Evidence map›Paper›PMID 41588450›Full record

Trial reportRespiratory research2026

Shape-sensing robotic-assisted bronchoscopy (ss-RAB) for peripheral pulmonary nodules: learning curve and diagnostic performance from an initial multicenter experience in China.

Dan Liu, Chun Li, Fangfang Xie, Xianya Hu, Jingyu Shi, Zilong Liu, Jie Liu, Michael J Simoff, Yuanlin Song, Jiayuan Sun

Registry-linked trialAbstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Respiratory research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06308120 (A Randomized Controlled Trial to Compare Robotic Assisted Bronchoscopy Ion's Clinical Utility for Peripheral Lung Nodule Access and Diagnosis to ENB), which is not on this 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.

NCT06308120 naactive not recruitingnot on this map

A Randomized Controlled Trial to Compare Robotic Assisted Bronchoscopy Ion's Clinical Utility for Peripheral Lung Nodule Access and Diagnosis to ENB

TypeinterventionalSponsorIntuitive SurgicalRan2024 to 2027Enrolled354ConditionsPulmonary Nodule, Solitary, Lung CancerArmsIon Endoluminal System, superDimension Navigation System and Accessories
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

10 authors.

Dan Liu *Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Chun Li *Shanghai Key Laboratory of Lung Inflammation and Injury, Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Fangfang Xie *Department of Respiratory Endoscopy, Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xianya Hu *Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Jingyu ShiDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Zilong LiuShanghai Key Laboratory of Lung Inflammation and Injury, Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Jie LiuShanghai Key Laboratory of Lung Inflammation and Injury, Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Michael J SimoffBronchoscopy and Interventional Pulmonology, Lung Cancer Screening Program, Department of Pulmonary and Critical Care Medicine, Henry Ford Hospital, Wayne State University School of Medicine, Detroit, MI, USA. Mike@simoff.net.
Yuanlin SongShanghai Key Laboratory of Lung Inflammation and Injury, Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China. song.yuanlin@zs-hospital.sh.cn.
Jiayuan SunDepartment of Respiratory Endoscopy, Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. xkyyjysun@163.com.

Funding

Chengdu Science and Technology Project 2023-YF09-00039-SNNational Natural Science Foundation of China 82173182Noncommunicable Chronic Disease-National Science and Technology Major Project 2024ZD0529500Science and Technology Program of Sichuan 2023NSFSC1939
6 · The paper itself

Abstract

backgroundShape-sensing robotic-assisted bronchoscopy (ssRAB) is an emerging technology in geographies outside the United States in use for complex pulmonary nodule biopsy. Geography specific data is needed to better understand outcomes in each population and health care system. The objective of this study is to assess the learning curve, diagnostic performance and safety of ssRAB in sampling peripheral pulmonary nodules (PPN) from an initial multicenter experience in China.

methodsConsecutive patients with solid or part-solid nodules 8-30 mm in largest diameter were prospectively enrolled across three centers. Biopsy was performed using the ssRAB platform with 2D fluoroscopy and radial EBUS guidance only. Biopsy workflow was standardized across all centers. Subjects were followed through 30 days post-procedure. The primary endpoint was diagnostic yield per American Thoracic Society (ATS) and American College of Chest Physicians (ACCP) definition. Secondary outcomes included procedure characteristics and incidence of procedure or device-related complications. Learning curve based on procedure time and diagnostic yield for each proceduralist was assessed using the cumulative sum method.

resultsNinety nodules from ninety subjects were biopsied with the ssRAB system. Average nodule size was (20.3 ± 4.9) mm. ATS/ACCP diagnostic yield was 90.0% (95% CI, 82.1%-94.7%). Multivariate analysis demonstrated no association with any nodule characteristic or imaging signal. Incidence of pneumothorax requiring chest tube was 1.1%. No severe airway bleeding was reported. Decreasing procedure time was observed through the case series with a suggested association to incremental procedure and bronchus sign presence. Two novice operators achieved diagnostic yield competency after 15 and 32 cases, respectively.

conclusionsFor PPN in China, ssRAB showed a strong diagnostic performance with high safety profile during first cases. Proficiency can be stably achieved among beginners at early stage of learning.

trial registrationClinicalTrials.gov (NCT06308120) 2024-04-03.

Indexed as

BronchoscopyLearning CurveLung NeoplasmsMultiple Pulmonary NodulesRobotic Surgical ProceduresSolitary Pulmonary NoduleAgedChinaFemaleHumansMaleMiddle AgedProspective StudiesLearning curveNavigation bronchoscopyPeripheral pulmonary noduleRobotic-assisted bronchoscopy

Identifiers

PMID41588450
PMCPMC13001241

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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.