Can micro-imaging based analysis methods quantify structural integrity of rat vertebrae with and without metastatic involvement?

Evaluation of Load-To-Strength Ratios in Metastatic Vertebrae and Comparison With Age- and Sex-Matched Healthy Individuals

Vertebrae containing osteolytic and osteosclerotic bone metastases undergo pathologic vertebral fracture (PVF) when the lesioned vertebrae fail to carry daily loads. We hypothesize that task-specific spinal loading patterns amplify the risk of PVF, with a higher degree of risk in osteolytic than in osteosclerotic vertebrae. To test this hypothesis, we obtained clinical CT images of 11 cadaveric spines with bone metastases, estimated the individual vertebral strength from the CT data, and created spine-specific musculoskeletal models from the CT data. We established a musculoskeletal model for each spine to compute vertebral loading for natural standing, natural standing + weights, forward flexion + weights, and lateral bending + weights and derived the individual vertebral load-to-strength ratio (LSR). For each activity, we compared the metastatic spines' predicted LSRs with the normative LSRs generated from a population-based sample of 250 men and women of comparable ages. Bone metastases classification significantly affected the CT-estimated vertebral strength (Kruskal-Wallis, p < 0.0001). Post-test analysis showed that the estimated vertebral strength of osteosclerotic and mixed metastases vertebrae was significantly higher than that of osteolytic vertebrae (p = 0.0016 and p = 0.0003) or vertebrae without radiographic evidence of bone metastasis (p = 0.0010 and p = 0.0003). Compared with the median (50%) LSRs of the normative dataset, osteolytic vertebrae had higher median (50%) LSRs under natural standing (p = 0.0375), natural standing + weights (p = 0.0118), and lateral bending + weights (p = 0.0111). Surprisingly, vertebrae showing minimal radiographic evidence of bone metastasis presented significantly higher median (50%) LSRs under natural standing (p < 0.0001) and lateral bending + weights (p = 0.0009) than the normative dataset. Osteosclerotic vertebrae had lower median (50%) LSRs under natural standing (p < 0.0001), natural standing + weights (p = 0.0005), forward flexion + weights (p < 0.0001), and lateral bending + weights (p = 0.0002), a trend shared by vertebrae with mixed lesions. This study is the first to apply musculoskeletal modeling to estimate individual vertebral loading in pathologic spines and highlights the role of task-specific loading in augmenting PVF risk associated with specific bone metastatic types. Our finding of high LSRs in vertebrae without radiologically observed bone metastasis highlights that patients with metastatic spine disease could be at an increased risk of vertebral fractures even at levels where lesions have not been identified radiologically.

Fracture risk assessment and clinical decision making for patients with metastatic bone disease

Metastatic breast, prostate, lung, and other cancers often affect bone, causing pain, increasing fracture risk, and decreasing function. Management of metastatic bone disease (MBD) is clinically challenging when there is potential but uncertain risk of pathological fracture. Management of MBD has become a major focus within orthopedic oncology with respect to fracture and impending fracture care. If impending skeletal-related events (SREs), particularly pathologic fracture, could be predicted, increasing evidence suggests that prophylactic surgical treatment improves patient outcomes. However, current fracture risk assessment and radiographic metrics do not have high accuracy and have not been combined with relevant patient survival tools. This review first explores the prevalence, incidence, and morbidity of MBD and associated SREs for different cancer types. Strengths and limitations of current fracture risk scoring systems for spinal stability and long bone fracture are highlighted. More recent computed tomography (CT)-based structural rigidity analysis (CTRA) and finite element (FE) analysis methods offer advantages of increased specificity (true negative rate), but are limited in availability. Other fracture prediction approaches including parametric response mapping and positron emission tomography/computed tomography measures show early promise. Substantial new information to inform clinical decision-making includes measures of survival, clinical benefits, and economic analysis of prophylactic treatment compared to after-fracture stabilization. Areas of future research include use of big data and machine learning to predict SREs, greater access and refinement of CTRA/FE approaches, combination of clinical survival prediction tools with radiographically based fracture risk assessment, and net benefit analysis for fracture risk assessment and prophylactic treatment.

