What question did this study set out to answer?

The aim is to evaluate how accurately clinicians distinguish between tracheobronchomalacia and excessive dynamic airway collapse on CT images.

Distinguishing Tracheobronchomalacia and Excessive Dynamic Airway Collapse on Dynamic CT Images

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Randomized trial investigates accuracy of diagnosing airway collapse types in clinicians, suggesting a need for early evaluation.

The aim is to evaluate how accurately clinicians distinguish between tracheobronchomalacia and excessive dynamic airway collapse on CT images.
Analysed CT images of 100 patients who underwent tracheobronchoplasty with input from 4 airway experts.
Images were classified into categories: tracheobronchomalacia, excessive dynamic airway collapse, normal, or unknown based on majority consensus.
Inter-rater agreement calculated using Fleiss' kappa, and linear regression assessed accuracy predictors.
Only 1 out of 70 clinicians correctly diagnosed all patients, while 18.6% identified less than 50% accurately.
Low inter-rater agreement observed (κ=0.21; 95% CI: 0.17-0.30; P<0.01).
Experience and subspecialty practice (≥10 years; pulmonology) correlated with diagnostic accuracy (P=0.03; P=0.02).

Angelis et al. (2026) studied this question.

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View Full Paper

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Authors

Randomized trial investigates accuracy of diagnosing airway collapse types in clinicians, suggesting a need for early evaluation.

The aim is to evaluate how accurately clinicians distinguish between tracheobronchomalacia and excessive dynamic airway collapse on CT images.
Analysed CT images of 100 patients who underwent tracheobronchoplasty with input from 4 airway experts.
Images were classified into categories: tracheobronchomalacia, excessive dynamic airway collapse, normal, or unknown based on majority consensus.
Inter-rater agreement calculated using Fleiss' kappa, and linear regression assessed accuracy predictors.
Only 1 out of 70 clinicians correctly diagnosed all patients, while 18.6% identified less than 50% accurately.
Low inter-rater agreement observed (κ=0.21; 95% CI: 0.17-0.30; P<0.01).
Experience and subspecialty practice (≥10 years; pulmonology) correlated with diagnostic accuracy (P=0.03; P=0.02).

Angelis et al. (2026) studied this question.

View Full Paper

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