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Real-world diagnostic yield and safety of electromagnetic navigation bronchoscopy for pulmonary nodules: Experience of a single centre
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DOI：10.1055/a-2831-4870.png)
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Abstract
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Electromagnetic navigation bronchoscopy (ENB) is a minimally invasive technology enabling the navigation of bronchoscopic instruments to reach peripheral pulmonary lesions (PPLs) that are otherwise challenging to reach. To date, ENB has primarily been assessed in high-volume centres or within the framework of multicentre trials. Consequently, the actual diagnostic yield in a real-world setting, particularly among patients with varying levels of risk, remains largely unknown.This prospective single-centre cohort study enrolled consecutive patients with PPLs between February 2023 and April 2024. The Medtronic ILLUMISITE platform was utilised to perform ENB procedures. The primary endpoints of the study were the diagnostic yield of ENB as a standalone procedure, assessed at the end of the intervention, and the overall diagnostic accuracy, which incorporated ENB in combination with other diagnostic techniques, evaluated after a 12-month follow-up period. The secondary endpoint was the rate of procedural complications.A total of thirty patients participated in this study. The median lesion size was 16.5 mm. ENB achieved a technical success rate of 93%. The diagnostic yield was 57%. When considering the combination of ENB and other diagnostic methods over the course of a year, the diagnostic accuracy increased to 67%. Two cases of pneumothorax (6.6%), but no instances of bronchopulmonary haemorrhage requiring intervention were observed.This small, single-centre, real-world cohort study, which applied strict definitions for diagnostic yield and accuracy, demonstrates that ENB-aided diagnosis can be successfully achieved in approximately two-thirds of eligible patients, with a low rate of procedural complications.
Keywords:
electromagnetic navigation
bronchoscopy
diagnostic yield
electromagnetic navigation
bronchoscopy
pulmonary
nodules
diagnostic yield
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