Skip to main content

Advertisement

Log in

FEA to Measure Bone Strength: A Review

  • Assessment of bone health
  • Published:
Clinical Reviews in Bone and Mineral Metabolism Aims and scope Submit manuscript

Abstract

Finite element analysis (FEA) based on CT datasets of the spine or hip or on high-resolution peripheral CT datasets of the distal forearm or tibia is now widely used in research and clinical trials to estimate bone strength. Its clinical potential has recently been endorsed by the International Society of Clinical Densitometry Zysset et al. (J Clin Densitom 18(3):359–92, 2015). In vitro validation studies demonstrated the superiority of FEA over DXA for the prediction of ultimate load. In vivo studies confirmed the superiority in the spine, but data were less conclusive in the hip and forearm. Here, in addition to low bone strength the risk of falling is a major determinant of fracture risk. The next level of FEA dissemination, the integration into clinical practice, still faces a number of challenges such as access to dedicated FE software and its integration into the clinical workflow. Also compared to DXA, current FEA techniques have not shown a consistent superiority for hip fracture prediction, while hip CT is associated with a higher radiation exposure than hip DXA. For many clinicians, FEA and the direct measurement of strength instead of BMD are a novel perspective. However, the increasing use of abdominal and pelvic CT scans initially obtained for other clinical diagnosis, for the secondary use to assess osteoporosis and fracture risk (opportunistic screening), may accelerate the use of FEA. In this contribution, the basic technical aspects and limitation of FEA are discussed and the clinically relevant outcome measures are presented. Further advanced topics will broaden the understanding of the various aspects of FEA. Afterward a summary of in vivo studies using FEA for fracture prediction is given, which also includes a discussion of the clinical value of FEA for bone strength measurements.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Baum T, Kutscher M, Muller D, Rath C, Eckstein F, Lochmuller EM, Rummeny EJ, Link TM, Bauer JS. Cortical and trabecular bone structure analysis at the distal radius-prediction of biomechanical strength by DXA and MRI. J Bone Miner Metab. 2013;31(2):212–21.

    Article  CAS  PubMed  Google Scholar 

  2. Bjarnason K, Hassager C, Svendsen OL, Stang H, Christiansen C. Anteroposterior and lateral spinal DXA for the assessment of vertebral body strength: comparison with hip and forearm measurement. Osteoporos Int. 1996;6(1):37–42.

    Article  CAS  PubMed  Google Scholar 

  3. Hudelmaier M, Kuhn V, Lochmuller EM, Well H, Priemel M, Link TM, Eckstein F. Can geometry-based parameters from pQCT and material parameters from quantitative ultrasound (QUS) improve the prediction of radial bone strength over that by bone mass (DXA)? Osteoporos Int. 2004;15(5):375–81.

    Article  CAS  PubMed  Google Scholar 

  4. Imamoto K, Hamanaka Y, Yamamoto I, Niiho C. Correlation between the values of bone measurements using DXA, QCT and USD methods and the bone strength in calcanei in vitro. Kaibogaku Zasshi. 1998;73(5):509–15.

    CAS  PubMed  Google Scholar 

  5. Lochmuller EM, Muller R, Kuhn V, Lill CA, Eckstein F. Can novel clinical densitometric techniques replace or improve DXA in predicting bone strength in osteoporosis at the hip and other skeletal sites? J Bone Miner Res. 2003;18(5):906–12.

    Article  PubMed  Google Scholar 

  6. Taton G, Rokita E, Wrobel A, Korkosz M. Combining areal DXA bone mineral density and vertebrae postero-anterior width improves the prediction of vertebral strength. Skeletal Radiol. 2013;42(12):1717–25.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Lochmuller EM, Lill CA, Kuhn V, Schneider E, Eckstein F. Radius bone strength in bending, compression, and falling and its correlation with clinical densitometry at multiple sites. J Bone Miner Res. 2002;17(9):1629–38.

