Treffer: Approach to implant monitoring and data processing with digital implant lifecycle management.

Title:
Approach to implant monitoring and data processing with digital implant lifecycle management.
Authors:
Denkena B; Institute of Production Engineering and Machine Tools, Leibniz University Hannover, An der Universität 2, 30823, Garbsen, Germany., Wichmann M; Institute of Production Engineering and Machine Tools, Leibniz University Hannover, An der Universität 2, 30823, Garbsen, Germany., Eggers ME; Institute of Production Engineering and Machine Tools, Leibniz University Hannover, An der Universität 2, 30823, Garbsen, Germany. eggers@ifw.uni-hannover.de., Emonde CK; Laboratory for Biomechanics and Biomaterials, Department of Orthopaedic Surgery Hanover Medical School, Anna-von-Borries-Strasse 1-7, 30625, Hannover, Germany., Hurschler C; Laboratory for Biomechanics and Biomaterials, Department of Orthopaedic Surgery Hanover Medical School, Anna-von-Borries-Strasse 1-7, 30625, Hannover, Germany.
Source:
Scientific reports [Sci Rep] 2025 Apr 29; Vol. 15 (1), pp. 15058. Date of Electronic Publication: 2025 Apr 29.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Imprint Name(s):
Original Publication: London : Nature Publishing Group, copyright 2011-
MeSH Terms:
Prostheses and Implants* , Electronic Data Processing*/methods, Humans ; Software ; Arthroplasty, Replacement, Knee ; Computer Simulation
References:
Knee Surg Relat Res. 2022 Mar 4;34(1):9. (PMID: 35246278)
Genome Med. 2019 Dec 31;12(1):4. (PMID: 31892363)
J Orthop Res. 2014 Apr;32(4):613-7. (PMID: 24395396)
J Pers Med. 2021 Jul 29;11(8):. (PMID: 34442389)
Clin Orthop Relat Res. 2007 Nov;464:205-9. (PMID: 18062052)
Contributed Indexing:
Keywords: Automatic monitoring; Condition-based maintenance; Database; Digital twin; Implant; Product lifecycle management; TKA
Entry Date(s):
Date Created: 20250429 Date Completed: 20250430 Latest Revision: 20250502
Update Code:
20250502
PubMed Central ID:
PMC12041358
DOI:
10.1038/s41598-025-99975-w
PMID:
40301673
Database:
MEDLINE

Weitere Informationen

Reducing implant failure rates is a primary research objective, involving the development of monitoring methods, new treatment options, improved manufacturing strategies, and innovative implant designs. The goal is to enhance product efficiency across generations by using information from previous iterations to improve patient outcomes. This paper aims to create an information management framework for implant-related data to enhance lifecycle monitoring. Strategies from product lifecycle management, condition-based maintenance, and the digital twin are applied to medical implant monitoring. The proposed digital implant lifecycle management concept records and processes data throughout the implant's lifecycle, from design and manufacturing to use and disposal. Implemented using an XML-data structure in simulation software, the concept focuses on manufacturing and monitoring, using total knee arthroplasty as an example. A simulation study demonstrates that the digital twin of the implant can simulate various manufacturing scenarios to optimize process parameters, reducing planning efforts for individual implants by up to 28%. The presented concept significantly improves implant and patient monitoring, enhances communication among stakeholders, and allows for scenario simulations to predict implant behaviour and improve future generations.
(© 2025. The Author(s).)

Declarations. Competing interests: The authors declare no competing interests.