Investigating the likelihood of pediatric femur fracture due to falls through finite element analysis.

Bone fracture is the second most common injury of child abuse. Studies have generally reported that femur fractures are more likely due to abuse than accidental causes in cases where the child is non-ambulatory. They have also found that household falls are commonly offered as the cause of injury in cases of abuse. In this study, a finite element (FE) pediatric femur model will be developed and used to evaluate likelihood of fracture in common household fall scenarios (bed falls and feet first falls). This will provide greater biomechanical evidence as to the likelihood of femur fracture due to common fall scenarios which may serve to better inform clinicians when assessing compatibility between stated cause and injury when household falls are reported. The purpose of this study is to determine the likelihood of fracture of a 12-month-old child’s femur due to commonly reported accidental fall scenarios using finite element analysis. Loading conditions in the FE model were derived from femur loads reported in a previously study measured using a 12-month old anthropomorphic test device (ATD) in experimentally simulated household falls. A FE femur model was derived from a CT scan performed on an 11-month old child. Validation of the FE model was conducted through mechanical testing of a bone surrogate printed using selective laser sintering of glass-fiber reinforced nylon. The finite element model used simple support for the constraints and the loads from the ATD study were applied at the corresponding location of the load cells, which bounded the diaphysis of the femur. The FE predicted outcomes including maximum principal stress and strain values were used to evaluate the likelihood of fracture by comparing to three different thresholds: (1) tensile yield strain, (2) ultimate tensile strength, and (3) ultimate flexural strength. Fifty-percent of bed falls exceeded the yield strain and ultimate tensile strength fracture threshold whereas only two (of 12) exceeded the flexural strength fracture threshold. Different bed fall dynamics considered resulted in a significant difference in peak strains while impact surface did not. Peak strains in bed falls were associated with the peak bending moment. No feet-first falls exceeded fracture thresholds. Fall height resulted in a significant difference in peak strains while the impact surface did not. Peak strains in feet-first falls were associated with the peak bending moment or torsional loads

Cancellous bone and theropod dinosaur locomotion. Part I—an examination of cancellous bone architecture in the hindlimb bones of theropods

This paper is the first of a three-part series that investigates the architecture of cancellous (‘spongy’) bone in the main hindlimb bones of theropod dinosaurs, and uses cancellous bone architectural patterns to infer locomotor biomechanics in extinct non-avian species. Cancellous bone is widely known to be highly sensitive to its mechanical environment, and has previously been used to infer locomotor biomechanics in extinct tetrapod vertebrates, especially primates. Despite great promise, cancellous bone architecture has remained little utilized for investigating locomotion in many other extinct vertebrate groups, such as dinosaurs. Documentation and quantification of architectural patterns across a whole bone, and across multiple bones, can provide much information on cancellous bone architectural patterns and variation across species. Additionally, this also lends itself to analysis of the musculoskeletal biomechanical factors involved in a direct, mechanistic fashion. On this premise, computed tomographic and image analysis techniques were used to describe and analyse the three-dimensional architecture of cancellous bone in the main hindlimb bones of theropod dinosaurs for the first time. A comprehensive survey across many extant and extinct species is produced, identifying several patterns of similarity and contrast between groups. For instance, more stemward non-avian theropods (e.g. ceratosaurs and tyrannosaurids) exhibit cancellous bone architectures more comparable to that present in humans, whereas species more closely related to birds (e.g. paravians) exhibit architectural patterns bearing greater similarity to those of extant birds. Many of the observed patterns may be linked to particular aspects of locomotor biomechanics, such as the degree of hip or knee flexion during stance and gait. A further important observation is the abundance of markedly oblique trabeculae in the diaphyses of the femur and tibia of birds, which in large species produces spiralling patterns along the endosteal surface. Not only do these observations provide new insight into theropod anatomy and behaviour, they also provide the foundation for mechanistic testing of locomotor hypotheses via musculoskeletal biomechanical modelling

Simulation of fracture strength improvements of a human proximal femur using finite element analysis.

