Prediction of local proximal tibial subchondral bone structural stiffness using subject-specific finite element modeling: Effect of selected density-modulus relationship

A posterior tibial slope angle over 12 degrees is critical to epiphyseal fracture of the proximal tibia: Three-dimensional finite element analysis

Introduction

The effects of the proximal tibial slope angle on the proximal tibial epiphysis remain unknown. To elucidate those effects, we investigated the strain distribution in proximal tibial epiphysis with different proximal tibial slope angles and proximal tibial epiphysis closure periods using finite element analysis.

Materials and methods

The finite element models of the proximal tibia were reconstructed from CT images and consisted of cancellous/cortical bone and epiphyseal plate. The variations in proximal tibial slope angle (range: 6-16°) and four closure variations in proximal tibial epiphysis (open, semi-open, semi-closed, and closed) were prepared. The loading force on the medial and lateral joint surface, and the tensile force by the patellar tendon were applied to the models, and the distal area of the tibia was fixed. The ratio of the equivalent strain in semi-open/semi-closed proximal tibial epiphysis to the strain in open proximal tibial epiphysis on different proximal tibial slope angles were calculated.

Results

The strain ratio between the semi-open/semi-closed and open proximal tibial epiphysis models indicated significant differences between 6 or 8° of proximal tibial slope angle and 12, 14, and 16° of proximal tibial slope angle models. In the increased proximal tibial slope angle model, a hoop-shaped strain in the closing proximal tibial epiphysis was found, and the maximum strain was found in the tibial tubercle.

Discussion

During epiphyseal closure, adolescents with an increased proximal tibial slope angle over 12° are significantly at risk for suffering from proximal tibial epiphyseal fractures compared with those under 10°.

Homogeneous material models can overestimate stresses in high tibial osteotomy: A finite element analysis

Although widely used numerical models can assess the stability of lateral hinges in high tibial osteotomy (HTO) and may provide acceptable results in comparative studies, accurate stress prediction may not be possible due to simplified homogeneous models of the bone. The present study aimed to investigate the effect of a heterogeneous versus four homogeneous models on the results of stress and force. Each of the four homogenized FE models utilized the same elastic modulus of 16,700 MPa for the cortical while employing a single elastic modulus varying from 155 to 5000 MPa for the cancellous. In heterogeneous model, the modulus of each element was assigned using the bone density. It was found that stresses at the hinge in homogeneous models were higher than those in the heterogeneous model. The maximum principal stress (MPS) was 437 MPa for the heterogeneous model while that was 2179, 2351, 2581, and 2637 MPa for the homogeneous models with the elastic moduli of 155, 500, 2130, and 5000 MPa, respectively. Also, the opening force was 150 N for the heterogeneous model significantly lower than 649-1534 N range predicted for the homogeneous models. The use of a homogeneous model in the FE analysis of HTO overestimated the stresses and force. Thus, in addition to casting doubt on the use of a single modulus in the numerical analysis of HTO, Future HTO studies can use our results as a benchmark for comparison purposes and highlight the use of patient-specific bone density - elastic modulus relation in simulation.

Development of Digital Twins to Optimize Trauma Surgery and Postoperative Management. A Case Study Focusing on Tibial Plateau Fracture

Background and context: Surgical procedures are evolving toward less invasive and more tailored approaches to consider the specific pathology, morphology, and life habits of a patient. However, these new surgical methods require thorough preoperative planning and an advanced understanding of biomechanical behaviors. In this sense, patient-specific modeling is developing in the form of digital twins to help personalized clinical decision-making.

Purpose: This study presents a patient-specific finite element model approach, focusing on tibial plateau fractures, to enhance biomechanical knowledge to optimize surgical trauma procedures and improve decision-making in postoperative management.

Study design: This is a level 5 study.

