Literature DB >> 33384039

The diagnosis of lung cancer in the era of interventional pulmonology.

C-K Liam1, P Lee2, C-J Yu3, C Bai4, K Yasufuku5.   

Abstract

Advances in bronchoscopic and other interventional pulmonology technologies have expanded the sampling procedures pulmonologist can use to diagnose lung cancer and accurately stage the mediastinum. Among the modalities available to the interventional pulmonologist are endobronchial ultrasound-guided transbronchial needles aspiration (EBUS-TBNA) and transoesophageal bronchoscopic ultrasound-guided fine-needle aspiration (EUS-B-FNA) for sampling peribronchial/perioesophageal central lesions and for mediastinal lymph node staging, as well as navigational bronchoscopy and radial probe endobronchial ultrasound (RP-EBUS) for the diagnosis of peripheral lung cancer. The role of the interventional pulmonologist in this setting is to apply these procedures based on the correct interpretation of clinical and radiological findings in order to maximise the chances of achieving the diagnosis and obtaining sufficient tissue for molecular biomarker testing to guide targeted therapies for advanced non-small cell lung cancer. The safest and the highest diagnosis-yielding modality should be chosen to avoid a repeat sampling procedure if the first one is non-diagnostic. The choice of site and biopsy modality are influenced by tumour location, patient comorbidities, availability of equipment and local expertise. This review provides a concise state-of-the art account of the interventional pulmonology procedures in the diagnosis and staging of lung cancer.

Entities:  

Year:  2021        PMID: 33384039     DOI: 10.5588/ijtld.20.0588

Source DB:  PubMed          Journal:  Int J Tuberc Lung Dis        ISSN: 1027-3719            Impact factor:   2.373


  2 in total

1.  Analysis on the Effects of CT- and Ultrasound-Guided Percutaneous Transthoracic Needle Biopsy Combined with Serum CA125 and CEA on the Diagnosis of Lung Cancer.

Authors:  Zhaoyin Wang; Jinbiao Huang; Minke Wang; Weixu Bi; Tianbing Fan
Journal:  J Healthc Eng       Date:  2022-01-07       Impact factor: 2.682

2.  Artificial Intelligence Algorithm-Based Feature Extraction of Computed Tomography Images and Analysis of Benign and Malignant Pulmonary Nodules.

Authors:  Yuantong Gao; Yuyang Chen; Yuegui Jiang; Yongchou Li; Xia Zhang; Min Luo; Xiaoyang Wang; Yang Li
Journal:  Comput Intell Neurosci       Date:  2022-09-14
  2 in total

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