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 behavior of metastatic vertebrae are influenced by tissue architecture, mineral content, and organic feature alterations

Diminished vertebral mechanical behavior with metastatic involvement is typically attributed to modified architecture and trabecular bone content. Previous work has identified organic and mineral phase bone quality changes in the presence of metastases, yet limited work exists on the potential influence of such tissue level modifications on vertebral mechanical characteristics. This work seeks to determine correlations between features of bone (structural and tissue level) and mechanical behavior in metastatically involved vertebral bone. It is hypothesized that tissue level properties (mineral and organic) will improve these correlations beyond architectural properties and BMD alone. Twenty-four female athymic rats were inoculated with HeLa or Ace-1 cancer cells lines producing osteolytic (N = 8) or mixed (osteolytic/osteoblastic, N = 7) metastases, respectively. Twenty-one days post-inoculation L1-L3 pathologic vertebral motion segments were excised and μCT imaged. 3D morphometric parameters and axial rigidity of the L2 vertebrae were quantified. Sequential loading and μCT imaging measured progression of failure, stiffness and peak force. Relationships between mechanical testing (whole bone and tissue-level) and tissue-level material property modifications with metastatic involvement were evaluated utilizing linear regression models. Osteolytic involvement reduced vertebral trabecular bone volume, structure, CT-derived axial rigidity, stiffness and failure force compared to healthy controls (N = 9). Mixed metastases demonstrated similar trends. Previously assessed collagen cross-linking and proline-based residues were correlated to mechanical behavior and improved the predictive ability of the regression models. Similarly, collagen organization improved predictive regression models for metastatic bone hardness. This work highlights the importance of both bone content/architecture and organic tissue-level features in characterizing metastatic vertebral mechanics. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:3013-3022, 2018.

Micro Finite Element models of the vertebral body: Validation of local displacement predictions

The estimation of local and structural mechanical properties of bones with micro Finite Element (microFE) models based on Micro Computed Tomography images depends on the quality bone geometry is captured, reconstructed and modelled. The aim of this study was to validate microFE models predictions of local displacements for vertebral bodies and to evaluate the effect of the elastic tissue modulus on model’s predictions of axial forces. Four porcine thoracic vertebrae were axially compressed in situ, in a step-wise fashion and scanned at approximately 39μm resolution in preloaded and loaded conditions. A global digital volume correlation (DVC) approach was used to compute the full-field displacements. Homogeneous, isotropic and linear elastic microFE models were generated with boundary conditions assigned from the interpolated displacement field measured from the DVC. Measured and predicted local displacements were compared for the cortical and trabecular compartments in the middle of the specimens. Models were run with two different tissue moduli defined from microindentation data (12.0GPa) and a back-calculation procedure (4.6GPa). The predicted sum of axial reaction forces was compared to the experimental values for each specimen. MicroFE models predicted more than 87% of the variation in the displacement measurements (R² = 0.87–0.99). However, model predictions of axial forces were largely overestimated (80–369%) for a tissue modulus of 12.0GPa, whereas differences in the range 10–80% were found for a back-calculated tissue modulus. The specimen with the lowest density showed a large number of elements strained beyond yield and the highest predictive errors. This study shows that the simplest microFE models can accurately predict quantitatively the local displacements and qualitatively the strain distribution within the vertebral body, independently from the considered bone types.

