172 research outputs found

    Some Practical Considerations for Compression Failure Characterization of Open-Cell Polyurethane Foams Using Digital Image Correlation

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    [EN] (1) Background: Open-cell polyurethane foam mechanical behavior is highly influenced by microstructure. The determination of the failure mechanisms and the characterization of the deformation modes involved at the micro scale is relevant for accurate failure modeling. (2) Methods: We use digital image correlation (DIC) to investigate strain fields of open-cell polyurethane foams of three different densities submitted to compression testing. We analyze the effect of some DIC parameters on the failure pattern definition and the equivalent strain magnification at the apparent ultimate point. Moreover, we explore speckle versus non-speckle approaches and discuss the importance of determining the pattern quality to perform the displacement correlation. (3) Results: DIC accurately characterizes the failure patterns. A variation in the subset size has a relevant effect on the strain magnification values. Step size effect magnitude depends on the subset size. The pattern matching criterion presented little influence (3.5%) on the strain magnification. (4) Conclusion: The current work provides a comprehensive analysis of the influence of some DIC parameters on compression failure characterization of foamed structures. It highlights that changes of subset and step sizes have a significant effect on the failure pattern definition and the strain magnification values, while the pattern matching criterion and the use of speckle have a minor influence on the results. Moreover, this work stands out that the determination of the pattern quality has a major importance for texture analysis. The in-depth, detailed study carried out with samples of three different apparent densities is a useful guide for DIC users as regards texture correlation and foamed structures.This research was funded by the Spanish Ministerio de Ciencia, Innovacion y Universidades grant numbers DPI2013-46641-R and DPI2017-89197-C2-2-R and the Generalitat Valenciana, Programme PROMETEO 2016/007 and Plan FDGENT 2018 GVA.Belda, R.; Megías-Díaz, R.; Feito-Sánchez, N.; Vercher Martínez, A.; Giner Maravilla, E. (2020). Some Practical Considerations for Compression Failure Characterization of Open-Cell Polyurethane Foams Using Digital Image Correlation. Sensors. 20(15):1-21. https://doi.org/10.3390/s20154141S121201

    Compression failure characterization of cancellous bone combining experimental testing, digital image correlation and finite element modeling

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    [EN] Cancellous bone yield strain has been reported in the literature to be relatively constant and independent from microstructure and apparent density, while fracture strain shows higher scattering. The objective of this work is to assess this hypothesis, characterizing the compression fracture in cancellous bone from a numerical approach and relating it to morphological parameters. Quasi-static compression fractures of cancellous bone samples are modeled using high-resolution image-based finite elements, correlating the numerical models and experimental results. The yield strain and the strain at fracture are inferred from the micro-CT-based finite element models by inverse analysis. The validation of the fracture models is carried out through digital image correlation (DIC). To develop this work, cancellous bone parallelepiped-shaped specimens were prepared and micro-CT scanned at 22 mu m spatial resolution. A morphometric analysis was carried out for each specimen in order to characterize its microstructure. Quasi-static compression tests were conducted, recording the force-displacement response and a sequence of images during testing for the application of the DIC technique. This was applied without the need of a speckle pattern benefiting from the irregular microstructure of cancellous bone. The finite element models are also used to simulate the local fracture of trabeculae at the micro level using a combination of continuum damage mechanics and the element deletion technique. Equivalent