An interventional study of AI-driven autonomous registration in Lung Nodules, Bronchoscopy and Localization Efficiency, sponsored by Ruijin Hospital. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-04-13.
Sponsored by Ruijin Hospital · Not applicable, Interventional, and Device feasibility
This study aims to evaluate the feasibility and safety of an artificial intelligence (AI)-driven autonomous registration technology in robotic navigational bronchoscopy. A total of 20 patients with pulmonary nodules requiring localization will be enrolled. The Langhe Bronchoscopy Robot System equipped with AI-based autonomous registration software will be used. Primary outcomes include the success rate of autonomous registration and the rate of manual intervention during the process. Secondary outcomes encompass registration time, complication rates, and nodule localization success.
Ruijin Hospital is the lead sponsor of 635 studies on the registry; 359 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
All participants in this arm will undergo robotic navigational bronchoscopy and pulmonary nodule localization performed using the Langhe Bronchoscopy Robot System. The key intervention is the use of artificial intelligence (AI)-driven autonomous registration technology to automatically align the pre-operative chest CT images with the real-time bronchoscopic anatomy prior to the procedure. This process aims to reduce reliance on the conventional, operator-dependent manual registration. Physicians will supervise the entire process and perform necessary manual intervention if the AI registration is unsatisfactory or for safety reasons.
Device: AI-driven autonomous registration
All participants in this arm will undergo robotic navigational bronchoscopy and pulmonary nodule localization performed using the Langhe Bronchoscopy Robot System. The key intervention is the use of artificial intelligence (AI)-driven autonomous registration technology to automatically align the pre-operative chest CT images with the real-time bronchoscopic anatomy prior to the procedure. This process aims to reduce reliance on the conventional, operator-dependent manual registration. Physicians will supervise the entire process and perform necessary manual intervention if the AI registration is unsatisfactory or for safety reasons.
Autonomous registration success rate
Proportion of registrations completed independently by the AI algorithm without manual intervention.
Time frame: Intraoperative
Manual intervention rate during autonomous registration
The proportion of cases requiring manual adjustment by the physician during the registration process.
Time frame: Intraoperative
Time consumed for autonomous registration
Time frame: Intraoperative
Complication rate during autonomous registration
Complication rate during autonomous registration (e.g., bleeding, pneumothorax)
Time frame: Immediate post-procedure to 24 hours
Localization success rate of pulmonary nodules
The proportion of successful bronchoscope arrivals at the target nodule after registration.
Time frame: Intraoperative
Plan to share: No
No publications or documents are linked to this record.
Eligibility is decided by the study team. Share this record with your doctor or contact the team directly.
Contact study teamGet an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
Ruijin Hospital