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

[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

Advanced Magnetic Resonance Imaging in Glioblastoma: A Review

INTRODUCTION In 2017, it is estimated that 26,070 patients will be diagnosed with a malignant primary brain tumor in the United States, with more than half having the diagnosis of glioblas- toma (GBM).1 Magnetic resonance imaging (MRI) is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma; standard modalities available from any clinical MRI scanner, including T1, T2, T2-FLAIR, and T1-contrast-enhanced (T1CE) sequences, provide critical clinical information. In the last decade, advanced imaging modalities are increasingly utilized to further charac- terize glioblastomas. These include multi-parametric MRI sequences, such as dynamic contrast enhancement (DCE), dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), functional imaging, and spectroscopy (MRS), to further characterize glioblastomas, and significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. A contemporary review of standard and advanced MR imaging in clinical neuro-oncologic practice is presented

Full Issue: Volume 13, Issue 1 - Winter 2018

Full Issue: Volume 13, Issue 1 - Winter 201

Characterization and digital restauration of XIV-XV centuries written parchments by means of non-destructive techniques. Three case studies

Parchment is the primary writing medium of the majority of documents with cultural importance. Unfortunately, this material suffers of several mechanisms of degradation that affect its chemical-physical structure and the readability of text. Due to the unique and delicate character of these objects, the use of nondestructive techniques is mandatory. In this work, three partially degraded handwritten parchments dating back to the XIV-XV centuries were analyzed by means of X-ray fluorescence spectroscopy, µ-ATR Fourier transform infrared spectroscopy, and reflectance and UV-induced fluorescence spectroscopy. 'e elemental and molecular results provided the identification of the inks, pigments, and superficial treatments. In particular, all manuscripts have been written with iron gall inks, while the capital letters have been realized with cinnabar and azurite. Furthermore, multispectral UV fluorescence imaging and multispectral VIS-NIR imaging proved to be a good approach for the digital restoration of manuscripts that suffer from the loss of inked areas or from the presence of brown spotting. Indeed, using ultraviolet radiation and collecting the images at different spectral ranges is possible to enhance the readability of the text, while by illuminating with visible light and by collecting the images at longer wavelengths, the hiding effect of brown spots can be attenuated

Characterization and digital restauration of XIV-XV centuries written parchments by means of non-destructive techniques. Three case studies

Parchment is the primary writing medium of the majority of documents with cultural importance. Unfortunately, this material suffers of several mechanisms of degradation that affect its chemical-physical structure and the readability of text. Due to the unique and delicate character of these objects, the use of nondestructive techniques is mandatory. In this work, three partially degraded handwritten parchments dating back to the XIV-XV centuries were analyzed by means of X-ray fluorescence spectroscopy, µ-ATR Fourier transform infrared spectroscopy, and reflectance and UV-induced fluorescence spectroscopy. 'e elemental and molecular results provided the identification of the inks, pigments, and superficial treatments. In particular, all manuscripts have been written with iron gall inks, while the capital letters have been realized with cinnabar and azurite. Furthermore, multispectral UV fluorescence imaging and multispectral VIS-NIR imaging proved to be a good approach for the digital restoration of manuscripts that suffer from the loss of inked areas or from the presence of brown spotting. Indeed, using ultraviolet radiation and collecting the images at different spectral ranges is possible to enhance the readability of the text, while by illuminating with visible light and by collecting the images at longer wavelengths, the hiding effect of brown spots can be attenuated

Acute Stroke Multimodal Imaging: Present and Potential Applications toward Advancing Care.

In the past few decades, the field of acute ischemic stroke (AIS) has experienced significant advances in clinical practice. A core driver of this success has been the utilization of acute stroke imaging with an increasing focus on advanced methods including multimodal imaging. Such imaging techniques not only provide a richer understanding of AIS in vivo, but also, in doing so, provide better informed clinical assessments in management and treatment toward achieving best outcomes. As a result, advanced stroke imaging methods are now a mainstay of routine AIS practice that reflect best practice delivery of care. Furthermore, these imaging methods hold great potential to continue to advance the understanding of AIS and its care in the future. Copyright © 2017 by Thieme Medical Publishers, Inc

A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer.

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of <3 minutes per nodule. We simulated additional digital biopsies using morphological procedures. Finally, we compared the features extracted from these digital biopsies with our reference standard using intraclass correlation coefficient (ICC) to characterize robustness. Comparing the reference standard segmentations to our digital biopsies, we found that 84/94 features had an ICC >0.7; comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs >0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required