Material Mapping of QCT-Derived Scapular Models: A Comparison with Micro-CT Loaded Specimens Using Digital Volume Correlation

Time-elapsed microstructural imaging of failure of the reverse shoulder implant

BACKGROUND

Reverse Shoulder Arthroplasties (RSA) have become a primary choice for improving shoulder function and pain. However, the biomechanical failure mechanism of the humeral component is still unclear. The present study reports a novel protocol for microstructural imaging of the entire humerus implant under load before and after fracture.

METHODS

A humerus specimen was obtained from a 75-year-old male donor. An expert surgeon implanted the specimen with a commonly used RSA implant (Aequalis reversed II, Stryker Orthopaedics, USA) and surgical procedure. The physiological glenohumeral contact force that maximized the distal implant migration was selected from a public repository ( orthoload.com ). Imaging and concomitant mechanical testing were performed using a large-volume micro-CT scanner (Nikon XT H 225 ST) and a custom-made compressive stage. Both when intact and once implanted, the specimen was tested under a pre-load and by imposing a constant deformation causing a physiological reaction load (650 N, 10 degrees adducted). The deformation of the implanted specimen was then increased up to fracture, which was identified by a sudden drop of the reaction force, and the specimen was then re-scanned.

RESULTS

The specimen's stiffness decreased from 874 N/mm to 464 N/mm after implantation, producing movements of the bone-implant interface consistent with the implant's long-term stability reported in the literature. The micro-CT images displayed fracture of the tuberosity, caused by a combined compression and circumferential tension, induced by the distal migration of the implant.

CONCLUSION

The developed protocol offers detailed information on implant mechanics under load relative to intact conditions and fracture, providing insights into the failure mechanics of RSA implants. This protocol can be used to inform future implant design and surgical technique improvements.

Comparison of linear and nonlinear stepwise μFE displacement predictions to digital volume correlation measurements of trabecular bone biopsies

Digital volume correlation (DVC) enables to evaluate the ability of μFE models in predicting experimental results on the mesoscale. In this study predicted displacement fields of three different linear and materially nonlinear μFE simulation methods were compared to DVC measured displacement fields at specific load steps in the elastic regime (Step_El) and after yield (Step_Ult). Five human trabecular bone biopsies from a previous study were compressed in several displacement steps until failure. At every compression step, μCT images (resolution: 36 μm) were recorded. A global DVC algorithm was applied to compute the displacement fields at all loading steps. The unloaded 3D images were then used to generate homogeneous, isotropic, linear and materially nonlinear μFE models. Three different μFE simulation methods were used: linear (L), nonlinear (NL), and nonlinear stepwise (NLS). Regarding L and NL, the boundary conditions were derived from the interpolated displacement fields at Step_El and Step_Ult, while for the NLS method nonlinear changes of the boundary conditions of the experiments were captured using the DVC displacement field of every available load step until Step_El and Step_Ult. The predicted displacement fields of all μFE simulation methods were in good agreement with the DVC measured displacement fields (individual specimens: R²>0.83 at Step_El and R²>0.59 at Step_Ult; pooled data: R²>0.97 at Step_El and R²>0.92 at Step_Ult). At Step_El, all three simulation methods showed similar intercepts, slopes, and coefficients of determination while the nonlinear μFE models improved the prediction of the displacement fields slightly in all Cartesian directions at Step_Ult (individual specimens: L: R²>0.59 and NL, NLS: R²>0.68; pooled data: L: R²>0.92 and NL, NLS: R²>0.94). Damaged/overstrained elements in L, NL, and NLS occurred at similar locations but the number of overstrained elements was overestimated when using the L simulation method. Considering the increased solving time of the nonlinear μFE models as well as the acceptable performance in displacement prediction of the linear μFE models, one can conclude that for similar use cases linear μFE models represent the best compromise between computational effort and accuracy of the displacement field predictions.

A practical guide for in situ mechanical testing of musculoskeletal tissues using synchrotron tomography

Musculoskeletal tissues are complex hierarchical materials where mechanical response is linked to structural and material properties at different dimensional levels. Therefore, high-resolution three-dimensional tomography is very useful for assessing tissue properties at different scales. In particular, Synchrotron Radiation micro-Computed Tomography (SR-microCT) has been used in several applications to analyze the structure of bone and biomaterials. In the past decade the development of digital volume correlation (DVC) algorithms applied to SR-microCT images and its combination with in situ mechanical testing (four-dimensional imaging) have allowed researchers to visualise, for the first time, the deformation of musculoskeletal tissues and their interaction with biomaterials under different loading scenarios. However, there are several experimental challenges that make these measurements difficult and at high risk of failure. Challenges relate to sample preparation, imaging parameters, loading setup, accumulated tissue damage for multiple tomographic acquisitions, reconstruction methods and data processing. Considering that access to SR-microCT facilities is usually associated with bidding processes and long waiting times, the failure of these experiments could notably slow down the advancement of this research area and reduce its impact. Many of the experimental failures can be avoided with increased experience in performing the tests and better guidelines for preparation and execution of these complex experiments; publication of negative results could help interested researchers to avoid recurring mistakes. Therefore, the goal of this article is to highlight the potential and pitfalls in the design and execution of in situ SR-microCT experiments, involving multiple scans, of musculoskeletal tissues for the assessment of their structural and/or mechanical properties. The advice and guidelines that follow should improve the success rate of this type of experiment, allowing the community to reach higher impact more efficiently.

