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Osteologie 2013; 22(01): 07-12
DOI: 10.1055/s-0038-1630103
Hochauflösende Methoden in der Osteologie
Schattauer GmbH

FE-Simulation in der klinischen Osteoporoseforschung[*]

Möglichkeiten und TrendsFinite element simulations in clinical osteoporosis research
D. H. Pahr
1   Institut für Leichtbau und Struktur-Biomechanik, Technische Universität Wien, Österreich
,
P. K. Zysset
2   Institute for Surgical Technology and Biomechanics, Universität Bern, Schweiz
› Author Affiliations
Further Information

Publication History

eingereicht: 19 October 2012

angenommen: 27 October 2012

Publication Date:
29 January 2018 (online)

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Zusammenfassung

Altersbedingte Osteoporose erhöht des Frakturrisiko. Übliche Diagnoseverfahren basieren auf DXA. Leider sind diese ungenau und erklären oft nicht die Effekte von Behandlungen. Eine neue Methode zur Bestimmung der Knochenfestigkeit beginnt derzeit, sich zu etablieren – die Finite-Elemente-Methode (FEM). Diese universelle, im Bereich der Technik weit verbreitete, Methode erlaubt es, die Diagnose und den Behandlungserfolg besser vorauszusagen als DXA. CT-basierende FEModelle sind stark von der Bildauflösung abhängig. In diesem Überblicksartikel werden drei unterschiedliche Modelltypen (μCT, HRpQCT, QCT) vorgestellt und die Ergebnisse von densitometrischen und FE-Analysen verglichen. Dabei waren die FE-Ergebnisse den densitometrischen immer überlegen. Darüber hinaus erlaubt die FEM die Angabe eines biomechanischen Frakturrisikos. Dieser Vorteil der FE-Methode muss jedoch im Licht der höheren Röntgendosen und Betriebskosten der CT-Bildgebung betrachtet werden. Zukünftig wird die FE-Methode klinisch eine weite Verbreitung finden – die Frage ist nur wann und wie!

Summary

Osteoporosis leads to higher bone fracture risk and is diagnosed by DXA. Unfortunately, DXA is not a perfect surrogate of bone strength and can often not explain the effect of pharmacological treatment. Currently a new methodology to determine bone strength becomes established: the Finite element method (FEM). This universal, widely accepted engineering method allows to diagnose bone fragility and the effect of treatment better than DXA and QCT. The CT-based FE models depend highly on image resolution. In this review, three types of models are presented (μCT, HR-pQCT, QCT) and the results of densitometric and FEM results are compared. In these cases, the FE results were always superior to densitometric ones. In addition, FE allows to determine a biomechanical fracture risk. Nevertheless, this advantage of FEM needs to be considered in the light of higher x-ray dose and service costs associated with CT imaging. In the future, FEM will be widely applied in the clinics, the question is only when and how!

Keywords

Osteoporosis - Finite element method - bone strength

Schlüsselwörter

Osteoporose - Finite-Elemente-Methode - Knochenfestigkeit

* Beide Autoren waren an der Zusammenstellung dieses Manuskripts beteiligt.


 

