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In Situ Parameter Identification Of Optimal Density-elastic Modulus Relationships In Subject-specific Finite Element Models Of The Proximal Femur.

A. Cong, J. O. D. Buijs, D. Dragomir-Daescu
Published 2011 · Engineering, Medicine

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Quantitative computed tomography based finite element analysis of the femur is currently being investigated as a method for non-invasive stiffness and strength predictions of the proximal femur. The specific objective of this study was to determine better conversion relationships from QCT-derived bone density to elastic modulus, in order to achieve accurate predictions of the overall femoral stiffness in a fall-on-the-hip loading configuration. Twenty-two femurs were scanned, segmented and meshed for finite element analysis. The elastic moduli of the elements were assigned according to the average density in the element. The femurs were then tested to fracture and force-displacement data were collected to calculate femoral stiffness. Using a training set of nine femurs, finite element analyses were performed and the parameters of the density-elastic modulus relationship were iteratively adjusted to obtain optimal stiffness predictions in a least-squares sense. The results were then validated on the remaining 13 femurs. Our novel procedure resulted in parameter identification of both power and sigmoid functions for density-elastic modulus conversion for this specific loading scenario. Our in situ estimated power law achieved improved predictions compared to published power laws, and the sigmoid function yielded even smaller prediction errors. In the future, these results will be used to further improve the femoral strength predictions of our finite element models.
This paper references
10.1016/0021-9290(84)90029-0
A continuous wave technique for the measurement of the elastic properties of cortical bone.
R. B. Ashman (1984)
10.1115/1.2895412
Fracture prediction for the proximal femur using finite element models: Part I--Linear analysis.
J. C. Lotz (1991)
10.1016/J.JBIOMECH.2007.02.010
Subject-specific finite element models can accurately predict strain levels in long bones.
E. Schileo (2007)
10.1109/42.832955
Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction
C. H. Yan (2000)
10.1016/J.JTBI.2006.09.013
'Universal' microstructural patterns in cortical and trabecular, extracellular and extravascular bone materials: micromechanics-based prediction of anisotropic elasticity.
A. Fritsch (2007)
10.1007/BF00298717
Impact near the hip dominates fracture risk in elderly nursing home residents who fall
W. Hayes (2004)
10.2106/00004623-197759070-00021
The compressive behavior of bone as a two-phase porous structure.
D. Carter (1977)
10.1016/J.CLINBIOMECH.2007.08.024
Mathematical relationships between bone density and mechanical properties: a literature review.
B. Helgason (2008)
10.1016/S0021-9290(03)00071-X
Trabecular bone modulus-density relationships depend on anatomic site.
E. Morgan (2003)
10.1016/0021-9290(74)90018-9
The elastic modulus for bone.
D. Reilly (1974)
10.1016/0021-9290(94)90014-0
The relationship between the structural and orthogonal compressive properties of trabecular bone.
R. Goulet (1994)
10.1016/j.jbiomech.2009.05.001
During sideways falls proximal femur fractures initiate in the superolateral cortex: evidence from high-speed video of simulated fractures.
P. D. de Bakker (2009)
10.1016/1350-4533(95)97314-F
Relations of mechanical properties to density and CT numbers in human bone.
J. Rho (1995)
10.1007/BF00310169
Effects of loading rate on strength of the proximal femur
A. Courtney (2004)
10.1038/NMAT832
Mechanistic fracture criteria for the failure of human cortical bone
R. K. Nalla (2003)
10.1016/J.JBIOMECH.2006.08.003
Prediction of strength and strain of the proximal femur by a CT-based finite element method.
M. Bessho (2007)
10.1016/0021-9290(94)90056-6
Predicting the compressive mechanical behavior of bone.
T. Keller (1994)
10.1088/0031-9155/55/2/N03
An anatomically shaped lower body model for CT scanning of cadaver femurs.
E. Tanck (2010)
10.1038/bjc.1964.55
DYNAMICS OF TUMOR GROWTH.
