AI-Driven Autonomous Registration in Robotic Bronchoscopy

Feasibility and Safety of Artificial Intelligence-Driven Autonomous Registration in Robotic Navigational Bronchoscopy

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.

Study Overview

• Status: Recruiting
• Conditions: Bronchoscopy; Lung Nodules; Localization Efficiency
• Intervention / Treatment: Device: AI-driven autonomous registration

• Study Type: Interventional
• Enrollment (Estimated): 20
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Hecheng Li, M.D., Ph.D.; Phone Number: +021 64370045; Email: lihecheng2000@hotmail.com

Study Locations

• China
  • Shanghai Municipality
    • Shanghai, Shanghai Municipality, China, 200025
      • Recruiting
      • Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
      • Contact: Hecheng Li; Phone Number: +021 64370045; Email: lihecheng2000@hotmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

• 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.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Device Feasibility
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Autonomous registration group; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Time consumed for autonomous registration		Intraoperative
Complication rate during autonomous registration	Complication rate during autonomous registration (e.g., bleeding, pneumothorax)	Immediate post-procedure to 24 hours
Localization success rate of pulmonary nodules	The proportion of successful bronchoscope arrivals at the target nodule after registration.	Intraoperative

Collaborators and Investigators

• Sponsor: Ruijin Hospital

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2026
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): June 30, 2026

Study Registration Dates

• First Submitted: January 20, 2026
• First Submitted That Met QC Criteria: January 20, 2026
• First Posted (Actual): January 27, 2026

Study Record Updates

• Last Update Posted (Actual): April 13, 2026
• Last Update Submitted That Met QC Criteria: April 9, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Artificial Intelligence; Pulmonary Nodule; Robotic Bronchoscopy
• Other Study ID Numbers: RTS-030

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No