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Updated: Jan 13, 2026

Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting
Published on: June 23, 2023
Bridging traditional gaps in medical training with mixed reality: insights from bronchoscopy education-a narrative
Binhe Tian1, Yuejun Liu2, Zixiang Zhou2
1Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background And Objective:
Medical education is undergoing a digital and intelligent revolution. Traditional bronchoscopy training methods have limitations in skill acquisition and anatomical comprehension. Mixed reality (MR), a technology that combines virtual and real environments for interactive learning, provides an innovative solution. This study reviews the current status and challenges of bronchoscopy training, highlighting the application potential of MR technology.
Methods:
The search strategy included literature from 2000 to 2025 in PubMed, Embase, Scopus, and China National Knowledge Infrastructure (CNKI). Eligible study types included reviews, meta-analyses, randomized controlled trials (RCTs), non-randomized trials, observational studies, case reports or series. Inclusion was restricted to studies specifically investigating MR applications in bronchoscopy procedures and medical education contexts.
Key Content And Findings:
MR can create immersive and interactive virtual medical training environments, equipped with anatomical reconstruction, haptic feedback, and adaptive learning functionalities. MR displays significant advantages across various medical training domains. MR technology has been successfully implemented in bronchoscopy training, demonstrating four key benefits: improved visualization of complex anatomical structures, creation of a risk-free simulated learning environment, facilitation of deliberate practice through real-time performance feedback, and enabling of remote collaborative training scenarios. In the future, MR will be deeply integrated with artificial intelligence (AI), high-fidelity haptic feedback systems (technology that simulates touch sensations like vibration or resistance), and remote collaboration technologies, offering more intelligent and personalized medical education solutions.
Conclusions:
MR holds considerable promise for revolutionizing bronchoscopy training. As hardware costs decrease and training systems become optimized, MR is expected to be widely adopted in medical education, potentially becoming an essential or even central component of bronchoscopy training.
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