Evidence map›Paper›PMID 42592462›Full record

ArticleAME case reports2026

Successful resection of multi-focal lung nodules in a 53-year-old male following preoperative 5G-assisted remote robotic bronchoscopy dye marking: a case report.

Dingpei Han, Xinyi Wang, Wenbo She, Jiajun Ma, Fang Chen, Hecheng Li

Abstract readCase Reports
In one paragraph

Article in AME case reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Dingpei Han *Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xinyi Wang *Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wenbo SheSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Jiajun MaSchool of Biomedical Engineering, Tsinghua University, Beijing, China.
Fang ChenSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Hecheng LiDepartment of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robotic-assisted bronchoscopy is an effective platform for transbronchial localization of pulmonary nodules before sublobar resection. However, access to this specialized technology and expertise is often limited to tertiary centers, creating geographic disparities in care. This case report describes the first clinical application of fifth-generation (5G)-assisted remote robotic bronchoscopy for preoperative dye marking, aiming to address this gap in surgical access and resource distribution. Case Description: A 53-year-old asymptomatic male with two persistent ground-glass nodules [14 mm in the right upper lobe (RUL) and 7 mm in the right lower lobe (RLL)] was scheduled for resection. His medical history was unremarkable. Preoperative localization was performed using an artificial intelligence-enhanced robotic bronchoscopy system (Polaris Conclusions: This initial case suggests the technical feasibility of 5G remote-controlled robotic bronchoscopy for preoperative localization. The ultra-low latency 5G network ensured real-time and precise control. This approach potentially expands access to specialized thoracic surgical expertise across geographical barriers. Its broader safety, efficacy, and clinical utility require validation in larger, prospective studies.

Indexed as

case reportFifth-generation telesurgery (5G telesurgery)preoperative localizationpulmonary nodulerobotic bronchoscopy

Identifiers

PMID42592462
PMCPMC13466810

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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.