Laird Ak (1964)
10.1111/j.1742-4658.2008.06844.x
Systems biology: parameter estimation for biochemical models
M. Ashyraliyev (2009)
Dynamics of Tumour Growth
Laird Ak (1964)
10.1016/S0021-9290(99)00099-8
Femoral strength is better predicted by finite element models than QCT and DXA.
D. Cody (1999)
10.1016/S1350-4533(01)00094-7
Prediction of fracture location in the proximal femur using finite element models.
J. Keyak (2001)
10.1529/biophysj.107.125567
Hierarchical modeling of the elastic properties of bone at submicron scales: the role of extrafibrillar mineralization.
S. Nikolov (2008)
10.1016/J.JBIOMECH.2005.07.018
Subject-specific finite element models of long bones: An in vitro evaluation of the overall accuracy.
F. Taddei (2006)
10.1016/J.JBIOMECH.2003.12.030
Automatic generation of accurate subject-specific bone finite element models to be used in clinical studies.
M. Viceconti (2004)
10.1038/NMAT843
How does bone break?
D. Taylor (2003)
10.1007/s00198-006-0162-6
Femoral neck cortical geometry measured with magnetic resonance imaging is associated with proximal femur strength
S. Manske (2006)
10.1016/S0021-9290(98)00177-8
The elastic properties of trabecular and cortical bone tissues are similar: results from two microscopic measurement techniques.
C. Turner (1999)
10.1016/S0021-9290(97)00123-1
Prediction of femoral fracture load using automated finite element modeling.
J. Keyak (1998)
Heterogeneity of age-related fractures: implications for epidemiology.
L. J. Melton (1987)
10.1016/S0140-6736(06)68891-0
Osteoporosis: trends in epidemiology, pathogenesis and treatment
P. Sambrook (2006)
10.1016/j.bone.2007.11.001
A reference standard for the description of osteoporosis.
J. Kanis (2008)
10.1016/0021-9290(76)90089-0
Ultrasonic wave propagation in human cortical bone--II. Measurements of elastic properties and microhardness.
H. S. Yoon (1976)
10.1016/j.bone.2009.06.009
Pathological fracture prediction in patients with metastatic lesions can be improved with quantitative computed tomography based computer models.
E. Tanck (2009)
10.1007/BF01622200
Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: Synopsis of a WHO report
J. Kanis (2005)
10.1002/JBM.820281111
Correlations between orthogonal mechanical properties and density of trabecular bone: use of different densitometric measures.
J. Keyak (1994)



This paper is referenced by
L’EFFET DES PROPRIETES DU MATERIAU SUR LE COMPORTEMENT DU MODELE ELEMENT FINI DE FEMUR HUMAIN.
Dalila Belaid (2016)
10.1007/978-3-319-21296-8_15
In-silico models of trabecular bone: a sensitivity analysis perspective
Marlène Mengoni (2016)
10.1007/s11914-016-0335-y
Finite Element-Based Mechanical Assessment of Bone Quality on the Basis of In Vivo Images
Dieter H Pahr (2016)
10.1016/j.jbiomech.2017.06.010
Experimental validation of finite element predicted bone strain in the human metatarsal.
Anita Fung (2017)
10.1080/10255842.2019.1661386
Separate modeling of cortical and trabecular bone offers little improvement in FE predictions of local structural stiffness at the proximal tibia
S Mehrdad Hosseini Kalajahi (2019)
10.1016/j.bone.2015.06.025
Comparison of proximal femur and vertebral body strength improvements in the FREEDOM trial using an alternative finite element methodology.
P. Zysset (2015)
10.1098/rsfs.2015.0055
Modelling of bone fracture and strength at different length scales: a review
F. Sabet (2016)
10.1016/j.jocd.2019.02.005
Liquid Calibration Phantoms in Ultra-Low-Dose QCT for the Assessment of Bone Mineral Density.