The most common hip fracture in the elderly occurs as a result of a fall to the side with impact over the greater trochanter resulting in a fracture of the proximal femur. The fracture usually involves the femoral neck or the intertrochanteric region. It has recently been determined that the fracture crack of a hip fracture typically initiates on the superior-lateral cortex of the femoral neck and then propagates across the femoral neck, resulting in a complete fracture. The strength of the superior-lateral cortex of the femoral neck is likely determined by the combined properties of the generally thin cortex (outer layer) and the underlying trabecular bone in this region. The objective of this study was to determine the relative effects of increasing or decreasing the thickness of these bone tissues on the overall failure strength of the proximal femur. The clinical significance of this work relates to hip fracture risk with various potential treatment options to improve either cortical or trabecular bone quality. A human femur obtained from a 68 year old female donor was scanned using computed tomography at 60-micron voxel resolution and a series of high-resolution finite element models were generated. The models were constructed with a base-element dimension of 120 microns and models included a basic model with cortical and trabecular thicknesses representative of the cadaver specimen from the original scan. Other models used a standardized algorithm to either dilate or erode the trabecular and cortical bone compartments of the femoral neck so that a total of nine models were created including the basic model. Each model was used to simulate a fall-to-the-side loading condition with appropriate boundary and loading conditions as used in previous models and experiments. An experimental test of the cadaver femur was also performed with three strain gauges placed on the proximal femur: on the superior-lateral cortex, on the inferior-medial cortex, and on the medial cortex positioned distal to the lesser trochanter. This femur was loaded at a rate of 100 mm/s until fracture of the femoral neck using a standard fall-to-the-side setup and the applied load and gauge strains were recorded. The femur neck fractured at a load of 2140 N. To validate the basic finite element model, the strain gauge strains at the load levels of 1000 N and 2000 N were compared to the calculated strains from the basic model at the same loads and same location as the gauge on the cadaver femur. After the basic model was validated, a failure criterion was determined as the volume percentage of the elements in the model that had exceeded 7000 µε at the failure load corresponding to the load at which the cadaver femur failed. Subsequently, this failure criterion was applied to the other eight models as a parametric analysis to estimate the increase or decrease in failure strength caused by the changes in cortical and trabecular thickness. The validation test results showed that the basic finite element model calculated strain on the superolateral cortex was within 2.1% of the experimentally measured strain at 1000 N loading. The validated basic model was then used to determine that the percentage of finite elements (by volume of the model) in excess of 7000 µε at the failure load was 4.2%. This failure criterion was then used to estimate the failure load for the other eight models with different combinations of either thicker (+120 µm) or thinner (-120 µm) cortex and trabeculae in the femoral neck. The calculated failure loads ranged from 324 N for the model with thinned cortex and thinned trabeculae to 3336 N for the model with thickened cortex and thickened trabeculae. The model with normal cortex and thickened trabeculae had a failure load of 3242 N, which is only 2.8% less than the strongest case. The largest single parameter effect on proximal femoral strength is realized by an increase in trabecular thickness. This is somewhat surprising considering that cortical bone is typically stronger than cancellous bone. However, the spatial arrangement of trabecular bone and the buttress support it provides to the thin cortex apparently plays an important role in the ability of a global increase in thickness to have a significant beneficial effect

Stochastic Assessment of Bone Fragility in Human Lumbar Spine

Osteoporotic fractures are a vital public health concern and create a great economic burden for our society. It is estimated that more than 2 million fractures occur in the United States at a cost of $17 billion each year. Deterioration of microarchitecture of trabecular bone is considered as a major contributor to bone fragility. Current clinical imaging modalities such as Dual-energy X-ray absorptiometry (DXA) are not able to describe bone microarchitecture due to their low resolution. The main objective of this study was to obtain the relationship between stochastic parameters calculated from bone mineral density (BMD) maps of DXA scans and the microarchitecture parameters measured from three dimensional (3D) images of human lumbar vertebrae acquired using a Micro-Computed Tomography (Micro-CT) scanner. Eighteen human lumbar vertebrae with intact posterior elements were scanned in the posterior-anterior projection using a DXA scanner. Stochastic parameters such as correlation length (L), sill variance (C) and nugget variance ( ) were calculated by fitting a theoretical model onto the experimental variogram of the BMD map of the human vertebrae. In addition, microarchitecture parameters such as bone volume fraction (BV/TV), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular number (Tb.N), connectivity density (Conn.Dn), and bone surface-to-volume ratio (BS/BV) were measured from 3D images of the same human lumbar vertebrae. Significant correlations were observed between stochastic predictors and microarchitecture parameters of trabecular bone. Specifically, the sill variance was positively correlated with the bone volume fraction, trabecular thickness, trabecular number, connectivity density and negatively correlated with the bone surface to volume ratio and trabecular separation. This study demonstrates that stochastic assessment of the inhomogeneity of bone mineral density from routine clinical DXA scans of human lumbar vertebrae may have the potential to serve as a valuable clinical tool in enhancing the prediction of risks for osteoporotic fractures in the spine. The main advantage of using DXA scans is that it would be cost effective, since most hospitals already have DXA machines and there would be no need for purchasing new equipment

ADDRESSING PARTIAL VOLUME ARTIFACTS WITH QUANTITATIVE COMPUTED TOMOGRAPHY-BASED FINITE ELEMENT MODELING OF THE HUMAN PROXIMAL TIBIA

