Bronchoscopy, Localization Efficiency, Lung Nodules
Conditions
Keywords
Artificial Intelligence, Robotic Bronchoscopy, Pulmonary Nodule
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.
Interventions
DEVICEAI-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.
Sponsors
Ruijin Hospital
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DEVICE_FEASIBILITY
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Autonomous registration success rate | Intraoperative | Proportion of registrations completed independently by the AI algorithm without manual intervention. |
| Manual intervention rate during autonomous registration | Intraoperative | The proportion of cases requiring manual adjustment by the physician during the registration process. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Time consumed for autonomous registration | Intraoperative | — |
| Complication rate during autonomous registration | Immediate post-procedure to 24 hours | Complication rate during autonomous registration (e.g., bleeding, pneumothorax) |
| Localization success rate of pulmonary nodules | Intraoperative | The proportion of successful bronchoscope arrivals at the target nodule after registration. |
Countries
China
Contacts
CONTACTHecheng Li, M.D., Ph.D.
Outcome results
None listed