Specimen-specific vertebral fracture modeling: a feasibility study using the extended finite element method

Gender differences in L1 vertebral strength in adults 50+ using automated CT-based finite element analysis

Osteoporosis is usually diagnosed using a Bone Mineral Density test using dual-energy X-ray Absorptiometry. However, it is limited by low testing rates and the inability to directly measure bone strength. Finite Element Analysis allows for a more detailed assessment of bone strength. However, its modeling complexity and high computational time requirements pose challenges. This study aims to develop customized MATLAB programs to automate the creation of heterogeneous bone models, streamlining preprocessing to reduce time, computational costs, and minimize variability from manual processes. The focus is on establishing a prediction model for the structural strength of the L1 vertebral body using patient-specific CT data, thereby aiding in the prediction of vertebral fracture risk. The CT images are stacked into a 3D array, and the pixel values are converted by Hounsfield units based on CT image. The bone segment and elasticity values are established based on the Hounsfield units. After modeling, strain and stress analysis were performed through the solver LS-DYNA. The compression force was distributed vertically on the upper endplate of the vertebral body. All nodes in the subvertebral plane were fully constrained. For comparison, vertebral models were automatically established and analyzed from recruited subjects. This study collected spine CT imaging datasets from 52 subjects, comprising 28 males and 24 females aged between 50 and 95 years. Preprocessing and mechanical analysis for each subject took an average of approximately 579.6 seconds. Analysis of the results indicated that women over 50 years of age exhibited higher strain and stress values in their vertebral models compared to men under the same applied force, highlighting gender-specific differences in biomechanical characteristics. This study effectively employed a practical approach to identify and select specific spinal segments from CT images, facilitating the automated creation of 3D models for subsequent finite element analysis. The predictive model generated results consistent with previous studies involving mechanical testing on actual human bones. Notably, the implementation of our predictive model substantially decreased processing time for Finite Element Analysis, rendering it more suitable for clinical use and easier to extend for future application.

Experimentally Validated Finite Element Analysis of Thoracic Spine Compression Fractures in a Porcine Model

Vertebral compression fractures (VCFs) occur in 1 to 1.5 million patients in the US each year and are associated with pain, disability, altered pulmonary function, secondary vertebral fracture, and increased mortality risk. A better understanding of VCFs and their management requires preclinical models that are both biomechanically analogous and accessible. We conducted a study using twelve spinal vertebrae (T12-T14) from porcine specimens. We created mathematical simulations of vertebral compression fractures (VCFs) using CT scans for reconstructing native anatomy and validated the results by conducting physical axial compression experiments. The simulations accurately predicted the behavior of the physical compressions. The coefficient of determination for stiffness was 0.71, the strength correlation was 0.88, and the failure of the vertebral bodies included vertical splitting on the lateral sides or horizontal separation in the anterior wall. This finite element method has important implications for the preventative, prognostic, and therapeutic management of VCFs. This study also supports the use of porcine specimens in orthopedic biomechanical research.

How to Optimize Pedicle Screw Parameters for the Thoracic Spine? A Biomechanical and Finite Element Method Study

STUDY DESIGN

Pedicle screw study.

OBJECTIVE

The selection of pedicle screw parameters usually involves the surgeon's analysis of preoperative CT imaging along with anatomical landmarks and tactile examination. However, there is minimal consensus on a standardized guideline for selection methods on pedicle screws. We aimed to determine the effects of thoracic screw diameter to pedicle width on pullout strength determined by cortical bone purchase.

METHODS

Biomechanical study performed with human cadaveric thoracic vertebrae and experimentally validated three-dimensional finite element model instrumented with pedicle screws of various diameters. We used a variable (SD/PW) ratio to express the screw selection. We hypothesized a positive correlation between the pullout load determined by the bone purchase and the SD/PW. This relationship was first investigated in a validated finite element model considering bone purchase related to the strength of an upper thoracic vertebra. Then, the correlation to the entire spine is evaluated.

RESULTS

The failure load ranged from 371.3 to 1601.0 N, respectively, for 3 and 6 mm screws. The determinant coefficient was increased to R2=.421 when a linear relationship between pullout load and the SD/PW ratio was used. The peak loads of 1216 and 1288N were found for an SD/PW ratio of .83.

