Skip to main content

Biomechanics of Bone

  • Chapter
  • First Online:
Osteoporosis

Part of the book series: Contemporary Endocrinology ((COE))

Abstract

The ability to bear loads is a critical function of the skeleton, in addition to its metabolic and physiological roles. Load-bearing ability depends on both the applied loads and the structural properties of the loaded bone. When the loads exceed the structural properties, fracture will occur. Because the nature of the applied loads can be difficult to predict, the best approach for minimizing fracture risk is through targeted interventions and therapies to improve bone strength. The strength and fracture resistance of the skeleton depend primarily on the quantity, geometry/architecture, and material properties of bone tissue. Although each of these attributes has been examined independently in both cortical and cancellous bone, no single measurement can fully characterize the structural integrity of bone or reliably predict the occurrence of a fracture in individuals. In addition, factors such as aging, trauma, and disease affect the tissue properties and can compromise bone strength. While bone quantity and, more recently, architecture have been widely examined in vivo, these measures do not fully explain variations in bone mechanical properties observed experimentally ex vivo. Healthy bone tissue exhibits spatial and temporal variations in tissue-level material properties that are altered by aging and disease. Accurately characterizing bone material properties, whether at the tissue level or at the chemical composition level of the mineral and matrix constituents, may improve the ability to predict structural competence and fracture risk reliably for individuals.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Gabriel SE, Tosteson AN, Leibson CL, Crowson CS, Pond GR, Hammond CS, et al. Direct medical costs attributable to osteoporotic fractures. Osteoporos Int. 2002;13(4):323–30.

    Article  CAS  PubMed  Google Scholar 

  2. Johnell O. The socioeconomic burden of fractures: today and in the 21st century. Am J Med. 1997;103(2A):20S–5S; discussion 5S–6S

    Article  CAS  PubMed  Google Scholar 

  3. Melton LJ 3rd. Who has osteoporosis? A conflict between clinical and public health perspectives. J Bone Miner Res. 2000;15(12):2309–14.

    Article  PubMed  Google Scholar 

  4. Hayes WC, Piazza SJ, Zysset PK. Biomechanics of fracture risk prediction of the hip and spine by quantitative computed tomography. Radiol Clin N Am. 1991;29(1):1–18.

    CAS  PubMed  Google Scholar 

  5. van der Meulen MCH, Jepsen KJ, Mikić B. Understanding bone strength: size isn’t everything. Bone. 2001;29(2):101–4.

    Article  PubMed  Google Scholar 

  6. Duncan RL, Turner CH. Mechanotransduction and the functional response of bone to mechanical strain. Calcif Tissue Int. 1995;57(5):344–58.

    Article  CAS  PubMed  Google Scholar 

  7. van der Meulen MCH, Huiskes R. Why mechanobiology? A survey article. J Biomech. 2002;35(4):401–14.

    Article  PubMed  Google Scholar 

  8. Carter DR. Mechanical loading history and skeletal biology. J Biomech. 1987;20:1095–109.

    Article  CAS  PubMed  Google Scholar 

  9. Roux W. Der Kampf der Theile im Organismus: ein Beitrag zur Vervollständigung der mechanischen Zweckmässigkeitslehre: W. Engelmann; 1881.

    Google Scholar 

  10. Wolff J. Das Gesetz der Transformation der Knochen (The law of bone remodeling). Berlin: Verlag von August Hirschwald; 1892.

    Google Scholar 

  11. Scheuren A, Wehrle E, Flohr F, Muller R. Bone mechanobiology in mice: toward single-cell in vivo mechanomics. Biomech Model Mechanobiol. 2017;16(6):2017–34.

    Article  PubMed  Google Scholar 

  12. Bergmann G, Graichen F, Rohlmann A. Hip joint loading during walking and running, measured in two patients. J Biomech. 1993;26(8):969–90.

    Article  CAS  PubMed  Google Scholar 

  13. Kotzar GM, Davy DT, Goldberg VM, Heiple KG, Berilla J, Heiple KG Jr, et al. Telemeterized in vivo hip joint force data: a report on two patients after total hip surgery. J Orthop Res. 1991;9(5):621–33.

    Article  CAS  PubMed  Google Scholar 

  14. Carter DR, Hayes WC. The compressive behavior of bone as a two-phase porous structure. J Bone Joint Surg Am. 1977;59-A:954–62.

    Article  Google Scholar 

  15. Goldstein SA. The mechanical properties of trabecular bone: dependence on anatomic location and function. J Biomech. 1987;20(11–12):1055–61.

    Article  CAS  PubMed  Google Scholar 

  16. Martin RB, Burr DB, Sharkey NA. Skeletal tissue mechanics. New York: Springer; 1998.

    Book  Google Scholar 

  17. Raux P, Townsend PR, Miegel R, Rose RM, Radin EL. Trabecular architecture of the human patella. J Biomech. 1975;8(1):1–7.

    Article  CAS  PubMed  Google Scholar 

  18. Townsend PR, Raux P, Rose RM, Miegel RE, Radin EL. The distribution and anisotropy of the stiffness of cancellous bone in the human patella. J Biomech. 1975;8(6):363–7.

    Article  CAS  PubMed  Google Scholar 

  19. Riggs BL, Wahner HW, Seeman E, Offord KP, Dunn WL, Mazess RB, et al. Changes in bone mineral density of the proximal femur and spine with aging. Differences between the postmenopausal and senile osteoporosis syndromes. J Clin Invest. 1982;70(4):716–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Schuit SC, van der Klift M, Weel AE, de Laet CE, Burger H, Seeman E, et al. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam study. Bone. 2004;34(1):195–202.

    Article  CAS  PubMed  Google Scholar 

  21. Carter DR, Bouxsein ML, Marcus R. New approaches for interpreting projected bone densitometry data. J Bone Miner Res. 1992;7(2):137–45.

    Article  CAS  PubMed  Google Scholar 

  22. Moro M, Hecker AT, Bouxsein ML, Myers ER. Failure load of thoracic vertebrae correlates with lumbar bone mineral density measured by DXA. Calcif Tissue Int. 1995;56(3):206–9.

    Article  CAS  PubMed  Google Scholar 

  23. Laib A, Hauselmann HJ, Ruegsegger P. In vivo high resolution 3D-QCT of the human forearm. Technol Health Care. 1998;6(5–6):329–37.

    Article  CAS  PubMed  Google Scholar 

  24. Burghardt AJ, Pialat JB, Kazakia GJ, Boutroy S, Engelke K, Patsch JM, et al. Multicenter precision of cortical and trabecular bone quality measures assessed by high-resolution peripheral quantitative computed tomography. J Bone Miner Res. 2013;28(3):524–36.

    Article  PubMed  Google Scholar 

  25. Manske SL, Zhu Y, Sandino C, Boyd SK. Human trabecular bone microarchitecture can be assessed independently of density with second generation HR-pQCT. Bone. 2015;79:213–21.

    Article  CAS  PubMed  Google Scholar 

  26. Laib A, Ruegsegger P. Comparison of structure extraction methods for in vivo trabecular bone measurements. Comput Med Imaging Graph. 1999;23(2):69–74.

    Article  CAS  PubMed  Google Scholar 

  27. Boutroy S, Bouxsein ML, Munoz F, Delmas PD. In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab. 2005;90(12):6508–15.

    Article  CAS  PubMed  Google Scholar 

  28. Goldstein SA, Wilson DL, Sonstegard DA, Matthews LS. The mechanical properties of human tibial trabecular bone as a function of metaphyseal location. J Biomech. 1983;16(12):965–9.

    Article  CAS  PubMed  Google Scholar 

  29. Gibson LJ. The mechanical behavior of cancellous bone. J Biomech. 1985;18:317–28.

    Article  CAS  PubMed  Google Scholar 

  30. Hodgskinson R, Currey JD. Young’s modulus, density and material properties in cancellous bone over a large density range. J Mater Sci Mater Med. 1992;3(5):377–81.

    Article  Google Scholar 

  31. Rho JY, Ashman RB, Turner CH. Young’s modulus of trabecular and cortical bone material: ultrasonic and microtensile measurements. J Biomech. 1993;26(2):111–9.

    Article  CAS  PubMed  Google Scholar 

  32. Rice JC, Cowin SC, Bowman JA. On the dependence of the elasticity and strength of cancellous bone on apparent density. J Biomech. 1988;21(2):155–68.

    Article  CAS  PubMed  Google Scholar 

  33. Snyder SM, Schneider E. Estimation of mechanical properties of cortical bone by computed tomography. J Orthop Res. 1991;9(3):422–31.

