Evidence map›Paper›PMID 41158404›Full record

ReviewJournal of thoracic disease2025

Bridging traditional gaps in medical training with mixed reality: insights from bronchoscopy education-a narrative review.

Binhe Tian, Yuejun Liu, Zixiang Zhou, Boyu Sun, Mingjian Piao, Shuofeng Li, Hanping Wang

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Binhe Tian *Department 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.ORCID https://orcid.org/0009-0009-3722-9611
Yuejun Liu *Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zixiang ZhouChinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Boyu SunChinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Mingjian PiaoDepartment of Liver Surgery, 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.
Shuofeng LiDepartment of Liver Surgery, 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.
Hanping WangDepartment 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.ORCID https://orcid.org/0000-0003-3540-2280

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

bronchoscopy trainingmedical education innovationmedical simulationMixed reality (MR)

Identifiers

PMID41158404
PMCPMC12557641

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.