strain, computed both from DIC and micro-FE, was the best predictor of the compression fracture pattern. The procedure followed in this work permits the estimation of failure parameters that are difficult to measure experimentally, which can be used in numerical models.This work was supported by the Spanish Ministerio de Ciencia, Innovacion y Universidades grant numbers DPI2013-46641-R and DPI2017-89197-C2-2-R and the Generalitat Valenciana (Programme PROMETEO 2016/007). The micro-CT acquisitions were performed at CENIEH facilities with the collaboration of CENIEH staff. The authors also gratefully acknowledge the collaboration of Ms. Lucia Gomez.Belda, R.; Palomar-Toledano, M.; Peris Serra, JL.; Vercher Martínez, A.; Giner Maravilla, E. (2020). Compression failure characterization of cancellous bone combining experimental testing, digital image correlation and finite element modeling. International Journal of Mechanical Sciences. 165:1-12. https://doi.org/10.1016/j.ijmecsci.2019.105213S112165Gold, D. T. (2001). The Nonskeletal Consequences of Osteoporotic Fractures. Rheumatic Disease Clinics of North America, 27(1), 255-262. doi:10.1016/s0889-857x(05)70197-6Keaveny, T. M., Morgan, E. F., Niebur, G. L., & Yeh, O. C. (2001). Biomechanics of Trabecular Bone. Annual Review of Biomedical Engineering, 3(1), 307-333. doi:10.1146/annurev.bioeng.3.1.307Rho, J.-Y., Kuhn-Spearing, L., & Zioupos, P. (1998). Mechanical properties and the hierarchical structure of bone. Medical Engineering & Physics, 20(2), 92-102. doi:10.1016/s1350-4533(98)00007-1Currey, J. D. (2011). The structure and mechanics of bone. Journal of Materials Science, 47(1), 41-54. doi:10.1007/s10853-011-5914-9Gupta, H. S., & Zioupos, P. (2008). Fracture of bone tissue: The ‘hows’ and the ‘whys’. Medical Engineering & Physics, 30(10), 1209-1226. doi:10.1016/j.medengphy.2008.09.007Nagaraja, S., Couse, T. L., & Guldberg, R. E. (2005). Trabecular bone microdamage and microstructural stresses under uniaxial compression. Journal of Biomechanics, 38(4), 707-716. doi:10.1016/j.jbiomech.2004.05.013Garcia, D., Zysset, P. K., Charlebois, M., & Curnier, A. (2008). A three-dimensional elastic plastic damage constitutive law for bone tissue. Biomechanics and Modeling in Mechanobiology, 8(2), 149-165. doi:10.1007/s10237-008-0125-2Ridha, H., & Thurner, P. J. (2013). Finite element prediction with experimental validation of damage distribution in single trabeculae during three-point bending tests. Journal of the Mechanical Behavior of Biomedical Materials, 27, 94-106. doi:10.1016/j.jmbbm.2013.07.005Hambli, R. (2012). A quasi-brittle continuum damage finite element model of the human proximal femur based on element deletion. Medical & Biological Engineering & Computing, 51(1-2), 219-231. doi:10.1007/s11517-012-0986-5Fan, R., Gong, H., Zhang, X., Liu, J., Jia, Z., & Zhu, D. (2016). Modeling the Mechanical Consequences of Age-Related Trabecular Bone Loss by XFEM Simulation. Computational and Mathematical Methods in Medicine, 2016, 1-12. doi:10.1155/2016/3495152Vellwock, A. E., Vergani, L., & Libonati, F. (2018). A multiscale XFEM approach to investigate the fracture behavior of bio-inspired composite materials. Composites Part B: Engineering, 141, 258-264. doi:10.1016/j.compositesb.2017.12.062Hambli, R. (2010). Multiscale prediction of crack density and crack length accumulation in trabecular bone based on neural networks and finite element simulation. International Journal for Numerical Methods in Biomedical Engineering, 27(4), 461-475. doi:10.1002/cnm.1413Hambli, R. (2011). Apparent damage accumulation in cancellous bone using neural networks. Journal of the Mechanical Behavior of Biomedical Materials, 4(6), 868-878. doi:10.1016/j.jmbbm.2011.03.002Lemaitre, J. (1985). A Continuous Damage Mechanics Model for Ductile Fracture. Journal of Engineering Materials and Technology, 107(1), 83-89. doi:10.1115/1.3225775Turner, C. H., & Burr, D. B. (1993). Basic biomechanical measurements of bone: A tutorial. Bone, 14(4), 595-608. doi:10.1016/8756-3282(93)90081-kBay, B. K. (1995). Texture correlation: A method for the measurement of detailed strain distributions within trabecular bone. Journal of Orthopaedic Research, 13(2), 258-267. doi:10.1002/jor.1100130214Peters, W. H., & Ranson, W. F. (1982). Digital Imaging Techniques In Experimental Stress Analysis. Optical Engineering, 21(3). doi:10.1117/12.7972925Sutton, M., Wolters, W., Peters, W., Ranson, W., & McNeill, S. (1983). Determination of displacements using an improved digital correlation method. Image and Vision Computing, 1(3), 133-139. doi:10.1016/0262-8856(83)90064-1Pan, B., Qian, K., Xie, H., & Asundi, A. (2009). Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review. Measurement Science and Technology, 20(6), 062001. doi:10.1088/0957-0233/20/6/062001Khoo, S.-W., Karuppanan, S., & Tan, C.-S. (2016). A Review of Surface Deformation and Strain Measurement Using Two-Dimensional Digital Image Correlation. Metrology and Measurement Systems, 23(3), 461-480. doi:10.1515/mms-2016-0028Palanca, M., Tozzi, G., & Cristofolini, L. (2015). The use of digital image correlation in the biomechanical area: a review. International Biomechanics, 3(1), 1-21. doi:10.1080/23335432.2015.1117395Grassi, L., & Isaksson, H. (2015). Extracting accurate strain measurements in bone mechanics: A critical review of current methods. Journal of the Mechanical Behavior of Biomedical Materials, 50, 43-54. doi:10.1016/j.jmbbm.2015.06.006Bayraktar, H. H., Morgan, E. F., Niebur, G. L., Morris, G. E., Wong, E. K., & Keaveny, T. M. (2004). Comparison of the elastic and yield properties of human femoral trabecular and cortical bone tissue. Journal of Biomechanics, 37(1), 27-35. doi:10.1016/s0021-9290(03)00257-4Carretta, R., Stüssi, E., Müller, R., & Lorenzetti, S. (2013). Within subject heterogeneity in tissue-level post-yield mechanical and material properties in human trabecular bone. Journal of the Mechanical Behavior of Biomedical Materials, 24, 64-73. doi:10.1016/j.jmbbm.2013.04.014Linde, F., & Sørensen, H. C. F. (1993). The effect of different storage methods on the mechanical properties of trabecular bone. Journal of Biomechanics, 26(10), 1249-1252. doi:10.1016/0021-9290(93)90072-mLinde, F., & Hvid, I. (1987). Stiffness behaviour of trabecular bone specimens. Journal of Biomechanics, 20(1), 83-89. doi:10.1016/0021-9290(87)90270-3Keaveny, T. M., Borchers, R. E., Gibson, L. J., & Hayes, W. C. (1993). Theoretical analysis of the experimental artifact in trabecular bone compressive modulus. Journal of Biomechanics, 26(4-5), 599-607. doi:10.1016/0021-9290(93)90021-6Keaveny, T. M., Guo, X. E., Wachtel, E. F., McMahon, T. A., & Hayes, W. C. (1994). Trabecular bone exhibits fully linear elastic behavior and yields at low strains. Journal of Biomechanics, 27(9), 1127-1136. doi:10.1016/0021-9290(94)90053-1Keaveny, T. M., Pinilla, T. P., Crawford, R. P., Kopperdahl, D. L., & Lou, A. (1997). Systematic and random errors in compression testing of trabecular bone. Journal of Orthopaedic Research, 15(1), 101-110. doi:10.1002/jor.1100150115Correlated Solutions. VIC-2d v6 reference manual. 2016. http://www.correlatedsolutions.com/supportcontent/Vic-2D-v6-Manual.pdf.Whitehouse, W. J. (1974). The quantitative morphology of anisotropic trabecular bone. Journal of Microscopy, 101(2), 153-168. doi:10.1111/j.1365-2818.1974.tb03878.xKabel, J., van Rietbergen, B., Dalstra, M., Odgaard, A., & Huiskes, R. (1999). The role of an effective isotropic tissue modulus in the elastic properties of cancellous bone. Journal of Biomechanics, 32(7), 673-680. doi:10.1016/s0021-9290(99)00045-7Nalla, R. K., Kinney, J. H., & Ritchie, R. O. (2003). Mechanistic fracture criteria for the failure of human cortical bone. Nature Materials, 2(3), 164-168. doi:10.1038/nmat832Taylor, D. (2003). A crack growth model for the simulation of fatigue in bone. International Journal of Fatigue, 25(5), 387-395. doi:10.1016/s0142-1123(02)00165-2Burr, D. B., & Stafford, T. (1990). Validity of the Bulk-Staining Technique to Separate Artifactual From In Vivo Bone Microdamage. Clinical Orthopaedics and Related Research, 260, 305-308. doi:10.1097/00003086-199011000-00047Keaveny, T. M., & Hayes, W. C. (1993). A 20-Year Perspective on the Mechanical Properties of Trabecular Bone. Journal of Biomechanical Engineering, 115(4B), 534-542. doi:10.1115/1.2895536Wolfram, U., Wilke, H.