  • Literatur

  • 1 Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int 2006; 17 (12) 1726-1733.
    CrossrefPubMedGoogle Scholar
  • 2 European Prospective Osteoporosis Study (EPOS) Group. Felsenberg D, Silman AJ, Lunt M. et al. Incidence of vertebral fracture in europe: results from the european prospective osteoporosis study (epos). J Bone Miner Res 2002; 17 (4) 716-724.
    CrossrefPubMedGoogle Scholar
  • 3 Schuit SCE, van der Klift M, Weel AEAM. et al. Fracture incidence and association with bone mineral density in elderly men and women: the rotterdam study. Bone 2004; 34 (1) 195-202.
    CrossrefPubMedGoogle Scholar
  • 4 Delmas PD, Seeman E. Changes in bone mineral density explain little of the reduction in vertebral or nonvertebral fracture risk with anti-resorptive therapy. Bone 2004; 34 (4) 599-604.
    CrossrefPubMedGoogle Scholar
  • 5 Bouxsein ML. Bone quality: an old concept revisited. Osteoporosis International 2003; 14 (Suppl 5) S1-S2.
    CrossrefPubMedGoogle Scholar
  • 6 Faulkner KG, Cann CE, Hasegawa BH. Effect of bone distribution on vertebral strength: assessment with patient-specic nonlinear finite element analysis. Radiology 1991; 179 (3) 669-674.
    CrossrefPubMedGoogle Scholar
  • 7 Lotz JC, Cheal EJ, Hayes WC. Fracture prediction for the proximal femur using finite element models: Part ii{nonlinear analysis. J Biomech Eng 1991; 113 (4) 361-365.
    CrossrefPubMedGoogle Scholar
  • 8 Crawford RP, Cann CE, Teaveny TM. Finite element models predict in vitro vertebral body compressive strength better than quantitative computed tomography. Bone 2003; 33 (4) 744-750.
    CrossrefPubMedGoogle Scholar
  • 9 Cody DD, Gross GJ, Hou FJ. et al. Femoral strength is better predicted by finite element models than qct and dxa. Journal of Biomechanics 1999; 32 (10) 1013-1020.
    CrossrefPubMedGoogle Scholar
  • 10 Pistoia W, van Rietbergen B, Lochmuller EM. et al. Image-based micro-finite-element modeling for improved distal radius strength diagnosis: moving from bench to bedside. J Clin Densitom 2004; 7 (2) 153-160.
    CrossrefPubMedGoogle Scholar
  • 11 Keaveny TM, Donley DW, Homann PF. et al. 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: 149-157.
    PubMedGoogle Scholar
  • 12 Grae C, Chevalier Y, Charlebois M. et al. Improvements in vertebral body strength under teriparatide treatment assessed in vivo by finite element analysis: results from the eurofors study. J Bone Miner Res 2009; 24 (10) 1672-1680.
    CrossrefPubMedGoogle Scholar
  • 13 Jones AC, Wilcox RK. Finite element analysis of the spine: towards a framework of verication, validation and sensitivity analysis. Med Eng Phys 2008; 30 (10) 1287-1304.
    CrossrefPubMedGoogle Scholar
  • 14 Anderson AE, Ellis BJ, Weiss JA. Verication, validation and sensitivity studies in computational biomechanics. Comput Methods Biomech Biomed Engin 2007; 10 (3) 171-184.
    PubMedGoogle Scholar
  • 15 Hayes WC, Piazza SJ, Zysset PK. Biomechanics of fracture risk prediction of the hip and spine by quantitative computed tomography. Radiologic Clinics in North America 1991; 29 (1) 1-18.
    Google Scholar
  • 16 Bouxsein ML. Determinants of skeletal fragility. Best Pract Res Clin Rheumatol 2005; 19 (6) 897-911.
    CrossrefPubMedGoogle Scholar
  • 17 Chevalier Y, Pahr D, Allmer H. et al. Validation of a voxel-based FE method for prediction of the uniaxial apparent modulus of human trabecular bone using macroscopic mechanical tests and nanoindentation. Journal of Biomechanics 2007; 40 (15) 3333-3340.
    CrossrefPubMedGoogle Scholar
  • 18 Varga P, Dall'Ara E, Pahr DH. et al. Validation of an hr-pqct-based homogenized finite element approach using mechanical testing of ultra-distal radius sections. Biomech Model Mechanobiol 2011; 10 (4) 431-444.
    CrossrefPubMedGoogle Scholar