    Article  PubMed  Google Scholar 

  8. Muller ME, Webber CE, Bouxsein ML. Predicting the failure load of the distal radius. Osteoporos Int. 2003;14(4):345–52.

    Article  PubMed  Google Scholar 

  9. Wu C, Hans D, He Y, Fan B, Njeh CF, Augat P, Richards J, Genant HK. Prediction of bone strength of distal forearm using radius bone mineral density and phalangeal speed of sound. Bone. 2000;26(5):529–33.

    Article  CAS  PubMed  Google Scholar 

  10. Johansson H, Kanis JA, Oden A, Johnell O, McCloskey E. BMD, clinical risk factors and their combination for hip fracture prevention. Osteoporos Int. 2009;20(10):1675–82.

    Article  CAS  PubMed  Google Scholar 

  11. Stewart A, Calder LD, Torgerson DJ, Seymour DG, Ritchie LD, Iglesias CP, Reid DM. Prevalence of hip fracture risk factors in women aged 70 years and over. QJM. 2000;93(10):677–80.

    Article  CAS  PubMed  Google Scholar 

  12. Black DM, Cummings SR, Karpf DB, Cauley JA, Thompson DE, Nevitt MC, Bauer DC, Genant HK, Haskell WL, Marcus R, Ott SM, Torner JC, Quandt SA, Reiss TF, Ensrud KE. Randomised trial of effect of alendronate on risk of fracture in women with existing vertebral fractures. Fracture intervention trial research group. Lancet. 1996;348(9041):1535–41.

    Article  CAS  PubMed  Google Scholar 

  13. Cummings SR, Black DM, Thompson DE, Applegate WB, Barrett-Connor E, Musliner TA, Palermo L, Prineas R, Rubin SM, Scott JC, Vogt T, Wallace R, Yates AJ, LaCroix AZ. Effect of alendronate on risk of fracture in women with low bone density but without vertebral fractures: results from the fracture intervention trial. JAMA. 1998;280(24):2077–82.

    Article  CAS  PubMed  Google Scholar 

  14. Harris ST, Watts NB, Genant HK, McKeever CD, Hangartner T, Keller M, Chesnut CH 3rd, Brown J, Eriksen EF, Hoseyni MS, Axelrod DW, Miller PD. Effects of risedronate treatment on vertebral and nonvertebral fractures in women with postmenopausal osteoporosis: a randomized controlled trial. Vertebral efficacy with risedronate therapy (VERT) study group. JAMA. 1999;282(14):1344–52.

    Article  CAS  PubMed  Google Scholar 

  15. McClung MR, Geusens P, Miller PD, Zippel H, Bensen WG, Roux C, Adami S, Fogelman I, Diamond T, Eastell R, Meunier PJ, Reginster JY, Hip G. Intervention program study, effect of risedronate on the risk of hip fracture in elderly women. Hip Intervention Program Study Group. N Engl J Med. 2001;344(5):333–40.

    Article  CAS  PubMed  Google Scholar 

  16. Zysset P, Qin L, Lang T, Khosla S, Leslie WD, Shepherd JA, Schousboe JT, Engelke K. Clinical use of quantitative computed tomography-based finite element analysis of the hip and spine in the management of osteoporosis in adults: the 2015 ISCD official positions-Part II. J Clin Densitom. 2015;18(3):359–92.

    Article  PubMed  Google Scholar 

  17. 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 

  18. Engelke K, Libanati C, Fuerst T, Zysset P, Genant HK. Advanced CT based in vivo methods for the assessment of bone density, structure, and strength. Curr Osteoporos Rep. 2013;11(3):246–55.

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed Central  PubMed  Google Scholar 

  20. Kopperdahl DL, Aspelund T, Hoffmann PF, Sigurdsson S, Siggeirsdottir K, Harris TB, Gudnason V, Keaveny TM. 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 Central  PubMed  Google Scholar 

  21. Keaveny TM, Wachtel EF, Guo XE, Hayes WC. Mechanical behavior of damaged trabecular bone. J Biomech. 1994;27(11):1309–18.

