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Anatomic modeling using 3D printing: quality assurance and optimization

BACKGROUND: The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to asse...

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Autores principales: Leng, Shuai, McGee, Kiaran, Morris, Jonathan, Alexander, Amy, Kuhlmann, Joel, Vrieze, Thomas, McCollough, Cynthia H., Matsumoto, Jane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5954797/
https://www.ncbi.nlm.nih.gov/pubmed/29782614
http://dx.doi.org/10.1186/s41205-017-0014-3
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author Leng, Shuai
McGee, Kiaran
Morris, Jonathan
Alexander, Amy
Kuhlmann, Joel
Vrieze, Thomas
McCollough, Cynthia H.
Matsumoto, Jane
author_facet Leng, Shuai
McGee, Kiaran
Morris, Jonathan
Alexander, Amy
Kuhlmann, Joel
Vrieze, Thomas
McCollough, Cynthia H.
Matsumoto, Jane
author_sort Leng, Shuai
collection PubMed
description BACKGROUND: The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis. RESULTS: A phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm. CONCLUSIONS: A comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications.
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spelling pubmed-59547972018-05-18 Anatomic modeling using 3D printing: quality assurance and optimization Leng, Shuai McGee, Kiaran Morris, Jonathan Alexander, Amy Kuhlmann, Joel Vrieze, Thomas McCollough, Cynthia H. Matsumoto, Jane 3D Print Med Research BACKGROUND: The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis. RESULTS: A phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm. CONCLUSIONS: A comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications. Springer International Publishing 2017-04-26 /pmc/articles/PMC5954797/ /pubmed/29782614 http://dx.doi.org/10.1186/s41205-017-0014-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Leng, Shuai
McGee, Kiaran
Morris, Jonathan
Alexander, Amy
Kuhlmann, Joel
Vrieze, Thomas
McCollough, Cynthia H.
Matsumoto, Jane
Anatomic modeling using 3D printing: quality assurance and optimization
title Anatomic modeling using 3D printing: quality assurance and optimization
title_full Anatomic modeling using 3D printing: quality assurance and optimization
title_fullStr Anatomic modeling using 3D printing: quality assurance and optimization
title_full_unstemmed Anatomic modeling using 3D printing: quality assurance and optimization
title_short Anatomic modeling using 3D printing: quality assurance and optimization
title_sort anatomic modeling using 3d printing: quality assurance and optimization
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5954797/
https://www.ncbi.nlm.nih.gov/pubmed/29782614
http://dx.doi.org/10.1186/s41205-017-0014-3
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