Influence of Skull Fracture on Traumatic Brain Injury Risk

International Journal of Environmental Research and Public Health

Article Inﬂuence of Skull Fracture on Traumatic Brain Injury Risk Induced by Blunt Impact

Lihai Ren 1,2, Dangdang Wang 2, Xi Liu 1,2,*, Huili Yu 3, Chengyue Jiang 2 and Yuanzhi Hu 1,2

1 State Key Laboratory of Vehicle NVH and Safety Technology, China Automotive Engineering Reasearch Institute Co., Ltd. and Chongqing Chang’An Automobile Co., Ltd., Chongqing 401122, China; [email protected] (L.R.); [email protected] (Y.H.) 2 Key Laboratory of Advanced Manufacturing Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China; [email protected] (D.W.); [email protected] (C.J.) 3 Chang’An Automobile Co., Ltd., Chongqing 400023, China; [email protected] * Correspondence: [email protected]

Received: 28 February 2020; Accepted: 30 March 2020; Published: 1 April 2020

Abstract: This study is aimed at investigating the influence of skull fractures on traumatic brain injury induced by blunt impact via numerous studies of head–ground impacts. First, finite element (FE) damage modeling was implemented in the skull of the Total HUman Model for Safety (THUMS), and the skull fracture prediction performance was validated against a head–ground impact experiment. Then, the original head model of the THUMS was assigned as the control model without skull element damage modeling. Eighteen (18) head–ground impact models were established using these two FE head models, with three head impact locations (frontal, parietal, and occipital regions) and three impact velocities (25, 35, and 45 km/h). The predicted maximum principal strain and cumulative strain damage measure of the brain tissue were employed to evaluate the effect of skull fracture on the cerebral contusion and diffuse brain injury risks, respectively. Simulation results showed that the skull fracture could reduce the risk of diffuse brain injury risk under medium and high velocities significantly, while it could increase the risk of brain contusion under high-impact velocity.

Keywords: blunt impact; head ﬁnite element model; skull fracture; traumatic brain injury

1. Introduction Road traffic collisions (RTCs) have become one of the most severe worldwide public health problems, and approximately 5 million people are injured and 1.2 million die from RTCs every year [1]. In China, approximately 200,000 RTCs occur annually, which leads to more than 200,000 injuries every year [2]. One of the main causes of the casualty in RTCs is severe traumatic brain injury (TBI) caused by head blunt impacts [3–5]. Blunt-impact head injuries of RTCs mainly include skull fracture and TBI [6,7]. The patterns of skull fracture depending on the initial head impact location (or direction), which can be divided into three main groups: anterior, lateral, and posterior, that is, frontal, lateral–parietal, and occipital, respectively [8–10]. According to the distribution of injury, TBIs can be divided into focal brain injuries and diffuse brain injuries (DBIs) [11–13]. Focal brain injuries usually lead to loss of partial brain function with contusions, intracranial hematomas, and so on [4,14]. DBIs include mild concussion, moderate concussion with brief coma, and diffuse axonal injury with long-term coma or death [12,13]. As demonstrated by real-world RTC data, approximately 50% and 25.8% of patients suffered from skull fractures [14] and cerebral contusions [3], respectively, while DBIs were found in approximately 35% of severe-head-injury-related deaths [11].

Int. J. Environ. Res. Public Health 2020, 17, 2392; doi:10.3390/ijerph17072392 www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2020, 17, 2392 2 of 12

Int. J. Environ. Res. Public Health 2020, 17, x 2 of 11 Even if numerous studies have been conducted to investigate mechanisms of blunt-impact head Even if numerous studies have been conducted to investigate mechanisms of blunt-impact head injury, the effect of skull fracture on TBIs has not been clearly understood. However, there is a significant injury, the effect of skull fracture on TBIs has not been clearly understood. However, there is a correlation between skull fractures and TBIs [3,4,14]. Partial impact energy could be absorbed during significant correlation between skull fractures and TBIs [3,4,14]. Partial impact energy could be the skull fractures, which could possibly reduce the energy transferred to the brain tissue [15]. Based absorbed during the skull fractures, which could possibly reduce the energy transferred to the brain on an investigation of the relationship between skull fractures and TBIs from 500 RTC-related head tissue [15]. Based on an investigation of the relationship between skull fractures and TBIs from 500 injuries, Yavuz et al. [3] indicated that the presence of skull fractures could lower the incidence of RTC-related head injuries, Yavuz et al. [3] indicated that the presence of skull fractures could lower TBIs, while TBI-related patients without skull fractures are more likely to die in traffic accidents than the incidence of TBIs, while TBI-related patients without skull fractures are more likely to die in traffic those with skull fractures based on an investigation of 54 cases with RTC-related head injuries by accidents than those with skull fractures based on an investigation of 54 cases with RTC-related head Carson et al. [14]. However, because of the complexity of traffic accident conditions, the physiological injuries by Carson et al. [14]. However, because of the complexity of traffic accident conditions, the structure of the human head, and the pathology of brain injuries, the mechanism of the influence of physiological structure of the human head, and the pathology of brain injuries, the mechanism of the skull fractures on blunt impact is still unclear. influence of skull fractures on blunt impact is still unclear. Therefore, finite element (FE) head–ground impact models were established, referring to an Therefore, finite element (FE) head–ground impact models were established, referring to an existing head–ground impact experiment. The objective of this study is to investigate the influence of existing head–ground impact experiment. The objective of this study is to investigate the influence skull fractures on the intracranial strain response of brain tissue associated with the brain contusion of skull fractures on the intracranial strain response of brain tissue associated with the brain contusion and DBIs following the head–ground impacts. and DBIs following the head–ground impacts. 2. Methods 2. Methods 2.1. Head FE Model 2.1. Head FE Model A 50th-percentile adult human head FE model (HFEM), extracted from the Total HUman Model for Safety (THMUS, Toyota CentralA 50th-percentile R&D Laboratories, adult human Nagakute, head Japan;FE model version (HFEM), 4.01) extracted modeled from by the Total HUman Model LS-DYNA software (versionfor 971), Safety was (THMUS, employed Toyota in this Central study. The R&D most Laboratori essentiales, anatomical Nagakute, features Japan; version 4.01) modeled by of the human head are represented,LS-DYNA including software (version the scalp, 971), skull, was epidural, employed cerebrospinal in this study. fluid, The cerebralmost essential anatomical features white matter, cerebral grayof matter, the human cerebellum head are white represented, matter, cerebellum including graythe scal matter,p, skull, brain epidural, stem, and cerebrospinal fluid, cerebral brain chamber (Figure1). Thewhite skull matter, was modeledcerebral gray as a sandwichmatter, cerebellum structure whit consistinge matter, of twocerebellum layers of gray matter, brain stem, and shell elements and one layerbrain of solid chamber elements, (Figure which 1). presentedThe skull was the outer modeled plastic as materiala sandwich of the structure table of consisting of two layers of the compact bone and the innershell elastic-viscoplasticelements and one layer material of solid of the elements, spongy bone,which respectively presented the (Figure outer2). plastic material of the table The Total HUman Model forof Safetythe compact (THUMS)–head bone and FE the model inner has elastic-viscoplastic been extensively validatedmaterial [of16 ]the and spongy bone, respectively is widely used in the research(Figure field 2). of theThe blunt Total impact-head HUman Model injuries for [17Safety–21]. (THUMS)–head The detailed modeling FE model has been extensively method and parameters ofvalidated the THUMS–head [16] and is FE widely model used are referencedin the resear inch Toyota field of Motor the blunt Corporation impact-head injuries [17−21]. The documentation [16] and Kimparadetailed et modeling al. [22]. method and parameters of the THUMS–head FE model are referenced in Toyota FE damage modelingMotor was implemented Corporation indocumentation the skull of the [16] original and Kimpara THUMS–head et al. [22]. FE model in order to predict the possible skullFE fracture damage under modeling head bluntwas implemented impact. According in the toskull the publishedof the original studies THUMS–head FE model in associated with skull fractureorder behavior to predict and thethe following possible headskull impactfracture loading under conditionshead blunt employed impact. According in to the published this study [23–25], materialstudies properties associated of the skullwith elementskull fracture damage behavior modeling and were the assignedfollowing as head yield impact loading conditions stresses of 95.88 and 4.794employed MPa and plasticin this strainstudy failure[23−25], thresholds material properties of 0.02 and of 0.006, the skull respectively, element damage modeling were for compact bone and spongyassigned bone. as yield stresses of 95.88 and 4.794 MPa and plastic strain failure thresholds of 0.02 and 0.006, respectively, for compact bone and spongy bone.