    Article  CAS  PubMed  Google Scholar 

  34. Keaveny TM, Pinilla TP, Crawford RP, Kopperdahl DL, Lou A. Systematic and random errors in compression testing of trabecular bone. J Orthop Res. 1997;15(1):101–10.

    Article  CAS  PubMed  Google Scholar 

  35. Kopperdahl DL, Keaveny TM. Yield strain behavior of trabecular bone. J Biomech. 1998;31(7):601–8.

    Article  CAS  PubMed  Google Scholar 

  36. Linde F, Gøthgen CB, Hvid I, Pongsoipetch B. Mechanical properties of trabecular bone by a non-destructive compression testing approach. Eng Med. 1988;17(1):23–9.

    Article  CAS  PubMed  Google Scholar 

  37. Linde F, Hvid I, Pongsoipetch B. Energy absorptive properties of human trabecular bone specimens during axial compression. J Orthop Res. 1989;7(3):432–9.

    Article  CAS  PubMed  Google Scholar 

  38. Morgan EF, Bayraktar HH, Keaveny TM. Trabecular bone modulus-density relationships depend on anatomic site. J Biomech. 2003;36(7):897–904.

    Article  PubMed  Google Scholar 

  39. Broy SB, Cauley JA, Lewiecki ME, Schousboe JT, Shepherd JA, Leslie WD. Fracture risk prediction by Non-BMD DXA measures: the 2015 ISCD official positions part 1: hip geometry. J Clin Densitom. 2015;18(3):287–308.

    Article  PubMed  Google Scholar 

  40. Leslie WD, Krieg MA, Hans D. Clinical factors associated with trabecular bone score. J Clin Densitom. 2013;16(3):374–9.

    Article  PubMed  Google Scholar 

  41. Faulkner KG, Cummings SR, Black D, Palermo L, Gluer CC, Genant HK. Simple measurement of femoral geometry predicts hip fracture: the study of osteoporotic fractures. J Bone Miner Res. 1993;8(10):1211–7.

    Article  CAS  PubMed  Google Scholar 

  42. Leslie WD, Lix LM, Morin SN, Johansson H, Oden A, McCloskey EV, et al. Hip axis length is a FRAX- and bone density-independent risk factor for hip fracture in women. J Clin Endocrinol Metab. 2015;100(5):2063–70.

    Article  CAS  PubMed  Google Scholar 

  43. Leslie WD, Lix LM, Morin SN, Johansson H, Oden A, McCloskey EV, et al. Adjusting hip fracture probability in men and women using hip axis length: the Manitoba bone density database. J Clin Densitom. 2016;19(3):326–31.

    Article  PubMed  Google Scholar 

  44. Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E. FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int. 2008;19(4):385–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Pothuaud L, Carceller P, Hans D. Correlations between grey-level variations in 2D projection images (TBS) and 3D microarchitecture: applications in the study of human trabecular bone microarchitecture. Bone. 2008;42(4):775–87.

    Article  PubMed  Google Scholar 

  46. Boutroy S, Hans D, Sornay-Rendu E, Vilayphiou N, Winzenrieth R, Chapurlat R. Trabecular bone score improves fracture risk prediction in non-osteoporotic women: the OFELY study. Osteoporos Int. 2013;24(1):77–85.

    Article  CAS  PubMed  Google Scholar 

  47. Briot K, Paternotte S, Kolta S, Eastell R, Reid DM, Felsenberg D, et al. Added value of trabecular bone score to bone mineral density for prediction of osteoporotic fractures in postmenopausal women: the OPUS study. Bone. 2013;57(1):232–6.

    Article  PubMed  Google Scholar 

  48. Hans D, Goertzen AL, Krieg MA, Leslie WD. Bone microarchitecture assessed by TBS predicts osteoporotic fractures independent of bone density: the Manitoba study. J Bone Miner Res. 2011;26(11):2762–9.

    Article  PubMed  Google Scholar 

  49. Iki M, Tamaki J, Kadowaki E, Sato Y, Dongmei N, Winzenrieth R, et al. Trabecular bone score (TBS) predicts vertebral fractures in Japanese women over 10 years independently of bone density and prevalent vertebral deformity: the Japanese Population-Based Osteoporosis (JPOS) cohort study. J Bone Miner Res. 2014;29(2):399–407.

    Article  PubMed  Google Scholar 

  50. Lamy O, Metzger M, Krieg MA, Aubry-Rozier B, Stoll D, Hans D. La cohorte OstéoLaus: évaluation des outils de routine clinique pour la prédiction de la fracture ostéoporotique [OsteoLaus: prediction of osteoporotic fractures by clinical risk factors and DXA, IVA and TBS]. Rev Med Suisse. 2011;7(315):2130, 2132–4, 2136.

    Google Scholar 

  51. Leslie WD, Aubry-Rozier B, Lix LM, Morin SN, Majumdar SR, Hans D. Spine bone texture assessed by trabecular bone score (TBS) predicts osteoporotic fractures in men: the Manitoba Bone Density Program. Bone. 2014;67:10–4.

    Article  CAS  PubMed  Google Scholar 

  52. Silva BC, Leslie WD. Trabecular bone score: a new DXA-derived measurement for fracture risk assessment. Endocrinol Metab Clin N Am. 2017;46(1):153–80.

    Article  Google Scholar 

  53. McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, et al. A meta-analysis of trabecular bone score in fracture risk prediction and its relationship to FRAX. J Bone Miner Res. 2016;31(5):940–8.

    Article  PubMed  Google Scholar 

  54. Roux JP, Wegrzyn J, Boutroy S, Bouxsein ML, Hans D, Chapurlat R. The predictive value of trabecular bone score (TBS) on whole lumbar vertebrae mechanics: an ex vivo study. Osteoporos Int. 2013;24(9):2455–60.

    Article  CAS  PubMed  Google Scholar 

  55. Martin RB, Burr DB. Non-invasive measurement of long bone cross-sectional moment of inertia by photon absorptiometry. J Biomech. 1984;17(3):195–201.

    Article  CAS  PubMed  Google Scholar 

  56. Hibbeler RC. Mechanics of materials. Upper Saddle River, New Jersey: Prentice Hall; 1997.

    Google Scholar 

  57. Cooper A. A treatise on dislocations and fractures of the joints. London: Longman, Hurst, Rees, Orme, and Brown; 1842.

    Google Scholar 

  58. Galante J, Rostoker W, Ray RD. Physical properties of trabecular bone. Calcif Tissue Res. 1970;5:236–46.

    Article  CAS  PubMed  Google Scholar 

  59. Ulrich D, Hildebrand T, van Rietbergen B, Müller R, Rüegsegger P. The quality of trabecular bone evaluated with micro-computed tomography, FEA and mechanical testing. Stud Health Technol Inform. 1997;40:97–112.

    CAS  PubMed  Google Scholar 

  60. Mosekilde L. Consequences of the remodelling process for vertebral trabecular bone structure: a scanning electron microscopy study (uncoupling of unloaded structures). Bone Miner. 1990;10(1):13–35.

    Article  CAS  PubMed  Google Scholar 

  61. Hans D, Barthe N, Boutroy S, Pothuaud L, Winzenrieth R, Krieg MA. Correlations between trabecular bone score, measured using anteroposterior dual-energy X-ray absorptiometry acquisition, and 3-dimensional parameters of bone microarchitecture: an experimental study on human cadaver vertebrae. J Clin Densitom. 2011;14(3):302–12.

    Article  PubMed  Google Scholar 

  62. Muschitz C, Kocijan R, Haschka J, Pahr D, Kaider A, Pietschmann P, et al. TBS reflects trabecular microarchitecture in premenopausal women and men with idiopathic osteoporosis and low-traumatic fractures. Bone. 2015;79:259–66.

    Article  PubMed  Google Scholar 

  63. Popp AW, Buffat H, Eberli U, Lippuner K, Ernst M, Richards RG, et al. Microstructural parameters of bone evaluated using HR-pQCT correlate with the DXA-derived cortical index and the trabecular bone score in a cohort of randomly selected premenopausal women. PLoS One. 2014;9(2):e88946.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Silva BC, Boutroy S, Zhang C, McMahon DJ, Zhou B, Wang J, et al. Trabecular bone score (TBS)--a novel method to evaluate bone microarchitectural texture in patients with primary hyperparathyroidism. J Clin Endocrinol Metab. 2013;98(5):1963–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Winzenrieth R, Michelet F, Hans D. Three-dimensional (3D) microarchitecture correlations with 2D projection image gray-level variations assessed by trabecular bone score using high-resolution computed tomographic acquisitions: effects of resolution and noise. J Clin Densitom. 2013;16(3):287–96.

