Development, calibration and validation of a comprehensive customizable lumbar spine FE model for simulating fusion constructs

面(心理学) 生物力学 有限元法 仪表(计算机编程) 力矩(物理) 旋转(数学) 运动学 弯矩 腰椎 扭矩 结构工程 计算机科学 生物医学工程 模拟 工程类 物理 解剖 医学 人工智能 人格 热力学 操作系统 五大性格特征 社会心理学 经典力学 心理学
作者
Subin Philip George,Venkatesh Krishnan,Girish Kumar
出处
期刊:Medical Engineering & Physics [Elsevier]
卷期号:118: 104016-104016
标识
DOI:10.1016/j.medengphy.2023.104016
摘要

Instrumentation alters the biomechanics of the spine, and therefore prediction of all output quantities that have critical influence post-surgically is significant for engineering models to aid in clinical predictions. Geometrical morphological finite element models can bring down the development time and cost of custom intact and instrumented models and thus aids in the better inference of biomechanics of surgical instrumentation on patient-specific diseased spine segments. A comprehensive hexahedral morphological lumbosacral finite element model is developed in this work to predict the range of motions, disc pressures, and facet contact forces of the intact and instrumented spine. Facet contact forces are needed to predict the impact of fusion surgeries on adjacent facet contacts in bending, axial rotation, and extension motions. Extensive validation in major physiological loading regimes of the pure moment, pure compression, and combined loading is undertaken. In vitro, experimental corridor results from six different studies reported in the literature are compared and the generated model had statistically significant comparable values with these studies. Flexion, extension and bending moment rotation curves of all segments of the developed model were favourable and within two separately established experimental corridor windows as well as recent simulation results. Axial torque moment rotation curves were comparable to in vitro results for four out of five lumbar functional units. The facet contact force results also agreed with in vitro experimental results. The current model is also computationally efficient with respect to contemporary models since it uses significantly smaller number of elements without losing the accuracy in terms of response prediction. This model can further be used for predicting the impact of different instrumentation techniques on the lumbar vertebral column.
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