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Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms

Franck Lacan, Richard Johnston Orcid Logo, Rhys Carrington, Emiliano Spezi, Peter Theobald Orcid Logo

Journal of Medical Engineering & Technology, Volume: 47, Issue: 3, Pages: 189 - 196

Swansea University Author: Richard Johnston Orcid Logo

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DOI (Published version): 10.1080/03091902.2023.2193267

Abstract

The design freedom afforded by additive manufacturing (AM) is now being leveraged across multiple applications, including many in the fields of imaging for personalised medicine. This study utilises a pellet-fed, multi-material AM machine as a route to fabricating new imaging phantoms, used for deve...

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Published in: Journal of Medical Engineering & Technology
ISSN: 0309-1902 1464-522X
Published: Informa UK Limited 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa62973
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This study utilises a pellet-fed, multi-material AM machine as a route to fabricating new imaging phantoms, used for developing and refining algorithms for the detection of subtle soft tissue anomalies. Traditionally comprising homogeneous materials, higher resolution scanning now allows for heterogeneous, multi-material phantoms. Polylactic acid (PLA), a thermoplastic urethane (TPU) and a thermoplastic elastomer (TPE) were investigated as potential materials. Manufacturing accuracy and precision was assessed relative to the digital design file, whilst potential to achieve structural heterogeneity was evaluated by quantifying infill density via micro-computer tomography. Hounsfield units (HU) were also captured via a clinical scanner. The PLA builds were consistently too small, by 0.2 – 0.3%. Conversely, TPE parts were consistently larger than the digital file, though by only 0.1%. The TPU components had negligible difference relative to the specified sizes. The accuracy and precision of material infill was inferior, with PLA exhibiting greater and lower densities relative to the digital file, across the 3 builds. Both TPU and TPE produced infills that were too dense. The PLA material produced repeatable HU values, with poorer precision across TPU and TPE. All HU values tended towards, and some exceeded, the reference value for water (0 HU) with increasing infill density. These data have demonstrated that pellet-fed AM can produce accurate and precise structures, with the potential to include multiple materials providing opportunity for more realistic and advanced phantom designs. 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spelling v2 62973 2023-03-17 Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms 23282e7acce87dd926b8a62ae410a393 0000-0003-1977-6418 Richard Johnston Richard Johnston true false 2023-03-17 MTLS The design freedom afforded by additive manufacturing (AM) is now being leveraged across multiple applications, including many in the fields of imaging for personalised medicine. This study utilises a pellet-fed, multi-material AM machine as a route to fabricating new imaging phantoms, used for developing and refining algorithms for the detection of subtle soft tissue anomalies. Traditionally comprising homogeneous materials, higher resolution scanning now allows for heterogeneous, multi-material phantoms. Polylactic acid (PLA), a thermoplastic urethane (TPU) and a thermoplastic elastomer (TPE) were investigated as potential materials. Manufacturing accuracy and precision was assessed relative to the digital design file, whilst potential to achieve structural heterogeneity was evaluated by quantifying infill density via micro-computer tomography. Hounsfield units (HU) were also captured via a clinical scanner. The PLA builds were consistently too small, by 0.2 – 0.3%. Conversely, TPE parts were consistently larger than the digital file, though by only 0.1%. The TPU components had negligible difference relative to the specified sizes. The accuracy and precision of material infill was inferior, with PLA exhibiting greater and lower densities relative to the digital file, across the 3 builds. Both TPU and TPE produced infills that were too dense. The PLA material produced repeatable HU values, with poorer precision across TPU and TPE. All HU values tended towards, and some exceeded, the reference value for water (0 HU) with increasing infill density. These data have demonstrated that pellet-fed AM can produce accurate and precise structures, with the potential to include multiple materials providing opportunity for more realistic and advanced phantom designs. In doing so, this will enable clinical scientists to develop more sensitive applications