    Article  CAS  PubMed  Google Scholar 

  22. Zysset PK, Curnier A. A 3D damage model for trabecular bone based on fabric tensors. J Biomech. 1996;29(12):1549–58.

    Article  CAS  PubMed  Google Scholar 

  23. Schwiedrzik JJ, Zysset PK. The influence of yield surface shape and damage in the depth-dependent response of bone tissue to nanoindentation using spherical and Berkovich indenters. Comput Methods Biomech Biomed Eng. 2015;18(5):492–505.

    Article  Google Scholar 

  24. Martin RB, Ishida J. The relative effects of collagen fiber orientation, porosity, density, and mineralization on bone strength. J Biomech. 1989;22(5):419–26.

    Article  CAS  PubMed  Google Scholar 

  25. Maquer G, Musy SN, Wandel J, Gross T, Zysset PK. Bone volume fraction and fabric anisotropy are better determinants of trabecular bone stiffness than other morphological variables. J Bone Miner Res. 2015;30(6):1000–8.

    Article  PubMed  Google Scholar 

  26. Gross T, Pahr DH, Peyrin F, Zysset PK. Mineral heterogeneity has a minor influence on the apparent elastic properties of human cancellous bone: a SRmuCT-based finite element study. Comput Methods Biomech Biomed Eng. 2012;15(11):1137–44.

    Article  Google Scholar 

  27. Roschger P, Gupta HS, Berzlanovich A, Ittner G, Dempster DW, Fratzl P, Cosman F, Parisien M, Lindsay R, Nieves JW, Klaushofer K. Constant mineralization density distribution in cancellous human bone. Bone. 2003;32(3):316–23.

    Article  CAS  PubMed  Google Scholar 

  28. Laib A, Hildebrand T, Hauselmann HJ, Ruegsegger P. Ridge number density: a new parameter for in vivo bone structure analysis. Bone. 1997;21(6):541–6.

    Article  CAS  PubMed  Google Scholar 

  29. 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 

  30. Chevalier Y, Pahr D, Zysset PK. The role of cortical shell and trabecular fabric in finite element analysis of the human vertebral body. J Biomech Eng. 2009;131(11):111003.

    Article  PubMed  Google Scholar 

  31. Marangalou JH, Ito K, Cataldi M, Taddei F, van Rietbergen B. A novel approach to estimate trabecular bone anisotropy using a database approach. J Biomech. 2013;46(14):2356–62.

    Article  Google Scholar 

  32. Marangalou JH, Ito K, van Rietbergen B. A novel approach to estimate trabecular bone anisotropy from stress tensors. Biomech Model Mechanobiol. 2015;14(1):39–48.

    Article  Google Scholar 

  33. Lekadir K, Hazrati-Marangalou J, Hoogendoorn C, Taylor Z, van Rietbergen B, Frangi AF. Statistical estimation of femur micro-architecture using optimal shape and density predictors. J Biomech. 2015;48(4):598–603.

    Article  PubMed  Google Scholar 

  34. Marangalou JH, Eckstein F, Kuhn V, Ito K, Cataldi M, Taddei F, van Rietbergen B. Locally measured microstructural parameters are better associated with vertebral strength than whole bone density. Osteoporos Int. 2014;25(4):1285–96.

    Article  Google Scholar 

  35. Pahr DH, Zysset PK. From high-resolution CT data to finite element models: development of an integrated modular framework. Comput Methods Biomech Biomed Eng. 2009;12(1):45–57.

    Article  Google Scholar 

  36. Viceconti M, Bellingeri L, Cristofolini L, Toni A. A comparative study on different methods of automatic mesh generation of human femurs. Med Eng Phys. 1998;20(1):1–10.

