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Related Concept Videos

Endoscopic Studies I: Bronchoscopy and Thoracoscopy01:30

Endoscopic Studies I: Bronchoscopy and Thoracoscopy

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Endoscopy is a non-surgical medical technique used to examine a person's internal organs and vessels. This lesson will focus on two types of endoscopic studies: bronchoscopy and thoracoscopy.
Bronchoscopy
Description
Bronchoscopy is a procedure that involves direct visualization of the larynx, trachea, and bronchi for diagnostic and therapeutic purposes. A flexible fiber optic or rigid bronchoscope is used to carry out the procedure. The fiber-optic bronchoscope is more frequently used due...
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  3. Artificial Intelligence Improves Bronchoscopy Performance: A Randomised Crossover Trial
  1. Home
  3. Artificial Intelligence Improves Bronchoscopy Performance: A Randomised Crossover Trial

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Artificial intelligence improves bronchoscopy performance: a randomised crossover trial

Kristoffer Mazanti Cold1,2, Kaladerhan Agbontaen3, Anne Orholm Nielsen1,2,4

  • 1Copenhagen Academy for Medical Education and Simulation, Rigshospitalet, The Capital Region of Denmark, Copenhagen, Denmark.

ERJ Open Research
|January 24, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

Artificial intelligence (AI) guidance significantly improved flexible bronchoscopy by increasing inspected segments and structured progressions for all experience levels. This AI system enhances procedural completeness and documentation for future clinical use.

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Area of Science:

  • Pulmonology
  • Medical Technology
  • Artificial Intelligence

Background:

  • Flexible bronchoscopy is a complex, operator-dependent procedure.
  • Enhancing procedural completeness and structure is crucial for effective diagnosis and treatment.
  • Automatic guidance systems can potentially standardize and improve bronchoscopy outcomes.

Purpose of the Study:

  • To evaluate the impact of an AI-driven guidance system on flexible bronchoscopy performance.
  • To assess whether AI guidance improves procedural completeness and structure across different experience levels.

Main Methods:

  • A randomized crossover study involving 101 participants with varying bronchoscopy experience.
  • Participants performed two bronchoscopies on a physical phantom, one with AI guidance and one standard procedure.
  • Outcomes measured included inspected segments, structured progressions, and procedure time, with automated rating.

    • Main Results:

    • AI guidance led to a significant increase in inspected segments (+6.0) and structured progressions (+5.2) compared to standard procedures (p<0.001).
    • These improvements were observed across all experience groups (novices, intermediates, experienced), with the most pronounced effects in novices.
    • AI guidance also increased procedure time (+72s, p<0.001).

    Conclusions:

    • AI guidance enhances the completeness and structure of flexible bronchoscopy for all skill levels.
    • The findings suggest that AI guidance can be a valuable tool for standardizing and improving bronchoscopy procedures.
    • Clinical implementation of AI could ensure more thorough and documented bronchoscopies in the future.