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Precision Of Digital Volume Correlation Approaches For Strain Analysis In Bone Imaged With Micro-Computed Tomography At Different Dimensional Levels

E. Dall’Ara, M. Peña-Fernandez, M. Palanca, M. Giorgi, L. Cristofolini, G. Tozzi
Published 2017 · Materials Science

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Accurate measurement of local strain in heterogeneous and anisotropic bone tissue is fundamental to understand the pathophysiology of musculoskeletal diseases, to evaluate the effect of interventions from preclinical studies, and to optimize the design and delivery of biomaterials. Digital volume correlation (DVC) can be used to measure the three-dimensional displacement and strain fields from micro-Computed Tomography (µCT) images of loaded specimens. However, this approach is affected by the quality of the input images, by the morphology and density of the tissue under investigation, by the correlation scheme, and by the operational parameters used in the computation. Therefore, for each application the precision of the method should be evaluated. In this paper we present the results collected from datasets analyzed in previous studies as well as new data from a recent experimental campaign for characterizing the relationship between the precision of two different DVC approaches and the spatial resolution of the outputs. Different bone structures scanned with laboratory source µCT or Synchrotron light µCT (SRµCT) were processed in zero-strain tests to evaluate the precision of the DVC methods as a function of the subvolume size that ranged from 8 to 2500 micrometers. The results confirmed that for every microstructure the precision of DVC improves for larger subvolume size, following power laws. However, for the first time large differences in the precision of both local and global DVC approaches have been highlighted when SRµCT or in vivo µCT images were used instead of conventional ex vivo µCT. These findings suggest that in situ mechanical testing protocols applied in SRµCT facilities should be optimized in order to allow DVC analyses of localized strain measurements. Moreover, for in vivo µCT applications DVC analyses should be performed only with relatively course spatial resolution for achieving a reasonable precision of the method. In conclusion, we have extensively shown that the precision of both tested DVC approaches is affected by different bone structures, different input image resolution and different subvolume sizes. Before each specific application DVC users should always apply a similar approach to find the best compromise between precision and spatial resolution of the measurements.
This paper references
10.1016/j.jbiomech.2008.05.017
An accurate estimation of bone density improves the accuracy of subject-specific finite element models.
E. Schileo (2008)
10.1016/j.jbiomech.2015.12.004
Accuracy of finite element analyses of CT scans in predictions of vertebral failure patterns under axial compression and anterior flexion.
T. Jackman (2016)
10.1115/1.3423690
Finite-Element Analysis
R. H. Gallagher (1975)
10.1016/j.jmbbm.2013.06.007
Numerical description and experimental validation of a rheology model for non-Newtonian fluid flow in cancellous bone.
R. P. Widmer Soyka (2013)
10.1016/j.jbiomech.2016.10.002
Load-adaptive bone remodeling simulations reveal osteoporotic microstructural and mechanical changes in whole human vertebrae.
S. D. Badilatti (2016)
10.1016/j.medengphy.2013.02.001
Computation of full-field displacements in a scaffold implant using digital volume correlation and finite element analysis.
K. Madi (2013)
10.1016/j.jmbbm.2016.12.006
Strain uncertainties from two digital volume correlation approaches in prophylactically augmented vertebrae: Local analysis on bone and cement-bone microstructures.
G. Tozzi (2017)
10.1115/1.4030174
Three-dimensional local measurements of bone strain and displacement: comparison of three digital volume correlation approaches.
M. Palanca (2015)
10.1002/jbmr.2528
Aging Leads to a Dysregulation in Mechanically Driven Bone Formation and Resorption
H. Razi (2015)
2016) Vertebral bodies
Palanca (2016)
10.1007/s00223-016-0217-4
Tomography-Based Quantification of Regional Differences in Cortical Bone Surface Remodeling and Mechano-Response
A. Birkhold (2016)
Feasibility study for a clinical application of digital volume correlation
M. Palanca (2017)
Automatic segmentation of medical images
D. R. Hose (2005)
1995)], makes it impossible to accurately validate the FE predictions of strain
Rietbergen (1995)
10.1016/j.jmbbm.2016.09.014
Micro-CT based finite element models of cancellous bone predict accurately displacement once the boundary condition is well replicated: A validation study.
