Department of Pediatrics, University of Utah, Salt Lake City, UT, USA.
Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA.
Pediatr Res. 2023 Jun;93(7):1990-1998. doi: 10.1038/s41390-022-02345-9. Epub 2022 Oct 26.
Prior research and experience has increased physician understanding of infant skull fracture prediction. However, patterns related to fracture length, nonlinearity, and features of complexity remain poorly understood, and differences across infant age groups have not been previously explored.
To determine how infant and low-height fall characteristics influence fracture patterns, we collected data from 231 head CT 3D reconstructions and quantified length and nonlinearity using a custom image processing code. Regression analysis was used to determine the effects of age and fall characteristics on nonlinearity, length, and features of fracture complexity.
While impact surface had an important role in the number of cracks present in a fracture, younger infants and greater fall heights significantly affected most features of fracture complexity, including suture-to-suture spanning and biparietal involvement. In addition, increasing fracture length with increasing fall height supports trends identified by prior finite-element modeling. Finally, this study yielded results supporting the presence of soft tissue swelling as a function of fracture location rather than impact site.
Age-related properties of the infant skull confer unique fracture patterns following head impact. Further characterization of these properties, particularly in infants <4 months of age, will improve our understanding of the infant skull's response to trauma.
Younger infant age and greater fall heights have significant effects on many features of fracture complexity resulting from low-height falls. Incorporating multiple crack formation and multiple bone involvement into computational models of young infant skull fractures may result in increased biofidelity. Drivers of skull fracture complexity are not well understood, and skull fracture patterns in real-world data across infant age groups have not been previously described. Understanding fracture complexity relative to age in accidental falls will improve the understanding of accidental and abusive head trauma.
先前的研究和经验增加了医生对婴儿颅骨骨折预测的理解。然而，与骨折长度、非线性和复杂性特征相关的模式仍未被充分理解，并且不同婴儿年龄组之间的差异尚未被探索。
为了确定婴儿和低高度跌落特征如何影响骨折模式，我们从 231 例头部 CT 3D 重建中收集数据，并使用定制的图像处理代码量化长度和非线性。回归分析用于确定年龄和跌落特征对非线性、长度和骨折复杂性特征的影响。
虽然撞击表面对骨折中存在的裂缝数量有重要影响，但婴儿年龄越小和跌落高度越高，显著影响了骨折复杂性的大多数特征，包括缝间跨越和双顶骨受累。此外，随着跌落高度的增加，骨折长度的增加支持了先前有限元建模确定的趋势。最后，本研究的结果支持了软组织肿胀是作为骨折位置而不是撞击部位的函数的存在。
婴儿颅骨的年龄相关特性赋予了头部撞击后独特的骨折模式。进一步描述这些特性，特别是在<4 个月大的婴儿中，将提高我们对婴儿颅骨对创伤反应的理解。
婴儿年龄越小和跌落高度越高，对许多由低高度跌落引起的骨折复杂性特征有显著影响。将多发裂缝形成和多块骨受累纳入年轻婴儿颅骨骨折的计算模型中可能会提高生物逼真度。颅骨骨折复杂性的驱动因素尚未得到很好的理解，并且不同婴儿年龄组的真实世界数据中的颅骨骨折模式以前没有被描述过。了解与年龄相关的意外跌倒骨折复杂性将提高对意外和虐待性头部创伤的理解。
