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PARametric Study for evaluating Interventions to Fracture Avoidance in Long bones.
PARSIFAL-Study: a µCT, Experimental and Finite Element Analysis Zully Ritter1, Wolfgang Baumann2, Dieter Felsenberg3 1 Charité Universitätsmedizin Berlin, Clinic for Radiology and Nuclear Medicine, Center for Muscle and Bone Research Quantification of pharmacological effectiveness (e.g. as required for osteoporosis treatment) on bone stiffness remains an unsolved topic. We propose a method to estimate how much each structural bone parameter (e.g. cortical thickness (Ct.Th), trabecular number (Tb.N.), trabecular thickness (Tb.Th)) and density parameters (e.g. cortical density (Dcomp), trabecular density (Dtrab)) are influencing the bone load transmission capacity and to determine the effects on maximal load before the bone fails mechanically. The aim of this project is then to find which of these density and structure bone parameters play a decisive role to maintain bone functionality at normal levels, during and after pharmacological intervention for osteoporosis treatment. A computational model of an intact bone geometry measured using µCT (XtremeCT, see 12.3) and reconstructions techniques will be developed. The computational model needs first to be validated after comparison of strain values after own experimentation (bending, torsion and compression) with those obtained using the finite element method. Identical boundary conditions as used for experimentation will be simulated computationally (Varghese et al. 2011). After model validation, it is then possible to change step by step each one of these structure and density parameters (Table 1) on the initial bone geometry and density. The new generated models could be then calculated again and the effect of each change on the bone stiffness after FE Analysis will be estimated. Since osteoporosis treatments induce measurable changes on the bone geometry for example at the periosteal bone surfaces, we can simulate this effect in our model by increasing cortical thickness. Methodologically this implies the usage of an additional outer layer on the original periosteal bone surface. Specifically after FE Analysis of such a model and comparing its maximal load capacity with those calculated from the original geometry it is possible to quantify the drug efficacy (e.g. Denosumab) on bone stiffness when the drug induce local changes at the periosteal bone (e.g. after RANKL inhibition). Similarly changes at the endosteal cortical bone could be simulated by modeling an additional inner layer on the original endosteal bone surface. Thus, expected or possible induced changes at selected bone regions (cortical and/or trabecular bone) can be simulated in silico in order to understand and to quantify their effect on bone stiffness. Pharmacological interventions are able to increase or maintain bone density at functional levels. In our FE-model this effect will be simulated by increasing the bone density value (increased elastic modulus of Young). Again a comparison between the original stiffness values and those obtained after artificially altered bone density provides information of how much induced pharmacological changes in the bone matrix -through target bone mineralization processes or target bone cells interactions - alter bone stiffness. In general, using this knowledge it is possible to quantify how much after pharmacological treatment of osteoporosis bone stiffness is affected. Medication normally aims to improve bone density and structural parameters which are essential for maintaining bone functionality and subsequently avoiding or reducing fracture risk. Rationale
Up to date it is not clear how medications against osteoporosis (anti - resorptive (inhibitors for bone resorption)
and/or osteo-anabolic (promoters for bone apposition)) are affecting bone mechanically by altering bone geometry
and/or bone density.
In the present proposal it will be analyzed how a drug against Osteoporosis (Denosumab) will affect bone
microstructure and bone density and how these changes are altering (improvement) bone stiffness. Primarily we
will focus on the radius bone due to the high number of fractures registered in the elderly population after long
term medication. This project also attempts to solve some questions such as: how much could bone stiffness
increase by increasing bone density by 10%? Or how much will the maximal supporting load be affected by
increasing endosteal cortical thickness? Will it be more convenient to increase periosteal cortical thickness or is it
sufficient to reduce cortical porosity by 10% or 20%? Each one of these parameters can be recreated
computationally on the original CT-reconstructed bone geometry of the scanned human radius (woman
healthy) used as reference bone.
The table 1 shows which changes on this human radius bone (taken from a cadaver, thus for ex-vivo
experimentation) will be performed (this proposal). This will allow to understand and to quantify contributions of
each one of these parameters as well as their combination on bone stiffness.
