Anesthesia strategies to minimize lung atelectasis in peripheral bronchoscopy.

Document Type

Article

Publication Date

1-1-2026

Publication Title

Current opinion in pulmonary medicine

Keywords

Humans, Pulmonary Atelectasis, Bronchoscopy, Anesthesia, Tomography, X-Ray Computed, Respiration, Artificial

Abstract

PURPOSE OF REVIEW: Peripheral bronchoscopy has become a widely adopted, minimally invasive modality for the diagnosis of peripheral lung lesions. However, its diagnostic yield remains limited in part due to intra-procedural atelectasis - a frequently overlooked phenomenon that obscures lesions and exacerbates computed tomography (CT)-to-body divergence. This review highlights the prevalence and clinical impact of atelectasis during navigational bronchoscopy and presents anesthesia and ventilation strategies to mitigate its occurrence.

RECENT FINDINGS: Emerging data from trials such as I-LOCATE, ventilatory strategy to prevent atelectasis (VESPA), and lung navigation ventilation protocol (LNVP) studies show that atelectasis develops early and frequently during bronchoscopy, particularly in dependent lung zones and patients with high BMI. Strategies to reduce atelectasis include high tidal volumes, optimized positive end-expiratory pressure, reduced FiO 2 , and recruitment maneuvers. Dedicated ventilation protocols like VESPA and LNVP have significantly reduced both incidence and severity of atelectasis, improved lesion visibility, and demonstrated safety. Apneic breath-hold techniques further enhance image quality and lesion targeting.

SUMMARY: Atelectasis is a modifiable barrier to diagnostic success in peripheral bronchoscopy. Proactive pre and intra-procedural planning, implementation of structured ventilation protocols, and close collaboration with anesthesia are essential. Future research should focus on protocol standardization, novel imaging synchronization techniques, and validation of atelectasis grading tools.

Medical Subject Headings

Humans; Pulmonary Atelectasis; Bronchoscopy; Anesthesia; Tomography, X-Ray Computed; Respiration, Artificial

PubMed ID

41065573

ePublication

ePub ahead of print

Volume

32

Issue

1

First Page

32

Last Page

37

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