μFE models can represent microdamaged regions of healthy and metastatically involved whole vertebrae identified through histology and contrast enhanced μCT imaging

Micro-damage formation within the skeleton is an important stimulant for bone remodeling, however abnormal build-up of micro-damage can lead to skeletal fragility. In this study, µCT imaging based micro finite element (μFE) models were used to evaluate tissue level damage criteria in whole healthy and metastatically-involved vertebrae. T13-L2 spinal segments were excised from osteolytic (n=3) and healthy (n=3) female athymic rnu/rnu rats. Osteolytic metastasis was generated by intercardiac injection of HeLa cancer cells. Micro-mechanical axial loading was applied to the spinal motion segments under μCT imaging. Vertebral samples underwent BaSO4 staining and sequential calcein/fuchsin staining to identify load induced micro-damage. μCT imaging was used generate specimen specific μFE models of the healthy and osteolytic whole rat vertebrae. Model boundary conditions were generated through deformable image registration of loaded and unloaded scans. Elevated stresses and strains were detected in regions of micro-damage identified through histological and BaSO4 staining within healthy and osteolytic vertebral models, as compared to undamaged regions. Additionally, damaged regions of metastatic vertebrae experienced significantly higher local stresses and strains than those in the damaged regions of healthy specimens. Areas identified by BaSO4 staining, however, yielded lower levels of stress and strain in damaged and undamaged regions of healthy and metastatic vertebrae as compared to fuschin staining. The multimodal (experimental, image-based and computational) techniques used in this study demonstrated the ability of local stresses and strains computed through µFE analysis to identify trabecular micro-damage, that can be applied to biomechanical analyses of healthy and diseased whole bones.

Finite element analysis and computed tomography based structural rigidity analysis of rat tibia with simulated lytic defects

Finite element analysis (FEA), CT based structural rigidity analysis (CTRA) and mechanical testing is performed to assess the compressive failure load of rat tibia with simulated lytic defects. Twenty rat tibia were randomly assigned to four equal groups (n=5). Three of the groups included a simulated defect at various locations: anterior bone surface (Group 1), posterior bone surface (Group 2) and through bone defect (Group 3). The fourth group was a control group with no defect (Group 4). Microcomputed tomography was used to assess bone structural rigidity properties and to provide 3D model data for generation of the finite element models for each specimen. Compressive failure load calculated using CT derived rigidity parameters (FCTRA) was well correlated to failure load recorded in mechanical testing (R(2)=0.96). The relationships between mechanical testing failure load and the axial rigidity (R(2)=0.61), bending rigidity (R(2)=0.71) and FEA calculated failure loads, considering bone as an elastic isotropic (R(2)=0.75) and elastic transversely isotropic (R(2)=0.90) are also well correlated. CTRA stress, calculated adjacent to the defect, were also shown to be well correlated with yield stresses calculated using the minimum density at the weakest cross section (R(2)=0.72). No statistically significant relationship between apparent density and mechanical testing failure load was found (P=0.37). In summary, the results of this study indicate that CTRA analysis of bone strength correlates well with both FEA and results obtained from compression experiments. In addition there exist a good correlation between structural rigidity parameters and experimental failure loads. In contrast, there was no correlation between average bone density and failure load.

A national portfolio of bone oncology trials-The Canadian experience in 2012

BACKGROUND

The impact of both cancer and its treatment on bone is an essential component of oncological practice. Bone oncology not only affects patients with both early stage and metastatic disease but also covers the entire spectrum of tumour types. We therefore decided to review and summarise bone oncology-related trials that are currently being conducted in Canada.

METHOD

We assessed ongoing and recently completed trials in Canada. We used available North American and Canadian cancer trial websites and also contacted known investigators in this field for their input.

RESULTS

Twenty seven clinical trials were identified. Seven pertained to local treatment of bone metastasis from any solid tumour type. Seven were systemic treatment trials, five focused on bone biology and predictive factors, three evaluated safety of bone-targeted agents, three were adjuvant trials and two trials investigated impact of cancer therapy on bone health. The majority of trials were related to systemic treatment and bone biology in breast cancer. Most were small, single centre, grant-funded studies. Not surprisingly the larger safety and adjuvant studies were pharmaceutical company driven.

DISCUSSION

Despite the widespread interest in bone-targeted therapies our survey would suggest that most studies are single centre and breast cancer focused. If major advances in bone oncology are to be made then collaborative strategies are needed to not only increase current sample sizes but to also expand these studies into non-breast cancer populations.