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Robotic bronchoscopy in diagnosing lung cancer—the evidence, tips and tricks: a clinical practice review

The development of robotic-assisted bronchoscopy has empowered bronchoscopists to access the periphery of the lung with more confidence and promising accuracy. This is due in large to the superior maneuverability, further reach, and stability of these technologies. Despite the advantages of robotic...

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Detalles Bibliográficos
Autores principales: Ho, Elliot, Hedstrom, Grady, Murgu, Septimiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10477625/
https://www.ncbi.nlm.nih.gov/pubmed/37675302
http://dx.doi.org/10.21037/atm-22-3078
Descripción
Sumario:The development of robotic-assisted bronchoscopy has empowered bronchoscopists to access the periphery of the lung with more confidence and promising accuracy. This is due in large to the superior maneuverability, further reach, and stability of these technologies. Despite the advantages of robotic bronchoscopy, there are some drawbacks to using these technologies, such as the loss of tactile feedback, the need to overcome computed tomography (CT)-to-body divergence, and the potential for overreliance on the navigation software. There are currently two robotic bronchoscopy platforms on the US market, the Monarch(TM) Platform by Auris Health(©) (Redwood City, CA, USA) and the Ion(TM) endoluminal robotic bronchoscopy platform by Intuitive Surgical(©) (Sunnyvale, CA, USA). In this clinical practice review, we highlight the evidence and strategies for successful clinical use of both robotic bronchoscopy platforms for pulmonary lesion sampling. Specifically, we will review pre-procedural considerations, such as procedural mapping, room set-up and anesthesia considerations. We will also review the technical aspects of using the robotic bronchoscopy platforms, such as how to compensate for the loss of tactile feedback, optimize visualization, use of ancillary technology to accommodate for CT-to-body divergence, employ best practices for sampling techniques, and utilize information from rapid on-site evaluation (ROSE) to aid in improving diagnostic yield.