A comparative study of bone remodeling around hydroxyapatite-coated and novel radial functionally graded dental implants using finite element simulation.

This comparative study simulates bone remodeling outcome around titanium dental implants and compares the final bone configuration with the one around novel implants composed of radial functionally graded materials (FGMs) and the titanium implants with hydroxyapatite (HA) coating. A dental implant system embedded in 3D mandibular bone with masticatory loading was simulated by the finite element method. A bone remodeling algorithm was applied to cancellous and cortical bones. Young's modulus and von Mises stress were obtained to ensure bone homeostasis and evaluate the final bone configuration. Local stress distribution in the bone-implant interface was analyzed before and after bone remodeling. The average final Young's modulus of cancellous bone reached 2.68, 2.49, and 2.32 GPa for the FGM, HA-coated, and the titanium models, respectively. These values for cortical bone were 17.75, 16.86, and 17.20 GPa in the same order. Radial FGM implants generated the highest remodeling stimulus and bone density. Their superiority over the HA-coated models was confirmed by four implant surface stiffness values (10, 20, 30, and 40 GPa). Remodeling increased bone density around the implant, consistent with clinical data and reduced stress concentration in the cortical neck. The stress values were in the safe zone regarding overload-induced bone resorption. The findings of this study were substantiated by clinical images and bone density values from previous literature.

Estimation and assessment of sagittal spinal curvature and thoracic muscle morphometry in different postures.

Spine models are typically developed from supine clinical imaging data, and hence clearly do not fully reflect postures that replicate subjects' clinical symptoms. Our objectives were to develop a method to: (i) estimate the subject-specific sagittal curvature of the whole spine in different postures from limited imaging data, (ii) obtain muscle lines-of-action in different postures and analyze the effect of posture on muscle fascicle length, and (iii) correct for cosine between the magnetic resonance imaging (MRI) scan plane and dominant fiber line-of-action for muscle parameters (cross-sectional area (CSA) and position). The thoracic spines of six healthy volunteers were scanned in four postures (supine, standing, flexion, and sitting) in an upright MRI. Geometry of the sagittal spine was approximated with a circular spline. A pipeline was developed to estimate spine geometry in different postures and was validated. The lines-of-action for two muscles, erector spinae (ES) and transversospinalis (TS) were obtained for every posture and hence muscle fascicle lengths were computed. A correction factor based on published literature was then computed and applied to the muscle parameters. The maximum registration error between the estimated spine geometry and MRI data was small (average RMSE∼1.2%). The muscle fascicle length increased (up to 20%) in flexion when compared to erect postures. The correction factor reduced muscle parameters (∼5% for ES and ∼25% for TS) when compared to raw MRI data. The proposed pipeline is a preliminary step in subject-specific modeling. Direction cosines of muscles could be used while improving the inputs of spine models.

Evaluation of La(XT), a novel lanthanide compound, in an OVX rat model of osteoporosis.

PURPOSE: The purpose of this study was to evaluate the efficacy and toxicity of a novel lanthanum compound, La(XT), in an ovariectomized (OVX) rat model of osteoporosis. METHODS: Twenty-four ovariectomized female Sprague Dawley rats were divided into 3 groups receiving a research diet with/without treatment compounds (alendronate: 3 mg/kg; La(XT) 100 mg/kg) for three months. At the time of sacrifice, the kidney, liver, brain, lung and spleen were collected for histological examination. The trabecular bone structure of the tibiae was evaluated using micro-CT and a three-point metaphyseal mechanical test was used to evaluate bone failure load and stiffness. RESULTS: No significant differences were noted in plasma levels of calcium, phosphorus, creatinine, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) between the La(XT) treatment compared to the non-treated OVX group. Alendronate-treated animals (positive control) showed higher BV/TV, Tb.N and lower Tb.Th and Tb.Sp when compared to the non-treated OVX group. Mechanical analysis indicated that stiffness was higher in the alendronate (32.88%, p = 0.04) when compared to the non-treated OVX group. Failure load did not differ among the groups. CONCLUSIONS: No kidney or liver toxicities of La(XT) treatments were found during the three-month study. The absence of liver and kidney toxicity with drug treatment for 3 months, as well as the increased trabecular bone stiffness are encouraging for the pursuit of further studies with La(XT) for a longer duration of time.

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.