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This review will examine papers about liver injuries, how and where they occur and how they can be tes
ted. Since the liver is a large organ it is a likely organ in the abdomen to be damaged by either blunt or penetrative trauma as discussed in several papers. The review also examines how data from these sources could be used for an abdominal ATD insert and the challenges involved with designing such an insert. The currently used Hybrid III anthropomorphic test dummy does not take into account the internal abdominal structure, it merely considers the entire area of the body to be homogeneous.
The article “Pressure-Based Abdominal Injury Criteria Using Isolated Liver and Full-Body Post-Mortem Human Subject Impact Tests” by (Kremer et al., 2011) examines the use of PMHS to study how blunt liver impacts injure the organ in vivo. The paper “Using Pressure to Predict Liver Injury Risk from Blunt Impact” by (Sparks et al., 2007) similarly conducts blunt impact testing on the liver however in this case the organ is tested ex vivo. In the Kremer paper new data as well as data from past studies, including (Sparks et al., 2007)eems to indicate that human livers experience more severe liver injury as a function of pressure.
Kremers purpose was to collect more data for the CIREN trauma database, the internal pressure data collected strengthened FMVSS no. 214 abdominal criteria. Sparks purpose was to collect data on how pressure and liver injury likelihood correlate with each other, the data it acquired was consistent with the already existing CIREN data. Both articles, and in addition (R. L. Stalnaker & Ulman, 2019), presented the idea of improving the current ATDs, the studies acquired data that could be used to design an ATD abdominal insert. This could be incorporated into the current widely used Hybrid III.
Stalnaker examined general abdominal trauma factors using primate scaling, it presented three studies of primates. Stalnaker also found little difference in the force-penetration response as a function of impact location, this is useful information for designing an ATD insert. Furthermore this articles methods included looking at velocity-compression impacting as a criteria for liver testing, however as Kremer as well as Sparks pointed out internal pressure seems to be a better criteria. Other articles have attempted to use force criteria, a notable example being (J. W. M. R. L. Stalnaker & Roberts, 2019), which tested Rhesus monkey livers. Sparks also discussed the importance of using just one parameter, that being internal pressure, for an ATD insert injury mechanism. The paper discussed how Internal pressure relates to applied force, applied stress, compression and velocity in a closed deformable system. This helps to simplify instrumentation without losing accuracy in injury risk assessment.
From the work done previously it was already known that abdominal injuries in vehicle accidents are generally more severe than those of other parts of the body such as limbs. It was also known that a smaller proportion of injuries make up abdominal organ damage however the injuries that do occur in the abdomen were much more likely to be of greater severity. Kremer also quoted (Elhagediab & Rouhana, n.d.) which found that 38% of all abdominal injuries were liver injuries. Furthermore both Kremer and Sparks noted the importance of internal fluid pressure as an injury mechanism, Sparks further investigated other injury mechanisms and mechanical responses to blunt abdominal loading.
Several articles also pointed out the issue of current ATDs having purely homogeneous internal structure as opposed to the real human abdomen, which is highly heterogeneous and varies from individual to individual. (Parenteau et al., 2013) studied how liver anatomy and location varies based on age, gender. The article quantified liver anatomy of different individuals from car crashes. The study found that the proportion of the liver in regards to the entire body decreases with age, it also stated that the ribcage protects a child liver less than of an adults; this can lead to more seat belt injuries in children. This information is important when considering the design of paediatric ATD models. (Yoganandan, Pintar, Gennarelli, & Maltese, n.d.) stated that the current paediatric ATDs are simply scaled adults which is not a very accurate representation of a real child. Combining this information with Parenteaus look at liver anatomy it can be concluded that if an abdominal implant were to be designed for a paediatric ATD it would have to be different from that of an adult ATDs insert.