    Article  CAS  PubMed  Google Scholar 

  37. Keyak JH, Fourkas MG, Meagher JM, Skinner HB. Validation of an automated method of three-dimensional finite element modelling of bone. J Biomed Eng. 1993;15(6):505–9.

    Article  CAS  PubMed  Google Scholar 

  38. Pistoia W, van Rietbergen B, Lochmuller EM, Lill CA, Eckstein F, Ruegsegger P. Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images. Bone. 2002;30(6):842–8.

    Article  CAS  PubMed  Google Scholar 

  39. Keaveny TM. Biomechanical computed tomography-noninvasive bone strength analysis using clinical computed tomography scans. Ann N Y Acad Sci. 2010;1192:57–65.

    Article  PubMed  Google Scholar 

  40. Nawathe S, Juillard F, Keaveny TM. Theoretical bounds for the influence of tissue-level ductility on the apparent-level strength of human trabecular bone. J Biomech. 2013;46(7):1293–9.

    Article  PubMed Central  PubMed  Google Scholar 

  41. Keyak JH, Rossi SA. Prediction of femoral fracture load using finite element models: an examination of stress- and strain-based failure theories. J Biomech. 2000;33(2):209–14.

    Article  CAS  PubMed  Google Scholar 

  42. Kelly N, Harrison NM, McDonnell P, McGarry JP. An experimental and computational investigation of the post-yield behaviour of trabecular bone during vertebral device subsidence. Biomech Model Mechanobiol. 2013;12(4):685–703.

    Article  PubMed  Google Scholar 

  43. Rincon-Kohli L, Zysset PK. Multi-axial mechanical properties of human trabecular bone. Biomech Model Mechanobiol. 2009;8(3):195–208.

    Article  PubMed  Google Scholar 

  44. Bousson VD, Adams J, Engelke K, Aout M, Cohen-Solal M, Bergot C, Haguenauer D, Goldberg D, Champion K, Aksouh R, Vicaut E, Laredo JD. In vivo discrimination of hip fracture with quantitative computed tomography: results from the prospective European Femur Fracture Study (EFFECT). J Bone Miner Res. 2011;26(4):881–93.

    Article  PubMed  Google Scholar 

  45. 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 

  46. 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 

  47. 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 

  48. Mueller TL, Christen D, Sandercott S, Boyd SK, van Rietbergen B, Eckstein F, Lochmuller EM, Muller R, van Lenthe GH. 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 

  49. Engelke K, Mastmeyer A, Bousson V, Fuerst T, Laredo JD, Kalender WA. Reanalysis precision of 3D quantitative computed tomography (QCT) of the spine. Bone. 2009;44(4):566–72.

    Article  PubMed  Google Scholar 

  50. Lang TF, Li J, Harris ST, Genant HK. Assessment of vertebral bone mineral density using volumetric quantitative CT. J Comput Assist Tomogr. 1999;23(1):130–7.

    Article  CAS  PubMed  Google Scholar 

  51. Li W, Sode M, Saeed I, Lang T. Automated registration of hip and spine for longitudinal QCT studies: integration with 3D densitometric and structural analysis. Bone. 2006;38(2):273–9.

    Article  PubMed Central  PubMed  Google Scholar 

  52. Museyko O, Bousson V, Adams J, Laredo J, Engelke K. QCT of the proximal femur-which parameters should be measured to discriminate hip fracture? Osteoporos Int. 2015. doi:10.1007/s00198-015-3324-6.

    PubMed  Google Scholar 

  53. Yang L, Burton AC, Bradburn M, Nielson CM, Orwoll ES, Eastell R, Osteoporotic G. Fractures in men study, 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 Central  PubMed  Google Scholar 

  54. Carpenter RD, Saeed I, Bonaretti S, Schreck C, Keyak JH, Streeper T, Harris TB, Lang TF. Inter-scanner differences in in vivo QCT measurements of the density and strength of the proximal femur remain after correction with anthropomorphic standardization phantoms. Med Eng Phys. 2014;36(10):1225–32.

