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      Finite Element Simulation and Additive Manufacturing of Stiffness-Matched NiTi Fixation Hardware for Mandibular Reconstruction Surgery

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          Abstract

          Process parameters and post-processing heat treatment techniques have been developed to produce both shape memory and superelastic NiTi using Additive Manufacturing. By introducing engineered porosity, the stiffness of NiTi can be tuned to the level closely matching cortical bone. Using additively manufactured porous superelastic NiTi, we have proposed the use of patient-specific, stiffness-matched fixation hardware, for mandible skeletal reconstructive surgery. Currently, Ti-6Al-4V is the most commonly used material for skeletal fixation devices. Although this material offers more than sufficient strength for immobilization during the bone healing process, the high stiffness of Ti-6Al-4V implants can cause stress shielding. In this paper, we present a study of mandibular reconstruction that uses a dry cadaver mandible to validate our geometric and biomechanical design and fabrication (i.e., 3D printing) of NiTi skeletal fixation hardware. Based on the reference-dried mandible, we have developed a Finite Element model to evaluate the performance of the proposed fixation. Our results show a closer-to-normal stress distribution and an enhanced contact pressure at the bone graft interface than would be in the case with Ti-6Al-4V off-the-shelf fixation hardware. The porous fixation plates used in this study were fabricated by selective laser melting.

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          Manufacturing and processing of NiTi implants: A review

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            Fabrication of NiTi through additive manufacturing: A review

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              An accurate estimation of bone density improves the accuracy of subject-specific finite element models.

              An experimental-numerical study was performed to investigate the relationships between computed tomography (CT)-density and ash density, and between ash density and apparent density for bone tissue, to evaluate their influence on the accuracy of subject-specific FE models of human bones. Sixty cylindrical bone specimens were examined. CT-densities were computed from CT images while apparent and ash densities were measured experimentally. The CT/ash-density and ash/apparent-density relationships were calculated. Finite element models of eight human femurs were generated considering these relationships to assess their effect on strain prediction accuracy. CT and ash density were linearly correlated (R(2)=0.997) over the whole density range but not equivalent (intercep t 1). A constant ash/apparent-density ratio (0.598+/-0.004) was found for cortical bone. A lower ratio, with a larger dispersion, was found for trabecular bone (0.459+/-0.100), but it became less dispersed, and equal to that of cortical tissue, when testing smaller trabecular specimens (0.598+/-0.036). This suggests that an experimental error occurred in apparent-density measurements for large trabecular specimens and a constant ratio can be assumed valid for the whole density range. Introducing the obtained relationships in the FE modelling procedure improved strain prediction accuracy (R(2)=0.95, RMSE=7%). The results suggest that: (i) a correction of the densitometric calibration should be used when evaluating bone ash-density from clinical CT scans, to avoid ash-density underestimation and overestimation for low- and high-density bone tissue, respectively; (ii) the ash/apparent-density ratio can be assumed constant in human femurs and (iii) the correction improves significantly the model accuracy and should be considered in subject-specific bone modelling.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Bioengineering (Basel)
                Bioengineering (Basel)
                bioengineering
                Bioengineering
                MDPI
                2306-5354
                19 December 2016
                December 2016
                : 3
                : 4
                : 36
                Affiliations
                [1 ]Dynamic and Smart Systems Laboratory, The University of Toledo, Toledo, OH 43606, USA; ajahada@ 123456rockets.utoledo.edu (A.J.); Narges.ShayestehMoghaddam@ 123456rockets.utoledo.edu (N.S.M.); Amirhesam.Amerinatanzi@ 123456rockets.utoledo.edu (A.A.)
                [2 ]Department of Plastic Surgery, The Ohio State University, Columbus, OH 43212, USA; David.Dean@ 123456osumc.edu
                [3 ]Department of Mechanical Engineering, The University of Kentucky, Lexington, KY 40506, USA; karacahaluk@ 123456uky.edu
                Author notes
                [* ]Correspondence: mohammad.elahinia@ 123456utoledo.edu ; Tel: +1-419-530-8224
                Article
                bioengineering-03-00036
                10.3390/bioengineering3040036
                5597279
                28952598
                247fc066-6ff4-4c90-aad8-d8a6fb9478dd
                © 2016 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 06 November 2016
                : 14 December 2016
                Categories
                Article

                additive manufacturing (am),superelastic niti,porosity,mandibular reconstructive surgery,finite element analysis,stiffness matching

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