MicroFE models of porcine vertebrae with induced bone focal lesions: Validation of predicted displacements with digital volume correlation

The evaluation of the local mechanical behavior as a result of metastatic lesions is fundamental for the characterization of the mechanical competence of metastatic vertebrae. Micro finite element (microFE) models have the potential of addressing this challenge through laboratory studies but their predictions of local deformation due to the complexity of the bone structure compromized by the lesion must be validated against experiments. In this study, the displacements predicted by homogeneous, linear and isotropic microFE models of vertebrae were validated against experimental Digital Volume Correlation (DVC) measurements. Porcine spine segments, with and without mechanically induced focal lesions, were tested in compression within a micro computed tomography (microCT) scanner. The displacement within the bone were measured with an optimized global DVC approach (BoneDVC). MicroFE models of the intact and lesioned vertebrae, including or excluding the growth plates, were developed from the microCT images. The microFE and DVC boundary conditions were matched. The displacements measured by the DVC and predicted by the microFE along each Cartesian direction were compared. The results showed an excellent agreement between the measured and predicted displacements, both for intact and metastatic vertebrae, in the middle of the vertebra, in those cases where the structure was not loaded beyond yield (0.69 < R² < 1.00). Models with growth plates showed the worst correlations (0.02 < R² < 0.99), while a clear improvement was observed if the growth plates were excluded (0.56 < R² < 1.00). In conclusion, these simplified models can predict complex displacement fields in the elastic regime with high reliability, more complex non-linear models should be implemented to predict regions with high deformation, when the bone is loaded beyond yield.

Complications of Reverse Total Shoulder Arthroplasty: A Computational Modelling Perspective

Reverse total shoulder arthroplasty (RTSA) is an established treatment for elderly patients with irreparable rotator cuff tears, complex proximal humerus fractures, and revision arthroplasty; however, with the increasing indications for RTSA over the last decade and younger implant recipients, post-operative complications have become more frequent, which has driven advances in computational modeling and simulation of reverse shoulder biomechanics. The objective of this study was to provide a review of previously published studies that employed computational modeling to investigate complications associated with RTSA. Models and applications were reviewed and categorized into four possible complications that included scapular notching, component loosening, glenohumeral joint instability, and acromial and scapular spine fracture, all of which remain a common cause of significant functional impairment and revision surgery. The computational shoulder modeling studies reviewed were primarily used to investigate the effects of implant design, intraoperative component placement, and surgical technique on postoperative shoulder biomechanics after RTSA, with the findings ultimately used to elucidate and mitigate complications. The most significant challenge associated with the development of computational models is in the encapsulation of patient-specific anatomy and surgical planning. The findings of this review provide a basis for future direction in computational modeling of the reverse shoulder.

Proximal Tibia Bone Stiffness and Strength in HR-pQCT- and QCT-Based Finite Element Models

Injury to the ACL significantly increases the risk of developing post-traumatic osteoarthritis. Following injury, considerable focus is placed on visualizing soft tissue changes using MRI, but there is less emphasis on the alterations to the underlying bone. It has recently been shown using high-resolution peripheral quantitative computed tomography (HR-pQCT) that significant reductions in bone quality occur in the knee post ACL-injury. Despite the ability of HR-pQCT to show these changes, the availability of scanners and computational time requirements required to assess bone stiffness and strength with HR-pQCT limit its widespread clinical use. As such, the objective of this study was to determine if clinical quantitative CT (QCT) finite element models (QCT-FEMs) can accurately replicate HR-pQCT FEM proximal tibial stiffness and strength. From FEMs of 30 participants who underwent both QCT and HR-pQCT bilateral imaging, QCT-FEMs were strongly correlated with HR-pQCT FEM stiffness (R² = 0.79). When QCT-FEM bone strength was estimated using the reaction force at 1% apparent strain, strong correlations were observed (R² = 0.81), with no bias between HR-pQCT FEMs and non-linear QCT-FEMs. These results indicate that QCT-FEMs can accurately replicate HR-pQCT FEM stiffness and strength in the proximal tibia. Although these models are not able to replicate the trabecular structure or tissue-level strains, they require significantly reduced computational time and use widely available clinical-CT images as input, which make them an attractive choice to monitor bone density, stiffness and strength alterations, such as those that occur post ACL-injury.

