Accuracy and Reproducibility of Endoscopic Ultrasound B-Mode Features for Observer-Based Lymph Nodal Malignancy Prediction.

Bronchoscopy Cancer Endobronchial ultrasound Endobronchial ultrasound-transbronchial needle aspiration Endoscopic ultrasound Esophageal ultrasound Lung cancer staging Lymph node staging Nonsmall-cell lung cancer Observer variability

Journal

Respiration; international review of thoracic diseases
ISSN: 1423-0356
Titre abrégé: Respiration
Pays: Switzerland
ID NLM: 0137356

Informations de publication

Date de publication:
Historique:
received: 16 11 2020
accepted: 06 04 2021
pubmed: 25 6 2021
medline: 17 5 2022
entrez: 24 6 2021
Statut: ppublish

Résumé

Endoscopic ultrasound routinely guides lymph node evaluation for the staging of a known or suspected lung cancer. Characteristics seen on B-mode imaging might help the observer decide on the lymph nodes of risk. The influence of nodal size on the predictivity of these characteristics and the agreement with which operators can combine these for malignancy risk prediction is to be determined. We evaluated (1) if prospectively scored individual B-mode ultrasound features predict malignancy when further divided by size and (2) assessed if observers were able to reproducibly agree on still lymph node image malignancy risk. Lymph nodes as visualized by EBUS were prospectively scored for B-mode characteristics. Still B-mode images were furthermore collected. After collection, a repeated scoring of a subset of lymph nodes was retrospectively performed (n = 11 observers). Analysis of 490 lymph nodes revealed the short axis size is an objective measure for stratifying risk of malignancy (ROC area under the curve 0.78). With ≥8-mm size, 210/237 malignant lymph nodes were correctly identified (89% sensitivity, 46% specificity, 61% PPV, and 81% NPV). Secondary addition of B-mode features in <8-mm nodes had limited value. Retrospective analysis of intra- and interobserver scoring furthermore revealed significant disagreement. Lymph nodes of ≥8-mm size and preferably even smaller should be aspirated regardless of other B-mode features. Observer disagreement in scoring both small and large lymph nodes suggests it is infeasible to include subjective features for stratification. Future research should focus on (integrating) other (semi)quantitative values for improving prediction.

Sections du résumé

BACKGROUND BACKGROUND
Endoscopic ultrasound routinely guides lymph node evaluation for the staging of a known or suspected lung cancer. Characteristics seen on B-mode imaging might help the observer decide on the lymph nodes of risk. The influence of nodal size on the predictivity of these characteristics and the agreement with which operators can combine these for malignancy risk prediction is to be determined.
OBJECTIVES OBJECTIVE
We evaluated (1) if prospectively scored individual B-mode ultrasound features predict malignancy when further divided by size and (2) assessed if observers were able to reproducibly agree on still lymph node image malignancy risk.
METHODS METHODS
Lymph nodes as visualized by EBUS were prospectively scored for B-mode characteristics. Still B-mode images were furthermore collected. After collection, a repeated scoring of a subset of lymph nodes was retrospectively performed (n = 11 observers).
RESULTS RESULTS
Analysis of 490 lymph nodes revealed the short axis size is an objective measure for stratifying risk of malignancy (ROC area under the curve 0.78). With ≥8-mm size, 210/237 malignant lymph nodes were correctly identified (89% sensitivity, 46% specificity, 61% PPV, and 81% NPV). Secondary addition of B-mode features in <8-mm nodes had limited value. Retrospective analysis of intra- and interobserver scoring furthermore revealed significant disagreement.
CONCLUSIONS CONCLUSIONS
Lymph nodes of ≥8-mm size and preferably even smaller should be aspirated regardless of other B-mode features. Observer disagreement in scoring both small and large lymph nodes suggests it is infeasible to include subjective features for stratification. Future research should focus on (integrating) other (semi)quantitative values for improving prediction.

Identifiants

pubmed: 34167125
pii: 000516505
doi: 10.1159/000516505
pmc: PMC8686713
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1088-1096

Informations de copyright

© 2021 The Author(s). Published by S. Karger AG, Basel.

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Auteurs

Roel L J Verhoeven (RLJ)

Department of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, The Netherlands.
Department of Radiology, Medical Ultrasound Imaging Center (MUSIC), Radboud University Medical Center, Nijmegen, The Netherlands.

Fausto Leoncini (F)

Interventional Pulmonology, Fondazione Policlinico Universitario A. Gemelli, Rome, Italy.

Jorik Slotman (J)

Department of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, The Netherlands.
Department of Radiology, Medical Ultrasound Imaging Center (MUSIC), Radboud University Medical Center, Nijmegen, The Netherlands.

Chris de Korte (C)

Department of Radiology, Medical Ultrasound Imaging Center (MUSIC), Radboud University Medical Center, Nijmegen, The Netherlands.

Rocco Trisolini (R)

Interventional Pulmonology, Fondazione Policlinico Universitario A. Gemelli, Rome, Italy.

Erik H F M van der Heijden (EHFM)

Department of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, The Netherlands.

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Classifications MeSH