Y. Chen (2017)
10.1007/s00198-003-1489-x
Bone quality: where do we go from here?
M. Bouxsein (2003)
Finite element analysis of the spine
A. C. jbiomech.2015.12.004 Jones (2008)
A NEW METHOD TO DETERMINE TRABECULAR BONE ELASTIC PROPERTIES AND LOADING USING MICRO MECHANICAL FINITE-ELEMENT MODELS
B. Rietbergen (2017)
10.1007/s00198-011-1568-3
QCT-based finite element models predict human vertebral strength in vitro significantly better than simulated DEXA
E. Dall’Ara (2011)
10.1016/j.medengphy.2015.08.017
Evaluation of in-vivo measurement errors associated with micro-computed tomography scans by means of the bone surface distance approach.
Yongtao Lu (2015)
10.1016/j.jmbbm.2011.12.009
Deformable image registration and 3D strain mapping for the quantitative assessment of cortical bone microdamage.
D. Christen (2012)
10.1016/j.jmbbm.2016.10.002
Comparison of specimen-specific vertebral body finite element models with experimental digital image correlation measurements.
H. Gustafson (2017)
10.1016/0031-3203(94)E0043-K
Image thresholding by minimizing the measures of fuzzines
Liang-Kai Huang (1995)
10.1016/j.medengphy.2008.09.006
Finite element analysis of the spine: towards a framework of verification, validation and sensitivity analysis.
A. Jones (2008)
10.1080/10255840601160484
Verification, validation and sensitivity studies in computational biomechanics
A. Anderson (2007)
10.1002/cnm.2739
Experimental validation of a nonlinear μFE model based on cohesive-frictional plasticity for trabecular bone.
J. Schwiedrzik (2016)
10.1016/j.clinbiomech.2013.12.019
The Clinical Biomechanics Award 2012 - presented by the European Society of Biomechanics: large scale simulations of trabecular bone adaptation to loading and treatment.
A. Levchuk (2014)
10.1016/j.biomaterials.2011.08.013
Characterization of the effects of x-ray irradiation on the hierarchical structure and mechanical properties of human cortical bone.
H. Barth (2011)
10.1016/j.jmbbm.2017.07.034
Longitudinal effects of Parathyroid Hormone treatment on morphological, densitometric and mechanical properties of mouse tibia.
Yongtao Lu (2017)
10.5201/IPOL.2011.BCM_NLM
Non-Local Means Denoising
A. Buades (2011)
10.1016/j.jbiomech.2017.04.007
Local displacement and strain uncertainties in different bone types by digital volume correlation of synchrotron microtomograms.
M. Palanca (2017)
10.1016/j.jmbbm.2013.09.014
The application of digital volume correlation (DVC) to study the microstructural behaviour of trabecular bone during compression.
F. Gillard (2014)
10.1016/j.jbiomech.2014.07.019
About the inevitable compromise between spatial resolution and accuracy of strain measurement for bone tissue: a 3D zero-strain study.
E. Dall’Ara (2014)
10.1017/CBO9781139049627
Multiscale Modeling of the Skeletal System
M. Viceconti (2011)
10.1007/BF02323555
Digital volume correlation: Three-dimensional strain mapping using X-ray tomography
B. K. Bay (1999)
10.1080/03091900412331289889
Automatic segmentation of medical images using image registration: diagnostic and simulation applications
D. Barber (2005)
10.1016/j.jbiomech.2016.10.018
Digital volume correlation can be used to estimate local strains in natural and augmented vertebrae: An organ-level study.