The Parenteau articles purpose was to use its data to help create better mathematical models, improve occupant protection and to give care to those who suffer from liver injury. It also developed a new method to assess liver injury patterns whereby the quantification of liver blood volume was compared to liver volume, once again as a function of age and gender. Another article which examined mathematical models was (Lu et al., 2019), the study used statistical modelling to quantify the shape variations of the human liver in a seated posture, it also quantified the material properties of the liver. By identifying material parameters from specimens a mean was calculated from the stress-strain curves which was used, amongst other statistical data, for a probabilistic finite element model. The purpose of this study was to help understand the biomechanical response variability.
Below is a summary of the methods of testing loading properties of livers and evaluating the injury probability of different forces from different review articles. There is also an emphasis on how these methods can benefit in the design of abdominal ATD inserts. All of the methods from the review papers had different approaches to obtain results in a similar field of interest.
The first article (Sparks et al., 2007) Involved the testing of 14 livers and this method involved using a drop tower to apply blunt impact to the anterior surface of the liver specimen. The drop plate consisted of 3 load cells and an accelerometer. Stress applied to the midline of the plate was calculated from the displacement of the liver from the highest point. High video analysis was used to capture this impact. Impact velocities ranged from 1.31 to 5.99 m/s. There was also pressure sensors inserted into the liver.
The liver was inspected for injury on the surface and interior. The ISS (Injury Severity Scale) was used to grade and compare the injuries to blunt injury data in actual crashes. Regression analysis was used to investigate whether vertical distance and radial distance from impact point were significant predictors of peak pressure.
Another study (Kremer et al., 2011) had a different approach and involved the testing of PMHS using a pneumatic ram with a six-axis load cell between ram and impactor plate. The side was impacted where the liver is located at 7m/s. Transducers were inserted into hepatic veins and measured impacted induced pressure change. Foley balloons were used to pressurize the venous system. External Instrumentation consisted of three linear accelerometers, three angular rate sensors and a chest band consisting of 40 strain gauges used to measure abdominal deflection. After impact each liver was inspected for surface and internal injuries. They were compared to blunt liver injuries documented similar to in (Sparks et al., 2007). A binary logistic regression was used to develop injury risk functions associated with ISS. Assumptions were that injury was more likely to occur in areas with higher pressure.
The methods above involve the use of PMHS. The current dummy in use, the Hybrid 3 lacks a biofidelic abdomen (Yoganandan, Pintar, Gennarelli, & Maltese, 2000) that can be used for different loading surfaces and loading rates, which would be useful in comparison to the experiments mentioned above or getting bigger data sets. An important aspect of this is finding criteria for an abdominal insert. Important information regarding this can be found in (Stalnaker & Ulman, 2019). The method of this paper involved analysing data from the NASS (National Automotive Sampling System) to determine frequency and severity of the injury to this region including the liver. Purpose of this study was to define sensors and parameters for the dummy insert. Another paper looking at the similar method of analysis was (Yoganandan et al., 2000). The methods used here again involved using data from NASS and selecting data to use for analysis. Essentially analyzing data that is already there can help define parameters and placement of testing equipment for an abdominal insert.
Other methods included animal testing, for example (Melvin, Stalnaker, Roberts, & Trollope, 1973) used Rhesus Monkey surgically mobilized livers. The test used high speed testing rams at (5, 250, and 500 cm/s) to impact the liver. The resulting load-deflection data were normalized and average stress-strain curves plotted for each test. In addition, the resulting injury severity was estimated immediately after impact using an injury scale of 1 to 5. A further idea in terms of designing abdomen inserts for dummies is that every human has a different size/ shape of liver. A study focusing on this (Lu, Kemper, Gayzik, Untaroiu, & Beillas, 2013) involved performing 52 uniaxial tensile tests on sections of cut liver at 4 different loading rates to calculate failure properties of human livers. Results were used to help determine FE (Finite element) analysis models , which may help better understand variability in biomechanical responses of the liver.
Even though it is relatively protected, the liver is one of the most frequently injured abdominal organs in vehicle crashes. Liver injuries related to blunt trauma have the highest morbidity and mortality rates of all abdominal injuries. Moreover, capsule laceration and parenchyma damage are common and could be severe (Lu, Kemper, Gayzik, Untaroiu, & Beillas, 2013).