FigureFigure 1. 1. THUMS–headTHUMS–head FE FE model. model. Figure 2. Three-layer structures of skull.

2.2. Skull Fracture Prediction Performance Validation

Int. J. Environ. Res. Public Health 2020, 17, x 2 of 11

Even if numerous studies have been conducted to investigate mechanisms of blunt-impact head injury, the effect of skull fracture on TBIs has not been clearly understood. However, there is a significant correlation between skull fractures and TBIs [3,4,14]. Partial impact energy could be absorbed during the skull fractures, which could possibly reduce the energy transferred to the brain tissue [15]. Based on an investigation of the relationship between skull fractures and TBIs from 500 RTC-related head injuries, Yavuz et al. [3] indicated that the presence of skull fractures could lower the incidence of TBIs, while TBI-related patients without skull fractures are more likely to die in traffic accidents than those with skull fractures based on an investigation of 54 cases with RTC-related head injuries by Carson et al. [14]. However, because of the complexity of traffic accident conditions, the physiological structure of the human head, and the pathology of brain injuries, the mechanism of the influence of skull fractures on blunt impact is still unclear. Therefore, finite element (FE) head–ground impact models were established, referring to an existing head–ground impact experiment. The objective of this study is to investigate the influence of skull fractures on the intracranial strain response of brain tissue associated with the brain contusion and DBIs following the head–ground impacts.

2. Methods

2.1. Head FE Model A 50th-percentile adult human head FE model (HFEM), extracted from the Total HUman Model for Safety (THMUS, Toyota Central R&D Laboratories, Nagakute, Japan; version 4.01) modeled by LS-DYNA software (version 971), was employed in this study. The most essential anatomical features of the human head are represented, including the scalp, skull, epidural, cerebrospinal fluid, cerebral white matter, cerebral gray matter, cerebellum white matter, cerebellum gray matter, brain stem, and brain chamber (Figure 1). The skull was modeled as a sandwich structure consisting of two layers of shell elements and one layer of solid elements, which presented the outer plastic material of the table of the compact bone and the inner elastic-viscoplastic material of the spongy bone, respectively (Figure 2). The Total HUman Model for Safety (THUMS)–head FE model has been extensively validated [16] and is widely used in the research field of the blunt impact-head injuries [17−21]. The detailed modeling method and parameters of the THUMS–head FE model are referenced in Toyota Motor Corporation documentation [16] and Kimpara et al. [22]. FE damage modeling was implemented in the skull of the original THUMS–head FE model in order to predict the possible skull fracture under head blunt impact. According to the published studies associated with skull fracture behavior and the following head impact loading conditions employed in this study [23−25], material properties of the skull element damage modeling were Int. J. Environ. Res. Public Health 2020, 17, 2392 3 of 12 assigned as yield stresses of 95.88 and 4.794 MPa Int.and J. Environ.plastic Res.strain Public failure Health thresholds 2020, 17, x of 0.02 and 0.006, 3 of 11 respectively, for compact bone and spongy bone. The skull fracture prediction performance of the improved THUMS–head FE model was evaluated via the reconstruction of an existing head–ground impact experiment carried out by Jiang et al. [26]. The original experimental equipment included an accelerator, asphalt road model, a high- speed camera, and an accelerating device (Figure 3). As demonstrated in the referenced study, the cadaver head was wrapped with white clothes and attached to the accelerating device by several seatbelts; the head was then accelerated to 44.1 km/h and impacted against the oblique ground at the occipital region; finally, the time history of the head acceleration at the foramen magnum region and the skull fracture were obtained through data acquisition system and CT scanner, respectively. A FE simulation model was established according to the referenced experimental data in LS- DYNA software, as shown in Figure 4. The ground with an asphalt surface (15 mm thick) and a concrete roadbed (45 mm thick) was modeled as an equivalent road using linear elastic solid elements Figure 1. THUMS–head FE model. FigureFigure 2. Three-layer2. Three-layer structures structures of skull.of skull. [27] (Figure 4). The material parameters of the FE road model that have been applied in the pedestrian 2.2. Skull Fracture Predictionhead–ground Performance impact Validation simulations were assigned [28] (Table 1). An initial velocity of 44.1 km/h was 2.2. Skull Fracture Prediction ThePerformance skull fracture Validation predictionassigned performance to ofthe improvedhead THUMS–head model, FE modeland was evaluatedthe key word of via the reconstruction of*AUTOMATIC_CONTACT_SURFACE_TO_SURFACE an existing head–ground impact experiment carried out was by Jiangemployed et al. [for26]. the head–ground contact The original experimentalwith equipment a friction included coefficient an accelerator, of 0.58 [29,30]. asphalt road model, a high-speed camera,

and an accelerating device (Figure3). As demonstrated in the referenced study, the cadaver head was Table 1. Material properties of asphalt concrete road FE model. wrapped with white clothes and attached to the accelerating device by several seatbelts; the head was then accelerated to 44.1 km/h and impacted against theDensity/ oblique groundElasticity at the occipital region; ﬁnally, Structure Poisson’s Ratio Material Model the time history of the head acceleration at the foramen(kg/m magnum3) regionModulus and (MPa) the skull fracture were obtained through data acquisitionasphalt system and CT scanner,1600 respectively. 5400 0.35 linear elastic roadbed 1600 9300 0.35 linear elastic

