目的:这项研究描述了脊柱的患者特异性(PS)骨韧带有限元(FE)模型的创建,胸腔,和骨盆,模拟长达三年的特定区域,应力调节生长,并通过患者临床角度测量验证模拟曲线进展。
目的:是否包含特定区域,应力调节椎体生长,除了根据年龄缩放,体重,骨骼成熟度,和脊柱的灵活性允许临床上准确的脊柱侧凸曲线进展预测患者特定的FE模型,胸腔,和骨盆?
方法:额叶,横向,获得了5名AIS患者的横向弯曲X射线,持续时间约为三年。PS-FE模型是通过在初始X射线时间点从患者X射线获得的界标点对标准模板FE模型进行变形来生成的。椎体生长行为和对压力的反应,以及模型材料属性基于几个预后因素而针对患者进行。将PS-FE模型的脊柱曲率角与相应的X射线测量值进行比较。
结果:平均有限元模型误差为6.3±4.6°,12.2±6.6°,8.9±7.7°,胸廓Cobb为5.3±3.4°,腰Cobb,后凸畸形,和脊柱前凸角度,分别。预测顶点和相邻水平的椎骨楔入的平均误差为3.2±2.2°。脊柱应力范围为拉伸0.11MPa至压缩0.79MPa。
结论:整合特定区域的应激调节生长,以及基于患者特定数据的生长和材料特性的调整产生了临床上有用的预测准确性,同时保持了生理压力大小。该框架可以进一步开发用于PS手术模拟。
This study describes the creation of patient-specific (PS) osteo-ligamentous finite element (FE) models of the spine, ribcage, and pelvis, simulation of up to three years of region-specific, stress-modulated growth, and validation of simulated curve progression with patient clinical angle measurements.
Does the inclusion of region-specific, stress-modulated vertebral growth, in addition to scaling based on age, weight, skeletal maturity, and spine flexibility allow for clinically accurate scoliotic curve progression prediction in patient-specific FE models of the spine, ribcage, and pelvis?
Frontal, lateral, and lateral bending X-Rays of five AIS patients were obtained for approximately three-year timespans. PS-FE models were generated by morphing a normative template FE model with landmark points obtained from patient X-rays at the initial X-ray timepoint. Vertebral growth behavior and response to stress, as well as model material properties were made patient-specific based on several prognostic factors. Spine curvature angles from the PS-FE models were compared to the corresponding X-ray measurements.
Average FE model errors were 6.3 ± 4.6°, 12.2 ± 6.6°, 8.9 ± 7.7°, and 5.3 ± 3.4° for thoracic Cobb, lumbar Cobb, kyphosis, and lordosis angles, respectively. Average error in prediction of vertebral wedging at the apex and adjacent levels was 3.2 ± 2.2°. Vertebral column stress ranged from 0.11 MPa in tension to 0.79 MPa in compression.
Integration of region-specific stress-modulated growth, as well as adjustment of growth and material properties based on patient-specific data yielded clinically useful prediction accuracy while maintaining physiological stress magnitudes. This framework can be further developed for PS surgical simulation.