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Recruiting NCT07368829

AI-Driven Autonomous Registration in Robotic Bronchoscopy

No phase Interventional Lung Nodules Bronchoscopy Localization Efficiency

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI-driven autonomous registration.
Who it may be relevant to
Registry conditions: Lung Nodules, Bronchoscopy, Localization Efficiency. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

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

Overview

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.

Interventions

  • 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

Primary outcome measures

  • Autonomous registration success rate [Time frame: Intraoperative]
  • Manual intervention rate during autonomous registration [Time frame: Intraoperative]
Secondary outcome measures (3)
  • Time consumed for autonomous registration [Time frame: Intraoperative]
  • Complication rate during autonomous registration [Time frame: Immediate post-procedure to 24 hours]
  • Localization success rate of pulmonary nodules [Time frame: Intraoperative]

Eligibility criteria

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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
N/A
Model
Single group
Masking
Open label
Primary purpose
Device feasibility

Study locations

China · 1 center
  • Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine — Shanghai

Identifiers

NCT: NCT07368829 · RTS-030

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