Figure 3. Head–groundHead–ground impact experiment. Figure 4. Setup of head-ground impact FE model. Black solid line is the parallel line of the vertical A FE simulation model was established according to the referenced experimental data in LS-DYNA plane, and red solid line is that of the brain sagittal software, as shown in Figure4. The ground with an asphalt surface (15 mm thick) and a concrete plane after rotating 8°. Red dotted line is located in roadbed (45 mm thick) was modeled as an equivalent road using linear elastic solid elements [27] the coronal plane of the head. The size of the ground (Figure4). The material parameters of the FE road model that have been appliedis 500 × in 500 the × 60 pedestrian mm. head–ground impact simulations were assigned [28] (Table1). An initial velocity of 44.1 km /h was assigned to the head model, and the key word of *AUTOMATIC_CONTACT_SURFACE_TO_SURFACE was employed for the head–ground contact with a friction coeﬃcient of 0.58 [29,30].

Figure 5. Comparison of skull fracture patterns Figure 6. Comparison of head resultant acceleration between the (A) experiment and (B) simulation. between the experiment and simulation.

Int. J. Environ. Res. Public Health 2020, 17, x 3 of 11

The skull fracture prediction performance of the improved THUMS–head FE model was evaluated via the reconstruction of an existing head–ground impact experiment carried out by Jiang et al. [26]. The original experimental equipment included an accelerator, asphalt road model, a high- speed camera, and an accelerating device (Figure 3). As demonstrated in the referenced study, the cadaver head was wrapped with white clothes and attached to the accelerating device by several seatbelts; the head was then accelerated to 44.1 km/h and impacted against the oblique ground at the occipital region; finally, the time history of the head acceleration at the foramen magnum region and the skull fracture were obtained through data acquisition system and CT scanner, respectively. A FE simulation model was established according to the referenced experimental data in LS- DYNA software, as shown in Figure 4. The ground with an asphalt surface (15 mm thick) and a Int. J. Environ. Res. Public Health 2020, 17, x 3 of 11 concrete roadbed (45 mm thick) was modeled as an equivalent road using linear elastic solid elements [27] (Figure 4). The material parameters of the FE road modelThe skull that havefracture been predictionapplied in theperformance pedestrian of the improved THUMS–head FE model was head–ground impact simulations were assigned [28]evaluated (Table via1). Anthe initialreconstruction velocity of 44.1an existing km/h was head–ground impact experiment carried out by Jiang assigned to the head model,et al. [26].and The originalthe experimentkey al wordequipment ofincluded an accelerator, asphalt road model, a high- *AUTOMATIC_CONTACT_SURFACE_TO_SURFACEspeed was camera, employed and an for accelerating the head–ground device contact(Figure 3). As demonstrated in the referenced study, the with a friction coefficient of 0.58 [29,30]. cadaver head was wrapped with white clothes and attached to the accelerating device by several seatbelts; the head was then accelerated to 44.1 km/h and impacted against the oblique ground at the Table 1. Material properties of asphalt concrete road FE model. occipital region; finally, the time history of the head acceleration at the foramen magnum region and Density/ Elasticitythe skull fracture were obtained through data acquisition system and CT scanner, respectively. Structure Poisson’s Ratio Material Model (kg/m3) Modulus (MPa)A FE simulation model was established according to the referenced experimental data in LS- asphalt Int. J.1600 Environ. Res. Public Health 54002020 , 17, 2392 0.35 linear elastic 4 of 12 Int. J. Environ. Res. Public Health 2020, 17, x DYNA software, as shown in Figure 4. The3 groundof 11 with an asphalt surface (15 mm thick) and a roadbed 1600 9300concrete roadbed 0.35(45 mm thick) waslinear modeled elastic as an equivalent road using linear elastic solid elements The skull fracture prediction performance [27]of the (Figure improved 4). The THUMS–headmaterial parameters FE model of the FEwas ro ad model that have been applied in the pedestrian evaluated via the reconstruction of an existing head–groundhead–ground impact impact experiment simulations carried were out assigned by Jiang [28] (Table 1). An initial velocity of 44.1 km/h was et al. [26]. The original experimental equipment includedassigned an accelerator,to asphaltthe roadhead model, a model,high- and the key word of speed camera, and an accelerating device (Figure *AUTOMATIC_CONTACT_SURFACE_TO_SURFACE3). As demonstrated in the referenced study, the was employed for the head–ground contact cadaver head was wrapped with white clothes andwith attached a friction to coefficientthe accelerating of 0.58 device [29,30]. by several seatbelts; the head was then accelerated to 44.1 km/h and impacted against the oblique ground at the occipital region; finally, the time history of the head acceleration at the foramenTable 1. magnumMaterial properties region and of asph alt concrete road FE model. the skull fracture were obtained through data acquisition system and CT scanner,Density/ respectively. Elasticity Structure 3 Poisson’s Ratio Material Model A FE simulation model was established according to the referenced experimental(kg/m ) dataModulus in LS- (MPa) DYNA software, as shown in Figure 4. The ground with asphaltan asphalt surface (151600 mm thick) and 5400a 0.35 linear elastic concreteFigure roadbed 3. Head–ground (45 mm thick) impactFigure was experiment. modeled 4. Setup ofas head-ground an equivalentFigure 4.roadbed impact Setup road FE usingof model.head-ground linear Black elastic1600 solidimpact solid line FE iselements model. the parallel 9300 line of the vertical 0.35 linear elastic [27] (Figure 4). The material parametersplane, and of red the solid FE lineroadBlack is model that solid of thethat line brain have is sagittal the been parallel planeapplied afterline in rotatingofthe the pedestrian vertical 8◦. Red dotted line is located in the coronal plane of theplane, head. Theand sizered ofsolid the line ground is that is 500 of the500 brain60 sagittal mm. head–ground impact simulations were assigned [28] (Table 1). An initial velocity of× 44.1× km/h was plane after rotating 8°. Red dotted line is located in assigned to the head model,Table 1. Materialand propertiesthe of asphaltkey concreteword road FE model.of the coronal plane of the head. The size of the ground *AUTOMATIC_CONTACT_SURFACE_TO_SURFACE was employed for the head–ground contact Densityis 500/ × 500 × 60 mm.Elasticity with a friction coefficient of 0.58 [29,30].Structure Poisson’s Ratio Material Model (kg/m3) Modulus (MPa)