    Article  PubMed  Google Scholar 

  66. Black DM, Bouxsein ML, Marshall LM, Cummings SR, Lang TF, Cauley JA, et al. Proximal femoral structure and the prediction of hip fracture in men: a large prospective study using QCT. J Bone Miner Res. 2008;23(8):1326–33.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Borggrefe J, de Buhr T, Shrestha S, Marshall LM, Orwoll E, Peters K, et al. Association of 3D geometric measures derived from quantitative computed tomography with hip fracture risk in older men. J Bone Miner Res. 2016;31(8):1550–8.

    Article  PubMed  Google Scholar 

  68. Bredbenner TL, Mason RL, Havill LM, Orwoll ES, Nicolella DP. Fracture risk predictions based on statistical shape and density modeling of the proximal femur. J Bone Miner Res. 2014;29(9):2090–100.

    Google Scholar 

  69. Carballido-Gamio J, Harnish R, Saeed I, Streeper T, Sigurdsson S, Amin S, et al. Proximal femoral density distribution and structure in relation to age and hip fracture risk in women. J Bone Miner Res. 2013;28(3):537–46.

    Article  PubMed  Google Scholar 

  70. Carballido-Gamio J, Harnish R, Saeed I, Streeper T, Sigurdsson S, Amin S, et al. Structural patterns of the proximal femur in relation to age and hip fracture risk in women. Bone. 2013;57(1):290–9.

    Article  PubMed  Google Scholar 

  71. Chalhoub D, Orwoll ES, Cawthon PM, Ensrud KE, Boudreau R, Greenspan S, et al. Areal and volumetric bone mineral density and risk of multiple types of fracture in older men. Bone. 2016;92:100–6.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Johannesdottir F, Poole KE, Reeve J, Siggeirsdottir K, Aspelund T, Mogensen B, et al. Distribution of cortical bone in the femoral neck and hip fracture: a prospective case-control analysis of 143 incident hip fractures; The AGES-REYKJAVIK Study. Bone. 2011;48(6):1268–76.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Orwoll ES, Marshall LM, Nielson CM, Cummings SR, Lapidus J, Cauley JA, et al. Finite element analysis of the proximal femur and hip fracture risk in older men. J Bone Miner Res. 2009;24(3):475–83.

    Article  PubMed  Google Scholar 

  74. Treece GM, Gee AH, Tonkin C, Ewing SK, Cawthon PM, Black DM, et al. Predicting hip fracture type with cortical bone mapping (CBM) in the osteoporotic fractures in men (MrOS) study. J Bone Miner Res. 2015;30(11):2067–77.

    Article  PubMed  Google Scholar 

  75. Yang L, Burton AC, Bradburn M, Nielson CM, Orwoll ES, Eastell R, et al. Distribution of bone density in the proximal femur and its association with hip fracture risk in older men: the osteoporotic fractures in men (MrOS) study. J Bone Miner Res. 2012;27(11):2314–24.

    Article  PubMed  Google Scholar 

  76. Kopperdahl DL, Aspelund T, Hoffmann PF, Sigurdsson S, Siggeirsdottir K, Harris TB, et al. Assessment of incident spine and hip fractures in women and men using finite element analysis of CT scans. J Bone Miner Res. 2014;29(3):570–80.

    Article  PubMed  Google Scholar 

  77. Wang X, Sanyal A, Cawthon PM, Palermo L, Jekir M, Christensen J, et al. Prediction of new clinical vertebral fractures in elderly men using finite element analysis of CT scans. J Bone Miner Res. 2012;27(4):808–16.

    Article  PubMed  Google Scholar 

  78. Burghardt AJ, Buie HR, Laib A, Majumdar S, Boyd SK. Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone. 2010;47(3):519–28.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Vico L, Zouch M, Amirouche A, Frere D, Laroche N, Koller B, et al. High-resolution pQCT analysis at the distal radius and tibia discriminates patients with recent wrist and femoral neck fractures. J Bone Miner Res. 2008;23(11):1741–50.

    Article  PubMed  Google Scholar 

  80. Cheung AM, Adachi JD, Hanley DA, Kendler DL, Davison KS, Josse R, et al. High-resolution peripheral quantitative computed tomography for the assessment of bone strength and structure: a review by the Canadian Bone Strength Working Group. Curr Osteoporos Rep. 2013;11(2):136–46.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Liu XS, Shane E, McMahon DJ, Guo XE. Individual trabecula segmentation (ITS)-based morphological analysis of microscale images of human tibial trabecular bone at limited spatial resolution. J Bone Miner Res. 2011;26(9):2184–93.

    Article  PubMed  Google Scholar 

  82. Sornay-Rendu E, Boutroy S, Duboeuf F, Chapurlat RD. Bone microarchitecture assessed by HR-pQCT as predictor of fracture risk in postmenopausal women: the OFELY study. J Bone Miner Res. 2017;32(6):1243–51.

    Article  CAS  PubMed  Google Scholar 

  83. Carballido-Gamio J, Nicolella DP. Computational anatomy in the study of bone structure. Curr Osteoporos Rep. 2013;11(3):237–45.

    Article  PubMed  Google Scholar 

  84. Li W, Kezele I, Collins DL, Zijdenbos A, Keyak J, Kornak J, et al. Voxel-based modeling and quantification of the proximal femur using inter-subject registration of quantitative CT images. Bone. 2007;41(5):888–95.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Li W, Kornak J, Harris T, Keyak J, Li C, Lu Y, et al. Identify fracture-critical regions inside the proximal femur using statistical parametric mapping. Bone. 2009;44(4):596–602.

    Article  PubMed  Google Scholar 

  86. Poole KE, Treece GM, Mayhew PM, Vaculik J, Dungl P, Horak M, et al. Cortical thickness mapping to identify focal osteoporosis in patients with hip fracture. PLoS One. 2012;7(6):e38466.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Allison SJ, Poole KE, Treece GM, Gee AH, Tonkin C, Rennie WJ, et al. The influence of high-impact exercise on cortical and trabecular bone mineral content and 3D distribution across the proximal femur in older men: a randomized controlled unilateral intervention. J Bone Miner Res. 2015;30(9):1709–16.

    Article  CAS  PubMed  Google Scholar 

  88. Poole KE, Treece GM, Gee AH, Brown JP, McClung MR, Wang A, et al. Denosumab rapidly increases cortical bone in key locations of the femur: a 3D bone mapping study in women with osteoporosis. J Bone Miner Res. 2015;30(1):46–54.

    Article  CAS  PubMed  Google Scholar 

  89. Seeherman HJ, Li XJ, Smith E, Parkington J, Li R, Wozney JM. Intraosseous injection of rhBMP-2/calcium phosphate matrix improves bone structure and strength in the proximal aspect of the femur in chronic ovariectomized nonhuman primates. J Bone Joint Surg Am. 2013;95(1):36–47.

    Article  PubMed  Google Scholar 

  90. Whitmarsh T, Treece GM, Gee AH, Poole KE. Mapping bone changes at the proximal femoral cortex of postmenopausal women in response to alendronate and teriparatide alone, combined or sequentially. J Bone Miner Res. 2015;30(7):1309–18.

    Article  CAS  PubMed  Google Scholar 

  91. Nicolella DP, Bredbenner TL. Development of a parametric finite element model of the proximal femur using statistical shape and density modelling. Comput Methods Biomech Biomed Engin. 2012;15(2):101–10.

    Article  PubMed  Google Scholar 

  92. Treece GM, Poole KE, Gee AH. Imaging the femoral cortex: thickness, density and mass from clinical CT. Med Image Anal. 2012;16(5):952–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Cowin SC. The relationship between the elasticity tensor and the fabric tensor. Mech Mater. 1985;4:137–47.

    Article  Google Scholar 

  94. Goldstein SA, Goulet R, McCubbrey D. Measurement and significance of three-dimensional architecture to the mechanical integrity of trabecular bone. Calcif Tissue Int. 1993;53:S127–32; discussion S32-3

    Article  PubMed  Google Scholar 

  95. Goulet RW, Goldstein SA, Ciarelli MJ, Kuhn JL, Brown MB, Feldkamp LA. The relationship between the structural and orthogonal compressive properties of trabecular bone. J Biomech. 1994;27(4):375–89.

    Article  CAS  PubMed  Google Scholar 

  96. Kabel J, Odgaard A, van Rietbergen B, Huiskes R. Connectivity and the elastic properties of cancellous bone. Bone. 1999;24(2):115–20.