aimed at detecting ever more subtle variations in tissue, confident that their calibration models reflect their intended designs. Journal Article Journal of Medical Engineering & Technology 47 3 189 196 Informa UK Limited 0309-1902 1464-522X Precision medicine, Imaging phantom, Multi-material deposition, Accuracy, Image registration 3 4 2023 2023-04-03 10.1080/03091902.2023.2193267 http://dx.doi.org/10.1080/03091902.2023.2193267 COLLEGE NANME Materials Science and Engineering COLLEGE CODE MTLS Swansea University The microCT work was supported by the Advanced Imaging of Materials (AIM) core facility (EPSRC Grant No. EP/M028267/1), the Welsh Government Enhancing Competitiveness Grant (MA/KW/5554/19), and the European Social Fund (ESF) through the European Union’s Convergence programme administered by the Welsh Government. 2023-06-12T14:40:26.4587626 2023-03-17T08:57:21.1644967 Faculty of Science and Engineering School of Engineering and Applied Sciences - Materials Science and Engineering Franck Lacan 1 Richard Johnston 0000-0003-1977-6418 2 Rhys Carrington 3 Emiliano Spezi 4 Peter Theobald 0000-0002-3227-7130 5 62973__27751__19ace16f5355494496d50d7f9f05a452.pdf 62973.pdf 2023-06-07T14:39:56.7562709 Output 1828053 application/pdf Version of Record true © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. true eng http://creativecommons.org/licenses/by/4.0/
title Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
spellingShingle Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
Richard Johnston
title_short Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
title_full Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
title_fullStr Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
title_full_unstemmed Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
title_sort Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms
author_id_str_mv 23282e7acce87dd926b8a62ae410a393
author_id_fullname_str_mv 23282e7acce87dd926b8a62ae410a393_***_Richard Johnston
author Richard Johnston
author2 Franck Lacan
Richard Johnston
Rhys Carrington
Emiliano Spezi
Peter Theobald
format Journal article
container_title Journal of Medical Engineering & Technology
container_volume 47
container_issue 3
container_start_page 189
publishDate 2023
institution Swansea University
issn 0309-1902
1464-522X
doi_str_mv 10.1080/03091902.2023.2193267
publisher Informa UK Limited
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Materials Science and Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Materials Science and Engineering
url http://dx.doi.org/10.1080/03091902.2023.2193267
document_store_str 1
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description The design freedom afforded by additive manufacturing (AM) is now being leveraged across multiple applications, including many in the fields of imaging for personalised medicine. This study utilises a pellet-fed, multi-material AM machine as a route to fabricating new imaging phantoms, used for developing and refining algorithms for the detection of subtle soft tissue anomalies. Traditionally comprising homogeneous materials, higher resolution scanning now allows for heterogeneous, multi-material phantoms. Polylactic acid (PLA), a thermoplastic urethane (TPU) and a thermoplastic elastomer (TPE) were investigated as potential materials. Manufacturing accuracy and precision was assessed relative to the digital design file, whilst potential to achieve structural heterogeneity was evaluated by quantifying infill density via micro-computer tomography. Hounsfield units (HU) were also captured via a clinical scanner. The PLA builds were consistently too small, by 0.2 – 0.3%. Conversely, TPE parts were consistently larger than the digital file, though by only 0.1%. The TPU components had negligible difference relative to the specified sizes. The accuracy and precision of material infill was inferior, with PLA exhibiting greater and lower densities relative to the digital file, across the 3 builds. Both TPU and TPE produced infills that were too dense. The PLA material produced repeatable HU values, with poorer precision across TPU and TPE. All HU values tended towards, and some exceeded, the reference value for water (0 HU) with increasing infill density. These data have demonstrated that pellet-fed AM can produce accurate and precise structures, with the potential to include multiple materials providing opportunity for more realistic and advanced phantom designs. In doing so, this will enable clinical scientists to develop more sensitive applications aimed at detecting ever more subtle variations in tissue, confident that their calibration models reflect their intended designs.
published_date 2023-04-03T14:40:25Z
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