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Table 1 Parameters to be analyzed in this study. In this table in the “FEM” column the number of FE models to be performed in this project is given. Value (percental variation of the base line value) the trabecular density) Trabecular density (without changes on the cortical density) Density (both: cortical and trabecular bone) Periosteal cortical thickness (Ct.Th) -3 - +3 % (in steps of 1%, ] 0 [ = zero excluded) -3 - +3 % (in steps of 1%, ] 0 [ = zero excluded) -1%, +1 % (expected), theoretical (-4 to -2 % in steps of 1% -10%, +10% (expected), theoretical (-30 to – 15 %, in steps of 5 We use the premise that the effect of Denosumab on cortical porosity and geometry affects the entire cortical bone homogeneously. Thus a mean increment of 3.4% in the cortical thickness after one year of Denosumab treatment as reported by Seeman and co-authors (Seeman et al. 2010) and measured after HR-pQCT (1 cm bone length) is supposed to be occurring along of the total bone length. Nowadays, due to methodological reasons, we can measure in vivo only the distal bones about 1 cm of the bone length using 82µm isometric resolution. Therefore computational models using the total bone (as in PARSIFAL) in which such variation on the total bone length can be modeled are more advantageous. It allows derivation of bone microstructure much more precisely and to estimate the maximal force required for fracturing the bone at any single site of the entire length. Note that for this study we will even use a resolution of 41 µm. The computational mechanic simulations allow simulating and determining which approach is more effective: an incremental cortical thickness at the periosteal or endosteal region. Beyond that we will be able by analyzing the treatment effects of any drug of any study on the total bone which force direction is more critical to fracture the bone by simulating the acting impact force as during falling using a finite element model. In the praxis it will be possible to predict for a specific patient who is taking Denosumab and after measuring in vivo its microstructural bone parameters if such a force magnitude will fracture the bone after falling. A parametric study as proposed in the PARSIFAL project using the finite element method allows not only analyzing the influence of each parameter alone but their combination to determine the “optimal” mechanism of action of a drug to prevent or reduce loss of bone mass. The principal aim of this project is to investigate the effects of bone geometry and density parameters on bone stiffness (parametric analysis). This approach will be used to quantify the effectiveness of pharmalocological interventions by identifying primordial parameters and regions that could increase or almost maintain bone stiffness for normal functionality. The secondary aim of this project is to develop a standard methodology for testing and measurements in vitro of human radius specimens with realistic boundary conditions not only for bending and torsion but impact testing which are required for validation of the computational models and finite element analysis. References
Genant, H. K., Engelke, K., Hanley, D. A., Brown, J. P., Omizo, M., Bone, H. G., Kivitz, A. J., Fuerst, T., Wang, H., Austin, M. and Libanati, C. Denosumab improves density and strength parameters as measured by QCT of the radius in postmenopausal women with low bone mineral density. Bone Vol.47,(1), 2010, pp:131-9. Hanley, D. A., Adachi, J. D., Bell, A. and Brown, V. Denosumab: mechanism of action and clinical outcomes. Int J Liu, X. S., Stein, E. M., Zhou, B., Zhang, C. A., Nickolas, T. L., Cohen, A., Thomas, V., McMahon, D. J., Cosman, F., Nieves, J., Shane, E. and Guo, X. E. Individual trabecula segmentation (ITS)-based morphological analyses and microfinite element analysis of HR-pQCT images discriminate postmenopausal fragility fractures independent of DXA measurements. J Bone Miner Res Vol.27,(2), 2012, pp:263-72. Seeman, E., Delmas, P. D., Hanley, D. A., Sellmeyer, D., Cheung, A. M., Shane, E., Kearns, A., Thomas, T., Boyd, S. K., Boutroy, S., Bogado, C., Majumdar, S., Fan, M., Libanati, C. and Zanchetta, J. Microarchitectural deterioration of cortical and trabecular bone: differing effects of denosumab and alendronate. J Bone Miner Res Vol.25,(8), 2010, pp:1886-94. Varghese, B., Short, D., Penmetsa, R., Goswami, T. and Hangartner, T. Computed-tomography-based finite- element models of long bones can accurately capture strain response to bending and torsion. J Biomech, 2011. Vilayphiou, N., Boutroy, S., Szulc, P., Van Rietbergen, B., Munoz, F., Delmas, P. D. and Chapurlat, R. Finite element analysis performed on radius and tibia HR-pQCT images and fragility fractures at all sites in men. J Bone Miner Res, 2011. Page 2 out of 2

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