Methods: We used a postoperative 3D X-ray image of a patient who suffered from depression and separation of the lateral tibial plateau. The surgeon stabilized the fracture with polymethyl methacrylate cement injection and bi-cortical screw osteosynthesis. A digital twin of the patient’s fracture was created by segmentation. From the digital twin, four stabilization methods were modeled including two screw lengths, whether or not, to inject PMMA cement. The four stabilization methods were associated with three bone healing conditions resulting in twelve scenarios. Mechanical strength, stress distribution, interfragmentary strains, and fragment kinematics were assessed by applying the maximum load during gait. Repeated fracture risks were evaluated regarding to the volume of bone with stress above the local yield strength and regarding to the interfragmentary strains.

Results: Stress distribution analysis highlighted the mechanical contribution of cement injection and the favorable mechanical response of uni-cortical screw compared to bi-cortical screw. Evaluation of repeated fracture risks for this clinical case showed fracture instability for two of the twelve simulated scenarios.

Conclusion: This study presents a patient-specific finite element modeling workflow to assess the biomechanical behaviors associated with different stabilization methods of tibial plateau fractures. Strength and interfragmentary strains were evaluated to quantify the mechanical effects of surgical procedures. We evaluate repeated fracture risks and provide data for postoperative management.

Personalised high tibial osteotomy has mechanical safety equivalent to generic device in a case-control in silico clinical trial

Background

Despite favourable outcomes relatively few surgeons offer high tibial osteotomy (HTO) as a treatment option for early knee osteoarthritis, mainly due to the difficulty of achieving planned correction and reported soft tissue irritation around the plate used to stablise the osteotomy. To compare the mechanical safety of a new personalised 3D printed high tibial osteotomy (HTO) device, created to overcome these issues, with an existing generic device, a case-control in silico virtual clinical trial was conducted.

Methods

Twenty-eight knee osteoarthritis patients underwent computed tomography (CT) scanning to create a virtual cohort; the cohort was duplicated to form two arms, Generic and Personalised, on which virtual HTO was performed. Finite element analysis was performed to calculate the stresses in the plates arising from simulated physiological activities at three healing stages. The odds ratio indicative of the relative risk of fatigue failure of the HTO plates between the personalised and generic arms was obtained from a multi-level logistic model.

Results

Here we show, at 12 weeks post-surgery, the odds ratio indicative of the relative risk of fatigue failure was 0.14 (95%CI 0.01 to 2.73, p = 0.20).

Conclusions

This novel (to the best of our knowledge) in silico trial, comparing the mechanical safety of a new personalised 3D printed high tibial osteotomy device with an existing generic device, shows that there is no increased risk of failure for the new personalised design compared to the existing generic commonly used device. Personalised high tibial osteotomy can overcome the main technical barriers for this type of surgery, our findings support the case for using this technology for treating early knee osteoarthritis.

QCT-FE modeling of the proximal tibia: Effect of mapping strategy on convergence time and model accuracy

Quantitative computed tomography (QCT) based finite element (FE) modeling, referred to as QCT-FE, has seen rapid growth and application for modeling bone mechanics. With this approach, varying bone material properties are set via experimentally-derived density-modulus equations. One challenge though associated with QCT-FE is to identify the appropriate mapping strategy for assigning elastic moduli to elements. The goal of this study was to evaluate different QCT-FE mapping strategies to identify the optimum approach with fastest convergence rate and highest accuracy. Four proximal tibial medial compartments were imaged using QCT and experimentally tested to characterize proximal tibial subchondral bone stiffness at four surface points, resulting in a total of 16 indentation measures. Three material mapping methods were analyzed: (1) constant-E where an average elastic modulus was assigned to each element; (2) node-based where the material properties were first mapped on nodes then interpolated to Gaussian integration points; and (3) element-based in which the material properties were directly assigned to Gaussian integration points. Different element sizes were assessed with edge-lengths ranging from 0.9 to 3 mm. Results indicated that all converged models showed similar coefficient-of-determination (R²) and normalized root-mean-square errors (RMSE%). Though, the constant-E and node-based methods converged with the element edge-length of 1.5 mm (prediction error of 4.8% and 2.5%, respectively) whereas the element-based method converged with a larger element having an edge-length 2.5 mm (error = 4.9%). In conclusion, the element-based method, with a larger element size, resulted in similar predictive accuracy, faster convergence and shorter run-times relative to the constant-E and node-based approaches. As such, we recommend the element-based method for future subject-specific QCT-FE modeling.

