Khurelbaatar Tsolmonbaatar, Sadati Mahzad, Schultz Rachel, Fisher Leah, Robertson Emilie, Budden Curtis, Popowics Tracy, Doschak Michael R, Dennison Christopher R, Westover Lindsey, Romanyk Dan L
Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada.
Department of Surgery, University of Alberta, Edmonton, AB, Canada.
Ann Biomed Eng. 2025 Jun;53(6):1370-1384. doi: 10.1007/s10439-025-03710-5. Epub 2025 Mar 19.
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.
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.
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.
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.
本研究旨在开发一种用于医学图像分割和有限元（FE）建模的半自动工作流程。随后，该工作流程被用于研究正常生长过程中大鼠冠状缝局部机械应变的时间演变。
基于从n = 4只大鼠（AUP00003759，2021年11月4日）获取的体内纵向微型计算机断层扫描图像创建特定受试者的有限元模型。有限元模型通过一个半自动工作流程创建，该流程包括大鼠颅骨缝线的半自动分割、简化的全颅骨模型和详细的冠状缝模型。实施模拟颅内压加载，并在沿缝线-骨界面选择的感兴趣体积（VOIs）处估计局部等效应变、最大主应变和最小主应变。
半自动分割在操作人员之间具有一致性，变异系数为1.8%，与手动分割相比显示出良好的一致性，缝线体积和表面积的最大差异分别为4.1%和2.0%。对于所有VOIs，估计应变在7至9周和9至11周时间间隔内呈增加趋势，在11至16周时间间隔内呈下降趋势。结果表明，VOIs处的应变随时间显著变化（p < 0.05）。缝线的凹陷区域经历了最高程度的应变。
本研究开发了一种合适的半自动有限元工作流程，能够评估生长过程中颅骨缝线机械应变的时间变化，并用于证明大鼠冠状缝的瞬时和位置特异性变化。
