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Computational models for characterisation and design of patient-specific spinal implant

Capelli, C; Serra, T; Kalaskar, D; Leong, J; (2016) Computational models for characterisation and design of patient-specific spinal implant. The Spine Journal , 16 (4) S53-S54. 10.1016/j.spinee.2016.01.049. Green open access

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Abstract

BACKGROUND CONTEXT: Spinal fusion is designed to reduce movements between vertebrae and therefore pain. The most used devices for this procedure are mainly made of titanium or polyether ether ketone (PEEK). However, the mismatch between devices, with standard shapes and materials, and the surrounding bones can lead to suboptimal outcomes. Computational models, namely, Finite Element Analyses (FEA), can be employed to optimise existing device and design more effective solutions. PURPOSE: The goal of this study was to compare the performance of different materials and material densities for spinal cages, and to design a novel geometry which can ideally match the anatomical characteristics of a patient. STUDY DESIGN/SETTING: Computational. PATIENT SAMPLE: Nil. OUTCOME MEASURES: Nil. METHODS: FEA were set up to simulate compression (400 N) and bending (7.5 Nm) on a generic cage design. Three materials were modelled: titanium, PEEK and polycarbonate. Polycarbonate was included as widely available within additive manufacturing techniques. For each of the cages, four designs were modelled with varying material filling density. Furthermore, a new cage was modelled to match the pre-operative computed tomography (CT) of a patient exactly. The patient-specific cage was also tested by means of FEA. RESULTS: Stress distribution was compared between all the three materials tested. Consistently, stresses increased with reducing material density. Stress peak values were lower than the respective risk of failure in all the simulated cases, confirming the feasibility of polycarbonate implants. The patient-specific design showed even stress distribution consistently within anatomical constraints. CONCLUSIONS: Computational analyses suggested the feasibility of a lighter, cheaper and patient-specific cage for spinal fusion.

Type: Article
Title: Computational models for characterisation and design of patient-specific spinal implant
Event: 2016 BritSpine Biennial Scientific Congress of the United Kingdom Spine Societies
Location: Nottingham
Dates: 06 April 2016 - 08 April 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.spinee.2016.01.049
Publisher version: http://dx.doi.org/10.1016/j.spinee.2016.01.049
Language: English
Additional information: Copyright © 2016 Elsevier B.V. This manuscript is made available under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International license (CC BY-NC-ND 4.0). This license allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licenses are available at http://creativecommons.org/ licenses/by/4.0. Access may be initially restricted by the publisher.
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Ortho and MSK Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Cardiovascular Science > Children's Cardiovascular Disease
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Cardiovascular Science > Congenital Heart Disease
URI: https://discovery.ucl.ac.uk/id/eprint/1477009
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