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

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.

A novel tool to quantify in vivo lumbar spine kinematics and 3D intervertebral disc strains using clinical MRI

Medical imaging modalities that calculate tissue morphology alone cannot provide direct information regarding the mechanical behaviour of load-bearing musculoskeletal organs. Accurate in vivo measurement of spine kinematics and intervertebral disc (IVD) strains can provide important information regarding the mechanical behaviour of the spine, help to investigate the effects of injuries on the mechanics of the spine, and assess the effectiveness of treatments. Additionally, strains can serve as a functional biomechanical marker for detecting normal and pathologic tissues. We hypothesised that combining digital volume correlation (DVC) with 3T clinical MRI can provide direct information regarding the mechanics of the spine. Here, we have developed a novel non-invasive tool for in vivo displacement and strain measurement within the human lumbar spine and we used this tool to calculate lumbar kinematics and IVD strains in six healthy subjects during lumbar extension. The proposed tool enabled spine kinematics and IVD strains to be measured with errors that did not exceed 0.17 mm and 0.5%, respectively. The findings of the kinematics study identified that during extension the lumbar spine of healthy subjects experiences total 3D translations ranging from 1 mm to 4.5 mm for different vertebral levels. The findings of strain analysis identified that the average of the maximum tensile, compressive, and shear strains for different lumbar levels during extension ranged from 3.5% to 7.2%. This tool can provide base-line data that can be used to describe the mechanical environment of healthy lumbar spine, which can help clinicians manage preventative treatments, define patient-specific treatments, and to monitor the effectiveness of surgical and non-surgical interventions.

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.

Mechanoregulation may drive osteolysis during bone metastasis: A finite element analysis of the mechanical environment within bone tissue during bone metastasis and osteolytic resorption

Metastatic bone disease occurs in 70-80% of advanced breast cancer patients and bone tissue is accepted to have attractive physical properties that facilitate cancer cell attraction, adhesion, and invasion. Bone cells also facilitate tumour invasion by biochemical signalling and through resorption of the bone matrix (osteolysis), which releases factors that further stimulate tumour cell activity. The evolving mechanical environment during tumour invasion might play an important role in these processes, as the activity of both bone and cancer cells is regulated by mechanical cues. In particular bone loss and altered mineralisation have been reported, yet how these alter the mechanical environment local to bone and tumour cells is unknown. The objective of this study is to quantify changes in the mechanical environment within bone tissue, during bone metastasis and osteolytic resorption, using finite element analysis (FEA) models reconstructed from high-resolution μCT images of metastatic mouse bone. In particular, we quantify time-dependent changes in mechanical stimuli, local to and distant from an invading tumour mass, to investigate putative mechanobiological cues for osteolysis during bone metastasis. We report here that in early metastasis (3 weeks after tumour inoculation), there was a decrease in strain distribution within the proximal femur trabecular and distal cortical bone tissue. These changes in the mechanical environment preceded extensive osteolytic destruction, but coincided with the onset of early osteolysis, cortical thickening and mineralisation of proximal and distal femur bone. We propose that early changes in the mechanical environment within bone tissue may activate resorption by osteoclast cells and thereby contribute to the extensive osteolytic bone loss at later stage (6 weeks) bone metastasis.

Digital Volume Correlation for large deformations of soft tissues: Pipeline and proof of concept for the application to breast ex vivo deformations

Being able to reposition tumors from prone imaging to supine surgery stances is key for bypassing current invasive marking used for conservative breast surgery. This study aims to demonstrate the feasibility of using Digital Volume Correlation (DVC) to measure the deformation of a female quarter thorax between two different body positioning when subjected to gravity. A segmented multipart mesh (bones, cartilage and tissue) was constructed and a three-step FE-based DVC procedure with heterogeneous elastic regularization was implemented. With the proposed framework, the large displacement field of a hard/soft breast sample was recovered with low registration residuals and small error between the measured and manually determined deformations of phase interfaces. The present study showed the capacity of FE-based DVC to faithfully capture large deformations of hard/soft tissues.

Nonlinear micro finite element models based on digital volume correlation measurements predict early microdamage in newly formed bone

Bone regeneration in critical-sized defects is a clinical challenge, with biomaterials under constant development aiming at enhancing the natural bone healing process. The delivery of bone morphogenetic proteins (BMPs) in appropriate carriers represents a promising strategy for bone defect treatment but optimisation of the spatial-temporal release is still needed for the regeneration of bone with biological, structural, and mechanical properties comparable to the native tissue. Nonlinear micro finite element (μFE) models can address some of these challenges by providing a tool able to predict the biomechanical strength and microdamage onset in newly formed bone when subjected to physiological or supraphysiological loads. Yet, these models need to be validated against experimental data. In this study, experimental local displacements in newly formed bone induced by osteoinductive biomaterials subjected to in situ X-ray computed tomography compression in the apparent elastic regime and measured using digital volume correlation (DVC) were used to validate μFE models. Displacement predictions from homogeneous linear μFE models were highly correlated to DVC-measured local displacements, while tissue heterogeneity capturing mineralisation differences showed negligible effects. Nonlinear μFE models improved the correlation and showed that tissue microdamage occurs at low apparent strains. Microdamage seemed to occur next to large cavities or in biomaterial-induced thin trabeculae, independent of the mineralisation. While localisation of plastic strain accumulation was similar, the amount of damage accumulated in these locations was slightly higher when including material heterogeneity. These results demonstrate the ability of the nonlinear μFE model to capture local microdamage in newly formed bone tissue and can be exploited to improve the current understanding of healing bone and mechanical competence. This will ultimately aid the development of BMPs delivery systems for bone defect treatment able to regenerate bone with optimal biological, mechanical, and structural properties.

Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments

Biological tissues are complex hierarchical materials, difficult to characterise due to the challenges associated to the separation of scale and heterogeneity of the mechanical properties at different dimensional levels. The Digital Volume Correlation approach is the only image-based experimental approach that can accurately measure internal strain field within biological tissues under complex loading scenarios. In this minireview examples of DVC applications to study the deformation of musculoskeletal tissues at different dimensional scales are reported, highlighting the potential and challenges of this relatively new technique. The manuscript aims at reporting the wide breath of DVC applications in the past 2 decades and discuss future perspective for this unique technique, including fast analysis, applications on soft tissues, high precision approaches, and clinical applications.