M. Palanca (2016)
10.1016/j.jbiomech.2014.01.001
Application of the digital volume correlation technique for the measurement of displacement and strain fields in bone: a literature review.
B. Roberts (2014)
10.1002/(SICI)1096-8644(199806)106:2<219::AID-AJPA8>3.0.CO;2-K
Variability in osteon size in recent human populations.
S. Pfeiffer (1998)
10.1016/j.media.2007.06.011
Efficient computational fluid dynamics mesh generation by image registration
D. Barber (2007)
10.1115/1.2146001
Comparison of the linear finite element prediction of deformation and strain of human cancellous bone to 3D digital volume correlation measurements.
R. Zauel (2006)
10.1016/j.clinbiomech.2016.07.010
Application of digital volume correlation to study the efficacy of prophylactic vertebral augmentation.
V. Danesi (2016)
10.1016/j.jbiomech.2009.11.022
Structural behaviour and strain distribution of the long bones of the human lower limbs.
L. Cristofolini (2010)
Application of the digital
B. C. jbmr.2528 Roberts (2014)
10.1016/j.medengphy.2013.04.008
DXA predictions of human femoral mechanical properties depend on the load configuration.
E. Dallara (2013)
10.1016/S0021-9290(03)00257-4
Comparison of the elastic and yield properties of human femoral trabecular and cortical bone tissue.
Harun H. Bayraktar (2004)
10.1111/jmi.12009
Measuring three‐dimensional strain distribution in tendon
G. Khodabakhshi (2013)
Load-adaptive bone
Biomed. Engin (2016)
10.1016/J.JBIOMECH.2007.04.019
Accuracy and precision of digital volume correlation in quantifying displacements and strains in trabecular bone.
L. Liu (2007)
10.1016/j.spinee.2013.06.014
Strain distribution in the lumbar vertebrae under different loading configurations.
L. Cristofolini (2013)
10.1098/rsta.2010.0046
Mechanical testing of bones: the positive synergy of finite–element models and in vitro experiments
L. Cristofolini (2010)
Accuracy and precision of digital volume
E. F. Morgan (2007)
10.1371/journal.pone.0180151
Micro Finite Element models of the vertebral body: Validation of local displacement predictions
M. C. Costa (2017)
10.1016/J.PIUTAM.2012.05.013
Digital Volume Correlation for Study of the Mechanics of Whole Bones.
A. Hussein (2012)
10.1016/j.jbiomech.2016.02.032
How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.
L. Grassi (2016)
1995)], makes it impossible to accurately validate the FE predictions of strain
Rietbergen (1995)
10.1016/j.bone.2012.09.006
A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro.
E. Dallara (2013)
10.1016/j.jbiomech.2010.02.026
Valid micro finite element models of vertebral trabecular bone can be obtained using tissue properties measured with nanoindentation under wet conditions.
U. Wolfram (2010)
10.1016/j.jmbbm.2015.12.017
Spatial resolution and measurement uncertainty of strains in bone and bone-cement interface using digital volume correlation.
Ming‐Liang Zhu (2016)
10.1038/bonekey.2013.120
Finite element analysis for prediction of bone strength.
P. Zysset (2013)
10.1002/jbm.b.33395
The effect of an alginate carrier on bone formation in a hydroxyapatite scaffold.