-J., & Zysset, P. K. (2011). Damage accumulation in vertebral trabecular bone depends on loading mode and direction. Journal of Biomechanics, 44(6), 1164-1169. doi:10.1016/j.jbiomech.2011.01.018Kopperdahl, D. L., & Keaveny, T. M. (1998). Yield strain behavior of trabecular bone. Journal of Biomechanics, 31(7), 601-608. doi:10.1016/s0021-9290(98)00057-8Hara, T., Tanck, E., Homminga, J., & Huiskes, R. (2002). The influence of microcomputed tomography threshold variations on the assessment of structural and mechanical trabecular bone properties. Bone, 31(1), 107-109. doi:10.1016/s8756-3282(02)00782-2Parkinson, I. H., Badiei, A., & Fazzalari, N. L. (2008). Variation in segmentation of bone from micro-CT imaging: implications for quantitative morphometric analysis. Australasian Physics & Engineering Sciences in Medicine, 31(2), 160-164. doi:10.1007/bf03178592Wachtel, E. F., & Keaveny, T. M. (1997). Dependence of trabecular damage on mechanical strain. Journal of Orthopaedic Research, 15(5), 781-787. doi:10.1002/jor.1100150522Nazarian, A., Meier, D., Müller, R., & Snyder, B. D. (2009). Functional dependence of cancellous bone shear properties on trabecular microstructure evaluated using time-lapsed micro-computed tomographic imaging and torsion testing. Journal of Orthopaedic Research, 27(12), 1667-1674. doi:10.1002/jor.20931Schwiedrzik, J., Taylor, A., Casari, D., Wolfram, U., Zysset, P., & Michler, J. (2017). Nanoscale deformation mechanisms and yield properties of hydrated bone extracellular matrix. Acta Biomaterialia, 60, 302-314. doi:10.1016/j.actbio.2017.07.030Bevill, G., Eswaran, S. K., Gupta, A., Papadopoulos, P., & Keaveny, T. M. (2006). Influence of bone volume fraction and architecture on computed large-deformation failure mechanisms in human trabecular bone. Bone, 39(6), 1218-1225. doi:10.1016/j.bone.2006.06.016Althouse, A. D. (2016). Adjust for Multiple Comparisons? It’s Not That Simple. The Annals of Thoracic Surgery, 101(5), 1644-1645. doi:10.1016/j.athoracsur.2015.11.02

    Photo-fenton degradation of pentachlorophenol l: competition between additives and photolysis

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    [EN] In the present work, the photo-Fenton degradation of pentachlorophenol (PCP, 1 mg/L) has been studied under simulated and natural solar irradiation; moreover, the effect on the process efficiency of urban waste-derived soluble bio-based substances (SBO), structurally comparable to humic acids, has been investigated. Experiments showed a crucial role of PCP photolysis, present in the solar pilot plant and hindered by the Pyrex (R) filter present in the solar simulator. Indeed, the SBO screen negatively affects PCP degradation when working under natural solar light, where the photolysis of PCP is relevant. In contrast, in the absence of PCP photolysis, a significant improvement of the photo-Fenton process was observed when added to SBO. Furthermore, SBO were able to extend the application of the photo-Fenton process at circumneutral pH values, due to their ability to complex iron, avoiding its precipitation as oxides or hydroxides. This positive effect has been observed at higher concentration of Fe(II) (4 mg/L), whereas at 1 mg/L, the degradation rates of PCP were comparable in the presence and absence of SBO.This work was realized with the financial support of the academic interchange from the Marie Sklodowska-Curie Research and Innovation Staff Exchange project, funded by the European Commission H2020-MSCA-RISE-2014 within the framework of the research project Mat4treaT (Project number: 645551).Vergura, EP.; García-Ballesteros, S.; Vercher Pérez, RF.; Santos-Juanes Jordá, L.; Bianco Prevot, A.; Arqués Sanz, A. (2019). Photo-Fenton Degradation of Pentachlorophenol: Competition between Additives and Photolysis. Nanomaterials. 9(8):1-8. https://doi.org/10.3390/nano9081157S189

    Non-destructive Techniques Methodologies for the Detection of Ancient Structures under Heritage Buildings

