Diagnostic accuracy of rapid on-site evaluation in subtyping lung cancer via bronchoscopic biopsy

ROSE effectively differentiates benign from malignant lesions and accurately classifies SCLC and NSCLC during bronchoscopic biopsy. While useful for preliminary subtyping of SCC and AC, its reduced sensitivity for AC and challenges in central lesion evaluation limit its utility as a standalone diagnostic tool. ROSE remains critical for optimizing biopsy workflows and reducing repeat procedures.

Authors

Faguang Jin (ORCID: https://orcid.org/0000-0002-2466-3306)
Lei Pan (ORCID: https://orcid.org/0000-0002-7420-0991)
Shuang Yan (ORCID: https://orcid.org/0000-0001-8728-3039)
Hua Jiang (ORCID: https://orcid.org/0000-0003-4913-5793)
Li Gong (ORCID: https://orcid.org/0000-0002-4103-9468)

Institutions

Air Force Medical University (CN)

Publication Details

Journal: Frontiers in Oncology
Published: 2025-05-09
DOI: https://doi.org/10.3389/fonc.2025.1566666
Citations: 2
Primary Topic: Lung Cancer Diagnosis and Treatment
Type: article
Field-Weighted Citation Impact: 3.04

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article

Diagnostic accuracy of rapid on-site evaluation in subtyping lung cancer via bronchoscopic biopsy

Faguang Jin, Lei Pan, Shuang Yan, Hua Jiang et al.

May 9, 2025

2 citations

Frontiers in Oncology

Lung Cancer Diagnosis and Treatment

3.04

article

Diagnostic accuracy of rapid on-site evaluation in subtyping lung cancer via bronchoscopic biopsy

Faguang Jin, Lei Pan, Shuang Yan, Hua Jiang, Li Gong

May 9, 2025article en

2 citations

Abstract

ROSE effectively differentiates benign from malignant lesions and accurately classifies SCLC and NSCLC during bronchoscopic biopsy. While useful for preliminary subtyping of SCC and AC, its reduced sensitivity for AC and challenges in central lesion evaluation limit its utility as a standalone diagnostic tool. ROSE remains critical for optimizing biopsy workflows and reducing repeat procedures.

Frontiers in OncologyVol. 15

Air Force Medical University (CN)

Good health and well-being

Openalex Percentile: Top 10%

Lung Cancer Diagnosis and Treatment

3.04

DOI Open Access PDF OpenAlex

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