CONCLUSION

We have found that the screw pullout load is more correlated to SD/PW than other pedicle measures for a maximized SD/PW ratio of .83. This particular value should be considered the upper limit of the indicated SD/PW ratio and a means to determine the optimal screw diameter to enhance pullout strength.

A Review of CT-Based Fracture Risk Assessment with Finite Element Modeling and Machine Learning

PURPOSE OF REVIEW

We reviewed advances over the past 3 years in assessment of fracture risk based on CT scans, considering methods that use finite element models, machine learning, or a combination of both.

RECENT FINDINGS

Several studies have demonstrated that CT-based assessment of fracture risk, using finite element modeling or biomarkers derived from machine learning, is equivalent to currently used clinical tools. Phantomless calibration of CT scans for bone mineral density enables accurate measurements from routinely taken scans. This opportunistic use of CT scans for fracture risk assessment is facilitated by high-quality automated segmentation with deep learning, enabling workflows that do not require user intervention. Modeling of more realistic and diverse loading conditions, as well as improved modeling of fracture mechanisms, has shown promise to enhance our understanding of fracture processes and improve the assessment of fracture risk beyond the performance of current clinical tools. CT-based screening for fracture risk is effective and, by analyzing scans that were taken for other indications, could be used to expand the pool of people screened, therefore improving fracture prevention. Finite element modeling and machine learning both provide valuable tools for fracture risk assessment. Future approaches should focus on including more loading-related aspects of fracture risk.

Incremental Element Deletion-Based Finite Element Analysis of the Effects of Impact Speeds, Fall Postures, and Cortical Thicknesses on Femur Fracture

The proximal femur’s numerical simulation could give an effective method for predicting the risk of femoral fracture. However, the majority of existing numerical simulations is static, which does not correctly capture the dynamic properties of bone fractures. On the basis of femoral fracture analysis, a dynamic simulation using incremental element deletion (IED)-based finite element analysis (FEA) was developed and compared to XFEM in this study. Mechanical tests were also used to assess it. Different impact speeds, fall postures, and cortical thicknesses were also studied for their implications on fracture types and mechanical responses. The time it took for the crack to shatter was shorter when the speed was higher, and the crack line slid down significantly. The fracture load fell by 27.37% when the angle was altered from 15° to 135°, indicating that falling forward was less likely to cause proximal femoral fracture than falling backward. Furthermore, the model with scant cortical bone was susceptible to fracture. This study established a theoretical foundation and mechanism for forecasting the risk of proximal femoral fracture in the elderly.

Establishment and validation of a T12-L2 3D finite element model for thoracolumbar segments

OBJECTIVE

To establish and verify the validity of a three-dimensional finite element model of the thoracolumbal segments T12-L2; the stress distribution of the model was analyzed, providing a theoretical basis for finite element analysis of thoracolumbal segment fracture as well as a surgical model.

METHODS

A healthy female volunteer with no history of lumbar spine injury was selected to obtain CT scan data of the T12-L2 vertebral bodies. Mimics 3D reconstruction software was used to generate the T12-L2 3D model, and surface mesh and body mesh were generated by smoothing treatment and mesh division. The normal finite element model of the T12-L2 vertebral bodies and the finite element model of osteoporosis were established with Ansys finite element software. Under a loading force of 500 N vertically downward and a load of 7.5 N•m bending moment, seven operating conditions were simulated to analyze the displacement and stress distribution of each vertebral body and intervertebral disc, and to verify the effectiveness of the model.

RESULTS

There were 31,901 nodes and 64,244 elements in the thoracolumbar T12-L2 three-dimensional finite element model. These results were similar to the conclusions found in a review of the domestic and global literature, and the finite element model was validated.

CONCLUSIONS

The results of this experiment can provide a practical reference for clinical work and help to establish a three-dimensional finite element model of the thoracolumbar junction.

