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Software development to optimize the minimal detectable difference in human airway images captured using optical

Carli M Peters1, Robert C Peters1, Anthony D Lee2

  • 1School of Kinesiology, Faculty of Education, University of British Columbia, Vancouver, Canada.

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|May 6, 2022
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Summary

A new semi-automated software tool enhances the analysis of optical coherence tomography (OCT) airway images. This tool improves measurement reproducibility and accuracy, aiding in the assessment of respiratory conditions.

Keywords:
airway areaairway lumenbronchilung, wall area percentage, wall thickness

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Area of Science:

  • Pulmonary Medicine
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Optical coherence tomography (OCT) is a non-ionizing radiation imaging technique suitable for high-resolution human airway assessment.
  • Manual analysis of OCT airway images exhibits significant inter- and intra-observer variability.
  • Accurate quantitative analysis is crucial for detecting airway structural changes.

Purpose of the Study:

  • To develop and validate a semi-automated software tool for analyzing OCT airway images.
  • To reduce inter- and intra-observer variability in OCT airway measurements.
  • To enhance the detection of airway differences and structural remodeling.

Main Methods:

  • Developed semi-automated software for OCT image processing, including grayscale conversion, image enhancement, and contour measurement.
  • Analyzed 140 OCT images from healthy volunteers (70 small airways <2mm, 70 medium airways 2-4mm).
  • Assessed inter- and intra-observer reproducibility and Bland-Altman bias for airway measurements.

Main Results:

  • Strong to very strong reproducibility was achieved for small airway measurements.
  • Moderate reproducibility was observed for medium airway measurements.
  • The software demonstrated lower minimal detectable differences compared to manual tracing in medium airways, with low Bland-Altman bias.

Conclusions:

  • The developed semi-automated software significantly improves the reproducibility and quantitative analysis of OCT airway images.
  • This tool has the potential to aid in quantifying airway remodeling in respiratory diseases and in elite athletes.
  • Further studies can leverage this software for more precise airway assessments.