Use of Computational Modeling to Study Joint Degeneration: A Review

Osteoarthritis (OA), a degenerative joint disease, is the most common chronic condition of the joints, which cannot be prevented effectively. Computational modeling of joint degradation allows to estimate the patient-specific progression of OA, which can aid clinicians to estimate the most suitable time window for surgical intervention in osteoarthritic patients. This paper gives an overview of the different approaches used to model different aspects of joint degeneration, thereby focusing mostly on the knee joint. The paper starts by discussing how OA affects the different components of the joint and how these are accounted for in the models. Subsequently, it discusses the different modeling approaches that can be used to answer questions related to OA etiology, progression and treatment. These models are ordered based on their underlying assumptions and technologies: musculoskeletal models, Finite Element models, (gene) regulatory models, multiscale models and data-driven models (artificial intelligence/machine learning). Finally, it is concluded that in the future, efforts should be made to integrate the different modeling techniques into a more robust computational framework that should not only be efficient to predict OA progression but also easily allow a patient’s individualized risk assessment as screening tool for use in clinical practice.

An exclusion approach for addressing partial volume artifacts with quantititive computed tomography-based finite element modeling of the proximal tibia

INTRODUCTION

Quantitative computed tomography based finite element modeling (QCT-FE) has potential to clarify the role of subchondral bone stiffness in osteoarthritis. The limited spatial resolution of clinical QCT systems, however, results in partial volume (PV) artifacts and low contrast between cortical and trabecular bone, which adversely affects the accuracy of QCT-FE models. The objective of this research was to evaluate the agreement between stiffness predictions offered by QCT-FE models of proximal tibial subchondral bone (constructed with and without a new voxel-exclusion algorithm) with experimentally-derived local subchondral bone structural stiffness.

METHODS

Thirteen proximal tibial compartments were obtained and imaged using QCT. Two types of QCT-FE models were developed: (1) standard model, which employed the standard procedure for QCT-FE modeling; and (2) "voxel exclusion (VE)" model, which addressed PV artifacts by excluding low density voxels during the material mapping stage of construction. We assessed agreement between QCT-FE stiffness estimates (using standard and VE approaches) with experimental stiffness by reporting predicted variance from linear regression and mean bias with 95% Limits of Agreement (LOA).

RESULTS

The standard and VE models explained 81% and 84% of the variance in experimentally measured stiffness, respectively. The standard model showed a mean bias of -268 N/mm (LOA -1210 to 679 N/mm); the VE model showed a mean bias of +59 N/mm (LOA -762 to 910 N/mm).

INTERPRETATION

The VE model explained more variance in subchondral bone stiffness with less bias. Our findings indicate that the VE method has potential to improve QCT-FE models of bone affected by PV artifacts.

Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis-A Survey

This paper provides a starting point for researchers and practitioners from biology, medicine, physics and engineering who can benefit from an up-to-date literature survey on patient-specific bone fracture modelling, simulation and risk analysis. This survey hints at a framework for devising realistic patient-specific bone fracture simulations. This paper has 18 sections: Section 1 presents the main interested parties; Section 2 explains the organzation of the text; Section 3 motivates further work on patient-specific bone fracture simulation; Section 4 motivates this survey; Section 5 concerns the collection of bibliographical references; Section 6 motivates the physico-mathematical approach to bone fracture; Section 7 presents the modelling of bone as a continuum; Section 8 categorizes the surveyed literature into a continuum mechanics framework; Section 9 concerns the computational modelling of bone geometry; Section 10 concerns the estimation of bone mechanical properties; Section 11 concerns the selection of boundary conditions representative of bone trauma; Section 12 concerns bone fracture simulation; Section 13 presents the multiscale structure of bone; Section 14 concerns the multiscale mathematical modelling of bone; Section 15 concerns the experimental validation of bone fracture simulations; Section 16 concerns bone fracture risk assessment. Lastly, glossaries for symbols, acronyms, and physico-mathematical terms are provided.