    Article  CAS  PubMed  Google Scholar 

  97. Odgaard A, Kabel J, van Rietbergen B, Dalstra M, Huiskes R. Fabric and elastic principal directions of cancellous bone are closely related. J Biomech. 1997;30(5):487–95.

    Article  CAS  PubMed  Google Scholar 

  98. van Rietbergen B, Majumdar S, Pistoia W, Newitt DC, Kothari M, Laib A, et al. Assessment of cancellous bone mechanical properties from micro-FE models based on micro-CT, pQCT and MR images. Technol Health Care. 1998;6(5–6):413–20.

    Article  PubMed  Google Scholar 

  99. Pugh JW, Rose RM, Radin EL. A structural model for the mechanical behavior of trabecular bone. J Biomech. 1973;6(6):657–70.

    Article  CAS  PubMed  Google Scholar 

  100. Mittra E, Rubin C, Qin YX. Interrelationship of trabecular mechanical and microstructural properties in sheep trabecular bone. J Biomech. 2005;38(6):1229–37.

    Article  PubMed  Google Scholar 

  101. Thomsen JS, Ebbesen EN, Mosekilde L. Predicting human vertebral bone strength by vertebral static histomorphometry. Bone. 2002;30(3):502–8.

    Article  CAS  PubMed  Google Scholar 

  102. Burr DB, Forwood MR, Fyhrie DP, Martin RB, Schaffler MB, Turner CH. Bone microdamage and skeletal fragility in osteoporotic and stress fractures. J Bone Miner Res. 1997;12(1):6–15.

    Article  CAS  PubMed  Google Scholar 

  103. Currey JD. Role of collagen and other organics in the mechanical properties of bone. Osteoporos Int. 2003;14(Suppl 5):S29–36.

    Google Scholar 

  104. Currey JD, Foreman J, Laketic I, Mitchell J, Pegg DE, Reilly GC. Effects of ionizing radiation on the mechanical properties of human bone. J Orthop Res. 1997;15(1):111–7.

    Article  CAS  PubMed  Google Scholar 

  105. Hamer AJ, Stockley I, Elson RA. Changes in allograft bone irradiated at different temperatures. J Bone Joint Surg Br. 1999;81(2):342–4.

    Article  CAS  PubMed  Google Scholar 

  106. Oxlund H, Barckman M, Ortoft G, Andreassen TT. Reduced concentrations of collagen cross-links are associated with reduced strength of bone. Bone. 1995;17(4 Suppl):365S–71S.

    CAS  PubMed  Google Scholar 

  107. Burstein AH, Zika JM, Heiple K, Klein L. Contribution of collagen and mineral to the elastic-plastic propeties of bone. J Bone Joint Surg Am. 1975;57(7):956–61.

    Article  CAS  PubMed  Google Scholar 

  108. Currey JD. The effect of porosity and mineral content on the Young’s modulus of elasticity of compact bone. J Biomech. 1988;21(2):131–9.

    Article  CAS  PubMed  Google Scholar 

  109. Currey JD. What determines the bending strength of compact bone? J Exp Biol. 1999;202(Pt 18):2495–503.

    CAS  PubMed  Google Scholar 

  110. Martin RB, Boardman DL. The effects of collagen fiber orientation, porosity, density, and mineralization on bovine cortical bone bending properties. J Biomech. 1993;26(9):1047–54.

    Article  CAS  PubMed  Google Scholar 

  111. Bonucci E, Ballanti P, Della Rocca C, Milani S, Lo Cascio V, Imbimbo B. Technical variability of bone histomorphometric measurements. Bone Miner. 1990;11(2):177–86.

    Article  CAS  PubMed  Google Scholar 

  112. Malluche HH, Meyer W, Sherman D, Massry SG. Quantitative bone histology in 84 normal American subjects. Micromorphometric analysis and evaluation of variance in iliac bone. Calcif Tissue Int. 1982;34(5):449–55.

    Article  CAS  PubMed  Google Scholar 

  113. Ninomiya JT, Tracy RP, Calore JD, Gendreau MA, Kelm RJ, Mann KG. Heterogeneity of human bone. J Bone Miner Res. 1990;5(9):933–8.

    Article  CAS  PubMed  Google Scholar 

  114. Handschin RG, Stern WB. Crystallographic and chemical analysis of human bone apatite (Crista Iliaca). Clin Rheumatol. 1994;13(Suppl 1):75–90.

    PubMed  Google Scholar 

  115. Handschin RG, Stern WB. X-ray diffraction studies on the lattice perfection of human bone apatite (Crista iliaca). Bone. 1995;16(4 Suppl):355S–63S.

    Article  Google Scholar 

  116. Choi K, Kuhn JL, Ciarelli MJ, Goldstein SA. The elastic moduli of human subchondral, trabecular, and cortical bone tissue and the size-dependency of cortical bone modulus. J Biomech. 1990;23(11):1103–13.

    Article  CAS  PubMed  Google Scholar 

  117. Kuhn JL, Goldstein SA, Choi K, London M, Feldkamp LA, Matthews LS. Comparison of the trabecular and cortical tissue moduli from human iliac crests. J Orthop Res. 1989;7(6):876–84.

    Article  CAS  PubMed  Google Scholar 

  118. Rho JY, Roy ME 2nd, Tsui TY, Pharr GM. Elastic properties of microstructural components of human bone tissue as measured by nanoindentation. J Biomed Mater Res. 1999;45(1):48–54.

    Article  CAS  PubMed  Google Scholar 

  119. Rho JY, Tsui TY, Pharr GM. Elastic properties of human cortical and trabecular lamellar bone measured by nanoindentation. Biomaterials. 1997;18(20):1325–30.

    Article  CAS  PubMed  Google Scholar 

  120. Turner CH, Rho J, Takano Y, Tsui TY, Pharr GM. The elastic properties of trabecular and cortical bone tissues are similar: results from two microscopic measurement techniques. J Biomech. 1999;32(4):437–41.

    Article  CAS  PubMed  Google Scholar 

  121. Zysset PK, Guo XE, Hoffler CE, Moore KE, Goldstein SA. Elastic modulus and hardness of cortical and trabecular bone lamellae measured by nanoindentation in the human femur. J Biomech. 1999;32(10):1005–12.

    Article  CAS  PubMed  Google Scholar 

  122. Matousek P, Draper ER, Goodship AE, Clark IP, Ronayne KL, Parker AW. Noninvasive Raman spectroscopy of human tissue in vivo. Appl Spectrosc. 2006;60(7):758–63.

    Article  CAS  PubMed  Google Scholar 

  123. Schulmerich MV, Cole JH, Kreider JM, Esmonde-White F, Dooley KA, Goldstein SA, et al. Transcutaneous Raman spectroscopy of murine bone in vivo. Appl Spectrosc. 2009;63(3):286–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Shu C, Chen K, Lynch M, Maher JR, Awad HA, Berger AJ. Spatially offset Raman spectroscopy for in vivo bone strength prediction. Biomed Opt Express. 2018;9(10):4781–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Mosekilde L, Mosekilde L, Danielsen CC. Biomechanical competence of vertebral trabecular bone in relation to ash density and age in normal individuals. Bone. 1987;8(2):79–85.

    Article  CAS  PubMed  Google Scholar 

  126. (None). Bone density reference data. In: Favus MJ, editor. Primer on the metabolic bone diseases and disorders of mineral metabolism. 4th ed. Philadelphia: Lippincott Williams & Wilkins; 1996. p. 483.

    Google Scholar 

  127. Barden H. Bone mineral density of the spine and femur in normal U.S. white females. J Bone Miner Res. 1997;12(Suppl. 1):S248.

    Google Scholar 

  128. Diaz Curiel M, Carrasco de la Peña JL, Honorato Perez J, Perez Cano R, Rapado A, Ruiz Martinez I. Study of bone mineral density in lumbar spine and femoral neck in a Spanish population. Multicentre Research Project on Osteoporosis. Osteoporos Int. 1997;7(1):59–64.

    Article  CAS  PubMed  Google Scholar 

  129. Lehmann R, Wapniarz M, Randerath O, Kvasnicka HM, John W, Reincke M, et al. Dual-energy X-ray absorptiometry at the lumbar spine in German men and women: a cross-sectional study. Calcif Tissue Int. 1995;56(5):350–4.

    Article  CAS  PubMed  Google Scholar 

  130. Löfman O, Larsson L, Ross I, Toss G, Berglund K. Bone mineral density in normal Swedish women. Bone. 1997;20(2):167–74.