Table 1. Materialasphalt properties of asph 1600alt concrete road 5400 FE model. 0.35 linear elastic roadbed 1600 9300 0.35 linear elastic Density/ Elasticity Structure Poisson’s Ratio Material Model (kg/m3) Modulus (MPa) The predicted skull fracture and head acceleration at the foramen magnum are illustrated in asphalt 1600 5400 0.35 linear elastic roadbed Figures16005 and6, respectively. 9300 TheFigure skull 3. fracture Head–ground 0.35 predicted impact atlinear the experiment. head elastic impact locationFigure (occipital4. Setup of region) head-ground impact FE model. correlated well with the corresponding skull fracture observed in the referencedBlack experiment solid line (Figure is the 5parallel). line of the vertical As illustrated in Figure6, the predicted time history of the resultant head accelerationplane, and wasred solid also wellline is that of the brain sagittal consistent with the referenced experimental data, with peak values of 307.79 andplane 281.32 after g.rotating Despite 8°. theRed dotted line is located in missed prediction of the skull fracture at the temporoparietal region, the currentthe coronal head model plane of indeed the head. The size of the ground applied for the following simulation. is 500 × 500 × 60 mm. Figure 5. Comparison of skull fracture patterns Figure 6. Comparison of head resultant acceleration between the (A) experiment and (B) simulation. between the experiment and simulation.

Figure 3. Head–ground impact experiment. Figure 4. Setup of head-ground impact FE model. Black solid line is the parallel line of the vertical plane, and red solid line is that of the brain sagittal plane after rotating 8°. Red dotted line is located in the coronal plane of the head. The size of the ground Figure 5. Comparisonis of500 skull × 500 fracture × 60 mm. patterns between the (A) experiment and (B) simulation. Figure 5. Comparison of skull fracture patterns Figure 6. Comparison of head resultant acceleration between the (A) experiment and (B) simulation. between the experiment and simulation.

Figure 5. Comparison of skull fractureFigure 6.patternsComparison Figure of head 6. Comparison resultant acceleration of head resultant between acceleration the experiment and simulation. between the (A) experiment and (B) simulation. between the experiment and simulation.

Int. J. Environ. Res. Public Health 2020, 17, x 4 of 11

The predicted skull fracture and head acceleration at the foramen magnum are illustrated in Figures 5 and 6, respectively. The skull fracture predicted at the head impact location (occipital region) correlated well with the corresponding skull fracture observed in the referenced experiment (Figure 5). As illustrated in Figure 6, the predicted time history of the resultant head acceleration was also Int.well J. Environ. consistent Res. Public with Health the 2020referenced, 17, 2392 experimental data, with peak values of 307.79 and 281.32 5g. of 12 Despite the missed prediction of the skull fracture at the temporoparietal region, the current head model indeed applied for the following simulation. 2.3. Head–Ground Impact Simulation Matrix 2.3.A Head–Ground matrix of Impact head–ground Simulation impact Matrix simulation was performed using the current improved THUMS–headA matrix FE of model head–ground and the originalimpact THUMS–headsimulation was FE performed model for ausing quantitative the current comparison improved of the predictedTHUMS–head intracranial FE model dynamic and the responses original underTHUMS–head three head FE impactmodel for locations: a quantitative frontal, comparison lateral–parietal, of andthe occipital predicted regions. intracranial Here, thedynamic current responses improved under THUMS–head three head FE impact model locations: was assigned frontal, as thelateral– fracture model,parietal, while and the occipital original regions. THUMS–head Here, the FE current model improved was assigned THUMS–head as the non-fracture FE model model.was assigned Three as head impactthe fracture velocities, model, 25, 35,while and the 45 original km/h (low, THUMS–he medium,ad and FE high)model were was assignedassigned toas eachthe non-fracture model of three impactmodel. locations. Three head Thus, impact a total velocities, of 18 simulations 25, 35, and 45 were km/h performed. (low, medium, The detailedand high) boundary were assigned conditions to areeach illustrated model of in three Figure impact7. locations. Thus, a total of 18 simulations were performed. The detailed boundary conditions are illustrated in Figure 7.

(a) frontal impact (b) parietal impact (c) occipital impact

FigureFigure 7. 7.Illustrations Illustrations ofof head–groundhead–ground mode modell for for three three impact impact locations. locations. Red Red dotted dotted line line is located is located in in thethe coronal coronal plane plane of of the the headhead forfor ((a)) and ( c)) and and in in the the mid-sagittal mid-sagittal plane plane of of the the head head for for (b). (b ).

ToTo simulate simulate the the same same riskrisk ofof brain injuries in in models models of of three three impact impact locations locations at the at the same same impact impact velocity,velocity, di differentﬀerent impact impact anglesangles ofof thethe head were designed. designed. Here, Here, the the Brain Brain Injury Injury Criteria Criteria (BrIC) (BrIC) werewere calculated. calculated. TheThe BrIC BrIC was was developed developed byby Takhounts et al. al. [31], [31], based based on on the the mechanism mechanism of ofthe the head head rotational rotational motionmotion for for brain brain injuries. injuries. Furthermore, angular angular veloci velocityty is is the the only only component component of the of the BrIC. BrIC. Therefore, Therefore, angularangular velocities velocities of ofthe the headhead modelmodel in three three axes axes we werere extracted, extracted, and and BrIC BrIC were were calculated calculated to assess to assess thethe risk risk of of brain brain injury. injury. BrIC BrIC areare expressedexpressed as follows: follows: s !2 !2 !2 = ωx + ωy + ω z (1) BrIC = + + (1) ωxC ωyC ωzC wherewhereω xω,xω, ωy,y, and andω ωzz areare maximummaximum angular angular velocities velocities about about the the XX-, -,Y-,Y -,and and Z-axesZ-axes respectively; respectively; ωxCω, xC, ωyCωyC, and, andω ωzCzCare are the the critical critical angular angular velocities velocities in in their their respective respective directions, directions, which which are are 66.25, 66.25, 56.45, 56.45, and 42.87and rad42.87/s rad/s [31]. [31]. The The BrIC BrIC values values at 50%at 50% risk risk of of the the Abbreviated Abbreviated InjuryInjury Scale (AIS) (AIS) 2+, 2+ and, and 4+ 4brain+ brain injuriesinjuries are are 0.5 0.5 and and 1, 1, respectively respectively [[31].31].

