Abstract
Rationale Flexible bronchoscopy is an operator dependent procedure. An automatic bronchial identification system based on artificial intelligence (AI) could help bronchoscopists to perform more complete and structured procedures through automatic guidance.
Methods 101 participants were included from six different continents at the European Respiratory Society annual conference in Milan, 9–13th September 2023. Participants were split into three groups based on experience: Novices (0 bronchoscopies), Intermediates (1-249 bronchoscopies), and Experienced (≥250 bronchoscopies). The participants performed two bronchoscopies on a realistic physical phantom, one with AI (AmbuBronchoSimulatorTrainingGUIDEv.0.0.1, Prototype version, Ambu) and one Standard procedure. The F1-group received AI-guidance for their first procedure, the F2-group for their second. A cross-over randomization controlled for learning by testing. All procedures were automatically rated according to the outcome measures: Inspected segments, Structured Progressions, and Procedure Time.
Results AI guidance caused the participants to inspect more segments, (mean difference, paired t-test: +6.0 segments, p<0.001), perform more Structured Progressions (+5.2 progressions, p<0.001), and spend more time on the procedure (+72 s, p<0.001) compared to their standard procedures. The effects of AI guidance on inspected segments and structured progression were highest for novices but significant for all experience groups: Novices (+8.2 segments, p=.012 and +6.6 progressions p<0.001), Intermediates (+5.7 segments, p=.006 and +5.1 progressions p<0.001, and Experienced (+4.3 segments, p=.006 and +3.8 progressions p<0.016).
Conclusions AI-guidance helped bronchoscopists of all experience levels to inspect more segments in a more structured order. Clinical implementation of AI guidance could help ensure and document more complete bronchoscopy procedures in the future.
Footnotes
This manuscript has recently been accepted for publication in the ERJ Open Research. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJOR online. Please open or download the PDF to view this article.
Conflict of interest: Dr. Kristoffer Mazanti Cold received funding from Ambu regarding The CoRS-feedback study in colonoscopy: NCT04862793. Professor, Dr Suveer Singh has received funding from Ambu A/S. Professor, Dr. Lars Konge has annotated clinical bronchoscopy videos for Ambu's development of the AI system. The other authors have no conflicts of interest to disclose.
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- Received April 16, 2024.
- Accepted August 16, 2024.
- Copyright ©The authors 2024
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