ReviewJournal of thoracic disease2024
Robotic-assisted bronchoscopy: a narrative review of systems.
Review in Journal of thoracic disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic performance and safety for robotic-assisted bronchoscopy in pulmonary nodules: a systematic review and meta-analysis.International journal of surgery (London, England) · 2025Pooled it
- Mitigating lateral sensing blind spots: A dual-segment bronchoscopic robot with a bioinspired skin.Science advances · 2026Article
- Review
- Advanced Bronchoscopic Approaches to Peripheral Pulmonary Lesions: a Narrative Review of Current and Emerging Techniques.Pulmonary therapy · 2026Review
- Robotic-assisted bronchoscopy for lung cancer: bibliometric and visualized analysis.Journal of robotic surgery · 2026Review
- Article
- Comparison of learning curves between electromagnetic navigation bronchoscopy and Ion robotic bronchoscopy for preoperative localization.Journal of thoracic disease · 2026Article
- Improved reachability during bronchoscopy with a novel multisection robotic bronchoscope.JTCVS techniques · 2026Article
- Predicting Diagnostic Success and Procedural Efficiency in Robotic Bronchoscopy Using Machine Learning.Diseases (Basel, Switzerland) · 2026Article
- Learning curve, safety and diagnostic yield of the GalaxyJournal of thoracic disease · 2026Article
- Artificial Intelligence in Pulmonary Endoscopy: Current Evidence, Limitations, and Future Directions.Journal of imaging · 2026Review
- Innovations in Robotic-Assisted Bronchoscopy: Current Trends and Future Prospects.Diagnostics (Basel, Switzerland) · 2026Review
- Learning Shape-Sensing Robotic-Assisted Bronchoscopy after Mastering Advanced Image-Guided Navigation Bronchoscopy.Respiration; international review of thoracic diseases · 2026Article
- Shape-Sensing Robotic-Assisted Bronchoscopic Microwave Ablation for Primary and Metastatic Pulmonary Nodules: Retrospective Case Series.Diagnostics (Basel, Switzerland) · 2025Article
- VirtualJournal of thoracic disease · 2025Article
- Radial endobronchial ultrasound (EBUS)-guided transbronchial needle aspiration (TBNA) enhances diagnostic yield in pulmonary nodule biopsy.Translational lung cancer research · 2025Article
- Chinese expert consensus on shape-sensing robotic-assisted bronchoscopy (ssRAB) in the management of peripheral pulmonary lesions.Translational lung cancer research · 2025Review
- Robotic-assisted bronchoscopy-advancing lung cancer management.Frontiers in surgery · 2025Review
- Unlocking the depths: the evolution of robotic-assisted bronchoscopy.Frontiers in oncology · 2025Article
- Evaluating diagnostic yield and accuracy as key performance metrics in pulmonary lung lesions.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objective: Robotic-assisted bronchoscopy (RAB) has emerged as an advanced technology for lung cancer diagnosis. This review explores the three approved robotic bronchoscopy systems: Ion™ Endoluminal (Intuitive Surgical, Sunnyvale, CA, USA), Monarch™ (Johnson & Johnson, Redwood City, CA, USA), and Galaxy System™ (Noah Medical, San Carlos, CA, USA), and their different operational systems. This narrative review aims to summarize their findings and outcomes for sampling peripheral pulmonary lesions (PPL) suspected of lung cancer. Methods: A search in PubMed and Google Scholar databases was conducted for articles and abstracts published between January 2018 to May 2024 using the terms "robotic bronchoscopy" or "robotic-assisted bronchoscopy" for biopsy of PPL. Key Content and Findings: Lung cancer is the leading cause of cancer-related mortality. The introduction of RAB aims to improve the feasibility and safety of sampling PPL. Current literature describes high diagnostic yields with low risk of complications, allowing concurrent hilar and mediastinal staging within the same procedure. RAB can potentially improve early diagnosis and treatment of pulmonary malignancies and survival rate in long term, while progressing towards therapeutic applications in the near future. Conclusions: As RAB evolves, its potential as a "one-stop shop" for diagnosis, staging, and treatment can positively impact lung cancer detection, focusing on improved patient-centered outcomes and reducing multiple diagnostic and therapeutic procedures.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.