Mechanical Metrics of the Proximal Tibia are Precise and Differentiate Osteoarthritic and Normal Knees: A Finite Element Study

Our objective was to identify precise mechanical metrics of the proximal tibia which differentiated OA and normal knees. We developed subject-specific FE models for 14 participants (7 OA, 7 normal) who were imaged three times each for assessing precision (repeatability). We assessed various mechanical metrics (minimum principal and von Mises stress and strain as well as structural stiffness) across the proximal tibia for each subject. In vivo precision of these mechanical metrics was assessed using CV%RMS. We performed parametric and non-parametric statistical analyses and determined Cohen's d effect sizes to explore differences between OA and normal knees. For all FE-based mechanical metrics, average CV%RMS was less than 6%. Minimum principal stress was, on average, 75% higher in OA versus normal knees while minimum principal strain values did not differ. No difference was observed in structural stiffness. FE modeling could precisely quantify and differentiate mechanical metrics variations in normal and OA knees, in vivo. This study suggests that bone stress patterns may be important for understanding OA pathogenesis at the knee.

Utility of cement injection to stabilize split-depression tibial plateau fracture by minimally invasive methods: A finite element analysis

BACKGROUND

Treatment for fractures of the tibial plateau is in most cases carried out by stable fixation in order to allow early mobilization. Minimally invasive technologies such as tibioplasty or stabilization by locking plate, bone augmentation and cement filling (CF) have recently been used to treat this type of fracture. The aim of this paper was to determine the mechanical behavior of the tibial plateau by numerically modeling and by quantifying the mechanical effects on the tibia mechanical properties from injury healing.

METHODS

A personalized Finite Element (FE) model of the tibial plateau from a clinical case has been developed to analyze stress distribution in the tibial plateau stabilized by balloon osteoplasty and to determine the influence of the cement injected. Stress analysis was performed for different stages after surgery.

FINDINGS

Just after surgery, the maximum von Mises stresses obtained for the fractured tibia treated with and without CF were 134.9 MPa and 289.9 MPa respectively on the plate. Stress distribution showed an increase of values in the trabecular bone in the treated model with locking plate and CF and stress reduction in the cortical bone in the model treated with locking plate only.

INTERPRETATION

The computed results of stresses or displacements of the fractured models show that the cement filling of the tibial depression fracture may increase implant stability, and decrease the loss of depression reduction, while the presence of the cement in the healed model renders the load distribution uniform.

Accounting for spatial variation of trabecular anisotropy with subject-specific finite element modeling moderately improves predictions of local subchondral bone stiffness at the proximal tibia

INTRODUCTION

Previously, a finite element (FE) model of the proximal tibia was developed and validated against experimentally measured local subchondral stiffness. This model indicated modest predictions of stiffness (R²=0.77, normalized root mean squared error (RMSE%)=16.6%). Trabecular bone though was modeled with isotropic material properties despite its orthotropic anisotropy. The objective of this study was to identify the anisotropic FE modeling approach which best predicted (with largest explained variance and least amount of error) local subchondral bone stiffness at the proximal tibia.

METHODS

Local stiffness was measured at the subchondral surface of 13 medial/lateral tibial compartments using in situ macro indentation testing. An FE model of each specimen was generated assuming uniform anisotropy with 14 different combinations of cortical- and tibial-specific density-modulus relationships taken from the literature. Two FE models of each specimen were also generated which accounted for the spatial variation of trabecular bone anisotropy directly from clinical CT images using grey-level structure tensor and Cowin's fabric-elasticity equations. Stiffness was calculated using FE and compared to measured stiffness in terms of R² and RMSE%.