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    [EN] Structures and elements buried beneath heritage buildings are frequent but are often unknown and inaccessible. Therefore, they are difficult to locate in general if an archaeological excavation is not carried out, with the economic cost and time involved. It is important to discover them in order to increase our knowledge of cultural heritage, as well as to know, recover and improve the state of conservation of the materials that make up these structures. This paper presents methodologies for locating old structures using a low-cost NDT approach, with a qualitative and quantitative analysis of GPR profiles in heritage buildings. Small perforations are performed at critical points and introducing an endoscope for verification. Various crypts have been located using the proposed methodologies in a real study case: The Church of the Asución of Llíria in Spain.Gil Benso, E.; Mas Tomas, MDLA.; Lerma Elvira, C.; Torner, ME.; Vercher Sanchis, J. (2021). Non-destructive Techniques Methodologies for the Detection of Ancient Structures under Heritage Buildings. International journal of architectural heritage (electronic). 15(10):1457-1473. https://doi.org/10.1080/15583058.2019.1700320S14571473151

    Explicit expressions for the estimation of the elastic constants of lamellar bone as a function of the volumetric mineral content using a multi-scale approach

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    [EN] In this work, explicit expressions to estimate all the transversely isotropic elastic constants of lamellar bone as a function of the volumetric bone mineral density (BMD) are provided. The methodology presented is based on the direct homogenization procedure using the finite element method, the continuum approach based on the Hill bounds, the least-square method and the mean field technique. Firstly, a detailed description of the volumetric content of the different components of bone is provided. The parameters defined in this step are related to the volumetric BMD considering that bone mineralization process occurs at the smallest scale length of the bone tissue. Then, a thorough description provides the details of the numerical models and the assumptions adopted to estimate the elastic behaviour of the forward scale lengths. The results highlight the noticeable influence of the BMD on the elastic modulus of lamellar bone. Power law regressions fit the Young's moduli, shear stiffness moduli and Poisson ratios. In addition, the explicit expressions obtained are applied to the estimation of the elastic constants of cortical bone. At this scale length, a representative unit cell of cortical bone is analysed including the fibril orientation pattern given by Wagermaier et al. (Biointerphases 1:1-5, 2006) and the BMD distributions observed by Granke et al. (PLoS One 8:e58043, 2012) for the osteon. Results confirm that fibril orientation arrangement governs the anisotropic behaviour of cortical bone instead of the BMD distribution. The novel explicit expressions obtained in this work can be used for improving the accuracy of bone fracture risk assessment.The authors acknowledge the Ministerio de Economia y Competitividad for the financial support received through the project DPI2013-46641-R and to the Generalitat Valenciana for Programme PROMETEO 2016/007. The authors declare that they have no conflict of interestVercher Martínez, A.; Giner Maravilla, E.; Belda, R.; Aigoun, A.; Fuenmayor Fernández, F. (2018). Explicit expressions for the estimation of the elastic constants of lamellar bone as a function of the volumetric mineral content using a multi-scale approach. Biomechanics and Modeling in Mechanobiology. 17(2):449-464. https://doi.org/10.1007/s10237-017-0971-xS449464172Akiva U, Wagner HD, Weiner S (1998) Modelling the three-dimensional elastic constants of parallel-fibred and lamellar bone. J Mater Sci 33:1497–1509Ascenzi A, Bonucci E (1967) The tensile properties of single osteons. Ana Rec 158:375–386Barbour KE, Zmuda JM, Strotmeyer ES, Horwitz MJ, Boudreau R, Evans RW, Ensrud K, Petit MA, Gordon CL, Cauley JA (2013) Correlates of trabecular and cortical volumetric bone mineral density of the radius and tibia older men: the osteoporotic fractures in men study. J Bone Miner Res 25(5):1017–1028Bar-On B, Wagner HD (2013) Structural motifs and elastic properties of hierarchical biological tissues—a review. J Struct Biol 183:149–164Cowin SC (2000) How is a tissue built? J Biomech Eng 122:553–569Cowin SC (2001) Bone mechanics handbook, 2nd edn. CRC Press, Boca RatonCurrey JD (1986) Power law models for