2.4.2.4. Intracranial Intracranial Dynamic Dynamic ResponseResponse and Data Analysis Analysis

2.4.1.2.4.1. Intracranial IntracranialDynamic Dynamic ResponsesResponses TheThe maximum maximum principalprincipal strainstrain (MPS) and and cumulative cumulative strain strain damage damage measure measure (CSDM) (CSDM) were were calculatedcalculated and and assigned assigned as as the the injury injury indexes indexes for for the the proper proper prediction prediction of cerebral of cerebral contusion contusion and and diffuse braindiffuse injury, brain respectively. injury, respectively. The MPS The has MPS been has suggested been suggested as an effi ascient an efficient injury index injury of index cerebral of cerebral contusion undercontusion blunt under impact blunt [32,33 impact]. In this [32,33]. study, In 18 this elements study, in18 aelements cube region in a in cube which region the maximumin which the strain response appeared in the brain impact region were selected for a calculation of average peak MPS. The CSDM has long been used as an essential injury index for the prediction of the DBI caused by brain tissue deformation [34,35], and is defined as the volume percentage of elements with the peak MPS exceeding a certain strain threshold for the target regions, as follows:

V (ε εc) CSDM = 1 ≥ (2) V Int. J. Environ. Res. Public Health 2020, 17, 2392 6 of 12 Int. J. Environ. Res. Public Health 2020, 17, x 5 of 11 wheremaximumε1 is thestrain elemental response peak appeared MPS and in theεc the brain defined impact strain region threshold. were selected The white for a mattercalculation of the of cerebrumaverage peak and brainstem MPS. The wasCSDM selected has long as the been target used regions as an foressential the CSDM injury calculation, index for the and prediction the current of strainthe DBI threshold caused was by setbrain to 0.15tissue [34 –deformation36]. [34,35], and is defined as the volume percentage of elements with the peak MPS exceeding a certain strain threshold for the target regions, as follows: 2.4.2. Data Analysis ( ≥) Differences in average peak MPS and CSDM = between the fracture and non-fracture models were(2) quantitatively analyzed by one-way analysis of variance (one-way ANOVA, Office Excel 2016). First, thewhere MPS ε time1 is the history elemental curves peak of the MPS selected and ε 18c the elements defined were strain obtained threshold. from The each white simulation; matter then,of the one-waycerebrum ANOVA and brainstem was performed was selected to evaluate as the thetarget diff regionserence between for the CSDM the average calculation, peak MPS and ofthe the current two headstrain models threshold under was the set same to 0.15 impact [34−36]. conditions. The difference between the two groups of CSDM predicted by the corresponding two head models was also evaluated by using the one-way ANOVA. The2.4.2. F-test Data was Analysis conducted to determine whether the skull fracture had a statistically meaningful effect on the average peak MPS and CSDM results: When the p-value is lower than 0.05, it can be said that a Differences in average peak MPS and CSDM between the fracture and non-fracture models were significant effect exists; otherwise, there is no such significant effect. quantitatively analyzed by one-way analysis of variance (one-way ANOVA, Office Excel 2016). First, 3.the Results MPS time history curves of the selected 18 elements were obtained from each simulation; then, one-way ANOVA was performed to evaluate the difference between the average peak MPS of the 3.1.two Skull head Fractures models andunder Head the Kinematic same impact Responses conditions. The difference between the two groups of CSDM predicted by the corresponding two head models was also evaluated by using the one-way ANOVA. Figure8 shows that varying degrees of fracture are predicted in these impact regions with di fferent The F-test was conducted to determine whether the skull fracture had a statistically meaningful effect head impact velocities. In general, there were distinct differences in fracture patterns in different skull on the average peak MPS and CSDM results: When the p-value is lower than 0.05, it can be said that regions. For 25 km/h, only small linear skull fractures were predicted in the frontal and occipital a significant effect exists; otherwise, there is no such significant effect. regions (Figure8a,g, respectively); but no fracture was predicted in the parietal region (Figure8d). Severe linear skull fractures and multiple skull fractures were predicted in the frontal and occipital 3. Results regions at 35 and 45 km/h, respectively (Figure8b,c,h,i). However, severely depressed skull fractures appeared3.1. Skull inFractures the parietal and Head region Kinematic with the Responses head impact velocities of 35 and 45 km/h (Figure8e,f).

Figure 8. Figure 8.Fracture Fracture patterns patterns of of head head fracture fracture model model for for three three locations locations under under three three impact impact velocities. velocities. (a–c) Frontal impact, (d–f) parietal impact, and (g–i) occipital impact; the impact velocities are 25, 35, (a–c) Frontal impact, (d–f) parietal impact, and (g–i) occipital impact; the impact velocities are 25, 35, 45 km/h from left to right, respectively; the skull fracture is represented in black. 45 km/h from left to right, respectively; the skull fracture is represented in black.