    Article  PubMed  Google Scholar 

  131. Vega E, Bagur A, Mautalen CA. Densidad mineral âosea en mujeres osteoporâoticas y normales de Buenos Aires. Medicina. 1993;53(3):211–6.

    CAS  PubMed  Google Scholar 

  132. Szulc P, Munoz F, Duboeuf F, Marchand F, Delmas PD. Bone mineral density predicts osteoporotic fractures in elderly men: the MINOS study. Osteoporos Int. 2005;16(10):1184–92.

    Article  PubMed  Google Scholar 

  133. Ahlborg HG, Johnell O, Turner CH, Rannevik G, Karlsson MK. Bone loss and bone size after menopause. N Engl J Med. 2003;349(4):327–34.

    Article  PubMed  Google Scholar 

  134. Aloia JF, Vaswani A, Mikhail M, Badshah M, Flaster E. Cancellous bone of the spine is greater in black women. Calcif Tissue Int. 1999;65(1):29–33.

    Article  CAS  PubMed  Google Scholar 

  135. Arlot ME, Sornay-Rendu E, Garnero P, Vey-Marty B, Delmas PD. Apparent pre- and postmenopausal bone loss evaluated by DXA at different skeletal sites in women: the OFELY cohort. J Bone Miner Res. 1997;12(4):683–90.

    Article  CAS  PubMed  Google Scholar 

  136. Riggs BL, Khosla S, Melton LJ 3rd. Sex steroids and the construction and conservation of the adult skeleton. Endocr Rev. 2002;23(3):279–302.

    Article  CAS  PubMed  Google Scholar 

  137. Hui SL, Slemenda CW, Johnston CC Jr. Age and bone mass as predictors of fracture in a prospective study. J Clin Invest. 1988;81(6):1804–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Ross PD, Davis JW, Epstein RS, Wasnich RD. Pre-existing fractures and bone mass predict vertebral fracture incidence in women. Ann Intern Med. 1991;114(11):919–23.

    Article  CAS  PubMed  Google Scholar 

  139. Ross PD, Davis JW, Vogel JM, Wasnich RD. A critical review of bone mass and the risk of fractures in osteoporosis. Calcif Tissue Int. 1990;46(3):149–61.

    Article  CAS  PubMed  Google Scholar 

  140. Melton LJ 3rd. Hip fractures: a worldwide problem today and tomorrow. Bone. 1993;14:S1–8.

    Article  PubMed  Google Scholar 

  141. National Osteoporosis Foundation. America’s bone health: the state of osteoporosis and low bone mass in our nation. Washington, D.C: National Osteoporosis Foundation; 2002.

    Google Scholar 

  142. Paschalis EP, Betts F, DiCarlo E, Mendelsohn R, Boskey AL. FTIR microspectroscopic analysis of normal human cortical and trabecular bone. Calcif Tissue Int. 1997;61(6):480–6.

    Article  CAS  PubMed  Google Scholar 

  143. Boskey AL, Dicarlo E, Paschalis E, West P, Mendelsohn R. Comparison of mineral quality and quantity in iliac crest biopsies from high- and low-turnover osteoporosis: an FT-IR microspectroscopic investigation. Osteoporos Int. 2005;16(12):2031–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Kozloff KM, Carden A, Bergwitz C, Forlino A, Uveges TE, Morris MD, et al. Brittle IV mouse model for osteogenesis imperfecta IV demonstrates postpubertal adaptations to improve whole bone strength. J Bone Miner Res. 2004;19(4):614–22.

    Article  PubMed  Google Scholar 

  145. Ou-Yang H, Paschalis EP, Mayo WE, Boskey AL, Mendelsohn R. Infrared microscopic imaging of bone: spatial distribution of CO3(2-). J Bone Miner Res. 2001;16(5):893–900.

    Article  CAS  PubMed  Google Scholar 

  146. Paschalis EP, Betts F, DiCarlo E, Mendelsohn R, Boskey AL. FTIR microspectroscopic analysis of human iliac crest biopsies from untreated osteoporotic bone. Calcif Tissue Int. 1997;61(6):487–92.

    Article  CAS  PubMed  Google Scholar 

  147. Tarnowski CP, Ignelzi MA Jr, Morris MD. Mineralization of developing mouse calvaria as revealed by Raman microspectroscopy. J Bone Miner Res. 2002;17(6):1118–26.

    Article  PubMed  Google Scholar 

  148. Kim G, Cole JH, Boskey AL, Baker SP, van der Meulen MC. Reduced tissue-level stiffness and mineralization in osteoporotic cancellous bone. Calcif Tissue Int. 2014;95(2):125–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. McCreadie BR, Morris MD, Chen TC, Sudhaker Rao D, Finney WF, Widjaja E, et al. Bone tissue compositional differences in women with and without osteoporotic fracture. Bone. 2006;39(6):1190–5.

    Article  CAS  PubMed  Google Scholar 

  150. Yerramshetty JS, Lind C, Akkus O. The compositional and physicochemical homogeneity of male femoral cortex increases after the sixth decade. Bone. 2006;39(6):1236–43.

    Article  CAS  PubMed  Google Scholar 

  151. Gourion-Arsiquaud S, Lukashova L, Power J, Loveridge N, Reeve J, Boskey AL. Fourier transform infrared imaging of femoral neck bone: reduced heterogeneity of mineral-to-matrix and carbonate-to-phosphate and more variable crystallinity in treatment-naive fracture cases compared with fracture-free controls. J Bone Miner Res. 2013;28(1):150–61.

    Article  CAS  PubMed  Google Scholar 

  152. Boskey AL, Donnelly E, Boskey E, Spevak L, Ma Y, Zhang W, et al. Examining the relationships between bone tissue composition, compositional heterogeneity, and fragility fracture: a matched case-controlled FTIRI study. J Bone Miner Res. 2016;31(5):1070–81.

    Article  CAS  PubMed  Google Scholar 

  153. Akkus O, Adar F, Schaffler MB. Age-related changes in physicochemical properties of mineral crystals are related to impaired mechanical function of cortical bone. Bone. 2004;34(3):443–53.

    Article  CAS  PubMed  Google Scholar 

  154. Nyman JS, Roy A, Tyler JH, Acuna RL, Gayle HJ, Wang X. Age-related factors affecting the postyield energy dissipation of human cortical bone. J Orthop Res. 2007;25(5):646–55.

    Article  PubMed  PubMed Central  Google Scholar 

  155. Wang X, Shen X, Li X, Agrawal CM. Age-related changes in the collagen network and toughness of bone. Bone. 2002;31(1):1–7.

    Article  PubMed  Google Scholar 

  156. Sroga GE, Karim L, Colon W, Vashishth D. Biochemical characterization of major bone-matrix proteins using nanoscale-size bone samples and proteomics methodology. Mol Cell Proteomics. 2011;10(9):M110 006718.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  157. Tang SY, Zeenath U, Vashishth D. Effects of non-enzymatic glycation on cancellous bone fragility. Bone. 2007;40(4):1144–51.

    Article  CAS  PubMed  Google Scholar 

  158. Gineyts E, Munoz F, Bertholon C, Sornay-Rendu E, Chapurlat R. Urinary levels of pentosidine and the risk of fracture in postmenopausal women: the OFELY study. Osteoporos Int. 2010;21(2):243–50.

    Article  CAS  PubMed  Google Scholar 

  159. Aaron JE, Makins NB, Sagreiya K. The microanatomy of trabecular bone loss in normal aging men and women. Clin Orthop Relat Res. 1987;215:260–71.

    Google Scholar 

  160. Dempster DW, Ferguson-Pell MW, Mellish RW, Cochran GV, Xie F, Fey C, et al. Relationships between bone structure in the iliac crest and bone structure and strength in the lumbar spine. Osteoporos Int. 1993;3(2):90–6.

    Article  CAS  PubMed  Google Scholar 

  161. Mosekilde L. Sex differences in age-related loss of vertebral trabecular bone mass and structure – biomechanical consequences. Bone. 1989;10:425–32.

    Article  CAS  PubMed  Google Scholar 

  162. Thomsen JS, Ebbesen EN, Mosekilde L. A new method of comprehensive static histomorphometry applied on human lumbar vertebral cancellous bone. Bone. 2000;27(1):129–38.

    Article  CAS  PubMed  Google Scholar 

  163. Mosekilde L, Mosekilde L. Sex differences in age-related changes in vertebral body size, density and biomechanical competence in normal individuals. Bone. 1990;11:67–73.