the mechanical properties of cancellous bone. Eng Med 15(3):153–154Currey JD (1988) The effect of porosity and mineral content on the Young’s modulus of elasticity of compact bone. J Biomech 21:131–139Daszkiewicz K, Maquer G, Zysset PK (2017) The effective elastic properties of human trabecular bone may be approximated using micro-finite element analyses of embedded volume elements. Biomech Model Mechanobiol 16:731–742Faingold A, Sidney RC, Wagner HD (2012) Nanoindentation of osteonal bone lamellae. J Mech Biomech Materials 9:198–206Fratzl P, Fratzl-Zelman N, Klaushofer K, Vogl G, Koller K (1991) Nucleation and growth of mineral crystals in bone studied by small-angle X-ray scattering. Calcif Tissue Int 48:407–413Fritsch A, Hellmich C (2007) ’Universal’ microstructural patterns in cortical and trabecular, extracellular and extravascular bone materials: micromechanics-based prediction of anisotropic elasticity. J Theo Biol 24:597–620Grampp S, Genant HK, Mathur A, Lang P, Jergas M, Takada M, Glüer CC, Lu Y, Chavez M (1997) Comparisons of noninvasive bone mineral measurements in assessing age-related loss, fracture discrimination and diagnostic classification. J Bone Miner Res 12:697–711Grant CA, Langton C, Schuetz MA, Epari DR (2011) Determination of the material properties of ovine cortical bone. Poster No. 2226, 57th Orthopaedic Research Society (ORS) Annual meeting, Long Beach, CaliforniaGranke M, Gourrier A, Rupin F, Raum K, Peyrin F, Burghammer M, Saïd A, Laugier P (2012) Microfibril orientation dominates the microelastic properties of human bone tissue at the lamellar length scale. PLoS One 8:e58043Gurtin ME (1972) The linear theory of elasticity. Handbuch del Physik VIa 2:1–296Hamed E, Jasiuk I (2012) Elastic modeling of bone at nanostructural level. Mat Sci Eng R73:27–49Hernández CJ, Beaupré GS, Keller TS, Carter DR (2001a) The influence of bone volume fraction and ash fraction on bone strength and modulus. Bone 29:74–78Hill R (1952) The elastic behaviour of a crystalline aggregate. Proc Phys Soc Sec A 65:349–354Hodge AJ, Petruska JA (1963) Recent studies with the electron microscope on ordered aggregates of the tropocollagen macromolecule. In: Ramachandran GN (ed) Aspects of protein structure. Academic Press, New York, pp 289–300Jäger I, Fratzl P (2000) Mineralized collagen: a mechanical model with a staggered arrangement of mineral particles. Biophys J 78:1737–1746Kuhn JL, Goldstein SA, Choi K, London M, Feldkamp LA, Matthews LS (1989) Comparison of the trabecular and cortical tissue moduli from human iliac crests. J Orthop Res 7:876–884Landis WJ, Song MJ, Leith A, McEwen L, McEwen BF (1993) Mineral and organic matrix interaction in normally calcifying tendon visualized in three dimensions by high-voltage electron microscopic tomography and graphic image reconstruction. J Struct Biol 110:39–54Lees S, Heeley JD, Cleary PF (1979) A study of some properties of a sample of bovine cortical bone using ultrasound. Calcif Tissue Int 29:107–117Lekhnitskii SG (1963) Theory of elasticity of anisotropic elastic body. Holden-Day, San Francisco, pp 1–73Lempriere BM (1968) Poisson’s ratio in orthotropic materials. Am Inst Aeronaut Astronaut J J6:2226–2227Liu Y, Kim YK, Dai L, Li N, Khan SO, Pashley DH, Tay FR (2011) Hierarchical and non-hierarchical mineralization of collagen. Biomater 32:1291–1300Majumdar S, Kothari M, Augat P, Newitt DC, Link TM, Lin JC, Lang T, Lu Y, Genant HK (1998) High-resolution magnetic resonance imaging: three-dimensional trabecular bone architecture and biomechanical properties. Bone 22(5):445–454Martínez-Reina J, Domínguez J, García-Aznar JM (2011) Effect of porosity and mineral content on the elastic constants of cortical bone: a multiscale approach. Biomech Model Mechanobiol 10:309–322Nobakhti S, Limbert G, Thurner PJ (2014) Cement lines and interlamellar areas in compact bone as strain amplifiers—Contributors to elasticity, fracture toughness and mechanotransduction. J Mech Behav Biomed Mater 29:235–251Orgel JPRO, Irving TC, Miller A, Wess TJ (2006) Microfibrillar structure of type I collagen in situ. PNAS USA 103:9001–9005Reisinger AG, Pahr DH, Zysset PK (2010) Sensitivity analysis and parametric study of elastic properties of unidirectional mineralized bone