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May 6, 2026Journal of Bronchology & Interventional Pulmonology1 citations

Distinguishing Tracheobronchomalacia and Excessive Dynamic Airway Collapse on Dynamic CT Images

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PAPaolo de AngelisJCJae ChoMRMartina Rama

Key Points

  • 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).

Abstract

BACKGROUND: Expiratory central airway collapse (ECAC) is caused by anterior displacement of the posterior membrane (EDAC) or weakening of the cartilaginous walls (TBM). Differentiating the 2 is challenging, resulting in misdiagnosis and missed opportunities for patients. We investigated how accurately providers identify each pathology on computed tomographic (CT) images. METHODS: Images from 100 patients who underwent tracheobronchoplasty (TBP) were reviewed by 4 airway experts and categorized into TBM, EDAC, normal airway, or unknown by majority consensus. Selected images of patients with TBM (n=9) and EDAC (n=9) were distributed to respondents. Linear regression was used to investigate overall accuracy; inter-rater agreement was measured using Fleiss' kappa (κ). RESULTS: We recruited 35 surgeons and 35 pulmonologists. Most practiced at an academic center (68.5%) and cared for patients with ECAC (61.4%). Among surgeons, 14 (40.0%) performed ≥5 complex airway cases yearly, and 13 (37.1%) performed TBP. Only 1 (1.5%) assigned the correct diagnosis to all 18 patients, while 13 (18.6%) identified <50.0% of the correct diagnoses. Inter-rater agreement for respondents was low (κ=0.21; 95% CI: 0.17-0.30; P<0.01). Predictors of accuracy included ≥10 years in practice (β=0.49; 95% CI: 0.03-0.95; P=0.03) and practicing pulmonology (β=0.72; 95% CI: 0.15-1.29; P=0.02). CONCLUSION: Distinguishing EDAC and TBM is challenging, with poor agreement among clinicians. Therefore, clinicians should consider referring any patient with ECAC early for multidisciplinary evaluation.

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Cite This Study

Angelis et al. (2026) studied this question.

synapsesocial.com/papers/69fadad703f892aec9b1e8a8https://doi.org/10.1097/lbr.0000000000001069
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