    Article  CAS  PubMed  Google Scholar 

  164. Bergot C, Laval-Jeantet AM, Preteux F, Meunier A. Measurement of anisotropic vertebral trabecular bone loss during aging by quantitative image analysis. Calcif Tissue Int. 1988;43(3):143–9.

    Article  CAS  PubMed  Google Scholar 

  165. Dunnill MS, Anderson JA, Whitehead R. Quantitative histological studies on age changes in bone. J Pathol. 1967;94(2):275–91.

    Article  CAS  Google Scholar 

  166. Weaver JK, Chalmers J. Cancellous bone: its strength and changes with aging and an evaluation of some methods for measuring its mineral content. J Bone Joint Surg Am. 1966;48(2):289–98.

    Article  CAS  PubMed  Google Scholar 

  167. Hildebrand T, Laib A, Müller R, Dequeker J, Rüegsegger P. Direct three-dimensional morphometric analysis of human cancellous bone: microstructural data from spine, femur, iliac crest, and calcaneus. J Bone Miner Res. 1999;14(7):1167–74.

    Article  CAS  PubMed  Google Scholar 

  168. Silva MJ, Gibson LJ. Modeling the mechanical behavior of vertebral trabecular bone: effects of age-related changes in microstructure. Bone. 1997;21(2):191–9.

    Article  CAS  PubMed  Google Scholar 

  169. Cummings SR, Melton LJ. Epidemiology and outcomes of osteoporotic fractures. Lancet. 2002;359(9319):1761–7.

    Article  PubMed  Google Scholar 

  170. US Department of Health and Human Services. Bone health and osteoporosis: a report of the surgeon general. Rockville, MD: U.S. Department of Health and Human Services, Office of the Surgeon General; 2004.

    Google Scholar 

  171. Kleerekoper M, Villanueva AR, Stanciu J, Rao DS, Parfitt AM. The role of three-dimensional trabecular microstructure in the pathogenesis of vertebral compression fractures. Calcif Tissue Int. 1985;37(6):594–7.

    Article  CAS  PubMed  Google Scholar 

  172. Parfitt AM, Mathews CH, Villanueva AR, Kleerekoper M, Frame B, Rao DS. Relationships between surface, volume, and thickness of iliac trabecular bone in aging and in osteoporosis. Implications for the microanatomic and cellular mechanisms of bone loss. J Clin Invest. 1983;72(4):1396–409.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Ciarelli TE, Fyhrie DP, Schaffler MB, Goldstein SA. Variations in three-dimensional cancellous bone architecture of the proximal femur in female hip fractures and in controls. J Bone Miner Res. 2000;15(1):32–40.

    Article  CAS  PubMed  Google Scholar 

  174. Gadeleta SJ, Boskey AL, Paschalis E, Carlson C, Menschik F, Baldini T, et al. A physical, chemical, and mechanical study of lumbar vertebrae from normal, ovariectomized, and nandrolone decanoate-treated cynomolgus monkeys (Macaca fascicularis). Bone. 2000;27(4):541–50.

    Article  CAS  PubMed  Google Scholar 

  175. Cole WG. Osteogenesis imperfecta. Bailliere Clin Endocrinol Metab. 1988;2(1):243–65.

    Article  CAS  Google Scholar 

  176. Lim J, Grafe I, Alexander S, Lee B. Genetic causes and mechanisms of Osteogenesis Imperfecta. Bone. 2017;102:40–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Misof BM, Roschger P, Baldini T, Raggio CL, Zraick V, Root L, et al. Differential effects of alendronate treatment on bone from growing osteogenesis imperfecta and wild-type mouse. Bone. 2005;36(1):150–8.

    Article  CAS  PubMed  Google Scholar 

  178. Camacho NP, Landis WJ, Boskey AL. Mineral changes in a mouse model of osteogenesis imperfecta detected by Fourier transform infrared microscopy. Connect Tissue Res. 1996;35(1–4):259–65.

    Article  CAS  PubMed  Google Scholar 

  179. Kurtz D, Morrish K, Shapiro J. Vertebral bone mineral content in osteogenesis imperfecta. Calcif Tissue Int. 1985;37(1):14–8.

    Article  CAS  PubMed  Google Scholar 

  180. Lund AM, Molgaard C, Muller J, Skovby F. Bone mineral content and collagen defects in osteogenesis imperfecta. Acta Paediatr. 1999;88(10):1083–8.

    Article  CAS  PubMed  Google Scholar 

  181. Diez-Perez A, Güerri R, Nogues X, Cáceres E, Peña MJ, Mellibovsky L, et al. Microindentation for in vivo measurement of bone tissue mechanical properties in humans. J Bone Miner Res. 2010;25(8):1877–85.

    Article  PubMed  PubMed Central  Google Scholar 

  182. Allen MR, McNerny EM, Organ JM, Wallace JM. True gold or pyrite: a review of reference point indentation for assessing bone mechanical properties in vivo. J Bone Miner Res. 2015;30(9):1539–50.

    Article  PubMed  Google Scholar 

  183. Farr JN, Drake MT, Amin S, Melton LJ 3rd, McCready LK, Khosla S. In vivo assessment of bone quality in postmenopausal women with type 2 diabetes. J Bone Miner Res. 2014;29(4):787–95.

    Article  PubMed  Google Scholar 

  184. Malgo F, Hamdy NA, Papapoulos SE, Appelman-Dijkstra NM. Bone material strength as measured by microindentation in vivo is decreased in patients with fragility fractures independently of bone mineral density. J Clin Endocrinol Metab. 2015;100(5):2039–45.

    Article  CAS  PubMed  Google Scholar 

  185. Malgo F, Hamdy NAT, Papapoulos SE, Appelman-Dijkstra NM. Bone material strength index as measured by impact microindentation is low in patients with fractures irrespective of fracture site. Osteoporos Int. 2017;28(8):2433–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. Rozental TD, Walley KC, Demissie S, Caksa S, Martinez-Betancourt A, Parker AM, et al. Bone material strength index as measured by impact microindentation in postmenopausal women with distal radius and hip fractures. J Bone Miner Res. 2018;33(4):621–6.

    Article  PubMed  Google Scholar 

  187. Sosa DD, Eriksen EF. Reduced bone material strength is associated with increased risk and severity of osteoporotic fractures. An impact microindentation study. Calcif Tissue Int. 2017;101(1):34–42.

    Article  CAS  PubMed  Google Scholar 

  188. Rudäng R, Zoulakis M, Sundh D, Brisby H, Diez-Perez A, Johansson L, et al. Bone material strength is associated with areal BMD but not with prevalent fractures in older women. Osteoporos Int. 2016;27(4):1585–92.

    Article  PubMed  Google Scholar 

  189. Popp KL, Caksa S, Martinez-Betancourt A, Yuan A, Tsai J, Yu EW, et al. Cortical bone material strength index and bone microarchitecture in postmenopausal women with atypical femoral fractures. J Bone Miner Res. 2019;34(1):75–82.

    Article  CAS  PubMed  Google Scholar 

  190. Guerri-Fernandez RC, Nogues X, Quesada Gomez JM, Torres Del Pliego E, Puig L, Garcia-Giralt N, et al. Microindentation for in vivo measurement of bone tissue material properties in atypical femoral fracture patients and controls. J Bone Miner Res. 2013;28(1):162–8.

    Article  CAS  PubMed  Google Scholar 

  191. Jenkins T, Coutts LV, D’Angelo S, Dunlop DG, Oreffo RO, Cooper C, et al. Site-dependent reference point microindentation complements clinical measures for improved fracture risk assessment at the human femoral neck. J Bone Miner Res. 2016;31(1):196–203.

    Article  PubMed  Google Scholar 

  192. Jenkins T, Katsamenis OL, Andriotis OG, Coutts LV, Carter B, Dunlop DG, et al. The inferomedial femoral neck is compromised by age but not disease: fracture toughness and the multifactorial mechanisms comprising reference point microindentation. J Mech Behav Biomed Mater. 2017;75:399–412.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  193. Milovanovic P, Rakocevic Z, Djonic D, Zivkovic V, Hahn M, Nikolic S, et al. Nano-structural, compositional and micro-architectural signs of cortical bone fragility at the superolateral femoral neck in elderly hip fracture patients vs. healthy aged controls. Exp Gerontol. 2014;55:19–28.

    Article  PubMed  Google Scholar 

  194. Karim L, Van Vliet M, Bouxsein ML. Comparison of cyclic and impact-based reference point indentation measurements in human cadaveric tibia. Bone. 2018;106:90–5.