Malakeh Malekzadeh (2019)
10.1007/S10409-015-0414-9
Tissue level microstructure and mechanical properties of the femoral head in the proximal femur of fracture patients
Linwei Lü (2015)
10.1016/j.clinbiomech.2013.12.018
How accurately can we predict the fracture load of the proximal femur using finite element models?
Sven van den Munckhof (2014)
10.1016/j.jcms.2017.12.020
Three-dimensional titanium miniplates for fixation of subcondylar mandibular fractures: Comparison of five designs using patient-specific finite element analysis.
M. H. Albogha (2018)
10.1016/j.jmbbm.2013.02.006
Experimental validation of finite element model for proximal composite femur using optical measurements.
L. Grassi (2013)
10.1016/j.jbiomech.2015.08.015
Generic finite element models of orthodontic mini-implants: Are they reliable?
Mhd Hassan Albogha (2015)
10.1186/s40634-016-0072-2
Quantitative Computed Tomography (QCT) derived Bone Mineral Density (BMD) in finite element studies: a review of the literature
N. Knowles (2016)
10.1038/s41598-019-43028-6
Neuro-musculoskeletal flexible multibody simulation yields a framework for efficient bone failure risk assessment
Andreas Geier (2019)
10.1557/JMR.2014.326
Quantitative intravoxel analysis of microCT-scanned resorbing ceramic biomaterials – Perspectives for computer-aided biomaterial design
Agnes Czenek (2014)
10.1007/s10439-016-1584-8
Predisposing Factors for Orthodontic Mini-Implant Failure Defined by Bone Strains in Patient-Specific Finite Element Models
Mhd Hassan Albogha (2016)
10.3390/bioengineering4010005
Fixation Release and the Bone Bandaid: A New Bone Fixation Device Paradigm
N. Shayesteh Moghaddam (2017)
10.3109/17453674.2012.678804
Experimental evaluation of new concepts in hip arthroplasty
T. Wik (2012)
10.1142/S0219876218420124
Automated Segmentation of Swine Skulls for Finite Element Model Creation Using High Resolution μ-CT Images
Zimo Zhu (2019)
10.1080/10255842.2019.1615481
A round-robin finite element analysis of human femur mechanics between seven participating laboratories with experimental validation
D. Kluess (2019)
10.1016/j.jbiomech.2013.06.035
Individual density-elasticity relationships improve accuracy of subject-specific finite element models of human femurs.
Sebastian Eberle (2013)
10.1080/15502287.2016.1145762
Coupling multiscale X-ray physics and micromechanics for bone tissue composition and elasticity determination from micro-CT data, by example of femora from OVX and sham rats
Patricia Hasslinger (2016)
10.3390/ma13010106
Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis—A Survey
Amadeus C S de Alcântara (2019)
10.1016/j.jbiomech.2013.06.036
Intravoxel bone micromechanics for microCT-based finite element simulations.
R. Blanchard (2013)
10.1080/10255842.2015.1006209
QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling
T. Rossman (2016)
10.1007/s11517-015-1348-x
Specimen-specific vertebral fracture modeling: a feasibility study using the extended finite element method
H. Giambini (2015)
10.1016/j.medengphy.2012.08.022
An investigation to determine if a single validated density-elasticity relationship can be used for subject specific finite element analyses of human long bones.
S. Eberle (2013)
10.1016/j.jbiomech.2014.09.016
Quantitative computed tomography-based finite element analysis predictions of femoral strength and stiffness depend on computed tomography settings.
D. Dragomir-Daescu (2015)
10.2316/P.2012.764-004
AN AUTOMATED METHOD TO ESTIMATE FEMORAL SHAPE AND MINERAL MASS
Danilo Pietro Pau (2012)
10.1115/1.4042172
The Effect of Inhomogeneous Trabecular Stiffness Relationship Selection on Finite Element Outcomes for Shoulder Arthroplasty.
Jacob M. Reeves (2019)
Inducible Displacement of a Knee Implant: A finite element study and validation of a loose and fixed tibial component
G. Wolfswinkel (2016)
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