fibril-array using mean field methods. Biomech Model Mechanobiol 9:499–510Reisinger AG, Pahr DH, Zysset PK (2011) Elastic anisotropy of bone lamellae as a function of fibril orientation pattern. Biomech Model Mechanobiol 10:67–77Rho JY, Kuhn-Spearing L, Zioupos P (1998) Mechanical properties and the hierarchical structure of bone. Med Eng Phys 20:92–102Robinson RA, Rochester MD (1952) An electron-microscopic study of the crystalline inorganic component of bone and its relationship to the organic matrix. J Bone Joint Surg 34–a:389–435Roque WL, Arcaro K, Alberich-Bayarri A (2013) Mechanical competence of bone: a new parameter to grade trabecular bone fragility from tortuosity and elasticity. IEEE Trans Bio Eng 60:1363–1370Rubin MA, Jasiuk I, Taylor J, Rubin J, Ganey T, Apkarian RP (2003) TEM analysis of the nanostructure of normal and osteoporotic human trabecular bone. Bone 33:270–282Sasaki N, Tagami A, Goto T, Taniguchi M, Nakata M, Hikichi K (2002) Atomic force microscopic studies on the structure of bovine femoral cortical bone at the collagen fibril-mineral level. J Mater Sci Mater Med 13(3):333–337Schaffler MB, Burr DB (1988) Stiffness of compact bone: effects of porosity and density. J Biomech 21:13–16Silver FH, Landis WJ (2011) Deposition of apatite in mineralizing vertebrate extracellular matrices: a model of possible nucleation sites on type I collagen. Connect Tissue Res 52:242–254Tommasini SM, Nasser P, Hu B, Jepsen KJ (2008) Biological co-adaptation of morphological and composition traits contributes to mechanical functionality and skeletal fragility. J Bone Miner Res 23:236–246Ulrich D, Rietbergen B, Weinans H, Rüegsegger P (1998) Finite element analysis of trabecular bone structure: a comparison of image-based meshing techniques. J Biomech 31:1187–1192Ulrich D, Rietbergen B, Laib A, Rüegsegger P (1999) The ability of three-dimensional structural indices to reflect mechanical aspects of trabecular bone. Bone 25:55–60Vercher A, Giner E, Arango C, Tarancón JE, Fuenmayor FJ (2014) Homogenized stiffness matrices for mineralized collagen fibrils and lamellar bone using unit cell finite element models. Biomech Model Mechanobiol 13:437–449Vercher-Martínez A, Giner E, Arango C, Fuenmayor FJ (2015) Influence of the mineral staggering on the elastic properties of the mineralized collagen fibril in lamellar bone. J Mech Behav Biomed Mater 42:243–256Wagermaier W, Gupta HS, Gourrier A, Burghammer M, Roschger P, Fratzl P (2006) Spiral twisting of fiber orientation inside bone lamellae. Biointerphases 1:1–5Weiner S, Traub W (1986) Organization of hydroxiapatite within collagen fibrils. FEBS Lett 206:262–266Weiner S, Wagner HD (1998) The material bone: structure-mechanical function relations. Annu Rev Mater Sci 28:271–298Yang L, Palermo L, Black DM, Eastell R (2014) Prediction of incident hip fracture with the estimated femoral strength by finite element analysis of DXA scans in the study of osteoporotic fractures. JBMR 29:2594–2600Yuan YJ, Cowin SC (2008a) The estimated elastic constants for a single bone osteonal lamella. Biomech Model Mechanobiol 7:1–11Yu W, Glüer CC, Grampp S, Jergas M, Fuerst T, Wu CY, Lu Y, Fan B, Genant HK (1995) Spinal bone mineral assessment in postmenopausal women: a comparison between dual X-ray absorptiometry and quantitative computed tomography. Osteoporos Int 5:433–439Yang L, Palermo L, Black DM, Eastell R (2014) Prediction of incident hip fracture with the estimated femoral strength by finite element analysis of DXS Scans in the study of osteoporotic fractures. J Bone Miner Res 29(12):2594–2600Yuan F, Stock SR, Haeffner DR, Almer JD, Dunand DC, Brinson LC (2011) A new model to simulate the elastic properties of mineralized collagen fibril. Biomech Model Mechanobiol 10:147–16

    Qualitative and Quantitative Performance of 18 F-FDG-PET/MRI versus 18 F-FDG-PET/CT in Patients with Head and Neck Cancer

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    ABSTRACT BACKGROUND AND PURPOSE: MR imaging and PET/CT are integrated in the work-up of head and neck cancer patients. The hybrid imaging technology 18 F-FDG-PET/MR imaging combining morphological and functional information might be attractive in this patien
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