Literature DB >> 32805534

Diagnostic utility of endobronchial ultrasound (EBUS) features in differentiating malignant and benign lymph nodes - A systematic review and meta-analysis.

Sumita Agrawal1, Akhil Dhanesh Goel2, Nitesh Gupta3, Ayush Lohiya4, Hari Kishan Gonuguntla5.   

Abstract

BACKGROUND: EBUS is being widely used today for echolocation of lymph nodes for FNAC. We present a systematic review and meta-analysis to assess the diagnostic accuracy of EBUS characteristics of lymph nodes in diagnosing malignancy.
METHODS: A systematic search of published literature was undertaken using databases like PubMed, Web of Science, Cochrane, Google Scholar and Researchgate. Those studies reporting any endobronchial ultrasonography features of malignant lymph nodes like size, margins, echogenicity, shape, central hilar structure (CHS), coagulation necrosis sign (CNS) or color power doppler index (CPDI) were included for review. Random effects model was used to calculate pooled sensitivity, specificity, positive and negative likelihood ratios (LR), and diagnostic odds ratio (DOR). The review protocol was registered with the International prospective register of systematic reviews (PROSPERO registration no. CRD42019117716).
RESULTS: 992 articles were retrieved of which 542 articles were evaluated in detail and finally 29 articles met the inclusion criteria. All EBUS features except CPDI showed a statistically significant area under the SROC curve. CNS showed highest area under the SROC curve [0.81 (SE: 0.09)] with maximum pooled specificity [0.93, 95%CI: 0.92-0.94], maximum pooled LR+ [5.12, 95%CI: 2.56-10.2] and DOR [9.23, 95%CI 3.85-22.15]. Maximum sensitivity was seen for CHS 0.91 [95%CI: 0.90-0.92].
CONCLUSION: EBUS features have the potential to help in more precise location of a malignant lymph node thereby helping in increasing the diagnostic yield. However, high diagnostic accuracy of various EBUS features can currently only be said to supplement tissue diagnosis.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Diagnostic imaging; Diagnostic techniques; Lung neoplasms; Respiratory system; Ultrasonography

Mesh:

Year:  2020        PMID: 32805534     DOI: 10.1016/j.rmed.2020.106097

Source DB:  PubMed          Journal:  Respir Med        ISSN: 0954-6111            Impact factor:   3.415


  3 in total

1.  Diagnostic value of endobronchial ultrasound elastography combined with rapid onsite cytological evaluation in endobronchial ultrasound-guided transbronchial needle aspiration.

Authors:  Jing Huang; Yuan Lu; Xihua Wang; Xiaoli Zhu; Ping Li; Jing Chen; Pingsheng Chen; Ming Ding
Journal:  BMC Pulm Med       Date:  2021-12-20       Impact factor: 3.317

2.  Prediction of Nodal Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images.

Authors:  Yuki Ito; Takahiro Nakajima; Terunaga Inage; Takeshi Otsuka; Yuki Sata; Kazuhisa Tanaka; Yuichi Sakairi; Hidemi Suzuki; Ichiro Yoshino
Journal:  Cancers (Basel)       Date:  2022-07-08       Impact factor: 6.575

3.  Correlating Ultrasonographic Features of Lymph Nodes During Endobronchial Ultrasound With Final Outcome.

Authors:  Tinku Joseph; Satish Reddy; Nitesh Gupta; Arvind Perathur; Archana George; Vidhya Chandraprabha; Namitha Shajil
Journal:  Cureus       Date:  2022-07-04
  3 in total

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