  • 19 Dall'ara E, Varga P, Pahr D, Zysset P. A calibration methodology of qct bmd for human vertebral body with registered micro-ct images. Med Phys 2011; 38: 2602-2608.
    CrossrefPubMedGoogle Scholar
  • 20 Dall'ara E, Luisier B, Schmidt R. et al. A nonlinear qct-based finite element model validation study for the human femur tested in two configurations in vitro. Bone 2012; 52 (1) 27-38.
    PubMedGoogle Scholar
  • 21 Van Rietbergen B, Weinans H, Huiskes R, Odgaard A. A new method to determine trabecular bone elastic properties and loading using micromechanical niteelement models. Journal of Biomechanics 1995; 28 (1) 69-81.
    CrossrefPubMedGoogle Scholar
  • 22 MacNeil JA, Boyd SK. Accuracy of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Medical Engineering Physics 2007; 29 (10) 1096-1105.
    CrossrefPubMedGoogle Scholar
  • 23 Keyak JH, Rossi SA, Jones KA, Skinner HB. Prediction of femoral fracture load using automated nite element modeling. Journal of Biomechanics 1997; 31 (2) 125-133.
    CrossrefPubMedGoogle Scholar
  • 24 Garcia D, Zysset PK, Charlebois M, Curnier A. A three-dimensional elastic plastic damage constitutive law for bone tissue. Biomech Model Mechanobiol 2009; 8 (2) 149-165.
    CrossrefPubMedGoogle Scholar
  • 25 Dall'ara E, Pahr D, Varga P. et al. Qct-based finite element models predict human vertebral strength in vitro signicantly better than simulated dexa. Osteoporos Int 2012; 23: 563-572.
    CrossrefPubMedGoogle Scholar
  • 26 Nazarian A, Muller J, Zurakowski D. et al. Densitometric, morphometric and mechanical distributions in the human proximal femur. J Biomech 2007; 40 (11) 2573-2579.
    CrossrefPubMedGoogle Scholar
  • 27 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) 982-988.
    CrossrefPubMedGoogle Scholar
  • 28 Maquer G, Dall'ara E, Zysset PK. Removal of the cortical endplates has little effect on ultimate load and damage distribution in qct-based voxel models of human lumbar vertebrae under axial compression. J Biomech 2012; 45 (9) 1733-1738.
    CrossrefPubMedGoogle Scholar
  • 29 Liebschner MA, Kopperdahl DL, Rosenberg WS, Keaveny TM. Finite element modeling of the human thoracolumbar spine. Spine 2003; 28 (6) 559-565.
    PubMedGoogle Scholar
  • 30 Homminga J, Weinans H, Gowin W. et al. Osteoporosis changes the amount of vertebral trabecular bone at risk of fracture but not the vertebral load distribution. Spine 2001; 26: 1555-1560.
    CrossrefPubMedGoogle Scholar
  • 31 Jones AC, Wilcox RK. Assessment of factors influencing finite element vertebral model predictions. J Biomech Eng 2007; 129 (6) 898-903.
    CrossrefPubMedGoogle Scholar
  • 32 Crawford RP, Rosenberg WS, Keaveny TM. Quantitative computed tomography-based finite element models of the human lumbar vertebral body: Effect of element size on stiffness, damage, and fracture strength predictions. Journal of Biomechanical Engineering 2003; 125 (4) 434-438.
    CrossrefPubMedGoogle Scholar
  • 33 Keaveny TM, Bouxsein ML. Theoretical implications of the biomechanical fracture threshold. J Bone Miner Res 2008; 23 (10) 1541-1547.
    CrossrefPubMedGoogle Scholar
  • 34 Seeman E, Delmas PD, Hanley DA. et al. Microarchitectural deterioration of cortical and trabecular bone: differing effects of denosumab and alendronate. J Bone Miner Res 2010; 25 (8) 1886-1894.
    CrossrefPubMedGoogle Scholar
  • 35 Mulder L, van Rietbergen B, Noordhoek NJ, Ito K. Determination of vertebral and femoral trabecular morphology and stiffness using a flat-panel c-armbased ct approach. Bone 2012; 50: 200-208.
    CrossrefPubMedGoogle Scholar
  • 36 Luo Y, Ferdous Z, Leslie WD. A preliminary dual-energy x-ray absorptiometry based finite element model for assessing osteoporotic hip fracture risk. Proceedings of the Institution of Mechanical Engineers, Part H. Journal of engineering in medicine 2011; 225 (12) 1188-1195.
    CrossrefPubMedGoogle Scholar