Trabecular bone strength predictions using finite element analysis of micro-scale images at limited spatial resolution

Bevill, Grant; Keaveny, Tony M.

doi:10.1016/j.bone.2008.11.020

Cited by 115 publications

(90 citation statements)

References 25 publications

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“…29 noted that even though strength predicted from linear models correlated well with experimental measurements, errors were appreciably reduced when nonlinear models were used (from 15% to 5%). Similar trends were also noted by Bevill and Keaveny 26 when using element sizes of 80 μm or less, especially for specimens with lower volume fraction.…”

supporting

confidence: 86%

“…23,24 We therefore posit that nonlinear μFEA might be a more powerful tool to predict fracture risk. 21,[25][26][27][28] A few studies showed the ability of nonlinear μFEA to predict tensile and compressive yield properties of bone. 23,28,29 However, there is little work aimed at predicting trabecular bone post-yield behavior through nonlinear analysis.…”

Section: Introductionmentioning

confidence: 99%

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Potential of in vivo MRI‐based nonlinear finite‐element analysis for the assessment of trabecular bone post‐yield properties

et al. 2013

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Purpose: Bone strength is the key factor impacting fracture risk. Assessment of bone strength from high-resolution (HR) images have largely relied on linear micro-finite element analysis (μFEA) even though failure always occurs beyond the yield point, which is outside the linear regime. Nonlinear μFEA may therefore be more informative in predicting failure behavior. However, existing nonlinear models applied to trabecular bone (TB) have largely been confined to micro-computed tomography (μCT) and, more recently, HR peripheral quantitative computed tomography (HR-pQCT) images, and typically have ignored evaluation of the post-yield behavior. The primary purpose of this work was threefold: (1) to provide an improved algorithm and program to assess TB yield as well as post-yield properties; (2) to explore the potential benefits of nonlinear μFEA beyond its linear counterpart; and (3) to assess the feasibility and practicality of performing nonlinear analysis on desktop computers on the basis of micro-magnetic resonance (μMR) images obtained in vivo in patients. Methods: A method for nonlinear μFE modeling of TB yield as well as post-yield behavior has been designed where material nonlinearity is captured by adjusting the tissue modulus iteratively according to the tissue-level effective strain obtained from linear analysis using a computationally optimized algorithm. The software allows for images at in vivo μMRI resolution as input with retention of grayscale information. Associations between axial stiffness estimated from linear analysis and yield as well as post-yield parameters from nonlinear analysis were investigated from in vivo μMR images of the distal tibia (N = 20; ages: 58-84) and radius (N = 20; ages: 50-75). Results: All simulations were completed in 1 h or less for 61 strain levels using a desktop computer (dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM). Although yield stress and ultimate stress correlated strongly (R 2 > 0.95, p < 0.001) with axial stiffness, toughness correlated moderately at the distal tibia (R 2 = 0.81, p < 0.001) and only weakly at the distal radius (R 2 = 0.34, p = 0.007). Further, toughness was found to vary by up to 16% for bone of very similar axial stiffness (<2%). Conclusions:The work demonstrates the practicality of nonlinear μFE simulations at in vivo μMRI resolution, as well as its potential for providing additional information beyond that obtainable from linear analysis. The data suggest that a direct assessment of toughness may provide information not captured by stiffness.

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confidence: 86%

Section: Introductionmentioning

confidence: 99%

Potential of in vivo MRI‐based nonlinear finite‐element analysis for the assessment of trabecular bone post‐yield properties

et al. 2013

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“…Second, the sensitivity of the load estimation algorithm with respect to the image resolution, location, and number of predefined unit loads was not yet thoroughly investigated. The effect of image resolution on the accuracy of micro-FE results, however, has been addressed in several earlier studies, and these studies found that for high-density bone in the femoral head, a resolution of 80 µm is adequate (Bevill and Keaveny 2009;Ulrich et al 1998;Van Rietbergen et al 1995). To further investigate this, we recently performed a pilot study using cubic bone microstructures.…”

Section: Discussionmentioning

confidence: 99%

Determination of hip-joint loading patterns of living and extinct mammals using an inverse Wolff’s law approach

Christen

Ito

Galis

et al. 2014

Biomech Model Mechanobiol

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“…FE calculations of apparent modulus were already expressed to be strongly influenced by the threshold used for segmentation of CT data to acquire the FE mesh Hara et al [20], and are highly sensitive to errors due to the strong relationship between volume fraction and mechanical properties. Bevill and Keaveny [21] they sought to settle whether forecasting of yield stress provided by nonlinear FE models could improve correlations with bone strength as compared to the application of anticipations of young modulus from linear FE models, and if this effect depended on a voxel size or bone volume fraction. Literature survey shows that there is no study addressed the effect of slice step size (shortly step size or slice thickness) on natural vibration properties of bone tissue.…”

Section: Introductionmentioning

confidence: 99%

Effect of Slice Step Size on Prediction of Natural Vibration Properties of Bone Tissue

Altıntaş

2012

MCA

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Abstract-Several vibration analysis procedures are used for determination of the level of bone loss, status of implant stability, modal damping factor and numerous other properties of tissues. The detection methods of bone properties are to compare the results of theoretical work with practical results. So, there are many options for processing of image data and establishing the finite element (FE) model that differentiation of calculated outputs is inevitable. Uncertainty of outputs can lead to mistakes while mechanical parameters or behaviors of tissue are determined. In this study, the effect of Micro-CT scanning intensity in connection with the reconstruction process on properties of the modal behavior of bone tissue were investigated. Results have shown that examined parameters have important effects on numerical values of the natural frequencies and modal behaviors. Furthermore, it has been revealed that numerical values and mode shapes must be considered together for properly understanding the natural vibration analysis of bone tissue.

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Trabecular bone strength predictions using finite element analysis of micro-scale images at limited spatial resolution

Cited by 115 publications

References 25 publications

Potential of in vivo MRI‐based nonlinear finite‐element analysis for the assessment of trabecular bone post‐yield properties

Potential of in vivo MRI‐based nonlinear finite‐element analysis for the assessment of trabecular bone post‐yield properties

Determination of hip-joint loading patterns of living and extinct mammals using an inverse Wolff’s law approach

Effect of Slice Step Size on Prediction of Natural Vibration Properties of Bone Tissue

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