Nuclear medicine technologists practice impacted by AI denoising applications in PET/CT images.

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State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_4DA95180161F
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Nuclear medicine technologists practice impacted by AI denoising applications in PET/CT images.
Journal
Radiography
Author(s)
Champendal M., Ribeiro RST, Müller H., Prior J.O., Sá Dos Reis C.
ISSN
1532-2831 (Electronic)
ISSN-L
1078-8174
Publication state
Published
Issued date
07/2024
Peer-reviewed
Oui
Volume
30
Number
4
Pages
1232-1239
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
Artificial intelligence (AI) in positron emission tomography/computed tomography (PET/CT) can be used to improve image quality when it is useful to reduce the injected activity or the acquisition time. Particular attention must be paid to ensure that users adopt this technological innovation when outcomes can be improved by its use. The aim of this study was to identify the aspects that need to be analysed and discussed to implement an AI denoising PET/CT algorithm in clinical practice, based on the representations of Nuclear Medicine Technologists (NMT) from Western-Switzerland, highlighting the barriers and facilitators associated.
Two focus groups were organised in June and September 2023, involving ten voluntary participants recruited from all types of medical imaging departments, forming a diverse sample of NMT. The interview guide followed the first stage of the revised model of Ottawa of Research Use. A content analysis was performed following the three-stage approach described by Wanlin. Ethics cleared the study.
Clinical practice, workload, knowledge and resources were de 4 themes identified as necessary to be thought before implementing an AI denoising PET/CT algorithm by ten NMT participants (aged 31-60), not familiar with this AI tool. The main barriers to implement this algorithm included workflow challenges, resistance from professionals and lack of education; while the main facilitators were explanations and the availability of support to ask questions such as a "local champion".
To implement a denoising algorithm in PET/CT, several aspects of clinical practice need to be thought to reduce the barriers to its implementation such as the procedures, the workload and the available resources. Participants emphasised also the importance of clear explanations, education, and support for successful implementation.
To facilitate the implementation of AI tools in clinical practice, it is important to identify the barriers and propose strategies that can mitigate it.
Keywords
Humans, Positron Emission Tomography Computed Tomography/methods, Focus Groups, Artificial Intelligence, Nuclear Medicine, Algorithms, Workload, Male, Female, AI readiness, Adoption, Artificial intelligence, Clinical practice, Image denoising, Implementation, PET/CT
Pubmed
Open Access
Yes
Create date
28/06/2024 12:27
Last modification date
10/07/2024 7:05
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