Yoganandan Narayan, Chirvi Sajal, Pintar Frank A, Banerjee Anjishnu, Voo Liming
Center for NeuroTrauma Research, Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI.
Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI.
Stapp Car Crash J. 2018 Nov;62:271-292. doi: 10.4271/2018-22-0006.
Cervical spine injuries can occur in military scenarios from events such as underbody blast events. Such scenarios impart inferior-to-superior loads to the spine. The objective of this study is to develop human injury risk curves (IRCs) under this loading mode using Post Mortem Human Surrogates (PMHS). Twenty-five PMHS head-neck complexes were obtained, screened for pre-existing trauma, bone densities were determined, pre-tests radiological images were taken, fixed in polymethylmethacrylate at the T2-T3 level, a load cell was attached to the distal end of the preparation, positioned end on custom vertical accelerator device based on the military-seating posture, donned with a combat helmet, and impacted at the base. Posttest images were obtained, and gross dissection was done to confirm injuries to all specimens. Axial and resultant forces at the cervico-thoracic joint was used to develop the IRCs using survival analysis. Data were censored into left, interval, and uncensored observations. The Brier score metric was used to rank the variables. The optimal metric describing the underlying response to injury was associated with the axial force, ranking slightly greater than the resultant force, both with BMD covariates. The results from the survival analysis indicated all IRCs are in the "fair" to "good" category, at all risk levels. The BMD was found to be a significant covariate that best describes the response of the helmeted head-neck specimens to injury. The present experimental protocol and IRCs can be used to conduct additional tests, matched-pair tests with the WIAMan and/or other devices to obtain injury assessment risk curves (IARCs) and injury assessment risk values (IARVs) to predict injury in crash environments, and these data can also be used for validating component-based head-neck and human body computational models.
颈椎损伤可能发生在军事场景中,如车底爆炸事件等。此类场景会给脊柱施加从下到上的负荷。本研究的目的是使用尸体人类 surrogate(PMHS)在这种负荷模式下开发人类损伤风险曲线(IRC)。获取了 25 个 PMHS 头颈部复合体,筛查是否存在既往创伤,测定骨密度,拍摄测试前的放射图像,在 T2 - T3 水平固定于聚甲基丙烯酸甲酯中,在制剂远端连接一个测力传感器,根据军事坐姿放置在定制的垂直加速器装置上,戴上战斗头盔,并在底部进行撞击。获取测试后的图像,并进行大体解剖以确认所有标本的损伤情况。使用生存分析,利用颈胸关节处的轴向力和合力来开发 IRC。数据被 censored 为左删失、区间删失和未删失观测值。使用 Brier 评分指标对变量进行排名。描述损伤潜在反应的最佳指标与轴向力相关,排名略高于合力,两者均带有骨密度协变量。生存分析结果表明,在所有风险水平下,所有 IRC 都处于“中等”到“良好”类别。发现骨密度是最佳描述戴头盔头颈部标本损伤反应的显著协变量。当前的实验方案和 IRC 可用于进行额外测试,与 WIAMan 和/或其他设备进行配对测试,以获得损伤评估风险曲线(IARC)和损伤评估风险值(IARV),以预测碰撞环境中的损伤,并且这些数据还可用于验证基于组件的头颈部和人体计算模型。