M. Coathup (2016)



This paper is referenced by
10.3389/fmats.2020.598973
Deformation Dependent Sound Absorption Property of a Novel Magnetorheological Membrane Sound Absorber
C. Sun (2020)
10.3390/ma11112155
Preservation of Bone Tissue Integrity with Temperature Control for In Situ SR-MicroCT Experiments
M. Peña Fernández (2018)
Prediction of the risk of vertebral fracture in patients with metastatic bone lesions as a tool for more effective patients' management
Ferreira Costa (2018)
The Development of a Temporomandibular Force Simulator to Study Craniofacial Strain In-Vitro
Kenneth Ip (2018)
10.1007/s10439-019-02312-2
Material Mapping of QCT-Derived Scapular Models: A Comparison with Micro-CT Loaded Specimens Using Digital Volume Correlation
N. Knowles (2019)
10.1111/jmi.12701
A review of techniques for visualising soft tissue microstructure deformation and quantifying strain Ex Vivo
C. Disney (2018)
10.1371/journal.pone.0197947
Prenatal growth map of the mouse knee joint by means of deformable registration technique
M. Giorgi (2019)
10.1007/s10439-020-02549-2
The Application of Digital Volume Correlation (DVC) to Evaluate Strain Predictions Generated by Finite Element Models of the Osteoarthritic Humeral Head
Jonathan R. Kusins (2020)
10.3390/ma13204619
Heterogeneous Strain Distribution in the Subchondral Bone of Human Osteoarthritic Femoral Heads, Measured with Digital Volume Correlation
Melissa K Ryan (2020)
10.3389/fbioe.2020.00934
Bone Damage Evolution Around Integrated Metal Screws Using X-Ray Tomography — in situ Pullout and Digital Volume Correlation
S. Le Cann (2020)
10.1016/j.jmbbm.2019.05.021
Performance of QCT-Derived scapula finite element models in predicting local displacements using digital volume correlation.
Jonathan R. Kusins (2019)
X-ray biomechanical imaging and digital volume correlation of bone : from regeneration to structure
M. P. Fernández (2018)
10.1007/s10439-018-02152-6
The Effect of Material Heterogeneity, Element Type, and Down-Sampling on Trabecular Stiffness in Micro Finite Element Models
N. Knowles (2018)
10.1016/j.jmbbm.2018.08.012
Effect of SR-microCT radiation on the mechanical integrity of trabecular bone using in situ mechanical testing and digital volume correlation.
M. Peña Fernández (2018)
10.1038/s41598-020-69850-x
Sub-trabecular strain evolution in human trabecular bone
M. J. Turunen (2020)
10.1063/1.5144889
Quantitative probing of the fast particle motion during the solidification of battery electrodes
Y. Yang (2020)
10.1016/j.medengphy.2020.08.008
Vertebral stiffness measured via tomosynthesis-based digital volume correlation is strongly correlated with reference values from micro-CT-based DVC.
Daniel J. Oravec (2020)
10.1016/j.jbiomech.2019.01.041
Uncertainties of synchrotron microCT-based digital volume correlation bone strain measurements under simulated deformation.
F. Comini (2019)
10.3390/ma13173890
Quantifying 3D Strain in Scaffold Implants for Regenerative Medicine
J. N. Clark (2020)
10.1111/jmi.12745
Optimization of digital volume correlation computation in SR‐microCT images of trabecular bone and bone‐biomaterial systems
M. Peña Fernández (2018)
10.1016/j.jmbbm.2018.06.022
Validation of finite element models of the mouse tibia using digital volume correlation.
S. Oliviero (2018)
10.1101/321828
Prenatal growth map of the mouse knee joint by mean of deformable registration technique
M. Giorgi (2018)
Non-invasive prediction of bone mechanical properties of the mouse tibia in longitudinal preclinical studies
S. Oliviero (2019)
10.1038/s41598-018-30334-8
Iterative and discrete reconstruction in the evaluation of the rabbit model of osteoarthritis
Juuso H. Ketola (2018)
10.3390/ma13112579
Full-Field Strain Uncertainties and Residuals at the Cartilage-Bone Interface in Unstained Tissues Using Propagation-Based Phase-Contrast XCT and Digital Volume Correlation
G. Tozzi (2020)
10.1016/J.MEDENGPHY.2020.09.009
Glenoid bone strain after anatomical total shoulder arthroplasty: In vitro measurements with micro-CT and digital volume correlation.
Y. Boulanaache (2020)
10.1007/s40032-020-00611-5
The Relevance of Biomechanical Analysis in Joint Replacements: A Review
B. Pal (2020)
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