Manufacture of Biomimetic Auricular Surgical Implants Using 3D Printed High Density Polyethylene Microfibers
Open access copy at publisher website
Description
This study demonstrates a new approach to manufacturing biomimetic auricular surgical implants using melt electrowriting (MEW) technology to fabricate microfiber high-density polyethylene (HDPE) scaffolds. An emerging filament-driven printhead and MEW printer, termed the “MEWron”, is used to enable precise control over the material extrusion process and fiber formation. By predicting the optimal extrusion conditions, continuous and uninterrupted fiber production is achieved, enabling further optimization of filament-driven MEW fibers with a diameter of 60.5 ± 2.6 µm. As a case study, an application of microfiber HDPE fabrication is selected that comprised the design and fabrication of personalized auricular (ear) surgical implants, specifically tailored to match the unique morphology of individual patients. Patient-specific implant models matched to the natural shape and structure of the human ear are successfully fabricated. Furthermore, the manufactured implants exhibit excellent mechanical properties, offering a 13-fold increase in tensile stiffness compared to MEW PCL scaffolds. Overall, this research demonstrates the feasibility and potential of MEW-based HDPE implants as a promising alternative to traditional auricular reconstruction methods, offering an alternative avenue for improved patient outcomes and enhanced aesthetic results.
Impact and interest:
Citation counts are sourced monthly from Scopus and Web of Science® citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
ID Code: | 245483 | ||||
---|---|---|---|---|---|
Item Type: | Contribution to Journal (Journal Article) | ||||
Refereed: | Yes | ||||
ORCID iD: |
|
||||
Additional Information: | Acknowledgements: The authors kindly acknowledge Taavet Kangur and Sönke Menke (University of Oregon) for their developmental work in filament extrusion modeling. Funding support was received from the Phil and Penny Knight Campus for Accelerating Scientific Impact, Wu Tsai Human Performance Alliance and the Joe and Clara Wu Foundation. NCP is supported by the Knight Campus-PeaceHealth Postdoctoral Fellowship Program and an Advance Queensland Industry Research Fellowship (AQIRF2020). PGS is supported by funding from the University of the Basque Country (UPV/EHU) for the Margarita Salas postdoctoral grant financed by the European Union – Next generation EU. PDD is supported by the Bradshaw and Holzapfel Research Professor in Transformational Science and Mathematics Fund. Some of the data reported in this paper were obtained at the Central Analytical Research Facility operated by Research Infrastructure (QUT). Open access publishing facilitated by Queensland University of Technology, as part of the Wiley - Queensland University of Technology agreement via the Council of Australian University Librarians. | ||||
Measurements or Duration: | 8 pages | ||||
Keywords: | mechanical testing, melt electrowriting, polyethylene, surgical implant | ||||
DOI: | 10.1002/admt.202301190 | ||||
ISSN: | 2365-709X | ||||
Pure ID: | 154913211 | ||||
Divisions: | Current > Research Centres > Centre for Biomedical Technologies Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Mechanical, Medical & Process Engineering |
||||
Funding Information: | The authors kindly acknowledge Taavet Kangur and Sönke Menke (University of Oregon) for their developmental work in filament extrusion modeling. Funding support was received from the Phil and Penny Knight Campus for Accelerating Scientific Impact, Wu Tsai Human Performance Alliance and the Joe and Clara Wu Foundation. NCP is supported by the Knight Campus‐PeaceHealth Postdoctoral Fellowship Program and an Advance Queensland Industry Research Fellowship (AQIRF2020). PGS is supported by funding from the University of the Basque Country (UPV/EHU) for the Margarita Salas postdoctoral grant financed by the European Union – Next generation EU. PDD is supported by the Bradshaw and Holzapfel Research Professor in Transformational Science and Mathematics Fund. Some of the data reported in this paper were obtained at the Central Analytical Research Facility operated by Research Infrastructure (QUT). | ||||
Copyright Owner: | 2023 The Authors | ||||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
Deposited On: | 11 Jan 2024 23:05 | ||||
Last Modified: | 26 Jul 2024 15:21 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page