson%2C+Emilie%22">Robertson, Emilie</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Budden%2C+Curtis%22">Budden, Curtis</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Popowics%2C+Tracy%22">Popowics, Tracy</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Doschak%2C+Michael+R%2E%22">Doschak, Michael R.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dennison%2C+Christopher+R%2E%22">Dennison, Christopher R.</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Westover%2C+Lindsey%22">Westover, Lindsey</searchLink><relatesTo>1,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Romanyk%2C+Dan+L%2E%22">Romanyk, Dan L.</searchLink><relatesTo>1,6,7</relatesTo> (AUTHOR)<i> dromanyk@ualberta.ca</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Annals+of+Biomedical+Engineering%22">Annals of Biomedical Engineering</searchLink>. Jun2025, Vol. 53 Issue 6, p1370-1384. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Cranial+sutures%22">Cranial sutures</searchLink><br /><searchLink fieldCode="DE" term="%22Strains+%26+stresses+%28Mechanics%29%22">Strains & stresses (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Image+segmentation%22">Image segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Workflow%22">Workflow</searchLink><br /><searchLink fieldCode="DE" term="%22Bone+mechanics%22">Bone mechanics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: This study aimed to develop a semi-automatic workflow for medical image segmentation and finite element (FE) modeling. The workflow was subsequently used to investigate the temporal evolution of the localized mechanical strain in the rat coronal suture during normal growth. Methods: The subject-specific FE models were created based on in vivo longitudinal micro-computed tomography images acquired from n = 4 rats (AUP00003759, 11/04/2021). The FE models were created through a semi-automatic workflow that consisted of a semi-automatic segmentation of the rat cranial sutures, a simplified full skull model, and the detailed coronal suture model. Simulated intracranial pressure loading was implemented, and the localized equivalent, maximum principal, and minimum principal strains were estimated at volumes of interest (VOIs) selected along the suture-bone interface. Results: The semi-automatic segmentations were consistent among operators with a coefficient of variation of 1.8% and showed good agreement compared to the manual segmentation, with maximum differences of 4.1% and 2.0% in terms of suture volume and surface area, respectively. The estimated strains evolved with a trend increasing from 7 to 9 week and 9 to 11 week time intervals and decreasing from 11 to 16 week time interval for all VOIs. The results showed that strains at VOIs significantly changed (p < 0.05) over time. The concave regions of the suture experienced the highest magnitude of strains. Conclusion: The presented research has developed an appropriate semi-automatic FE workflow capable of evaluating temporal changes in mechanical strain of cranial sutures during growth, and was utilized to demonstrate transient and location-specific changes in the rat coronal suture. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10439-025-03710-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1370 Subjects: – SubjectFull: Cranial sutures Type: general – SubjectFull: Strains & stresses (Mechanics) Type: general – SubjectFull: Finite element method Type: general – SubjectFull: Image segmentation Type: general – SubjectFull: Workflow Type: general – SubjectFull: Bone mechanics Type: general Titles: – TitleFull: Development of a Semi-automatic Finite Element Modeling Workflow for the Evaluation of Cranial Suture-Bone Complex Temporal Strain Evolution During Growth. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khurelbaatar, Tsolmonbaatar – PersonEntity: Name: NameFull: Sadati, Mahzad – PersonEntity: Name: NameFull: Schultz, Rachel – PersonEntity: Name: NameFull: Fisher, Leah – PersonEntity: Name: NameFull: Robertson, Emilie – PersonEntity: Name: NameFull: Budden, Curtis – PersonEntity: Name: NameFull: Popowics, Tracy – PersonEntity: Name: NameFull: Doschak, Michael R. – PersonEntity: Name: NameFull: Dennison, Christopher R. – PersonEntity: Name: NameFull: Westover, Lindsey – PersonEntity: Name: NameFull: Romanyk, Dan L. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00906964 Numbering: – Type: volume Value: 53 – Type: issue Value: 6 Titles: – TitleFull: Annals of Biomedical Engineering Type: main |
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