Evidence map›Paper›PMID 42291365›Full record

ArticleTranslational lung cancer research2026

3D computed tomography airway geometry for predicting bronchoscopic accessibility in peripheral pulmonary nodules: a prospective study.

Byeong-Ho Jeong, Jonghoon Kim, Hwanho Cho, Youjin Oh, Ho Yun Lee

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Article in Translational lung cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Byeong-Ho Jeong *Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Jonghoon Kim *Department of Health Sciences and Technology, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea.
Hwanho ChoDepartment of Electronics Engineering, Incheon National University, Incheon, Republic of Korea.
Youjin OhDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea.
Ho Yun LeeDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bronchoscopic diagnosis of peripheral pulmonary nodules (PPNs) using radial probe endobronchial ultrasound (rEBUS) has been widely studied. However, the prospective utility of computed tomography (CT)-derived airway geometrical analysis for predicting rEBUS accessibility remains underexplored. This study aimed to determine whether quantitative CT airway geometric characteristics can improve preprocedural planning by predicting the bronchoscopic accessibility of PPNs. Methods: The accessibility of 219 PPNs in 199 patients to rEBUS was prospectively evaluated as easily accessible or difficult/inaccessible. Preprocedural airway geometry was quantified from individual CT scans and used both to guide the procedure and develop predictive models using logistic-least absolute shrinkage and selection operator (LASSO) analyses. Model performance was assessed using the area under the curve (AUC). Results: Of the 219 PPNs, 182 (83.1%) were easily accessible, and 37 (16.9%) were difficult or inaccessible. The mean age was 68.7 (±10.3) years, the average size of the PPNs was 24.5 (±16.1) mm, the mean distance from the pleural surface was 10.8 (±12.5) mm, and 83.1% showed a 'within' bronchus sign. Airway geometrical features-including more acute bifurcation angles, more sharply curved branches, and more elliptical and narrower lumen shapes-were significant risk factors for limited bronchoscopic access. A composite model incorporating these features with clinical variables achieved the highest performance (AUC =0.84), better than both the clinical model (AUC =0.68) and the airway geometrical model (AUC =0.79). Conclusions: CT-based quantitative airway analysis enhances the prediction of PPN accessibility to rEBUS and could support more accurate procedural planning in clinical practice.

Indexed as

accessibilityairway geometryPeripheral pulmonary nodule (PPN)quantitative computed tomography (quantitative CT)radial probe endobronchial ultrasound (rEBUS)

Identifiers

PMID42291365
PMCPMC13263827

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.