    Article  PubMed Central  PubMed  Google Scholar 

  55. Burghardt AJ, Pialat JB, Kazakia GJ, Boutroy S, Engelke K, Patsch JM, Valentinitsch A, Liu D, Szabo E, Bogado CE, Zanchetta MB, McKay HA, Shane E, Boyd SK, Bouxsein ML, Chapurlat R, Khosla S, Majumdar S. 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 Central  PubMed  Google Scholar 

  56. Engelke K, Stampa B, Timm W, Dardzinski B, de Papp AE, Genant HK, Fuerst T. Short-term in vivo precision of BMD and parameters of trabecular architecture at the distal forearm and tibia. Osteoporos Int. 2012;23(8):2151–8.

    Article  CAS  PubMed  Google Scholar 

  57. Cody DD, Hou FJ, Divine GW, Fyhrie DP. Short term in vivo precision of proximal femoral finite element modeling. Ann Biomed Eng. 2000;28(4):408–14.

    Article  CAS  PubMed  Google Scholar 

  58. Ellouz R, Chapurlat R, van Rietbergen B, Christen P, Pialat JB, Boutroy S. Challenges in longitudinal measurements with HR-pQCT: evaluation of a 3D registration method to improve bone microarchitecture and strength measurement reproducibility. Bone. 2014;63:147–57.

    Article  PubMed  Google Scholar 

  59. Paggiosi MA, Eastell R, Walsh JS. Precision of high-resolution peripheral quantitative computed tomography measurement variables: influence of gender, examination site, and age. Calcif Tissue Int. 2014;94(2):191–201.

    Article  CAS  PubMed  Google Scholar 

  60. MacNeil JA, Boyd SK. Improved reproducibility of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys. 2008;30(6):792–9.

    Article  PubMed  Google Scholar 

  61. Wang X, Sanyal A, Cawthon PM, Palermo L, Jekir M, Christensen J, Ensrud KE, Cummings SR, Orwoll E, Black DM, Osteoporotic Fractures in Men Research, Keaveny TM. 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 Central  PubMed  Google Scholar 

  62. Graeff C, Marin F, Petto H, Kayser O, Reisinger A, Pena J, Zysset P, Gluer CC. High resolution quantitative computed tomography-based assessment of trabecular microstructure and strength estimates by finite-element analysis of the spine, but not DXA, reflects vertebral fracture status in men with glucocorticoid-induced osteoporosis. Bone. 2013;52(2):568–77.

    Article  CAS  PubMed  Google Scholar 

  63. Imai K, Ohnishi I, Matsumoto T, Yamamoto S, Nakamura K. Assessment of vertebral fracture risk and therapeutic effects of alendronate in postmenopausal women using a quantitative computed tomography-based nonlinear finite element method. Osteoporos Int. 2009;20(5):801–10.

    Article  CAS  PubMed  Google Scholar 

  64. Orwoll ES, Marshall LM, Nielson CM, Cummings SR, Lapidus J, Cauley JA, Ensrud K, Lane N, Hoffmann PR, Kopperdahl DL, Keaveny TM, Osteoporotic G. Fractures in Men Study, 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 Central  PubMed  Google Scholar 

  65. Amin S, Kopperdhal DL, Melton LJ 3rd, Achenbach SJ, Therneau TM, Riggs BL, Keaveny TM, Khosla S. Association of hip strength estimates by finite-element analysis with fractures in women and men. J Bone Miner Res. 2011;26(7):1593–600.

    Article  PubMed Central  PubMed  Google Scholar 

  66. Nishiyama KK, Ito M, Harada A, Boyd SK. Classification of women with and without hip fracture based on quantitative computed tomography and finite element analysis. Osteoporos Int. 2014;25(2):619–26.

