Skip to main content
SpringerLink
Log in

Einsatzgebiete der numerischen Simulation in der muskuloskelettalen Forschung und ihre Bedeutung für die Orthopädische Chirurgie

Applications of numerical simulation in musculoskeletal research and its impact on orthopedic surgery

  • Leitthema
  • Published:
Der Orthopäde Aims and scope Submit manuscript

Zusammenfassung

In der muskuloskelettalen Forschung kommen für numerische Simulationen vorrangig die Finite-Elemente-Methode (FEM) und die Mehrkörpersimulation (MKS) zum Einsatz. Während mittels FEM meist lokale Feldprobleme wie Spannungs- und Dehnungsverteilungen berechnet werden, wird die MKS für kinematische Analysen z. B. zur Berechnung von Muskel- und Gelenkkräften angewendet. Die Modellierung von biologischem Gewebe kann je nach Anforderung von einfachem homogenem Materialverhalten bis zur Modellierung biochemischer Prozesse auf Mikro- und Nanoebene erfolgen. Einen wichtigen Meilenstein in der biomechanischen Forschung stellte die Analyse des „stress shielding“ dar, woraufhin Knochenumbauvorgänge in den Fokus der Simulation traten. Zahlreiche Modelle zur Verankerung von Implantaten mit Vorhersagen der Mikrobewegungen sind veröffentlicht. Die Einbeziehung komplexer Muskelkräfte aus der MKS in die FE-Analyse eröffnet neue Möglichkeiten zur Bearbeitung biomechanischer Fragestellungen. Ein numerisches Modell bedarf immer der experimentellen Validierung. Sofern die Ergebnisse experimentell bestätigt sind, können die zahlreichen Vorteile der Simulation genutzt werden: Probleme lassen sich isoliert von vielen Einflussfaktoren betrachten und Parameter können einfach und reproduzierbar variiert werden, wodurch Studien möglich sind, die auf experimentellem oder klinischem Wege meist unlösbar wären.

Abstract

Finite element analyses (FEA) as well as multibody system dynamics (MSD) are the main tools used for numerical simulation in the field of musculoskeletal research. While FEA is utilized for field problems, such as calculation of stress and strain distribution, MSD is applied for solving kinematic analyses, such as calculation of muscle and joint forces. Depending on the focus of investigation, modelling of biological tissue may vary from simple homogeneous behavior to modelling biochemical processes on the microscale and nanoscale. An important milestone in biomechanical research was the analysis of stress shielding, which led to further research on bone remodelling. Various models of implant-bone fixation used for the prediction of micromotion have been published. New possibilities for biomechanical analyses are achieved by consideration of complex muscle forces which are generated by MSD simulation and imported into FEA models as limiting conditions. A numerical model always requires experimental validation. If the results are confirmed experimentally, various advantages of numerical simulation apply and problems can be analysed isolated from many influencing factors. Therefore, straightforward parameter variation is possible, enabling studies which would be impossible in an experimental or clinical setup.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Abb. 1
Abb. 2
Abb. 3
Abb. 4
Abb. 5
Abb. 6
Abb. 7
Abb. 8

Literatur

  1. Ateshian GA, Friedman MH (2009) Integrative biomechanics: a paradigm for clinical applications of fundamental mechanics. J Biomech 42(10):1444–1451

    Article  PubMed  Google Scholar 

  2. Bader R, Scholz R, Steinhauser E et al (2004) Methode zur Evaluierung von Einflussfaktoren auf die Luxationsstabilität von künstlichen Hüftgelenken. Biomed Tech 49:137–144

    Article  CAS  Google Scholar 

  3. Bah MT, Nair PB, Taylor M, Browne M (2011) Efficient computational method for assessing the effects of implant positioning in cementless total hip replacements. J Biomech 44(7):1417–1422

    Article  PubMed  Google Scholar 

  4. Lerch M, Kurtz A, Stukenborg-Colsmann C et al (2012) Bone remodeling after total hip arthroplasty with a short stemmed metaphyseal loading implant: finite element analysis validated by a prospective DEXA investigation. J Orthop Res 30(11):1822–1829