Prediction of fracture initiation and propagation in pelvic bones

The objective is developing an XFEM model that is capable of predicting different types of fracture in the pelvic bone under various loading conditions. Previously published mechanical and failure characteristics of cortical and cancellous tissues were implemented and assigned to an intact pelvic bone with specified cortical and cancellous tissues. Various loading conditions, including combined load directions, were applied to the acetabulum to model different types of fracture (e.g., anterior/posterior wall fracture and transverse fracture) in the pelvic bone. The predicated types of fracture and the maximum force at fracture were compared to those acquired from previously published experimental tests. Anterior/posterior wall fracture and transverse fracture were the most common types of fractures determined in the simulations. The XFEM simulations were able to predict similar fractures to those reported in the experimental tests. The maximum fracture force in the XFEM model was found to be 18.6 kN compared to 8.85 kN reported in the previous experimental tests. The results revealed that different types of fracture in the pelvic bones can be caused by the various loading conditions in unstable high-rate impact loads. Using proper mechanical and failure behaviors of cortical and cancellous tissues, XFEM modeling of pelvic bone is capable of predicting bone fracture. In future work, the XFEM models of cancellous and cortical tissues can be assigned to other bones in human body skeleton so that the failure mechanism in such bones can be investigated.

Finite Element Method for the Evaluation of the Human Spine: A Literature Overview

The finite element method (FEM) represents a computer simulation method, originally used in civil engineering, which dates back to the early 1940s. Applications of FEM have also been used in numerous medical areas and in orthopedic surgery. Computing technology has improved over the years and as a result, more complex problems, such as those involving the spine, can be analyzed. The spine is a complex anatomical structure that maintains the erect posture and supports considerable loads. Applications of FEM in the spine have contributed to the understanding of bone biomechanics, both in healthy and abnormal conditions, such as scoliosis, fractures (trauma), degenerative disc disease and osteoporosis. However, since FEM is only a digital simulation of the real condition, it will never exactly simulate in vivo results. In particular, when it concerns biomechanics, there are many features that are difficult to represent in a FEM. More FEM studies and spine research are required in order to examine interpersonal spine stiffness, young spine biomechanics and model accuracy. In the future, patient-specific models will be used for better patient evaluations as well as for better pre- and inter-operative planning.

Opportunistic application of phantom-less calibration methods for fracture risk prediction using QCT/FEA

OBJECTIVES

Quantitative computed tomography (QCT)-based finite element analysis (FEA) implements a calibration phantom to estimate bone mineral density (BMD) and assign material properties to the models. The objectives of this study were to (1) propose robust phantom-less calibration methods, using subject-specific tissues, to obtain vertebral fracture properties estimations using QCT/FEA; and (2) correlate QCT/FEA predictions to DXA values of areal BMD.

METHODS

Eighty of a cohort of 111 clinical QCT scans were used to obtain subject-specific parameters using a phantom calibration approach and for the development of the phantom-less calibration equations. Equations were developed based on the HU measured from various soft tissues and regions, and using multiple linear regression analyses. Thirty-one additional QCT scans were used for cross-validation of QCT/FEA estimated fracture loads from the L₃ vertebrae based on the phantom and phantom-less equations. Finally, QCT/FEA-predicted fracture loads were correlated with aBMD obtained from DXA.

RESULTS

Overall, 217 QCT/FEA models from 31 subjects (20 females, 11 men) with mean ages of 69.6 (13.1) and 67.3 (14) were used to cross-validate the phantom-less equations and assess bone strength. The proposed phantom-less equations showed high correlations with phantom-based estimates of BMD (99%). Cross-validation of QCT/FEA-predicted fracture loads from phantom-less equations and phantom-specific outcomes resulted in high correlations for all proposed methods (0.94-0.99). QCT/FEA correlation outcomes from the phantom-less equations and DXA-aBMD were moderately high (0.64-0.68).

CONCLUSIONS

The proposed QCT/FEA subject-specific phantom-less calibration methods demonstrated the potential to be applied to both prospective and retrospective applications in the clinical setting.

KEY POINTS

• QCT/FEA overcomes the disadvantages of DXA and improves fracture properties predictions of vertebrae. • QCT/FEA fracture estimates using the phantom-less approach highly correlated to values obtained using a calibration phantom. • QCT/FEA prediction using a phantom-less approach is an accurate alternative over phantom-based methods.