RESULTS

The uniform anisotropic FE model explained 53-74% of the measured stiffness variance, with RMSE% ranging from 12.4 to 245.3%. The models which accounted for spatial variation of trabecular bone anisotropy predicted 76-79% of the variance in stiffness with RMSE% being 11.2-11.5%.

CONCLUSIONS

Of the 16 evaluated finite element models in this study, the combination of Synder and Schneider (for cortical bone) and Cowin's fabric-elasticity equations (for trabecular bone) best predicted local subchondral bone stiffness.

Optimizing finite element predictions of local subchondral bone structural stiffness using neural network-derived density-modulus relationships for proximal tibial subchondral cortical and trabecular bone

BACKGROUND

Quantitative computed tomography based subject-specific finite element modeling has potential to clarify the role of subchondral bone alterations in knee osteoarthritis initiation, progression, and pain. However, it is unclear what density-modulus equation(s) should be applied with subchondral cortical and subchondral trabecular bone when constructing finite element models of the tibia. Using a novel approach applying neural networks, optimization, and back-calculation against in situ experimental testing results, the objective of this study was to identify subchondral-specific equations that optimized finite element predictions of local structural stiffness at the proximal tibial subchondral surface.

METHODS

Thirteen proximal tibial compartments were imaged via quantitative computed tomography. Imaged bone mineral density was converted to elastic moduli using multiple density-modulus equations (93 total variations) then mapped to corresponding finite element models. For each variation, root mean squared error was calculated between finite element prediction and in situ measured stiffness at 47 indentation sites. Resulting errors were used to train an artificial neural network, which provided an unlimited number of model variations, with corresponding error, for predicting stiffness at the subchondral bone surface. Nelder-Mead optimization was used to identify optimum density-modulus equations for predicting stiffness.

FINDINGS

Finite element modeling predicted 81% of experimental stiffness variance (with 10.5% error) using optimized equations for subchondral cortical and trabecular bone differentiated with a 0.5g/cm³ density.

INTERPRETATION

In comparison with published density-modulus relationships, optimized equations offered improved predictions of local subchondral structural stiffness. Further research is needed with anisotropy inclusion, a smaller voxel size and de-blurring algorithms to improve predictions.

Quantitative Computed Tomography (QCT) derived Bone Mineral Density (BMD) in finite element studies: a review of the literature

BACKGROUND

Finite element modeling of human bone provides a powerful tool to evaluate a wide variety of outcomes in a highly repeatable and parametric manner. These models are most often derived from computed tomography data, with mechanical properties related to bone mineral density (BMD) from the x-ray energy attenuation provided from this data. To increase accuracy, many researchers report the use of quantitative computed tomography (QCT), in which a calibration phantom is used during image acquisition to improve the estimation of BMD. Since model accuracy is dependent on the methods used in the calculation of BMD and density-mechanical property relationships, it is important to use relationships developed for the same anatomical location and using the same scanner settings, as these may impact model accuracy. The purpose of this literature review is to report the relationships used in the conversion of QCT equivalent density measures to ash, apparent, and/or tissue densities in recent finite element (FE) studies used in common density-modulus relationships. For studies reporting experimental validation, the validation metrics and results are presented.

RESULTS

Of the studies reviewed, 29% reported the use of a dipotassium phosphate (K2HPO4) phantom, 47% a hydroxyapatite (HA) phantom, 13% did not report phantom type, 7% reported use of both K2HPO4 and HA phantoms, and 4% alternate phantom types. Scanner type and/or settings were omitted or partially reported in 31% of studies. The majority of studies used densitometric and/or density-modulus relationships derived from different anatomical locations scanned in different scanners with different scanner settings. The methods used to derive various densitometric relationships are reported and recommendations are provided toward the standardization of reporting metrics.

CONCLUSIONS

This review assessed the current state of QCT-based FE modeling with use of clinical scanners. It was found that previously developed densitometric relationships vary by anatomical location, scanner type and settings. Reporting of all parameters used when referring to previously developed relationships, or in the development of new relationships, may increase the accuracy and repeatability of future FE models.