    Article  PubMed  Google Scholar 

  5. Bryan R, Mohan PS, Hopkins A et al (2011) Statistical modelling of the whole human femur incorporating geometric and material properties. Med Eng Phys 32(1):57–65

    Article  Google Scholar 

  6. Cowin S (2001) Bone mechanics handbook. CRC Press

  7. Duda GN, Heller M, Albinger J et al (1998) Influence of muscle forces on femoral strain distribution. J Biomech 31:841–846

    Article  PubMed  CAS  Google Scholar 

  8. Heller MO, Bergmann G, Deuretzbacher G et al (2001) Musculo-skeletal loading conditions at the hip during walking and stair climbing. J Biomech 34(7):883–893

    Article  PubMed  CAS  Google Scholar 

  9. Henninger HB, Reese SP, Anderson AE, Weiss JA (2010) Validation of computational models in biomechanics. Proc Inst Mech Eng H 224(7):801–812

    Article  PubMed  CAS  Google Scholar 

  10. Herrmann S, Kaehler M, Souffrant R et al (2012) HiL simulation in biomechanics: a new approach for testing total joint replacements. Comput Methods Programs Biomed 105(2):109–119

    Article  PubMed  Google Scholar 

  11. Hoffmann F, Ellguth M, Klöhn C et al (2011) Bone remodeling simulation of the human pelvic bone and comparison of the results with CT data. In: Kluess D, Mittelmeier W, Bader R (eds) Proceedings of SimOrtho, 1st International Symposium on Numerical Simulation in Orthopaedic Biomechanics. Shaker, Aachen, pp 59–66

  12. Huiskes R, Rietbergen B van (1995) Preclinical testing of total hip stems. The effects of coating placement. Clin Orthop Relat Res 64–76

  13. Huiskes R, Weinans H, Rietbergen B van (1992) The relationship between stress shielding and bone resorption around total hip stems and the effects of flexible materials. Clin Orthop Relat Res 319:124–134

    Google Scholar 

  14. Kessler O, Patil S, Colwell CW Jr, D’Lima DD (2008) The effect of femoral component malrotation on patellar biomechanics. J Biomech 41(16):3332–3339

    Article  PubMed  Google Scholar 

  15. Kluess D, Martin H, Mittelmeier W et al (2007) Influence of femoral head size on impingement, dislocation and stress distribution in total hip replacement. Med Eng Phys 29(4):465–471

    Article  PubMed  Google Scholar 

  16. Kluess D, Souffrant R, Mittelmeier W et al (2009) A convenient approach for finite-element-analyses of orthopaedic implants in bone contact: modeling and experimental validation. Comput Methods Programs Biomed 95:23–30

    Article  PubMed  Google Scholar 

  17. Kunze M, Schaller A, Steinke H et al (2012) Combined multi-body and finite element investigation of the effect of the seat height on acetabular implant stability during the activity of getting up. Comput Methods Programs Biomed 105(2):175–182

    Article  PubMed  Google Scholar 

  18. Loparic M, Wirz D, Daniels AU et al (2010) Micro- and nanomechanical analysis of articular cartilage by indentation-type atomic force microscopy – validation with a gel-microfiber composite. Biophys J 98:2731–2740

    Article  PubMed  CAS  Google Scholar 

  19. Mair S, Weninger P, Hogel F et al (2013) Die Stabilität von distalen Radiusfrakturen mit volaren winkelstabilen Plattenosteosynthesen: Versagensmechanismen im osteoporotischen Knochen. Unfallchirurg, in Druck

  20. Neugebauer R, Werner M, Voigt C et al (2011) Experimental modal analysis on fresh-frozen human hemipelvic bones employing a 3D laser vibrometer for the purpose of modal parameter identification. J Biomech 44(8):1610–1613

    Article  PubMed  CAS  Google Scholar 

  21. Rothstock S, Uhlenbrock A, Bishop N et al (2011) Influence of interface condition and implant design on bone remodelling and failure risk for the resurfaced femoral head. J Biomech 44(9):1646–1653

    Article  PubMed  Google Scholar 

  22. Stops A, Wilcox R, Jin Z (2012) Computational modelling of the natural hip: a review of finite element and multibody simulations. Comput Methods Biomech Biomed Engin 15(9):963–979

    Article  PubMed  Google Scholar 

  23. Taddei F, Cristofolini L, Martelli S et al (2006) Subject-specific finite element models of long bones: an in vitro evaluation of the overall accuracy. J Biomech 39:2457–2467

    Article  PubMed  Google Scholar 

  24. Taddei F, Schileo E, Helgason B et al (2007) The material mapping strategy influences the accuracy of CT-based finite element models of bones: an evaluation against experimental measurements. Med Eng Phys 29(9):973–979

    Article  PubMed  Google Scholar 

  25. Taylor WR, Roland E, Ploeg H et al (2002) Determination of orthotropic bone elastic constants using FEA and modal analysis. J Biomech 35(6):767–773

    Article  PubMed  CAS  Google Scholar 

  26. Turner AW, Gillies RM, Sekel R et al (2005) Computational bone remodelling simulations and comparisons with DEXA results. J Orthop Res 23:705–712

    Article  PubMed  CAS  Google Scholar 

  27. Viceconti M, Davinelli M, Taddei F, Cappello A (2004) Automatic generation of accurate subject-specific bone finite element models to be used in clinical studies. J Biomech 37:1597–1605

    Article  PubMed  Google Scholar 

  28. Viceconti M, Olsen S, Nolte LP, Burton K (2005) Extracting clinically relevant data from finite element simulations. Clin Biomech (Bristol, Avon) 20(5):451–454

    Google Scholar 

  29. Voigt C, Hucke D, Steinke H, Scholz R (2011) Automatic strategy for segmentation of the cortical bone shell and experimental validation on human pelvic bone. In: Kluess D, Mittelmeier W, Bader R (eds) Proceedings of SimOrtho, 1st International Symposium on Numerical Simulation in Orthopaedic Biomechanics. Shaker, Aachen, pp 81–82

  30. Wong J, Steklov N, Patil S et al (2011) Predicting the effect of tray malalignment on risk for bone damage and implant subsidence after total knee arthroplasty. J Orthop Res 29(3):347–353

    Article  PubMed  Google Scholar 

  31. Zannoni C, Mantovani R, Viceconti M (1998) Material properties assignment to finite element models of bone structures: a new method. Med Eng Phys 20:735–740

    Article  PubMed  CAS  Google Scholar 

Download references

Interessenkonflikt

Der korrespondierende Autor gibt für sich und seine Koautoren an, dass kein Interessenkonflikt besteht.

Author information

Authors and Affiliations

  1. Forschungslabor für Biomechanik und Implantattechnologie, Orthopädische Klinik und Poliklinik, Universitätsmedizin Rostock, Doberaner Str. 142, 18057, Rostock, Deutschland

    D. Kluess

  2. Labor für Biomechanik und Biomaterialien, Orthopädische Klinik, Medizinische Hochschule Hannover – Annastift, Hannover, Deutschland

    C. Hurschler

  3. Labor für Biomechanik, Klinik und Poliklinik für Orthopädie, Universität Leipzig, Leipzig, Deutschland

    C. Voigt

  4. Orthopädische Klinik und Poliklinik, Klinikum der Ludwig-Maximilians-Universität München, München, Deutschland

    A. Hölzer

  5. Institut für Allgemeine Mechanik, RWTH Aachen, Templergraben 64, 52056, Aachen, Deutschland

    M. Stoffel

Authors
  1. D. Kluess
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. Hurschler
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. Voigt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. Hölzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Stoffel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to D. Kluess or M. Stoffel.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kluess, D., Hurschler, C., Voigt, C. et al. Einsatzgebiete der numerischen Simulation in der muskuloskelettalen Forschung und ihre Bedeutung für die Orthopädische Chirurgie. Orthopäde 42, 220–231 (2013). https://doi.org/10.1007/s00132-012-1949-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00132-012-1949-0

Schlüsselwörter

Keywords

Search

Navigation