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Figure 8 shows that varying degrees of fracture are predicted in these impact regions with different head impact velocities. In general, there were distinct differences in fracture patterns in different skull regions. For 25 km/h, only small linear skull fractures were predicted in the frontal and occipital regions (Figure 8a,g, respectively); but no fracture was predicted in the parietal region (Figure 8d). Severe linear skull fractures and multiple skull fractures were predicted in the frontal and occipital regions at 35 and 45 km/h, respectively (Figure 8b,c,h,i). However, severely depressed skull fractures appeared in the parietal region with the head impact velocities of 35 and 45 km/h (Figure 8e,f). Figure 9 shows the comparison of the resultant acceleration (filter of 1000 Hz) with a parietal Figure 9. Comparison ofFigure resultant 9. Comparison acceleration of (ﬁlter resultant of 1000 acceleration Hz) with (filter parietal of impactFigure contrecoup 10. BrIC side of the non-fracture model for three impact contrecoup side between fracture and non-fracture models at 35 km/h. The predicted resultant between fracture and non-fracture1000 Hz) with models parietal at 35 impact km/h. contrecoup side between impacts at three impact velocities. Dotted lines are 50% acceleration of the fracture model was 19.8% lower than the corresponding value of the non-fracture fracture and non-fracture models at 35 km/h. risk of AIS 2+ and AIS 4+ brain injuries from the bottom model. Figure 10 shows the BrIC of the non-fracture model for three impact locations under three impact up. Figure 10 shows the BrICvelocities. of the Thenon-fracture calculated mo averagedel for three BrIC impact values locations of the three under impacts three atimpact 25, 35, and 45 km/h were 0.78, velocities. The calculated1.13, average and BrIC 1.41, respectively.values of the Accordingthree impacts to the at BrIC25, 35, risk and curves 45 km/h of brain were injuries 0.78, [29], the AIS 2+ injuries 1.13, and 1.41, respectively.could According be realized to the in BrIC all simulations. risk3.2. Straincurves Responses of brain injuries of Brain [29], Tissue the AIS 2+ injuries could be realized in all simulations. Figure 11 shows the MPS contour for occipital impacts at three impact velocities. At medium and high impact velocities, the brain of the fracture model exhibited severe extrusion deformation, which resulted in relatively higher MPS responses (Figure 11b,c). The average peak MPS values of the selected elements of the fracture model are lower than the corresponding values of the non-fracture model at 25 and 35 km/h, as illustrated in Figure 12. For 25 km/h, compared with MPS values of the non-fracture model, corresponding values of the fracture model were 45.7%, 0.3%, and 38.0% lower, for the frontal, parietal, and occipital impacts, respectively. Similarly, for 35 km/h, the MPS values of the fracture model were 1.5%, 4.5%, and 4.5% lower than the corresponding values of the non-fracture model, respectively. Inversely, the average peak MPS values of the fracture model were generally higher than the corresponding values of the non-fracture model at 45 km/h. For 45 km/h, compared with MPS values of the non-fracture model, corresponding Figure 9. Comparison of resultantFigure acceleration 10. BrIC (filter of the of non-fractureFigure 10. modelBrIC of for the three non-fracture impacts at modelthree impact for three velocities. Dotted lines are values of the fracture model were 6.7%, −22.8%, and 16.1% higher for the frontal, parietal, and 1000 Hz) with parietal impact contrecoup50% risk sideof AIS between 2+ and AISimpacts 4+ brainat three injuries impact from velocities. the bottom Dotted up. lines are 50% occipital impacts, respectively. fracture and non-fracture models at 35 km/h. risk of AIS 2+ and AIS 4+ brain injuries from the bottom 3.2. Strain Responses of Brain TissueAs shown in Figure 12, there was a significant effect of the skull fracture on average MPS values; up. Figure 11 shows theexcept MPS contourfor the parietal for occipital impact impacts at 25 km/h at three (p = impact0.975), velocities.the p-values At were medium less than 0.01 for frontal and and high impact velocities,occipital the brain impacts. of the However, fracture model there exhibitedwas no significant severe extrusion effect of deformation, skull fractures on the average MPS 3.2. Strain Responses of Brainwhich Tissue resulted in relativelyvalues higher for MPSall simulation responses (Figureat 35 km/h 11b,c). (p > 0.05). Inversely, significant effects were observed for all simulations at 45 km/h with p-values less than 0.01. Figure 11 shows the MPSThe contour average for peakoccipital MPS im valuespacts at of three the selected impact elementsvelocities. of At the medium fracture model are lower than and high impact velocities,the the corresponding brain of the fractu valuesre of model the non-fracture exhibited severe model extrusion at 25 and deformation, 35 km/h, as illustrated in Figure 12. which resulted in relativelyFor higher 25 km MPS/h, compared responses with (Figure MPS 11b,c). values of the non-fracture model, corresponding values of the The average peak MPSfracture values model of the were selected 45.7%, elem 0.3%,ents andof the 38.0% fracture lower, model for are the lower frontal, than parietal, the and occipital impacts, corresponding values of therespectively. non-fracture Similarly, model forat 25 35 and km /35h, km/h, the MPS as valuesillustrated of the in fractureFigure 12. model For 25 were 1.5%, 4.5%, and 4.5% km/h, compared with MPSlower values than of the the corresponding non-fracture model, values ofcorresponding the non-fracture values model, of the respectively. fracture Inversely, the average model were 45.7%, 0.3%, andpeak 38.0% MPS lo valueswer, for of the frontal, fracture parietal, model wereand occipital generally impacts, higher respectively. than the corresponding values of the Similarly, for 35 km/h, thenon-fracture MPS values model of the at fracture 45 km/ h.model For 45were km /1.5%,h, compared 4.5%, and with 4.5% MPS lower values than of the non-fracture model, corresponding values of the fracture model were 6.7%, 22.8%, and 16.1% higher for the frontal, the corresponding values of the non-fracture model, respectively. Inversely, the average− peak MPS values of the fracture modelparietal, were andgenerally occipital higher impacts, than the respectively. corresponding values of the non-fracture model at 45 km/h. For 45 km/h, compared with MPS values of the non-fracture model, corresponding values of the fracture model were 6.7%, −22.8%, and 16.1% higher for the frontal, parietal, and occipital impacts, respectively. As shown in Figure 12, there was a significant effect of the skull fracture on average MPS values; except for the parietal impact at 25 km/h (p = 0.975), the p-values were less than 0.01 for frontal and occipital impacts. However, there was no significant effect of skull fractures on the average MPS values for all simulation at 35 km/h (p > 0.05). Inversely, significant effects were observed for all simulations at 45 km/h with p-values less than 0.01.

Int. J. Environ. Res. Public Health 2020, 17, 2392 8 of 12

As shown in Figure 12, there was a significant effect of the skull fracture on average MPS values; except for the parietal impact at 25 km/h (p = 0.975), the p-values were less than 0.01 for frontal and occipital impacts. However, there was no significant effect of skull fractures on the average MPS values for all simulation at 35 km/h (p > 0.05). Inversely, significant effects were observed for all simulations atInt.Int. 45 J. J. Environ. kmEnviron./h with Res. Res. Public Publicp-values Health Health less 2020 2020 than, ,17 17, ,x x 0.01. 77 of of 11 11

Figure 11. MPS contour for occipital impacts at three impact velocities. (a–c) Fracture model, Figure 11. MPS contour for occipital impacts at three impact velocities. (a–c) Fracture model, (d–f) (d–fFigure) non-fracture 11. MPS contour model; impactfor occipital velocities impacts are 25,at 35,three and impact 45 km /velocities.h from left (a–c to right;) Fracture dotted model, line box (d–f is) atnon-fracturenon-fracture the peak MPS model;model; region impactimpact of impact. velocitiesvelocities areare 25,25, 35,35, andand 4545 km/hkm/h fromfrom leftleft toto right;right; dotteddotted lineline boxbox isis atat thethe peak peak MPS MPS region region of of impact. impact.

