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      A Cortical Thickness Mapping Method for the Coxal Bone Using Morphing

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          Abstract

          As human body finite element models become more integrated with the design of safety countermeasures and regulations, novel models need to be developed that reflect the variation in the population's anthropometry. However, these new models may be missing information which will need to be translated from existing models. During the development of a 5th percentile female occupant model (F05), cortical thickness information of the coxal bone was unavailable due to resolution limits in the computed tomography (CT) scans. In this study, a method for transferring cortical thickness information from a source to a target model with entirely different geometry and architecture is presented. The source and target models were the Global Human Body Models Consortium (GHBMC) 50th percentile male (M50) and F05 coxal bones, respectively. To project the coxal bone cortical thickness from the M50 to the F05, the M50 model was first morphed using a Kriging method with 132 optimized control points to the F05 anthropometry. This technique was found to be accurate with a mean nodal discrepancy of 1.27 mm between the F05 and morphed M50 (mM50) coxal bones. Cortical thickness at each F05 node was determined by taking the average cortical thickness of every mM50 node, non-linearly weighted by its distance to the F05 nodes. The non-linear weighting coefficient, β, had a large effect on the accuracy and smoothness of the projected cortical bone thickness. The optimal projection had β = 4 and was defined when the tradeoff between projection accuracy and smoothness was equal. Finally, a quasi-static pelvis compression was simulated to examine to effect of β. As β, increased from 0 to 4, the failure force decreased by ~100 N, whereas the failure displacement increased by 0.9 mm. Results from quasi-static compression tests of the F05 pelvis were comparable to experimental results. This method could be applied to other anatomical regions where cortical thickness variation is important, such as the femur and ribs and is not limited to GHBMC-family models. Furthermore, this process will aid the development of subject-specific finite element models where accurate cortical bone thickness measurements cannot be obtained.

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          Most cited references30

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          Subject-specific finite element model of the pelvis: development, validation and sensitivity studies.

          A better understanding of the three-dimensional mechanics of the pelvis, at the patient-specific level, may lead to improved treatment modalities. Although finite element (FE) models of the pelvis have been developed, validation by direct comparison with subject-specific strains has not been performed, and previous models used simplifying assumptions regarding geometry and material properties. The objectives of this study were to develop and validate a realistic FE model of the pelvis using subject-specific estimates of bone geometry, location-dependent cortical thickness and trabecular bone elastic modulus, and to assess the sensitivity of FE strain predictions to assumptions regarding cortical bone thickness as well as bone and cartilage material properties. A FE model of a cadaveric pelvis was created using subject-specific computed tomography image data. Acetabular loading was applied to the same pelvis using a prosthetic femoral stem in a fashion that could be easily duplicated in the computational model. Cortical bone strains were monitored with rosette strain gauges in ten locations on the left hemipelvis. FE strain predictions were compared directly with experimental results for validation. Overall, baseline FE predictions were strongly correlated with experimental results (r2=0.824), with a best-fit line that was not statistically different than the line y=x (experimental strains = FE predicted strains). Changes to cortical bone thickness and elastic modulus had the largest effect on cortical bone strains. The FE model was less sensitive to changes in all other parameters. The methods developed and validated in this study will be useful for creating and analyzing patient-specific FE models to better understand the biomechanics of the pelvis.
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            A review of geometric transformations for nonrigid body registration.

            This paper provides a comprehensive and quantitative review of spatial transformations models for nonrigid image registration. It explains the theoretical foundation of the models and classifies them according to this basis. This results in two categories, physically based models described by partial differential equations of continuum mechanics (e.g., linear elasticity and fluid flow) and basis function expansions derived from interpolation and approximation theory (e.g., radial basis functions, B-splines and wavelets). Recent work on constraining the transformation so that it preserves the topology or is diffeomorphic is also described. The final section reviews some recent evaluation studies. The paper concludes by explaining under what conditions a particular transformation model is appropriate.
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              Accuracy limits for the determination of cortical width and density: the influence of object size and CT imaging parameters.

              In this study we analysed the accuracy of computed tomography (CT) measurements in assessing cortical bone. We determined the dependency of thickness and density measurements on the true width and density of the cortex and on the spatial resolution in the CT images using two optimized segmentation methods. As a secondary goal, we assessed the ability of CT to reflect small changes in cortical thickness. Two different bone-mimicking phantoms with varying cortical thickness were scanned with single-slice CT on a Somatom Plus 4 scanner. Images were reconstructed with both a standard and a high-resolution convolution kernel. Two special operator-independent segmentation methods were used to automatically detect the edges of the cortical shell. We measured cortical thickness and density and compared the phantom measurements with theoretical computations by simulating a cross-sectional shape of the cortical shell. Based on the simulations, we calculated CT's power to detect small changes in cortical thickness. Simulations and phantom measurements were in very good agreement. Cortical thickness could be measured with an error of less than 10% if the true thickness was larger than 0.9 (0.7) mm for the standard (high-resolution) kernel which is close to the full width at half maximum (FWHM) of the point spread functions for these kernels and our scanner. Density measurements yielded errors of less than 10% for true cortical thickness values above two to three times the FWHM corresponding to 2.5 (2) mm in our case. The simulations showed that a 10% change in cortical width would not be detected with satisfying probability in bones with a cortical shell thinner than 1.2 mm. An accurate determination of the cortical thickness is limited to bones with a thickness higher than the FWHM of the scanner's point spread function. Therefore, the use of a high-resolution reconstruction kernel is crucial. Cortical bone mineral density can only be measured accurately in bones two to three times thicker than this number. In thinner bones, the measured density becomes dependent on the thickness. Changes in cortical thickness can only be assessed if the change is rather large or if the measured bone has sufficient thickness. Therefore, assessing density or thickness of the vertebral shell by CT should be treated with caution.
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                Author and article information

                Contributors
                Journal
                Front Bioeng Biotechnol
                Front Bioeng Biotechnol
                Front. Bioeng. Biotechnol.
                Frontiers in Bioengineering and Biotechnology
                Frontiers Media S.A.
                2296-4185
                18 October 2018
                2018
                : 6
                : 149
                Affiliations
                Department of Mechanical and Aerospace Engineering, Center for Applied Biomechanics, University of Virginia , Charlottesville, VA, United States
                Author notes

                Edited by: Stefan Scheiner, Technische Universität Wien, Austria

                Reviewed by: Pascal Buenzli, School of Mathematical Sciences, Queensland University of Technology, Australia; Enrico Dall'Ara, University of Sheffield, United Kingdom

                *Correspondence: Matthew B. Panzer panzer@ 123456virginia.edu

                This article was submitted to Biomechanics, a section of the journal Frontiers in Bioengineering and Biotechnology

                Article
                10.3389/fbioe.2018.00149
                6200845
                36321630-c975-4f29-8046-b8db91f79d0a
                Copyright © 2018 Giudice, Poulard, Nie, Wu and Panzer.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 08 June 2018
                : 28 September 2018
                Page count
                Figures: 8, Tables: 1, Equations: 8, References: 31, Pages: 9, Words: 5894
                Categories
                Bioengineering and Biotechnology
                Original Research

                pelvis,finite element modeling,kriging,ghbmc,human body modeling,cortical bone

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