Pelvic Bones

ICDPIC-R is intended to be freely available for any user, and accordingly has been implemented using the open-source statistical software R (R Foundation for Statistical Computing, Vienna, Austria). For development and testing purposes, the National Trauma Data Bank (NTDB) research data set for admission year 2015 was obtained from the American College of Surgeons (ACS) (Hedegaard et al., 2016 ) in compliance with its standard Data Use Agreement. For purposes of validation, the National Inpatient Sample (NIS) data sets for the Fourth Quarter of 2015 were also obtained from the Agency for Healthcare Research and Quality (AHRQ) in compliance with its standard Data Use Agreement.
For each valid ICD-9-CM or ICD-10-CM injury diagnosis, ICDPIC-R is programmed to generate an approximate AIS and body region, using the original AIS anatomic classification (as modified by Baker and colleagues) into six body regions: Head and neck, face, chest, abdomen and pelvic contents, extremities and pelvic bones, and general (Committee on Medical Aspects of Automotive Safety, AMA, 1971 (link); Baker et al., 1974 (link)). In addition, each code referring to a mechanism of injury is categorized as recommended or proposed by the CDC (CDC, 1997 (link); Annest et al., 2014 ). For each injured person, ICDPIC-R determines the maximal AIS in each body region and overall, an Injury Severity Score (RISS), and a CDC mechanism category.
Mapping of ICD-9-CM codes to AIS severity and body region utilizes essentially the same table that was used for the Stata implementation of ICDPIC. After initial testing, we reclassified code 850.11 to AIS = 2 as recommended by Fleischman et al. (Fleischman et al., 2017 (link)), and codes 806.1 and 862.8 to AIS = 5 as recommended by DiBartolomeo et al. (Di Bartolomeo et al., 2010 (link))
Mapping of ICD-9-CM E-codes to CDC mechanism categories simply involved translation of the programming code from Stata into R, using the same table. Mapping of ICD-10-CM codes to mechanism categories was based on a similar table published by the CDC (Annest et al., 2014 ).
The National Trauma Data Standard used by NTDB considers valid ICD-10-CM injury codes to be those in the ranges S00-S99, T07, T14, T20-T28, and T30–32. ICDPIC-R recognizes only these codes in the calculation of injury severity from ICD-10, and also requires that the codes conclude with the letter “A” (indicating an initial encounter).
Mapping of ICD-10-CM codes to AIS severity can be performed in several ways, as described below.

The good state of preservation and the representativeness of the excavated skeletons allowed a biological identification of the two individuals buried at Huaca Grande. The estimation of the age at death of these two adult individuals is based on the study of their dentition [37 ] and the analysis of the sacroiliac surface which allows to refine the age class by chronological intervals with reliability [38 (link)]. This probabilistic method is based on the scoring of four morphological characters of the iliac auricular surface: the presence or absence of undulations and striations on the transverse organization (SSPIA), the modification of the articular surface with the progressive appearance of granulation and porosities (SSPIB), the modification of the apical surface with a thin or blunt edge (SSPIC), and the modification of the iliac tuberosity with a smooth or reshaped surface (SSPID).
Regarding sexual diagnosis, the good preservation of the coxal bone of both adult individuals allows the use of two reliable methods based on a world reference sample. The first method is morphoscopic with a minimum reliability of 95% [39 (link)]. It consists of assessing five characters distributed over three morpho-functional segments of the bony pelvis: the pre-auricular region, the shape of the greater ischial incisure, the sexual shape of the compound arch, the shape of the inferior border and the relative length of the pubis and ischium. The second method is morphometric based on metric variability with a reliability varying between 98.7% and 100% [40 ]. It is based on the principle of discriminant analysis from four to ten variables to determine the probability of belonging to a male or female group.

In this study, we used 3D-FEA software (Mechanical Finder [MF], version 10.0, Extended Edition, RCCM Co. Ltd., Tokyo, Japan). We analyzed computed tomography (CT) data obtained from a 64-year-old woman with a bone mineral density of 0.717 g/cm². CT was performed at 0.625-mm intervals from the cervical spine to the pelvis, and the CT data were transferred to MF. The ethics committee of our institute approved the use of this patient’s CT data (Approval No. 1748). We created 3D-FEA bone models from the first thoracic vertebra (T1) to the pelvis by extracting bone contour lines using MF. The models consisted of tetrahedral elements with a length of 1.4 mm.
We derived the mass density of the bone ρ (g/cm³) from the CT value (Hounsfield Unit, HU) and calculated the non-homogeneous Young's modulus distribution based on Keyak's formula [3 (link), 4 (link)] to determine the material properties of the finite elements. The Young's modulus E (MPa) is expressed as indicated in Formula 1, as follows: $$E=\left\{\begin{array}{c}0.001\left(\rho ,=,0\right)\\ 33900{\rho }^{2.20}\left(0,<,\rho ,\le ,0.27\right)\\ 5307\rho +469\left(0.27,<,\rho ,<,0.6\right)\\ 10200{\rho }^{2.01}\left(0.6,\le ,\rho \right)\end{array}\right)$$
Figures 1A and B show the diagrams of element decomposition and non-homogeneous Young's modulus distribution, respectively. Table 1 shows the Young's modulus and Poisson's ratio values for the vertebral body and intervertebral discs.Fig. 1

Element segmentation diagram of multi-vertebrae and Young’s modulus distribution diagram. A FE models of spinal fusion. B Heterogeneous distribution of Young's modulus, E. FE, finite element; E, Young’s modulus (MPa)

Table 1

Young's modulus and Poisson's ratio of each element

	Young’s modulus	Poisson’s ratio	Element type
Cortical bone	Determined by Formula 1	0.4	Tetrahedral
Cancellous bone	Determined by Formula 1	0.4	Tetrahedral
Disc	7.5 MPa	0.4	Tetrahedral

We obtained imaging data for the implants used in the actual surgery via micro-CT, which included a pedicle screw (PS; screw), an S2-alar-iliac screw (S2AI), and a transverse hook (TH; hook). Computer-aided design (CAD) data for these implants were created based on the CT data. The CAD software SOLIDWORKS^® (Concord, MA, USA) was used to create the implant models. The diameter of the screw analyzed in the current study was 5.5 mm, with a length ranging from 35 to 40 mm. The diameter and length of the S2AI screw were 8.5 and 90 mm, respectively. The diameter of the rod was 6.0 mm. After creating the implant models, we imported the bone and implant models into MF and created the FE models of long spinal fusion by combining these data. All screws and rods were fixed. The contact condition between implant and bone was set as bonding contact.

An institutional database was utilized for the acquisition of conventional radiographs that were used for limb alignment analysis. The included radiographs were created using long-leg standing X-rays, as described below. Gender and age were noted. Radiographs of patients who had undergone bony surgery around the pelvis and femur (e.g., osteotomies or arthroplasty) were excluded. Radiographs that did not allow for visualization of the pubic-arc region or the ischii due to the presence of gonadal shielding, were excluded. Two orthopedic surgeons independently performed all radiographic measurements. Both observers repeated the assessments after six weeks. For the second phase, the order of all radiographic images was randomized to eliminate any bias from the first reading.