Full-field comparisons between strains predicted by QCT-derived finite element models of the scapula and experimental strains measured by digital volume correlation

Subject-specific finite element models (FEMs) of the shoulder can be used to evaluate joint replacement designs preclinically. However, to ensure accurate conclusions are drawn, experimental validation is critical. The objective of the current study was to evaluate the accuracy of strain predictions generated by subject-specific scapula FEMs through comparisons against full-field experimental strains measured using digital volume correlation (DVC). Three cadaveric scapulae were mechanically loaded using a custom-hexapod robot within a micro-CT scanner. BoneDVC was used to quantify resultant experimental full-field strains. Scapula FEMs were generated using three different density-modulus relationships to assign material properties. Two types of boundary conditions (BCs) were simulated: DVC-displacement-driven or applied-force-driven. Third principal strains were compared between the DVC measurements and FEM predictions. With applied-force BCs, poor agreement was observed between the predicted and measured strains (slope range: 0.16-0.19, r² range: 0.04-0.30). Agreement was improved with the use of DVC-displacement BCs (slope range: 0.54-0.59, r² range: 0.73-0.75). Strain predictions were independent of the density-modulus relationship used for DVC-displacement BCs, but differences were observed in the correlation coefficient and intercept for applied-force BCs. Overall, this study utilized full-field DVC-derived experimental strains for comparison with FEM predicted strains in models with varying material properties and BCs. It was found that fair agreement can be achieved in localized strain measurements between DVC measurements and FEM predictions when DVC-displacement BCs are used. However, performance suffered with use of applied-force BCs.

Bone Damage Evolution Around Integrated Metal Screws Using X-Ray Tomography - in situ Pullout and Digital Volume Correlation

Better understanding of the local deformation of the bone network around metallic implants subjected to loading is of importance to assess the mechanical resistance of the bone-implant interface and limit implant failure. In this study, four titanium screws were osseointegrated into rat tibiae for 4 weeks and screw pullout was conducted in situ under x-ray microtomography, recording macroscopic mechanical behavior and full tomographies at multiple load steps before failure. Images were analyzed using Digital Volume Correlation (DVC) to access internal displacement and deformation fields during loading. A repeatable failure pattern was observed, where a ∼300–500 μm-thick envelope of bone detached from the trabecular structure. Fracture initiated close to the screw tip and propagated along the implant surface, at a distance of around 500 μm. Thus, the fracture pattern appeared to be influenced by the microstructure of the bone formed closely around the threads, which confirmed that the model is relevant for evaluating the effect of pharmacological treatments affecting local bone formation. Moreover, cracks at the tibial plateau were identified by DVC analysis of the tomographic images acquired during loading. Moderate strains were first distributed in the trabecular bone, which localized into higher strains regions with subsequent loading, revealing crack-formation not evident in the tomographic images. The in situ loading methodology followed by DVC is shown to be a powerful tool to study internal deformation and fracture behavior of the newly formed bone close to an implant when subjected to loading. A better understanding of the interface failure may help improve the outcome of surgical implants.

The Application of Digital Volume Correlation (DVC) to Evaluate Strain Predictions Generated by Finite Element Models of the Osteoarthritic Humeral Head

Continuum-level finite element models (FEMs) of the humerus offer the ability to evaluate joint replacement designs preclinically; however, experimental validation of these models is critical to ensure accuracy. The objective of the current study was to quantify experimental full-field strain magnitudes within osteoarthritic (OA) humeral heads by combining mechanical loading with volumetric microCT imaging and digital volume correlation (DVC). The experimental data was used to evaluate the accuracy of corresponding FEMs. Six OA humeral head osteotomies were harvested from patients being treated with total shoulder arthroplasty and mechanical testing was performed within a microCT scanner. MicroCT images (33.5 µm isotropic voxels) were obtained in a pre- and post-loaded state and BoneDVC was used to quantify full-field experimental strains (≈ 1 mm nodal spacing, accuracy = 351 µstrain, precision = 518 µstrain). Continuum-level FEMs with two types of boundary conditions (BCs) were simulated: DVC-driven and force-driven. Accuracy of the FEMs was found to be sensitive to the BC simulated with better agreement found with the use of DVC-driven BCs (slope = 0.83, r² = 0.80) compared to force-driven BCs (slope = 0.22, r² = 0.12). This study quantified mechanical strain distributions within OA trabecular bone and demonstrated the importance of BCs to ensure the accuracy of predictions generated by corresponding FEMs.