    Article  CAS  PubMed  Google Scholar 

  67. Johannesdottir F, Poole KE, Reeve J, Siggeirsdottir K, Aspelund T, Mogensen B, Jonsson BY, Sigurdsson S, Harris TB, Gudnason VG, Sigurdsson G. 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 Central  PubMed  Google Scholar 

  68. Engelke K, Lang T, Khosla S, Qin L, Zysset P, Leslie WD, Shepherd JA, Shousboe JT. Clinical use of quantitative computed tomography-based advanced techniques in the management of osteoporosis in adults: the 2015 ISCD official positions-part III. J Clin Densitom. 2015;18(3):393–407.

    Article  PubMed  Google Scholar 

  69. Majumdar SR, Leslie WD. Conventional computed tomography imaging and bone mineral density: opportunistic screening or “incidentaloporosis”? Ann Intern Med. 2013;158(8):630–1.

    Article  PubMed  Google Scholar 

  70. Pickhardt PJ, Bodeen G, Brett A, Brown JK, Binkley N. Comparison of femoral neck BMD evaluation obtained using lunar DXA and QCT with asynchronous calibration from CT colonography. J Clin Densitom. 2015;18(1):5–12.

    Article  PubMed  Google Scholar 

  71. Buckens CF, Dijkhuis G, de Keizer B, Verhaar HJ, de Jong PA. Opportunistic screening for osteoporosis on routine computed tomography? An external validation study. Eur Radiol. 2015;25(7):2074–9.

    Article  PubMed  Google Scholar 

  72. 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 

  73. Christen D, Melton LJ 3rd, Zwahlen A, Amin S, Khosla S, Muller R. Improved fracture risk assessment based on nonlinear micro-finite element simulations from HRpQCT images at the distal radius. J Bone Miner Res. 2013;28(12):2601–8.

    Article  PubMed  Google Scholar 

  74. Melton LJ 3rd, Christen D, Riggs BL, Achenbach SJ, Muller R, van Lenthe GH, Amin S, Atkinson EJ, Khosla S. Assessing forearm fracture risk in postmenopausal women. Osteoporos Int. 2010;21(7):1161–9.

    Article  PubMed Central  PubMed  Google Scholar 

  75. Nishiyama KK, Macdonald HM, Hanley DA, Boyd SK. Women with previous fragility fractures can be classified based on bone microarchitecture and finite element analysis measured with HR-pQCT. Osteoporos Int. 2013;24(5):1733–40.

    Article  CAS  PubMed  Google Scholar 

  76. Vilayphiou N, Boutroy S, Sornay-Rendu E, Van Rietbergen B, Munoz F, Delmas PD, Chapurlat R. 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 

  77. 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 

  78. Pahr DH, Schwiedrzik J, Dall’Ara E, Zysset PK. Clinical versus pre-clinical FE models for vertebral body strength predictions. J Mech Behav Biomed Mater. 2014;33:76–83.

    Article  PubMed  Google Scholar 

  79. Zysset P, Pahr D, Engelke K, Genant HK, McClung MR, Kendler DL, Recknor C, Kinzl M, Schwiedrzik J, Museyko O, Wang A, Libanati C. Comparison of proximal femur and vertebral body strength improvements in the FREEDOM trial using an alternative finite element methodology. Bone. 2015;81:122–30.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Klaus Engelke.

Ethics declarations

Conflict of interest

Bert van Rietbergen is a consultant for Scanco Medical AG. Klaus Engelke is a part time employee of BioClinica, Inc. Philippe Zysset has no conflict of interest.

Human and Animal Rights

This is a review article. Studies with human or animal subjects were not specifically performed for the purpose of this article by any of the author.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Engelke, K., van Rietbergen, B. & Zysset, P. FEA to Measure Bone Strength: A Review. Clinic Rev Bone Miner Metab 14, 26–37 (2016). https://doi.org/10.1007/s12018-015-9201-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12018-015-9201-1

Keywords

Navigation