Effect of pedicle screw angles on the fracture risk of the human vertebra: A patient-specific computational model

The assessment of a human vertebra's stability after a screws fixation procedure and its fracture risk is still an open clinical problem. The accurate evaluation of fracture risk requires that all fracture mechanical determinants such as geometry, constitutive behavior, loading modes, and screws angulation are accounted for, which requires biomechanics-based analyses. As such, in the present work we investigate the effect of pedicle screws angulation on a patient-specific model of non osteoporotic lumbar vertebra, derived from clinical CT images. We propose a novel computational approach of fracture analysis and compare the effects of fixation stability in the lumbar spine. We considered a CT-based three-dimensional FE model of bilaterally instrumented L4 vertebra virtually implanting pedicle screws according to clinical guidelines. Nine screws trajectories were selected combining three craniocaudal and mediolateral angles, thus investigated through a parametric computational analysis. Bone was modeled as an elastic material with element-wise inhomogeneous properties fine-tuned on CT data. We implemented a custom algorithm to identify the thin cortical layer correctly from CT images ensuring reliable material properties in the computational model. Physiological motion (i.e., flexion, extension, axial rotation, lateral bending) was further accomplished by simultaneously loading the vertebra and the implant. We simulated local progressive damage of the bone by using a quasi-static force-driven incremental approach and considering a stress-based fracture criterion. Ductile-like and brittle-like fractures were found. Statistical analyses show significant differences comparing screws trajectories and averaging the results among six loading modes. In particular, we identified the caudomedial trajectory as the least critical case, thus safer from a clinical perspective. Instead, medial and craniolaterally oriented screws entailed higher peak and average stresses, though no statistical evidence classified such loads as the most critical scenarios. A quantitative validation procedure will be required in the future to translate our findings into clinical practice. Besides, to apply the results to the target osteoporotic population, new studies will be needed, including a specimen from an osteoporotic patient and the effect of osteoporosis on the constitutive model of bone.

An Equivalent Constitutive Model of Cancellous Bone With Fracture Prediction

To simulate the mechanical and fracture behaviors of cancellous bone in three anatomical directions and to develop an equivalent constitutive model. Microscale extended finite element method (XFEM) models of a cancellous specimen were developed with mechanical behaviors in three anatomical directions. An appropriate abaqus macroscale model replicated the behavior observed in the microscale models. The parameters were defined based on the intermediate bone material properties in the anatomical directions and assigned to an equivalent nonporous specimen of the same size. The equivalent model capability was analyzed by comparing the micro- and macromodels. The hysteresis graphs of the microscale model show that the modulus is the same in loading and unloading; similar to the metal plasticity models. The strength and failure strains in each anatomical direction are higher in compression than in tension. The microscale models exhibited an orthotropic behavior. Appropriate parameters of the cast iron plasticity model were chosen to generate macroscale models that are capable of replicating the observed microscale behavior of cancellous bone. Cancellous bone is an orthotropic material that can be simulated using a cast iron plasticity model. This model is capable of replicating the microscale behavior in finite element (FE) analysis simulations without the need for individual trabecula, leading to a reduction in computational resources without sacrificing model accuracy. Also, XFEM of cancellous bone compared to traditional finite element method proves to be a valuable tool to predict and model the fractures in the bone specimen.

Advanced Modeling Methods-Applications to Bone Fracture Mechanics

PURPOSE OF REVIEW

The goal of this review is to summarize recent advances in modeling of bone fracture using fracture mechanics-based approaches at multiple length scales spanning nano- to macroscale.

RECENT FINDINGS

Despite the additional information that fracture mechanics-based models provide over strength-based ones, the application of this approach to assessing bone fracture is still somewhat limited. Macroscale fracture models of bone have demonstrated the potential of this approach in uncovering the contributions of geometry, material property variation, as well as loading mode and rate on whole bone fracture response. Cortical and cancellous microscale models of bone have advanced the understanding of individual contributions of microstructure, microarchitecture, local material properties, and material distribution on microscale fracture resistance of bone. Nano/submicroscale models have provided additional insight into the effect of specific changes in mineral, collagen, and non-collagenous proteins as well as their interaction on energy dissipation and fracture resistance at small length scales. Advanced modeling approaches based on fracture mechanics provide unique information about the underlying multiscale fracture mechanisms in bone and how these mechanisms are influenced by the structural and material constituents of bone at different length scales. Fracture mechanics-based modeling provides a powerful approach that complements experimental evaluations and advances the understanding of critical determinants of fracture risk.

Material property calibration is more important than element size and number of different materials on the finite element modelling of vertebral bodies: A Taguchi study

Finite element (FE) modelling of a vertebral body (VB) is considered challenging due to the many parameters involved such as element size and type, and material properties. Previous studies have reported how these parameters affect the mechanical behaviour of a VB model; however, most studies just compared results without any specific statistical tool to quantify their influence. The Taguchi Method (TM) has been successfully used in manufacturing and biomechanics to evaluate process parameters and to determine optimum set-up conditions. This study aimed to evaluate the influence of the main finite element modelling parameters on the mechanical behaviour of a VB model using the Taguchi Method. A FE model was developed based on a C2 juvenile porcine vertebral body and three of the most commonly used modelling parameters were evaluated using TM in terms of the change in the predicted stiffness in comparison to experimental values: element size, number of different material properties for VB (based on grey-scale bins) and calibration factor for grey-scale to density to Young's Modulus equation. The influence of the combined factors was also assessed. The Taguchi analysis showed that the three factors are independent. The calibration factor is the main contributor, accounting for 97% of the predicted stiffness, with the value of 0.03 most closely aligning the numerical and experimental results. Element size accounted for 2% of the predicted stiffness, with 0.75 mm being the optimal, while the number of grey-scale bins influenced the results by less than 1%. Our findings indicate that the calibration factor is the main modelling parameter, with the element size and number of bins accounting for less than 3% of the predicted stiffness. Therefore, calibration of material properties should be done based on a large number of samples to ensure reliable results.

A Novel Modelling Methodology Which Predicts the Structural Behaviour of Vertebral Bodies under Axial Impact Loading: A Finite Element and DIC Study

Cervical spine injuries (CSIs) arising from collisions are uncommon in contact sports, such as rugby union, but their consequences can be devastating. Several FE modelling approaches are available in the literature, but a fully calibrated and validated FE modelling framework for cervical spines under compressive dynamic-impact loading is still lacking and material properties are not adequately calibrated for such events. This study aimed to develop and validate a methodology for specimen-specific FE modelling of vertebral bodies under impact loading. Thirty-five (n = 35) individual vertebral bodies (VBs) were dissected from porcine spine segments, potted in bone cement and μCT scanned. A speckle pattern was applied to the anterior faces of the bones to allow digital image correlation (DIC), which monitored the surface displacements. Twenty-seven (n = 27) VBs were quasi-statically compressively tested to a load up to 10 kN from the cranial side. Specimen-specific FE models were developed for fourteen (n = 14) of the samples in this group. The material properties were optimised based on the experimental load-displacement data using a specimen-specific factor (kGSstatic) to calibrate a density to Young’s modulus relationship. The average calibration factor arising from this group was calculated (K¯GSstatic) and applied to a control group of thirteen (n = 13) samples. The resulting VB stiffnesses was compared to experimental findings. The final eight (n = 8) VBs were subjected to an impact load applied via a falling mass of 7.4kg at a velocity of 3.1ms⁻¹. Surface displacements and strains were acquired from the anterior VB surface via DIC, and the impact load was monitored with two load cells. Specimen-specific FE models were created for this dynamic group and material properties were assigned again based on the density–Young’s modulus relationship previously validated for static experiments, supplemented with an additional factor (KGSdynamic). The optimised conversion factor for quasi-static loading, K¯GSstatic, had an average of 0.033. Using this factor, the validation models presented an average numerical stiffness value 3.72% greater than the experimental one. From the dynamic loading experiments, the value for KGSdynamic was found to be 0.14, 4.2 times greater than K¯GSstatic. The average numerical stiffness was 2.3% greater than in the experiments. Almost all models presented similar stiffness variations and regions of maximum displacement to those observed via DIC. The developed FE modelling methodology allowed the creation of models which predicted both static and dynamic behaviour of VBs. Deformation patterns on the VB surfaces were acquired from the FE models and compared to DIC data, achieving high agreement. This methodology is now validated to be fully applied to create whole cervical spine models to simulate axial impact scenarios replicating rugby collision events.

Density-Dependent Material and Failure Criteria Equations Highly Affect the Accuracy and Precision of QCT/FEA-Based Predictions of Osteoporotic Vertebral Fracture Properties

About 700,000 vertebral fractures occur in the US as a result of bone loss. Quantitative computed tomography (QCT)-based finite element analysis (FEA) is a promising tool for fracture risk prediction that is becoming attractive in the clinical setting. The goals of this study were (1) to perform individual and pooled specimen optimization using inverse QCT/FEA modeling to obtain ash density-elastic modulus equations incorporating the whole vertebral body and accounting for all variables used during FE modeling, and (2) to determine the effect of material equations and failure criteria on the accuracy and precision of mechanical properties. Fifty-four (54) human vertebrae were used to optimize material equations based on experimental outcomes and, together with a previously proposed material equation, were implemented in our models using three different failure criteria to obtain fracture loads. Our robust QCT/FEA approach predicted 78% of the failure loads. Material equations resulted in poor accuracy in the predicted stiffness, yet yielded good precision and, more importantly, strong correlations with fracture loads. Both material and fracture criterion equations are equally important in estimating accurate and precise QCT/FEA predictions. Results suggest that both elastic modulus and fracture criterion equations should be validated against experimental outcomes to better explain the response of the tissue under various conditions.

Prediction of failure in cancellous bone using extended finite element method

The objective of our study is to develop extended finite element method models of cancellous bone specimens that are capable of accurately predicting the onset and propagation of cracks under mechanical loading. In order to do so, previously published three-point bending test results of a single trabecula were replicated using two different extended finite element method approaches, namely, elastic-plastic-fracture and elastic-fracture that considered different configurations of the elasto-plastic properties of bone from which the best approach to fit the experimental data was identified. The behavior of a single trabecula was then used in 2D extended finite element method models to quantify the strength of the trabecular tissue of the forearm along three perpendicular anatomical axes. The results revealed that the elastic-plastic-fracture model better represented the experimental data in the model of a single trabecula. Considering the 2D trabecular specimens, the elastic fracture model predicted higher strength than the elastic-plastic-fracture model and there was no difference in stiffness between the two models. In general, the specimens exhibited higher failure strain and more ductile behavior in compression than in tension. In addition, strength and stiffness were found to be higher in tension than compression on average. It can be concluded that with proper parameters, extended finite element method is capable of simulating the ductile behavior of cancellous bone. The models are able to quantify the tensile strength of trabecular tissue in the various anatomical directions reporting an increased strength in the longitudinal direction of forearm cancellous bone tissue. Extended finite element method of cancellous bone proves to be a valuable tool to predict the mechanical characteristics of cancellous bones as a function of the microstructure.

Effect of metastatic lesion size and location on the load-bearing capacity of vertebrae using an optimized ash density-modulus equation

About 1.8 million new cancer cases are estimated in the US in 2019 from which 50-85% might metastasize to the thoracic and lumbar spines. Subject-specific quantitative computed tomography-based finite element analysis (QCT/FEA) is a promising used tool to predict vertebral fracture properties. The aims of this study were twofold: First, to develop an optimized equation for the elastic modulus accounting for all input parameters in FE modeling of fracture properties. Second, to assess the effect of lesion size and location on the predicted fracture loads. An inverse QCT/FEA method was implemented to determine optimal coefficients for the modulus equation as a function of ash density. Lesions of 16 and 20 mm were then virtually located at the center, off-centered, anterior, and posterior regions of the vertebrae. A total of 6426 QCT/FEA models were run to optimize the coefficients and evaluate the effect of lesions on fracture properties. QCT/FEA predicted stiffness showed high correlations (50%) with the experimentally measured values. Compared to a 16 mm lesion size, a 20 mm lesion had a reduction in failure load of 55%, 57%, 52%, and 44% at the center, off-centered, anterior cortex, and pedicle, respectively (p < 0.001). Lesions affecting mostly trabecular bone showed the largest reduction in predicted failure loads (about 55%), and females presented weaker outcomes than males. An optimal elastic modulus equation resulted in accurate vertebral stiffness predictions. A deterioration of the trabecular bone due to the presence of a lesion highly affected the predicted fracture loads, and this reduction was significantly higher in females compared to males.