    Article  PubMed  Google Scholar 

  195. Granke M, Coulmier A, Uppuganti S, Gaddy JA, Does MD, Nyman JS. Insights into reference point indentation involving human cortical bone: sensitivity to tissue anisotropy and mechanical behavior. J Mech Behav Biomed Mater. 2014;37:174–85.

    Article  PubMed  PubMed Central  Google Scholar 

  196. Idkaidek A, Jasiuk I. Modeling of Osteoprobe indentation on bone. J Mech Behav Biomed Mater. 2019;90:365–73.

    Article  PubMed  Google Scholar 

  197. Abraham AC, Agarwalla A, Yadavalli A, Liu JY, Tang SY. Microstructural and compositional contributions towards the mechanical behavior of aging human bone measured by cyclic and impact reference point indentation. Bone. 2016;87:37–43.

    Article  PubMed  PubMed Central  Google Scholar 

  198. Krege JB, Aref MW, McNerny E, Wallace JM, Organ JM, Allen MR. Reference point indentation is insufficient for detecting alterations in traditional mechanical properties of bone under common experimental conditions. Bone. 2016;87:97–101.

    Article  PubMed  PubMed Central  Google Scholar 

  199. McAndrew CM, Agarwalla A, Abraham AC, Feuchtbaum E, Ricci WM, Tang SY. Local bone quality measurements correlates with maximum screw torque at the femoral diaphysis. Clin Biomech (Bristol, Avon). 2018;52:95–9.

    Article  Google Scholar 

  200. Beck TJ, Ruff CB, Warden KE, Scott WWJ, Rao GU. Predicting femoral neck strength from bone mineral data. A structural approach. Investig Radiol. 1990;25:6–18.

    Article  CAS  Google Scholar 

  201. Myers ER, Hecker AT, Rooks DS, Hipp JA, Hayes WC. Geometric variables from DXA of the radius predict forearm fracture load in vitro. Calcif Tissue Int. 1993;52(3):199–204.

    Article  CAS  PubMed  Google Scholar 

  202. Yoshikawa T, Turner CH, Peacock M, Slemenda CW, Weaver CM, Teegarden D, et al. Geometric structure of the femoral neck measured using dual-energy x-ray absorptiometry [published erratum appears in J Bone Miner Res 1995 Mar;10(3):510]. J Bone Miner Res. 1994;9(7):1053–64.

    Article  CAS  PubMed  Google Scholar 

  203. Beck TJ, Oreskovic TL, Stone KL, Ruff CB, Ensrud K, Nevitt MC, et al. Structural adaptation to changing skeletal load in the progression toward hip fragility: the study of osteoporotic fractures. J Bone Miner Res. 2001;16(6):1108–19.

    Article  CAS  PubMed  Google Scholar 

  204. Beck TJ, Ruff CB, Scott WW Jr, Plato CC, Tobin JD, Quan CA. Sex differences in geometry of the femoral neck with aging: a structural analysis of bone mineral data. Calcif Tissue Int. 1992;50:24–9.

    Article  CAS  PubMed  Google Scholar 

  205. Moro M, van der Meulen MCH, Kiratli BJ, Marcus R, Bachrach LK, Carter DR. Body mass is the primary determinant of midfemoral bone acquisition during adolescent growth. Bone. 1996;19(5):519–26.

    Article  CAS  PubMed  Google Scholar 

  206. Baker AM, Wagner DW, Kiratli BJ, Beaupre GS. Pixel-based DXA-derived structural properties strongly correlate with pQCT measures at the one-third distal femur site. Ann Biomed Eng. 2017;45(5):1247–54.

    Article  PubMed  Google Scholar 

  207. Villa-Camacho JC, Iyoha-Bello O, Behrouzi S, Snyder BD, Nazarian A. Computed tomography-based rigidity analysis: a review of the approach in preclinical and clinical studies. Bonekey Rep. 2014;3:587.

    Article  PubMed  PubMed Central  Google Scholar 

  208. Hong J, Cabe GD, Tedrow JR, Hipp JA, Snyder BD. Failure of trabecular bone with simulated lytic defects can be predicted non-invasively by structural analysis. J Orthop Res. 2004;22(3):479–86.

    Article  PubMed  Google Scholar 

  209. Whealan KM, Kwak SD, Tedrow JR, Inoue K, Snyder BD. Noninvasive imaging predicts failure load of the spine with simulated osteolytic defects. J Bone Joint Surg Am. 2000;82(9):1240–51.

    Article  CAS  PubMed  Google Scholar 

  210. Windhagen HJ, Hipp JA, Silva MJ, Lipson SJ, Hayes WC. Predicting failure of thoracic vertebrae with simulated and actual metastatic defects. Clin Orthop Relat Res. 1997;344:313–9.

    Article  Google Scholar 

  211. Morgan EF, Keaveny TM. Dependence of yield strain of human trabecular bone on anatomic site. J Biomech. 2001;34(5):569–77.

    Article  CAS  PubMed  Google Scholar 

  212. Snyder BD, Hauser-Kara DA, Hipp JA, Zurakowski D, Hecht AC, Gebhardt MC. Predicting fracture through benign skeletal lesions with quantitative computed tomography. J Bone Joint Surg Am. 2006;88(1):55–70.

    PubMed  Google Scholar 

  213. Buckley JM, Loo K, Motherway J. Comparison of quantitative computed tomography-based measures in predicting vertebral compressive strength. Bone. 2007;40(3):767–74.

    Article  PubMed  Google Scholar 

  214. Buckley JM, Cheng L, Loo K, Slyfield C, Xu Z. Quantitative computed tomography-based predictions of vertebral strength in anterior bending. Spine. 2007;32(9):1019–27.

    Article  PubMed  Google Scholar 

  215. Bouxsein ML, Melton LJ 3rd, Riggs BL, Muller J, Atkinson EJ, Oberg AL, et al. Age- and sex-specific differences in the factor of risk for vertebral fracture: a population-based study using QCT. J Bone Miner Res. 2006;21(9):1475–82.

    Article  PubMed  Google Scholar 

  216. Riggs BL, Melton LJ 3rd, Robb RA, Camp JJ, Atkinson EJ, Oberg AL, et al. Population-based analysis of the relationship of whole bone strength indices and fall-related loads to age- and sex-specific patterns of hip and wrist fractures. J Bone Miner Res. 2006;21(2):315–23.

    Article  PubMed  Google Scholar 

  217. Snyder BD, Cordio MA, Nazarian A, Kwak SD, Chang DJ, Entezari V, et al. Noninvasive prediction of fracture risk in patients with metastatic cancer to the spine. Clin Cancer Res. 2009;15(24):7676–83.

    Article  CAS  PubMed  Google Scholar 

  218. Leong NL, Anderson ME, Gebhardt MC, Snyder BD. Computed tomography-based structural analysis for predicting fracture risk in children with benign skeletal neoplasms: comparison of specificity with that of plain radiographs. J Bone Joint Surg Am. 2010;92(9):1827–33.

    Article  PubMed  PubMed Central  Google Scholar 

  219. Keaveny TM, Donley DW, Hoffmann PF, Mitlak BH, Glass EV, San Martin JA. Effects of teriparatide and alendronate on vertebral strength as assessed by finite element modeling of QCT scans in women with osteoporosis. J Bone Miner Res. 2007;22(1):149–57.

    Article  CAS  PubMed  Google Scholar 

  220. Lian KC, Lang TF, Keyak JH, Modin GW, Rehman Q, Do L, et al. Differences in hip quantitative computed tomography (QCT) measurements of bone mineral density and bone strength between glucocorticoid-treated and glucocorticoid-naive postmenopausal women. Osteoporos Int. 2005;16(6):642–50.

    Article  CAS  PubMed  Google Scholar 

  221. Cody DD, Hou FJ, Divine GW, Fyhrie DP. Femoral structure and stiffness in patients with femoral neck fracture. J Orthop Res. 2000;18(3):443–8.

    Article  CAS  PubMed  Google Scholar 

  222. Crawford RP, Cann CE, Keaveny TM. Finite element models predict in vitro vertebral body compressive strength better than quantitative computed tomography. Bone. 2003;33(4):744–50.

    Article  PubMed  Google Scholar 

  223. Keyak JH, Kaneko TS, Tehranzadeh J, Skinner HB. Predicting proximal femoral strength using structural engineering models. Clin Orthop Relat Res. 2005;437:219–28.

    Article  Google Scholar 

  224. Bessho M, Ohnishi I, Matsuyama J, Matsumoto T, Imai K, Nakamura K. Prediction of strength and strain of the proximal femur by a CT-based finite element method. J Biomech. 2007;40(8):1745–53.

