Autofluorescence imaging-assisted medical thoracoscopy in the diagnosis of malignant pleural disease.


Journal

Respiratory medicine
ISSN: 1532-3064
Titre abrégé: Respir Med
Pays: England
ID NLM: 8908438

Informations de publication

Date de publication:
02 2023
Historique:
received: 06 09 2022
revised: 04 12 2022
accepted: 02 01 2023
pubmed: 8 1 2023
medline: 14 2 2023
entrez: 7 1 2023
Statut: ppublish

Résumé

Medical thoracoscopy (MT) does not always provide a conclusive diagnosis of pleural diseases because the endoscopic appearance of pleural diseases can be misleading. Autofluorescence imaging (AFI) is an effective assistive diagnostic tool. However, its clinical application for pleural disease remains controversial. This prospective study evaluated the clinical usefulness of AFI-assisted MT for diagnosis of malignant pleural diseases. Patients with unexplained pleural effusion admitted to our clinics between December 2018 and September 2021 were enrolled. We performed white-light thoracoscopy (WLT) first, and then AFI, during MT. Images of endoscopic real-time lesions were recorded under both modes. Pleural biopsy specimens were analyzed pathologically. Between-groups differences in diagnostic sensitivity, specificity, positive-predictive value (PPV), and negative-predictive value (NPV) were assessed using 95% confidence intervals (CI). Receiver operating characteristic curves and decision curve analyses were employed to analyze the diagnostic efficiency of these two modes. Of 126 eligible patients, 73 cases were diagnosed with malignant pleural disease. A total of 1292 biopsy specimens from 492 pleural sites were examined for pathological changes. The diagnostic sensitivity, PPV, and NPV of AFI were 99.7%, 58.2%, and 99.2%, respectively. AFI was significantly superior to WLT, which had a sensitivity of 79.7%, PPV of 50.7%, and NPV of 62.8%. Subgroup analysis showed that the AFI type III pattern was significantly more specific for pleural malignant disease than that of WLT. AFI could further improve the diagnostic efficacy of MT by providing better visualization, convenience, and safety.

Sections du résumé

BACKGROUND
Medical thoracoscopy (MT) does not always provide a conclusive diagnosis of pleural diseases because the endoscopic appearance of pleural diseases can be misleading. Autofluorescence imaging (AFI) is an effective assistive diagnostic tool. However, its clinical application for pleural disease remains controversial.
OBJECTIVES
This prospective study evaluated the clinical usefulness of AFI-assisted MT for diagnosis of malignant pleural diseases.
METHODS
Patients with unexplained pleural effusion admitted to our clinics between December 2018 and September 2021 were enrolled. We performed white-light thoracoscopy (WLT) first, and then AFI, during MT. Images of endoscopic real-time lesions were recorded under both modes. Pleural biopsy specimens were analyzed pathologically. Between-groups differences in diagnostic sensitivity, specificity, positive-predictive value (PPV), and negative-predictive value (NPV) were assessed using 95% confidence intervals (CI). Receiver operating characteristic curves and decision curve analyses were employed to analyze the diagnostic efficiency of these two modes.
RESULTS
Of 126 eligible patients, 73 cases were diagnosed with malignant pleural disease. A total of 1292 biopsy specimens from 492 pleural sites were examined for pathological changes. The diagnostic sensitivity, PPV, and NPV of AFI were 99.7%, 58.2%, and 99.2%, respectively. AFI was significantly superior to WLT, which had a sensitivity of 79.7%, PPV of 50.7%, and NPV of 62.8%. Subgroup analysis showed that the AFI type III pattern was significantly more specific for pleural malignant disease than that of WLT.
CONCLUSIONS
AFI could further improve the diagnostic efficacy of MT by providing better visualization, convenience, and safety.

Identifiants

pubmed: 36608860
pii: S0954-6111(23)00002-1
doi: 10.1016/j.rmed.2023.107114
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107114

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest This original research entitled “Autofluorescence imaging-assisted medical thoracoscopy in the diagnosis of malignant pleural disease “aimed to evaluate the value of autofluorescence imaging (AFI) in the assisted diagnosis of pleural diseases. This study was performed in accordance with the tenets of the Declaration of Helsinki. All adult participants provided written informed consent to participate in this study. We confirm that this paper has not been published in print or electronic form and is not under consideration by any other publication. All authors have contributed significantly to the content of the article. All authors have read and approved the submission of the manuscript to Respiratory Medicine. There are no ethical or undeclared conflicts of interest related to this article.

Auteurs

Feng Wang (F)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Lefei Zhou (L)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Zhen Wang (Z)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Lili Xu (L)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Yanbing Wu (Y)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Xue Li (X)

Department of Pathology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Xiaojian Qiu (X)

Department of Respiratory and Critical Care Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Songlin Zhao (S)

Department of Respiratory and Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.

Yushan Zheng (Y)

Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.

Zhiguo Jiang (Z)

Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.

Huanzhong Shi (H)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Zhaohui Tong (Z)

Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China. Electronic address: tongzhaohuicy@sina.com.

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