Experimental and numerical investigation of secondary screw perforation in the human proximal humerus

Homogenized finite element simulations can predict the primary stability of dental implants in human jawbone

Adequate primary stability is a pre-requisite for the osseointegration and long-term success of dental implants. Primary stability depends essentially on the bone mechanical integrity at the implantation site. Clinically, a qualitative evaluation can be made on medical images, but finite element (FE) simulations can assess the primary stability of a bone-implant construct quantitatively based on high-resolution CT images. However, FE models lack experimental validation on clinically relevant bone anatomy. The aim of this study is to validate such an FE model on human jawbones. Forty-seven bone biopsies were extracted from human cadaveric jawbones. Dental implants of two sizes (Ø3.5 mm and Ø4.0 mm) were inserted and the constructs were subjected to a quasi-static bending-compression loading protocol. Those mechanical tests were replicated with sample-specific non-linear homogenized FE models. Bone was modeled with an elastoplastic constitutive law that included damage. Density-based material properties were mapped based on μCT images of the bone samples. The experimental ultimate load was better predicted by FE (R2 = 0.83) than by peri-implant bone density (R2 = 0.54). Unlike bone density, the simulations were also able to capture the effect of implant diameter. The primary stability of a dental implant in human jawbones can be predicted quantitatively with FE simulations. This method may be used for improving the design and insertion protocols of dental implants.

Comparison of simplified bone-screw interface models in materially nonlinear μFE simulations

Micro finite-element (μFE) simulations serve as a crucial research tool to assist laboratory experiments in the biomechanical assessment of screw anchorage in bone. However, accurately modelling the interface between bone and screw threads at the microscale poses a significant challenge. Currently, the gold-standard approach involves employing computationally intensive physical contact models to simulate this interface. This study compared nonlinear μFE predictions of deformations, whole-construct stiffness, maximum force and damage patterns of three different computationally efficient simplified interface approaches to the general contact interface in Abaqus Explicit, which was defined as gold-standard and reference model. The μCT images (resolution: 32.8 μm) of two human radii with varying bone volume fractions were utilized and a screw was virtually inserted up to 50% and 100% of the volar-dorsal cortex distance. Materially nonlinear μFE models were generated and loaded in tension, compression and shear. In a first step, the common simplification of using a fully-bonded interface was compared to the general contact interface, revealing overestimations of whole-construct stiffness (19% on average) and maximum force (26% on average), along with inaccurate damage pattern replications. To enhance predictions, two additional simplified interface models were compared: tensionally strained element deletion (TED) and a novel modification of TED (TED-M). TED deletes interface elements strained in tension based on a linear-elastic simulation before the actual simulation. TED-M extends the remaining contact interface of TED by incorporating neighboring elements to the contact area. Both TED and TED-M reduced the errors in whole-construct stiffness and maximum force and improved the replication of the damage distributions in comparison to the fully-bonded approach. TED was better in predicting whole-construct stiffness (average error of 1%), while TED-M showed lowest errors in maximum force (1% on average). In conclusion, both TED and TED-M offer computationally efficient alternatives to physical contact modelling, although the fully-bonded interface may deliver sufficiently accurate predictions for many applications.

Critical loss of primary implant stability in osteosynthesis locking screws under cyclic overloading

Primary implant stability, which refers to the stability of the implant during the initial healing period is a crucial factor in determining the long-term success of the implant and lays the foundation for secondary implant stability achieved through osseointegration. Factors affecting primary stability include implant design, surgical technique, and patient-specific factors like bone quality and morphology. In vivo, the cyclic nature of anatomical loading puts osteosynthesis locking screws under dynamic loads, which can lead to the formation of micro cracks and defects that slowly degrade the mechanical connection between the bone and screw, thus compromising the initial stability and secondary stability of the implant. Monotonic quasi-static loading used for testing the holding capacity of implanted screws is not well suited to capture this behavior since it cannot capture the progressive deterioration of peri‑implant bone at small displacements. In order to address this issue, this study aims to determine a critical point of loss of primary implant stability in osteosynthesis locking screws under cyclic overloading by investigating the evolution of damage, dissipated energy, and permanent deformation. A custom-made test setup was used to test implanted 2.5 mm locking screws under cyclic overloading test. For each loading cycle, maximum forces and displacement were recorded as well as initial and final cycle displacements and used to calculate damage and energy dissipation evolution. The results of this study demonstrate that for axial, shear, and mixed loading significant damage and energy dissipation can be observed at approximately 20 % of the failure force. Additionally, at this load level, permanent deformations on the screw-bone interface were found to be in the range of 50 to 150 mm which promotes osseointegration and secondary implant stability. This research can assist surgeons in making informed preoperative decisions by providing a better understanding of the critical point of loss of primary implant stability, thus improving the long-term success of the implant and overall patient satisfaction.

Preventing secondary screw perforation following proximal humerus fracture after locking plate fixation: a new clinical prognostic risk stratification model

INTRODUCTION

After locking plate (LP) fixation, secondary screw perforation (SSP) is the most common complication in proximal humerus fracture (PHF). SSP is the main cause of glenoid destruction and always leads to reoperation. This study aimed to identify independent risk parameters for SSP and establish an individualized risk prognostic model to facilitate its clinical management.

METHODS

We retrospectively reviewed the medical information of patients with PHF who underwent open reduction and internal LP fixation at one medical center (n = 289) between June 2013 and June 2021. Uni- and multivariate regression analyses identified the independent risk factors. A novel nomogram was formulated based on the final independent risk factors for predicting the risk of SSP. We performed internal validation through concordance indices (C-index) and calibration curves. To implement the clinical use of the model, we performed decision curve analyses (DCA) and risk stratification according to the optimal cutoff value.

RESULTS

A total of 232 patients who met the inclusion criteria were enrolled. The incidence of SSP was 21.98% at the last follow-up. We found that fracture type (odds ratio [OR], 3.111; 95% confidence interval [CI], 1.223-7.914; P = 0.017), postoperative neck-shaft angle (OR, 4.270; 95% CI 1.622-11.239; P = 0.003), the absence of calcar screws (OR, 3.962; 95% CI 1.753-8.955; P = 0.003), and non-medial metaphyseal support (OR,7.066; 95% CI 2.747-18.174; P = 0.000) were independent predictors of SSP. Based on these variables, we developed a nomogram that showed good discrimination (C-index = 0.815). The predicted values of the new model were in good agreement with the actual values demonstrated by the calibration curve. Furthermore, the model's DCA and risk stratification (cutoff = 140 points) showed significantly higher clinical benefits.

CONCLUSIONS

We developed and validated a visual and personalized nomogram that could predict the individual risk of SSP and provide a decision basis for surgeons to create the most optional management plan. However, future prospective and externally validated design studies are warranted to verify our model's efficacy.

Fatigue life of 3D-printed porous titanium dental implants predicted by validated finite element simulations

Introduction: Porous dental implants represent a promising strategy to reduce failure rate by favoring osseointegration or delivering drugs locally. Incorporating porous features weakens the mechanical capacity of an implant, but sufficient fatigue strength must be ensured as regulated in the ISO 14801 standard. Experimental fatigue testing is a costly and time-intensive part of the implant development process that could be accelerated with validated computer simulations. This study aimed at developing, calibrating, and validating a numerical workflow to predict fatigue strength on six porous configurations of a simplified implant geometry. Methods: Mechanical testing was performed on 3D-printed titanium samples to establish a direct link between endurance limit (i.e., infinite fatigue life) and monotonic load to failure, and a finite element model was developed and calibrated to predict the latter. The tool was then validated by predicting the fatigue life of a given porous configuration. Results: The normalized endurance limit (10% of the ultimate load) was the same for all six porous designs, indicating that monotonic testing was a good surrogate for endurance limit. The geometry input of the simulations influenced greatly their accuracy. Utilizing the as-designed model resulted in the highest prediction error (23%) and low correlation between the estimated and experimental loads to failure (R2 = 0.65). The prediction error was smaller when utilizing specimen geometry based on micro computed tomography scans (14%) or design models adjusted to match the printed porosity (8%). Discussion: The validated numerical workflow presented in this study could therefore be used to quantitatively predict the fatigue life of a porous implant, provided that the effect of manufacturing on implant geometry is accounted for.

Predicting fracture in the proximal humerus using phase field models

Proximal humerus impacted fractures are of clinical concern in the elderly population. Prediction of such fractures by CT-based finite element methods encounters several major obstacles such as heterogeneous mechanical properties and fracture due to compressive strains. We herein propose to investigate a variation of the phase field method (PFM) embedded into the finite cell method (FCM) to simulate impacted humeral fractures in fresh frozen human humeri. The force-strain response, failure loads and the fracture path are compared to experimental observations for validation purposes. The PFM (by means of the regularization parameter ℓ₀) is first calibrated by one experiment and thereafter used for the prediction of the mechanical response of two other human fresh frozen humeri. All humeri are fractured at the surgical neck and strains are monitored by Digital Image Correlation (DIC). Experimental strains in the elastic regime are reproduced with good agreement (R²=0.726), similarly to the validated finite element method (Dahan et al., 2022). The failure pattern and fracture evolution at the surgical neck predicted by the PFM mimic extremely well the experimental observations for all three humeri. The maximum relative error in the computed failure loads is 3.8%. To the best of our knowledge this is the first method that can predict well the experimental compressive failure pattern as well as the force-strain relationship in proximal humerus fractures.

Locking Plates With Computationally Enhanced Screw Trajectories Provide Superior Biomechanical Fixation Stability of Complex Proximal Humerus Fractures

Joint-preserving surgical treatment of complex unstable proximal humerus fractures remains challenging, with high failure rates even following state-of-the-art locked plating. Enhancement of implants could help improve outcomes. By overcoming limitations of conventional biomechanical testing, finite element (FE) analysis enables design optimization but requires stringent validation. This study aimed to computationally enhance the design of an existing locking plate to provide superior fixation stability and evaluate the benefit experimentally in a matched-pair fashion. Further aims were the evaluation of instrumentation accuracy and its potential influence on the specimen-specific predictive ability of FE. Screw trajectories of an existing commercial plate were adjusted to reduce the predicted cyclic cut-out failure risk and define the enhanced (EH) implant design based on results of a previous parametric FE study using 19 left proximal humerus models (Set A). Superiority of EH versus the original (OG) design was tested using nine pairs of human proximal humeri (N = 18, Set B). Specimen-specific CT-based virtual preoperative planning defined osteotomies replicating a complex 3-part fracture and fixation with a locking plate using six screws. Bone specimens were prepared, osteotomized and instrumented according to the preoperative plan via a standardized procedure utilizing 3D-printed guides. Cut-out failure of OG and EH implant designs was compared in paired groups with both FE analysis and cyclic biomechanical testing. The computationally enhanced implant configuration achieved significantly more cycles to cut-out failure compared to the standard OG design (p < 0.01), confirming the significantly lower peri-implant bone strain predicted by FE for the EH versus OG groups (p < 0.001). The magnitude of instrumentation inaccuracies was small but had a significant effect on the predicted failure risk (p < 0.01). The sample-specific FE predictions strongly correlated with the experimental results (R2 = 0.70) when incorporating instrumentation inaccuracies. These findings demonstrate the power and validity of FE simulations in improving implant designs towards superior fixation stability of proximal humerus fractures. Computational optimization could be performed involving further implant features and help decrease failure rates. The results underline the importance of accurate surgical execution of implant fixations and the need for high consistency in validation studies.

Non-linear explicit micro-FE models accurately predict axial pull-out force of cortical screws in human tibial cortical bone

Screws are the most frequently used implants for treatment of bone fractures and play an essential role in determining fixation stability. Robust prediction of the bone-screw interface failure would enable development of improved fixation strategies and implant designs, ultimately reducing failure rates and improving outcomes of bone fracture treatments. This study aimed to compare the accuracy of micro-computed tomography image based bone volume measures, linear micro-finite element (FE) and non-linear micro-FE simulations in predicting pull-out force of 3.5 mm screws in human cadaveric tibial cortical bone. Axial pull-out experiments were performed in forty samples harvested from a single human tibia to measure ultimate force, which was correlated with bone volume around the screw and the predictions by both linear micro-FE and non-linear explicit micro-FE models. Correlation strength was similar for bone volume around the screw (R² = 0.866) and linear micro-FE (R² = 0.861), but the explicit non-linear micro-FE models were able to capture the experimental results more accurately (R² = 0.913) and quantitatively correctly. Therefore, this technique may have potential for future in silico studies aiming at implant design optimization.

Finite Element Analysis of Fracture Fixation

PURPOSE OF REVIEW

Fracture fixation aims to provide stability and promote healing, but remains challenging in unstable and osteoporotic fractures with increased risk of construct failure and nonunion. The first part of this article reviews the clinical motivation behind finite element analysis of fracture fixation, its strengths and weaknesses, how models are developed and validated, and how outputs are typically interpreted. The second part reviews recent modeling studies of the femur and proximal humerus, areas with particular relevance to fragility fractures.

RECENT FINDINGS

There is some consensus in the literature around how certain modeling aspects are pragmatically formulated, including bone and implant geometries, meshing, material properties, interactions, and loads and boundary conditions. Studies most often focus on predicted implant stress, bone strain surrounding screws, or interfragmentary displacements. However, most models are not rigorously validated. With refined modeling methods, improved validation efforts, and large-scale systematic analyses, finite element analysis is poised to advance the understanding of fracture fixation failure, enable optimization of implant designs, and improve surgical guidance.