基于多数据集的有限元人体模型骨盆损伤生存分析

C. Weaver, A. Miller, Joel Stitzel
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摘要

在过去的几十年里,有限元计算人体模型(HBMs)作为人体替代品在钝性损伤研究中得到了广泛的应用。FE HBMs对于局部损伤机制的分析至关重要。这些指标在实验测量中具有挑战性,并证明了HBMs的重要优势。本研究的目的是评估局部指标预测FE HBM骨盆骨折风险的损伤风险预测能力。本研究采用全球人体模型联盟(GHBMC)第50百分位详细男性模型(v4.3)。在GHBMC骨盆中实施横断面和皮质骨表面内固定。横向冲击有限元模拟使用来自死后人体受试者(PMHS)试验的输入数据进行。利用接收算子特征(ROC)曲线分析评估有限元力和应变输出对局部断裂风险的预测能力。ROC曲线分析显示上耻骨支和骶骨的预测能力中等。此外,将横截面力与最大主值、最小主值和有效皮质单元应变的百分位数输出范围进行比较。从这个分析中,我们确定横截力是局部骨盆骨折的最佳预测指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pelvic Injury Survival Analysis for a Finite Element Human Body Model Using Multiple Data Sets
Finite element (FE) computational human body models (HBMs) have gained popularity over the past several decades as human surrogates for use in blunt injury research. FE HBMs are critical for the analysis of local injury mechanisms. These metrics are challenging to measure experimentally and demonstrate an important advantage of HBMs. The objective of this study is to evaluate the injury risk predictive power of localized metrics to predict the risk of pelvic fracture in a FE HBM. The Global Human Body Models Consortium (GHBMC) 50th percentile detailed male model (v4.3) was used for this study. Cross-sectional and cortical bone surface instrumentation was implemented in the GHBMC pelvis. Lateral impact FE simulations were performed using input data from tests performed on post mortem human subjects (PMHS). Predictive power of the FE force and strain outputs on localized fracture risk was evaluated using the receiver operator characteristic (ROC) curve analysis. The ROC curve analysis showed moderate predictive power for the superior pubic ramus and sacrum. Additionally, cross-sectional force was compared to a range of percentile outputs of maximum principal, minimum principal, and effective cortical element strains. From this analysis it was determined that cross-sectional force was the best predictor of localized pelvic fracture.
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