((aa)) frontalfrontal impactimpact ( (bb)) parietalparietal impactimpact

((cc)) occipitaloccipital impactimpact

FigureFigure 12.12.12. AverageAverage peakpeak MPSMPS fromfrom thethe impactimpact regionregion ofof threethreethree impact impactimpact modelsmodelsmodels underunderunder threethreethree impact impactimpact velocities.velocities.velocities. ShownShownShown are areare the thethe average averageaverage and andand standard standardstandard deviations devideviationsations of of peakof peakpeak MPS MPSMPS response respresponseonse of 18 ofof elements 1818 elementselements in the inin selectedthethe selectedselected region. region.region. Asterisks AsterisksAsterisks on fracture onon fracturefracture and non-fractureandand nonnon-fracture-fracture models modelsmodels indicate indicateindicate the significant thethe significantsignificant level oflevellevel skull ofof fractureskullskull fracturefracture effect on effecteffect MPS on on peaks MPSMPS at peakspeaks each velocity; atat eacheach velocity; *velocity; denotes * significant* denotes denotes significantsignificant effect, that effect, is,effect,0.01 thatthat< p is, is,0.05 0.010.01; ** << p denotesp ≤≤ 0.05;0.05; ≤ extremely**** denotesdenotes significant extremelyextremely e ffsignificantsignificantect, that is, effect,effect,p 0.01. thatthat (a is,)is, frontal pp ≤≤ 0.01.0.01. impact ((aa)) (frontalbfrontal) parietal impactimpact impact ((bb)) ( cparietalparietal) occipital impactimpact impact. ((cc)) ≤ occipitaloccipital impact. impact.

3.3.3.3. CSDMCSDM CSDMCSDM valuesvalues ofof thethe whitewhite mattermatter ofof thethe cerebrcerebrumum andand brainstembrainstem forfor modelsmodels ofof threethree impactimpact locationslocations areare illustratedillustrated inin FigureFigure 13.13. CSDMCSDM valuvalueses ofof thethe fracturefracture modemodell werewere lowerlower thanthan thethe correspondingcorresponding valuesvalues ofof thethe non-fracturenon-fracture model.model. TheThe averageaverage CSDMCSDM valuesvalues andand standardstandard deviationdeviation ofof threethree impactimpact velocitiesvelocities areare illustratedillustrated inin FiFiguregure 14.14. ComparedCompared withwith CSDMCSDM valuesvalues ofof thethe non-non- fracturefracture model,model, correspondingcorresponding valuesvalues ofof thethe fractufracturere modelmodel werewere decreaseddecreased byby anan averageaverage ofof 49.3%,49.3%,

Int. J. Environ. Res. Public Health 2020, 17, 2392 9 of 12

3.3. CSDM CSDM values of the white matter of the cerebrum and brainstem for models of three impact locations are illustrated in Figure 13. CSDM values of the fracture model were lower than the correspondingInt. J. Environ. Res. values Public Health of the 2020 non-fracture, 17, x model. The average CSDM values and standard deviation8 ofof 11 three impact velocities are illustrated in Figure 14. Compared with CSDM values of the non-fracture 55.0%, and 45.2% at 25, 35, and 45 km/h, respectively. In addition, significant differences could be model,Int. J. corresponding Environ. Res. Public valuesHealth 2020 of, the17, x fracture model were decreased by an average of 49.3%, 55.0%,8 of 11 and 45.2%observed at 25, for 35, simulations and 45 km at/h, 35 respectively. km/h (p = 0.027) In addition, and 45 km/h signiﬁcant (p = 0.022). diﬀerences could be observed for simulations55.0%, and at 3545.2% km /ath (25,p = 35,0.027) and 45 and km/h, 45 km respectively./h (p = 0.022). In addition, significant differences could be observed for simulations at 35 km/h (p = 0.027) and 45 km/h (p = 0.022).

Figure 13. Comparison of cumulative strain damage measure (CSDM) between fracture and non- Figure 13. Comparison of cumulative strain damage measure (CSDM) between fracture and non-fracture fractureFigure models 13. Comparison (strain threshold of cumulative of 0.15). strain damage measure (CSDM) between fracture and non- models (strain threshold of 0.15). fracture models (strain threshold of 0.15).

