AI-Driven Autonomous Registration in Robotic Bronchoscopy

NCT07368829 | Recruiting

• 1 other identifier: RTS-030
• Study Type: interventional
• Target: 20
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Lung Nodules; Bronchoscopy; Localization Efficiency

Keywords

Artificial Intelligence; Robotic Bronchoscopy; Pulmonary Nodule

Outcome Measures

Primary Outcomes (2)

• Autonomous registration success rate

  Proportion of registrations completed independently by the AI algorithm without manual intervention.

  Intraoperative

• Manual intervention rate during autonomous registration

  The proportion of cases requiring manual adjustment by the physician during the registration process.

  Intraoperative

Secondary Outcomes (3)

• Time consumed for autonomous registration

  Intraoperative

• Complication rate during autonomous registration

  Immediate post-procedure to 24 hours

• Localization success rate of pulmonary nodules

  Intraoperative

Study Arms (1)

Autonomous registration group

EXPERIMENTAL

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

Interventions

AI-driven autonomous registration DEVICE

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 group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age ≥ 18 years.
• Radiologically confirmed pulmonary nodules requiring preoperative localization.
• Scheduled for robotic navigational bronchoscopy using the Bronchoscopy Robot System.
• Willing to provide written informed consent.

You may not qualify if:

• Severe cardiopulmonary dysfunction (e.g., FEV1 \< 30% predicted).
• Coagulopathy or anticoagulation therapy that cannot be safely interrupted.
• Pregnancy or lactation.
• Inability to tolerate bronchoscopy under general anesthesia.

Sponsors & Collaborators

• Ruijin Hospital: lead

Study Sites (1)

Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine

Shanghai, Shanghai Municipality, 200025, China

RECRUITING

Central Study Contacts

Hecheng Li, M.D., Ph.D.

CONTACT

+021 64370045; lihecheng2000@hotmail.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DEVICE FEASIBILITY
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director, Department of Thoracic Surgery, Ruijin Hospital

Study Record Dates

• First Submitted: January 20, 2026
• First Posted: January 27, 2026
• Study Start: March 1, 2026
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): June 30, 2026
• Last Updated: April 13, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)