Mechanical testing setups affect spine segment fracture outcomes

The purpose of the work presented here was to establish an experimental testing configuration that would generate a bending compression fracture in a laboratory setting. To this end, we designed and fabricated a fixture to accommodate a three level spine segment and to be able to perform mechanical testing by applying an off-centric compressive loading to create a flexion-type motion. Forces and moments occurring during testing were measured with a six-channel load cell. The initial testing configuration (Fixture A) included plates connected to the superior potted vertebral body and to the ball-socket joint of the testing system ram. Surprisingly, while all cadaveric specimens underwent a similar off-centric compressive loading, most of the specimens showed extension outcomes as opposed to the intended pure-flexion motion. The extension was due to fixture size and weight; by applying an off-centric load directly on the top plate, unintended large shear forces were generated. To resolve the issue, several modifications were made to the original fixture configuration. These modifications included the removal of the superior plates and the implementation of wedges at the superior surface of the fixture (Fixture B). A synthetic sample was used during this modification phase to minimize the number of cadaveric specimens while optimizing the process. The best outcomes were consistently observed when a 15°-wedge was used to provide flexion-type loading. Cadaveric specimens were then experimentally tested to fracture using the modified testing configuration (Fixture B). A comparison between both fixtures, A and B, revealed that almost all biomechanical parameters, including force, moment, and displacement data, were affected by the testing setup. These results suggest that fixture design and implementation for testing is of extreme importance, and can influence the fracture properties and affect the intended motion.

A novel technique with reduced computed tomography exposure to predict vertebral compression fracture: a finite element study based on rat vertebrae

Vertebral compression fractures are a significant clinical issue with an annual incidence of approximately 750,000 cases in the USA alone. Mechanical properties of vertebrae are successfully evaluated through finite element (FE) models based on vertebrae CT. However, clinical drawbacks associated to radiation transmission encouraged to explore the possibility to use selected or reduced portions of the vertebra. The objective of our study was to develop a new procedure to predict vertebral compression fracture from sub-volumes. We reconstructed rat vertebras from micro-CT of thoracic and lumbar groups. Each vertebra was partitioned into three sub-volumes of different axial thickness. FE simulating compression tests were performed on each model to evaluate their failure load and stiffness. Using a power function, a high correlation was found for stiffness and strength. The sub-volume with three fifths thickness had a failure load of 180.7 ± 19.2 N for thoracic and of 209.5 ± 27.4 N for the lumbar vertebra. These values were not significantly different from the values found for the entire vertebra (p > 0.05). Based on our findings, failure loads and stiffnesses obtained with reduced CT scans can be successfully used to predict full vertebral failure. This sub-region analysis and power relationship suggests that one can limit radiation exposure to patients when bone characterization is needed. Graphical abstract Estimated mechanical properties in relation to the extent of the computed tomography reconstruction.

Quantitative Computed Tomography Protocols Affect Material Mapping and Quantitative Computed Tomography-Based Finite-Element Analysis Predicted Stiffness

Quantitative computed tomography-based finite-element analysis (QCT/FEA) has become increasingly popular in an attempt to understand and possibly reduce vertebral fracture risk. It is known that scanning acquisition settings affect Hounsfield units (HU) of the CT voxels. Material properties assignments in QCT/FEA, relating HU to Young's modulus, are performed by applying empirical equations. The purpose of this study was to evaluate the effect of QCT scanning protocols on predicted stiffness values from finite-element models. One fresh frozen cadaveric torso and a QCT calibration phantom were scanned six times varying voltage and current and reconstructed to obtain a total of 12 sets of images. Five vertebrae from the torso were experimentally tested to obtain stiffness values. QCT/FEA models of the five vertebrae were developed for the 12 image data resulting in a total of 60 models. Predicted stiffness was compared to the experimental values. The highest percent difference in stiffness was approximately 480% (80 kVp, 110 mAs, U70), while the lowest outcome was ∼1% (80 kVp, 110 mAs, U30). There was a clear distinction between reconstruction kernels in predicted outcomes, whereas voltage did not present a clear influence on results. The potential of QCT/FEA as an improvement to conventional fracture risk prediction tools is well established. However, it is important to establish research protocols that can lead to results that can be translated to the clinical setting.