FigureFigureFigure 14.14. 14.ComparisonComparison Comparison ofof of averageaverage average CSDMCSDM CSDM betweenbetween head head fr fracturefractureacture and andand non-fractu non-fracturenon-fracture models.re models.models. Shown ShownShown are areare averageaverageaverage CSDMCSDM CSDM andand and standardstandard standard deviationdeviation deviation of of thethe whitewhitwhitee matter mattermatter of ofof the thethe cerebrum cerebrumcerebrum and andand brainstem brainstembrainstem for three forfor threethree impactimpactimpact velocities.velocities. velocities. AsterisksAsterisks Asterisks onon on fracturefracture fracture and andand non-fracturenon-fractureture models modelsmodels indicate indicateindicate the thethe significant significantsignificant level levellevel of skull ofof skullskull fracturefracture effect effect on on CSDMs CSDMs at at each each velocity; velocity; * * denotes denotes significantsignificant effect, effect, that that is, is, p p≤ 0.05.0.05. fracture effect on CSDMs at each velocity; * denotes significant effect, that is, p≤ ≤ 0.05. 4. Discussion4. Discussion 4. Discussion TheThe objective objective of of this this studystudy is is to to investigate investigate the theinfluence influence of the of skull the fracture skull fracture on TBIs under on TBIs head- under The objective of this study is to investigate the influence of the skull fracture on TBIs under headhead-groundground impacts. impacts. A total A total of 18 of head–ground 18 head–ground impa impactct simulations simulations were conducted were conducted by applying by applying the ground impacts. A total of 18 head–ground impact simulations were conducted by applying the the newlynewly improved THUMS–head THUMS–head FE FE model model with with skull skull element element damage damage modeling modeling and and the theoriginal original newly improved THUMS–head FE model with skull element damage modeling and the original THUMS–headTHUMS–head FE FE model, model, while while three three head head impactimpact locations (frontal, (frontal, parietal, parietal, and and occipital occipital regions) regions) THUMS–headand three impact FE model, velocities while (25, three35, and head 45 km/h) impact were locations employed. (frontal, As the parietal, impact location and occipital was varied, regions) and three impact velocities (25, 35, and 45 km/h) were employed. As the impact location was varied, andthe three BrIC impact values velocities of three impact (25, 35, models and 45 were km/h) calcul wereated employed. to assess whether As the impactthe risk location of brain wasinjuries varied, the BrIC values of three impact models were calculated to assess whether the risk of brain injuries was the wasBrIC consistent values of at three the same impact velocity. models A 50% were risk calcul of brainated injury to assess predicted whether by the the three risk impact of brain models injuries consistent at the same velocity. A 50% risk of brain injury predicted by the three impact models was waswas consistent generally at consistentthe same velocity.at the same A 50% velocity risk of(F igurebrain 10).injury Therefore, predicted three by theimpact three models impact were models generally consistent at the same velocity (Figure 10). Therefore, three impact models were utilized to wasutilized generally to investigate consistent the at influence the same of velocityskull fractures (Figure on 10).brain Therefore, injuries, which three are impact suitable models for this were investigate the influence of skull fractures on brain injuries, which are suitable for this study. utilizedstudy. to investigate the influence of skull fractures on brain injuries, which are suitable for this As illustratedAs illustrated in in Figure Figure8, 8, di differentfferent head head impactimpact locations locations could could result result in indifferent different skull skull fracture fracture study. patternspatterns [3,37 [3,37–39−].39]. Linear Linear fractures fractures in in frontal frontal [[37]37] and occi occipitalpital regions regions and and depressed depressed fractures fractures in the in the As illustrated in Figure 8, different head impact locations could result in different skull fracture parietalparietal region region were were found found at higher at higher velocities velocities [3], and [3], fractureand fracture patterns patterns were observedwere observed to be consistentto be patternsconsistent [3,37 −with39]. Linearthose commonly fractures inreported frontal in[37] the and literature. occipital In regions addition, and the depressed predicted fractures resultant in the parietalacceleration region of were the fracture found model at higher was lower velocities than the [3], corresponding and fracture value patterns of the non-fracturewere observed model to be consistent(Figure 9),with suggesting those commonly that a certain reported amount in of theimpact literature. energy couldIn addition, be absorbed the duringpredicted the skullresultant accelerationfracture [15,39]. of the fracture model was lower than the corresponding value of the non-fracture model (Figure The9), suggesting power of thethat MPSa certain for the amount prediction of impact of cerebral energy contusion could be hasabsorbed been confirmedduring the in skull fractureexperimental [15,39]. studies [33]. Therefore, the MPS of two models at the impact region of the cerebrum The power of the MPS for the prediction of cerebral contusion has been confirmed in experimental studies [33]. Therefore, the MPS of two models at the impact region of the cerebrum

Int. J. Environ. Res. Public Health 2020, 17, 2392 10 of 12 with those commonly reported in the literature. In addition, the predicted resultant acceleration of the fracture model was lower than the corresponding value of the non-fracture model (Figure9), suggesting that a certain amount of impact energy could be absorbed during the skull fracture [15,39]. The power of the MPS for the prediction of cerebral contusion has been confirmed in experimental studies [33]. Therefore, the MPS of two models at the impact region of the cerebrum were compared with the analysis of the influence of skull fractures on contusions in this study. For low impact velocity, the MPS values of the fracture model were significantly lower than the corresponding values of the non-fracture model, except for the parietal impact. When a small linear skull fracture occurred, the skull could still play a protective role regarding the brain tissue, and also a certain amount of impact energy could be absorbed, which could reduce the energy transferred to the brain tissue. However, for high-impact velocity, the MPS values of the fracture model were distinctly higher than the corresponding values of the non-fracture model, except for the parietal impact. The higher MPS values at the region of impact in the presence of the skull fracture model are likely induced by direct impression (Figure 11)[40]. Compared with the cerebral deformations of the frontal and occipital fracture models, a probable reason for the relatively low MPS obtained in the parietal impact of the skull fracture model at high head impact velocity was that the cerebrum suffered a relatively small deformation at the region of impact. For all of these impact conditions, the predicted CSDM values of fracture models were lower than the corresponding values of non-fracture models. CSDM values could be reduced significantly with the appearance of skull fractures, especially for frontal and parietal impacts. Even though the appearance of a skull fracture has no significant effect on the CSDM values at low head impact velocity, the average CSDM values of the fracture models are generally relatively lower than corresponding values predicted by non-fracture models, with an average reduction of 49.3%, and the results observed were consistent with those reported in Carson et al. [14] study. As previously discussed, a certain amount of energy was absorbed during the skull fracture [15,39], while still being able to protect the brain. Therefore, we could deduce that the presence of skull fractures can reduce the injury risk of DBIs. Owing to the lack of data on head trauma in traffic accidents, the impact of skull fracture on the intracranial response cannot be quantified for validity, which needs further improvement.

5. Conclusions Simulation of head–ground impact models of three locations predicted MPS and CSDM values that had an effect between the fracture and non-fracture models. The influences of skull fracture on cerebral contusion and diffuse brain injury were investigated. The results show that MPS values could be reduced significantly after skull fracture at low head impact velocity, which presents a lower risk of cerebral contusion. Conversely, the risk of cerebral contusion rises significantly after skull fracture at higher head impact velocity. CSDM values are employed to evaluate the risk of DBIs. Overall, the predicted average values of these injury indices of the skull fracture model are lower than the corresponding values of the non-fracture model. Therefore, it was found that skull fracture significantly reduces the risk of DBIs per results obtained using current head–ground impact models.

Author Contributions: Conceptualization, L.R.; methodology, C.J.; validation, D.W.; formal analysis, X.L.; writing—original draft preparation, D.W.; writing—review and editing, L.R.; supervision, H.Y.; project administration, Y.H.; All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Scientific and Technological Research Program of Chongqing Municipal Commission (Grant No. KJQN201801107), Graduate Student Innovation Program of Chongqing University of Technology (Grant No. ycx20192014), and State Key Laboratory of Vehicle NVH and Safety Technology Open Foundation (Grant No. NVHSKL-201908). Acknowledgments: The authors would like to extend special thanks to the editor and anonymous reviewers for their constructive comments and suggestions for improving the quality of this study. Conflicts of Interest: The authors declare no conflict of interest. Int. J. Environ. Res. Public Health 2020, 17, 2392 11 of 12

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