    Article  PubMed  Google Scholar 

  225. Cody DD, Gross GJ, Hou FJ, Spencer HJ, Goldstein SA, Fyhrie DP. Femoral strength is better predicted by finite element models than QCT and DXA. J Biomech. 1999;32(10):1013–20.

    Article  CAS  PubMed  Google Scholar 

  226. Dall’Ara E, Luisier B, Schmidt R, Kainberger F, Zysset P, Pahr D. A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro. Bone. 2013;52(1):27–38.

    Article  PubMed  Google Scholar 

  227. Dall’Ara E, Schmidt R, Pahr D, Varga P, Chevalier Y, Patsch J, et al. A nonlinear finite element model validation study based on a novel experimental technique for inducing anterior wedge-shape fractures in human vertebral bodies in vitro. J Biomech. 2010;43(12):2374–80.

    Article  PubMed  Google Scholar 

  228. Dragomir-Daescu D, Op Den Buijs J, McEligot S, Dai Y, Entwistle RC, Salas C, et al. Robust QCT/FEA models of proximal femur stiffness and fracture load during a sideways fall on the hip. Ann Biomed Eng. 2011;39(2):742–55.

    Article  PubMed  Google Scholar 

  229. Koivumaki JE, Thevenot J, Pulkkinen P, Kuhn V, Link TM, Eckstein F, et al. Ct-based finite element models can be used to estimate experimentally measured failure loads in the proximal femur. Bone. 2012;50(4):824–9.

    Article  PubMed  Google Scholar 

  230. Liebschner MA, Kopperdahl DL, Rosenberg WS, Keaveny TM. Finite element modeling of the human thoracolumbar spine. Spine (Phila Pa 1976). 2003;28(6):559–65.

    Google Scholar 

  231. Nishiyama KK, Gilchrist S, Guy P, Cripton P, Boyd SK. Proximal femur bone strength estimated by a computationally fast finite element analysis in a sideways fall configuration. J Biomech. 2013;46(7):1231–6.

    Article  PubMed  Google Scholar 

  232. Johannesdottir F, Thrall E, Muller J, Keaveny TM, Kopperdahl DL, Bouxsein ML. Comparison of non-invasive assessments of strength of the proximal femur. Bone. 2017;105:93–102.

    Article  PubMed  Google Scholar 

  233. Keyak JH, Sigurdsson S, Karlsdottir G, Oskarsdottir D, Sigmarsdottir A, Zhao S, et al. Male-female differences in the association between incident hip fracture and proximal femoral strength: a finite element analysis study. Bone. 2011;48(6):1239–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  234. Keyak JH, Sigurdsson S, Karlsdottir GS, Oskarsdottir D, Sigmarsdottir A, Kornak J, et al. Effect of finite element model loading condition on fracture risk assessment in men and women: the AGES-Reykjavik study. Bone. 2013;57(1):18–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  235. Lang TF, Sigurdsson S, Karlsdottir G, Oskarsdottir D, Sigmarsdottir A, Chengshi J, et al. Age-related loss of proximal femoral strength in elderly men and women: the Age Gene/Environment Susceptibility Study--Reykjavik. Bone. 2012;50(3):743–8.

    Article  CAS  PubMed  Google Scholar 

  236. Eberle S, Gottlinger M, Augat P. An investigation to determine if a single validated density-elasticity relationship can be used for subject specific finite element analyses of human long bones. Med Eng Phys. 2013;35(7):875–83.

    Article  PubMed  Google Scholar 

  237. Schileo E, Dall’ara E, Taddei F, Malandrino A, Schotkamp T, Baleani M, et al. An accurate estimation of bone density improves the accuracy of subject-specific finite element models. J Biomech. 2008;41(11):2483–91.

    Article  PubMed  Google Scholar 

  238. Eberle S, Gottlinger M, Augat P. Individual density-elasticity relationships improve accuracy of subject-specific finite element models of human femurs. J Biomech. 2013;46(13):2152–7.

    Article  PubMed  Google Scholar 

  239. Enns-Bray WS, Bahaloo H, Fleps I, Ariza O, Gilchrist S, Widmer R, et al. Material mapping strategy to improve the predicted response of the proximal femur to a sideways fall impact. J Mech Behav Biomed Mater. 2018;78:196–205.

    Article  CAS  PubMed  Google Scholar 

  240. Zysset PK, Dall’ara E, Varga P, Pahr DH. Finite element analysis for prediction of bone strength. Bonekey Rep. 2013;2:386.

    Article  PubMed  PubMed Central  Google Scholar 

  241. van Rietbergen B, Ito K. A survey of micro-finite element analysis for clinical assessment of bone strength: the first decade. J Biomech. 2015;48(5):832–41.

    Article  PubMed  Google Scholar 

  242. Boutroy S, Van Rietbergen B, Sornay-Rendu E, Munoz F, Bouxsein ML, Delmas PD. Finite element analysis based on in vivo HR-pQCT images of the distal radius is associated with wrist fracture in postmenopausal women. J Bone Miner Res. 2008;23(3):392–9.

    Article  PubMed  Google Scholar 

  243. Liu XS, Zhang XH, Sekhon KK, Adams MF, McMahon DJ, Bilezikian JP, et al. High-resolution peripheral quantitative computed tomography can assess microstructural and mechanical properties of human distal tibial bone. J Bone Miner Res. 2010;25(4):746–56.

    CAS  PubMed  Google Scholar 

  244. MacNeil JA, Boyd SK. Accuracy of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys. 2007;29(10):1096–105.

    Article  PubMed  Google Scholar 

  245. Varga P, Zysset PK. Assessment of volume fraction and fabric in the distal radius using HR-pQCT. Bone. 2009;45(5):909–17.

    Article  CAS  PubMed  Google Scholar 

  246. Macneil JA, Boyd SK. Bone strength at the distal radius can be estimated from high-resolution peripheral quantitative computed tomography and the finite element method. Bone. 2008;42(6):1203–13.

    Article  PubMed  Google Scholar 

  247. Mueller TL, Christen D, Sandercott S, Boyd SK, van Rietbergen B, Eckstein F, et al. Computational finite element bone mechanics accurately predicts mechanical competence in the human radius of an elderly population. Bone. 2011;48(6):1232–8.

    Article  PubMed  Google Scholar 

  248. Pistoia W, van Rietbergen B, Lochmuller EM, Lill CA, Eckstein F, Ruegsegger P. Image-based micro-finite-element modeling for improved distal radius strength diagnosis: moving from bench to bedside. J Clin Densitom. 2004;7(2):153–60.

    Article  CAS  PubMed  Google Scholar 

  249. Varga P, Pahr DH, Baumbach S, Zysset PK. HR-pQCT based FE analysis of the most distal radius section provides an improved prediction of Colles’ fracture load in vitro. Bone. 2010;47(5):982–8.

    Article  PubMed  Google Scholar 

  250. Zhou B, Wang J, Yu YE, Zhang Z, Nawathe S, Nishiyama KK, et al. High-resolution peripheral quantitative computed tomography (HR-pQCT) can assess microstructural and biomechanical properties of both human distal radius and tibia: ex vivo computational and experimental validations. Bone. 2016;86:58–67.

    Article  PubMed  Google Scholar 

  251. Vilayphiou N, Boutroy S, Sornay-Rendu E, Van Rietbergen B, Munoz F, Delmas PD, et al. Finite element analysis performed on radius and tibia HR-pQCT images and fragility fractures at all sites in postmenopausal women. Bone. 2010;46(4):1030–7.

    Article  PubMed  Google Scholar 

  252. Vilayphiou N, Boutroy S, Szulc P, van Rietbergen B, Munoz F, Delmas PD, et al. Finite element analysis performed on radius and tibia HR-pQCT images and fragility fractures at all sites in men. J Bone Miner Res. 2011;26(5):965–73.

    Article  PubMed  Google Scholar 

  253. Kroker A, Plett R, Nishiyama KK, McErlain DD, Sandino C, Boyd SK. Distal skeletal tibia assessed by HR-pQCT is highly correlated with femoral and lumbar vertebra failure loads. J Biomech. 2017;59:43–9.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jacqueline H. Cole .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Cole, J.H., van der Meulen, M.C.H. (2020). Biomechanics of Bone. In: Leder, B., Wein, M. (eds) Osteoporosis. Contemporary Endocrinology. Humana, Cham. https://doi.org/10.1007/978-3-319-69287-6_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-69287-6_10

  • Published:

  • Publisher Name: Humana, Cham

  • Print ISBN: 978-3-319-69286-9

  • Online ISBN: 978-3-319-69287-6

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics