The Application of an Isotropic Crushable Foam Model to Predict the Femoral Fracture Risk

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2023 Jul 27

PMID 37498946

Authors

Navid Soltanihafshejani

Federica Peroni

Sara Toniutti

Thom Bitter

Esther Tanck

Florieke Eggermont

Nico Verdonschot

Dennis Janssen

Affiliations

Soon will be listed here.

Abstract

For biomechanical simulations of orthopaedic interventions, it is imperative to implement a material model that can realistically reproduce the nonlinear behavior of the bone structure. However, a proper material model that adequately combines the trabecular and cortical bone response is not yet widely identified. The current paper aims to investigate the possibility of using an isotropic crushable foam (ICF) model dependent on local bone mineral density (BMD) for simulating the femoral fracture risk. The elastoplastic properties of fifty-nine human femoral trabecular cadaveric bone samples were determined and combined with existing cortical bone properties to characterize two forms of the ICF model, a continuous and discontinuous model. Subsequently, the appropriateness of this combined material model was evaluated by simulating femoral fracture experiments, and a comparison with earlier published results of a softening Von-Mises (sVM) material model was made. The obtained mechanical properties of the trabecular bone specimens were comparable to previous findings. Furthermore, the ultimate failure load predicted by the simulations of femoral fractures was on average 79% and 90% for the continuous and discontinuous forms of the ICF model and 82% of the experimental value for the sVM material model. Also, the fracture locations predicted by ICF models were comparable to the experiments. In conclusion, a nonlinear material model dependent on BMD was characterized for human femoral bone. Our findings indicate that the ICF model could predict the femoral bone strength and reproduce the variable fracture locations in the experiments.

References

Keyak J, Kaneko T, Tehranzadeh J, Skinner H . Predicting proximal femoral strength using structural engineering models. Clin Orthop Relat Res. 2005; (437):219-28. DOI: 10.1097/01.blo.0000164400.37905.22. View

Goldstein S . The mechanical properties of trabecular bone: dependence on anatomic location and function. J Biomech. 1987; 20(11-12):1055-61. DOI: 10.1016/0021-9290(87)90023-6. View

Derikx L, Vis R, Meinders T, Verdonschot N, Tanck E . Implementation of asymmetric yielding in case-specific finite element models improves the prediction of femoral fractures. Comput Methods Biomech Biomed Engin. 2011; 14(2):183-93. DOI: 10.1080/10255842.2010.542463. View

Kaneko T, Pejcic M, Tehranzadeh J, Keyak J . Relationships between material properties and CT scan data of cortical bone with and without metastatic lesions. Med Eng Phys. 2003; 25(6):445-54. DOI: 10.1016/s1350-4533(03)00030-4. View

Schileo E, Pitocchi J, Falcinelli C, Taddei F . Cortical bone mapping improves finite element strain prediction accuracy at the proximal femur. Bone. 2020; 136:115348. DOI: 10.1016/j.bone.2020.115348. View

Duchemin L, Bousson V, Raossanaly C, Bergot C, Laredo J, Skalli W . Prediction of mechanical properties of cortical bone by quantitative computed tomography. Med Eng Phys. 2007; 30(3):321-8. DOI: 10.1016/j.medengphy.2007.04.008. View

Keyak J . Improved prediction of proximal femoral fracture load using nonlinear finite element models. Med Eng Phys. 2001; 23(3):165-73. DOI: 10.1016/s1350-4533(01)00045-5. View

Hambli R, Allaoui S . A robust 3D finite element simulation of human proximal femur progressive fracture under stance load with experimental validation. Ann Biomed Eng. 2013; 41(12):2515-27. DOI: 10.1007/s10439-013-0864-9. View

Herrera A, Ibarz E, Cegonino J, Lobo-Escolar A, Puertolas S, Lopez E . Applications of finite element simulation in orthopedic and trauma surgery. World J Orthop. 2012; 3(4):25-41. PMC: 3329620. DOI: 10.5312/wjo.v3.i4.25. View

10.

Eggermont F, Derikx L, Free J, van Leeuwen R, van der Linden Y, Verdonschot N . Effect of different CT scanners and settings on femoral failure loads calculated by finite element models. J Orthop Res. 2018; . PMC: 6120464. DOI: 10.1002/jor.23890. View

11.

Eggermont F, Derikx L, Verdonschot N, van der Geest I, de Jong M, Snyers A . Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians?: Towards computational modelling in daily clinical practice. Bone Joint Res. 2018; 7(6):430-439. PMC: 6035356. DOI: 10.1302/2046-3758.76.BJR-2017-0325.R2. View

12.

Soltanihafshejani N, Bitter T, Janssen D, Verdonschot N . Development of a crushable foam model for human trabecular bone. Med Eng Phys. 2021; 96:53-63. DOI: 10.1016/j.medengphy.2021.08.009. View

13.

MEEMA H, MEEMA S . Cortical bone mineral density versus cortical thickness in the diagnosis of osteoporosis: a roentgenologic-densitometric study. J Am Geriatr Soc. 1969; 17(2):120-41. DOI: 10.1111/j.1532-5415.1969.tb03167.x. View

14.

Derikx L, van Aken J, Janssen D, Snyers A, van der Linden Y, Verdonschot N . The assessment of the risk of fracture in femora with metastatic lesions: comparing case-specific finite element analyses with predictions by clinical experts. J Bone Joint Surg Br. 2012; 94(8):1135-42. DOI: 10.1302/0301-620X.94B8.28449. View

15.

Tanck E, van Aken J, van der Linden Y, Schreuder H, Binkowski M, Huizenga H . Pathological fracture prediction in patients with metastatic lesions can be improved with quantitative computed tomography based computer models. Bone. 2009; 45(4):777-83. DOI: 10.1016/j.bone.2009.06.009. View

16.

Charlebois M, Pretterklieber M, Zysset P . The role of fabric in the large strain compressive behavior of human trabecular bone. J Biomech Eng. 2010; 132(12):121006. DOI: 10.1115/1.4001361. View

17.

Kinzl M, Wolfram U, Pahr D . Identification of a crushable foam material model and application to strength and damage prediction of human femur and vertebral body. J Mech Behav Biomed Mater. 2013; 26:136-47. DOI: 10.1016/j.jmbbm.2013.04.026. View

18.

Ward K, Adams J, Hangartner T . Recommendations for thresholds for cortical bone geometry and density measurement by peripheral quantitative computed tomography. Calcif Tissue Int. 2005; 77(5):275-80. DOI: 10.1007/s00223-005-0031-x. View

19.

Kaneko T, Bell J, Pejcic M, Tehranzadeh J, Keyak J . Mechanical properties, density and quantitative CT scan data of trabecular bone with and without metastases. J Biomech. 2004; 37(4):523-30. DOI: 10.1016/j.jbiomech.2003.08.010. View

20.

Kelly N, Harrison N, McDonnell P, McGarry J . An experimental and computational investigation of the post-yield behaviour of trabecular bone during vertebral device subsidence. Biomech Model Mechanobiol. 2012; 12(4):685-703. DOI: 10.1007/s10237-012-0434-3. View