Although seemingly significant insight has been gained about the relationship between impact-induced pressures and blunt liver injury by the first article, the limited sample of 14 subjects contributes to wide 95% confidence bands for the injury risk functions studied (Sparks et al., 2007). In addition, more data points in the pressure range near 50% probability of serious injury (40-70kPa) would benefit these risk functions to more accurately explain the hypothesis that human livers experience more severe liver injury as a function of pressure. The later use of PMHS for the follow-up study (Kremer et al., 2011) meant more reliable results and more conclusions to be drawn, especially as their paired results with the first article accounted for a systematic error in the data acquisition settings from said article.
In search for the biofidelic insert, this article provides us with pressure results that more closely resemble the liver’s response when subjected to a car crash. This is due to their location in the venous vasculature, either in the hepatic veins or in the IVC at the level of the liver, and due to the initial conditions set to better simulate the pre-impact physiologic conditions of the liver. In the future a supplemental criterion will be needed to further investigate the role of pressure, as discrepancies were found between skeletal and liver injury in the same test points (Kremer et al., 2011).
These hypothetical developments could help create criteria to be added to the FMVSS 214, the current side impact standard, as there are no specific abdominal injury criteria at the moment. The reason behind choosing that specific standard is that in fact side impacts account for more liver injuries than frontal impacts while occurring at lower changes in velocity (Yoganandan, Pintar, Gennarelli, & Maltese, 2000).
The next article (R. L. Stalnaker & Ulman, 2019) disagrees with this idea through its study with animals, in which it prematurely assumes there is no difference between frontal and side impacts. It is worth mentioning that it determines that the right part of the abdomen is more susceptible to injury. Scaling their results for subhuman primate tests led to a 10 m/s abdominal impact response corridor, which could serve as a useful aspect to design a Hybrid III abdomen.
However, this tests once again lack the biofidelity that is needed for the task for obvious reasons: the subjects are monkeys. In contrast, there is another study (Lu, Kemper, Gayzik, Untaroiu, & Beillas, 2013) which presents the idea that Finite Element (FE) models are the most sophisticated human models, as it is possible to calculate precise stress-train distributions inside the model wich could in turn be associated with the risk of injury. In this particular case they over-simplified the models due to high computational costs. However, it introduces the first five modes of the liver statistical shape model, coupled with the established mean and boundary models, a future and more complete liver statistical FE model could be developed.
There are many distinct and competent ways to approach the advancements in the field of liver injuries due to impact. From crash tests to animal testing to high-speed biplane x-rays, they all contribute to the unveilling of this still very unknown field. However, it is most clear that the design of more sophisticated FE models will play a crucial role from now onwards. Most of these studies are recent and many base their testing on the findings of the one before them. There is no doubt that in the very near future a liver insert will be at the forefront of research for the design of ATDs.
Kremer, M. A., Gustafson, H. M., Bolte, J. H., Stammen, J., Donnelly, B., & Herriott, R. (2011). Pressure-based abdominal injury criteria using isolated liver and full-body post-mortem human subject impact tests. Stapp Car Crash Journal, 55(November 2011), 317–350. https://doi.org/10.4271/2011-22-0012
Lu, Y., Kemper, A. R., Gayzik, S., Untaroiu, C. D., Beillas, P., & Lyon, U. De. (2019). Statistical Modeling of Human Liver Incorporating the Variations in Shape , Size , and Material Properties. 57(November 2013), 285–311.
Parenteau, C. S., Ehrlich, P., Ma, L., Su, G. L., Holcombe, S., & Wang, S. C. (2013). The quantification of liver anatomical changes and assessment of occupant liver injury patterns. Stapp Car Crash Journal, 57(November), 267–283. https://doi.org/10.4271/2013-22-0011
Sparks, J. L., Bolte, J. H., Dupaix, R. B., Jones, K. H., Steinberg, S. M., Herriott, R. G., … Donnelly, B. R. (2007). Using pressure to predict liver injury risk from blunt impact. Stapp Car Crash Journal, 51(October), 401–432. https://doi.org/10.4271/2007-22-0017
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