Literature DB >> 30527199

Ultrasonographic characteristics of lymph nodes as predictors of malignancy during endobronchial ultrasound (EBUS): A systematic review.

Danielle A Hylton1, Jane Turner2, Yaron Shargall3, Christian Finley4, John Agzarian5, Kazuhiro Yasufuku6, Christine Fahim7, Waël C Hanna8.   

Abstract

OBJECTIVES: The primary objective of this study is to systematically review all pertinent literature related to the use of ultrasonographic features to predict malignancy in mediastinal lymph nodes seen during endobronchial ultrasound (EBUS) procedures.
MATERIALS AND METHODS: Two independent reviewers completed the search and review (PubMed, EMBASE, Medline, and Cochrane databases) of the resulting titles and abstracts. Following full-text screening, thirteen articles met the inclusion criteria. Heterogeneity prevented any meta-analysis, instead a narrative review was completed. Results from each included article are categorized by the following ultrasonographic features: shape, echogenicity, margin status, central necrosis, short axis length, and central hilar structure. Diagnostic tools are also described in detail.
RESULTS: Absence of a central hilar structure and heterogeneous echogenicity were often associated with malignancy; however, consensus was not achieved amongst the included articles. The remaining ultrasonographic features were not consistently associated with malignancy or benign disease status, suggesting a need for prospective analysis. Four diagnostic tools were also assessed. These tools demonstrate that a combination of ultrasonographic features may accurately predict lymph node malignancy rather than a single feature.
CONCLUSION: Analysis of ultrasonographic features may prevent the need for repeat EBUS procedures when initial biopsy results are inconclusive. However, prospective external validation of these features is required to determine their true predictive capability. PROSPERO registration number: CRD42017068468.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Endobronchial ultrasound; Lung cancer; Ultrasonographic features

Mesh:

Year:  2018        PMID: 30527199     DOI: 10.1016/j.lungcan.2018.10.020

Source DB:  PubMed          Journal:  Lung Cancer        ISSN: 0169-5002            Impact factor:   5.705


  5 in total

1.  The combination of endobronchial elastography and sonographic findings during endobronchial ultrasound-guided transbronchial needle aspiration for predicting nodal metastasis.

Authors:  Taiki Fujiwara; Takahiro Nakajima; Terunaga Inage; Yuki Sata; Yuichi Sakairi; Hajime Tamura; Hironobu Wada; Hidemi Suzuki; Masako Chiyo; Ichiro Yoshino
Journal:  Thorac Cancer       Date:  2019-09-01       Impact factor: 3.500

Review 2.  Linear Endobronchial Ultrasound in the Era of Personalized Lung Cancer Diagnostics-A Technical Review.

Authors:  Filiz Oezkan; Stephan Eisenmann; Kaid Darwiche; Asmae Gassa; David P Carbone; Robert E Merritt; Peter J Kneuertz
Journal:  J Clin Med       Date:  2021-11-30       Impact factor: 4.241

3.  Malignant thoracic lymph node classification with deep convolutional neural networks on real-time endobronchial ultrasound (EBUS) images.

Authors:  Seung Hyun Yong; Sang Hoon Lee; Sang-Il Oh; Ji-Soo Keum; Kyung Nam Kim; Moo Suk Park; Yoon Soo Chang; Eun Young Kim
Journal:  Transl Lung Cancer Res       Date:  2022-01

4.  Combination of 18F-FDG PET/CT and convex probe endobronchial ultrasound elastography for intrathoracic malignant and benign lymph nodes prediction.

Authors:  Xinxin Zhi; Xiaoyan Sun; Junxiang Chen; Lei Wang; Lin Ye; Ying Li; Wenhui Xie; Jiayuan Sun
Journal:  Front Oncol       Date:  2022-08-05       Impact factor: 5.738

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

Authors:  Roel L J Verhoeven; Fausto Leoncini; Jorik Slotman; Chris de Korte; Rocco Trisolini; Erik H F M van der Heijden
Journal:  Respiration       Date:  2021-06-24       Impact factor: 3.580

  5 in total

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