Quantitative computed tomography (QCT) based finite element modeling (FE) has potential to clarify the role of subchondral bone stiffness in osteoarthritis. The limited spatial resolution of clinical CT systems, however, results in partial volume (PV) artifacts and low contrast between the cortical and trabecular bone, which adversely affect the accuracy of QCT-FE models. Using different cortical modeling and partial volume correction algorithms, the overall aim of this research was to improve the accuracy of QCT-FE predictions of stiffness at the proximal tibial subchondral surface. For Study #1, QCT-FE models of the human proximal tibia were developed by (1) separate modeling of cortical and trabecular bone (SM), and (2) continuum models (CM). QCT-FE models with SM and CM explained 76%-81% of the experimental stiffness variance with error ranging between 11.2% and 20.2%. SM did not offer any improvement relative to CM. The segmented cortical region indicated densities below the range reported for cortical bone, suggesting that cortical voxels were corrupted by PV artifacts. For Study #2, we corrected PV layers at the cortical bone using four different methods including: (1) Image Deblurring of all of the proximal tibia (IDA); (2) Image Deblurring of the cortical region (IDC); (3) Image Remapping (IR); and (4) Voxel Exclusion (VE). IDA resulted in low predictive accuracy with R2=50% and error of 76.4%. IDC explained 70% of the measured stiffness variance with 23.3% error. The IR approach resulted in an R2 of 81% with 10.6% error. VE resulted in the highest predictive accuracy with R2=84%, and 9.8% error. For Study #3, we investigated whether PV effects could be addressed by mapping bone’s elastic modulus (E) to mesh Gaussian points. Corresponding FE models using the Gauss-point method converged with larger elements when compared to the conventional method which assigned a single elastic modulus to each element (constant-E). The error at the converged mesh was similar for constant-E and Gauss-point; though, the Gauss-point method indicated this error with larger elements and less computation time (30 min vs 180 min). This research indicated that separate modeling of cortical and trabecular bone did not improve predictions of stiffness at the subchondral surface. However, this research did indicate that PV correction has potential to improve QCT-FE models of subchondral bone. These models may help to clarify the role of subchondral bone stiffness in knee OA pathogenesis with living people

Femoral Strength Prediction using Finite Element Models : Validation of models based on CT and reconstructed DXA images against full-field strain measurements

Osteoporosis is defined as low bone density, and results in a markedly increased risk of skeletal fractures. It has been estimated that about 40% of all women above 50 years old will suffer from an osteoporotic fracture leading to hospitalization. Current osteoporosis diagnostics is largely based on statistical tools, using epidemiological parameters and bone mineral density (BMD) measured with dual energy X-ray absorptiometry (DXA). However, DXA-based BMD proved to be only a moderate predictor of bone strength. Therefore, novel methods that take into account all mechanical characteristics of the bone and their influence on bone resistance to fracture are advocated. Finite element (FE) models may improve the bone strength prediction accuracy, since they can account for the structural determinants of bone strength, and the variety of external loads acting on the bones during daily life. Several studies have proved that FE models can perform better than BMD as a bone strength predictor. However, these FE models are built from Computed Tomography (CT) datasets, as the 3D bone geometry is required, and take several hours of work by an experienced engineer. Moreover, the radiation dose for the patient is higher for CT than for DXA scan. All these factors contributed to the low impact that FE-based methods have had on the current clinical practice so far. This thesis work aimed at developing accurate and thoroughly validated FE models to enable a more accurate prediction of femoral strength. An accurate estimation of femoral strength could be used as one of the main determinant of a patient’s fracture risk during population screening. In the first part of the thesis, the ex vivo mechanical tests performed on cadaver human femurs are presented. Digital image correlation (DIC), an optical method that allows for a full-field measurement of the displacements over the femur surface, was used to retrieve strains during the test. Then, a subject-specific FE modelling technique able to predict the deformation state and the overall strength of human femurs is presented. The FE models were based on clinical images from 3D CT datasets, and were validated against the measurements collected during the ex vivo mechanical tests. Both the experimental setup with DIC and the FE modelling procedure have been initially tested using composite bones (only the FE part of the composite bone study is presented in this thesis). After that, the method was extended to human cadaver bones. Once validated against experimental strain measurements, the FE modelling procedure could be used to predict bone strength. In the last part of the thesis, the predictive ability of FE models based on the shape and BMD distribution reconstructed from a single DXA image using a statistical shape and appearance model (SSAM, developed outside this thesis) was assessed. The predictions were compared to the experimental measurements, and the obtained accuracy compared to that of CT-based FE models. The results obtained were encouraging. The CT-based FE models were able to predict the deformation state with very good accuracy when compared to thousands of full-field measurements from DIC (normalized root mean square error, NRMSE, below 11%), and, most importantly, could predict the femoral strength with an error below 2%. The performances of SSAM-based FE models were also promising, showing only a slight reduction of the performances when compared to the CT-based approach (NRMSE below 20% for the strain prediction, average strength prediction error of 12%), but with the significant advantage of the models being built from one single conventional DXA image. In conclusion, the concept of a new, accurate and semi-automatic FE modelling procedure aimed at predicting fracture risk on individuals was developed. The performances of CT-based and SSAM-based models were thoroughly compared, and the results support the future translation of SSAM-based FE model built from a single DXA image into the clinics. The developed tool could therefore allow to include a mechanistic information into the fracture risk screening, which may ultimately lead to an increased accuracy in the identification of the subjects at risk