Rationale: Severe pneumonia often requires bronchoscopy for diagnosis and therapy, yet accurate segmental localization and consistent interpretation are operator-dependent and time-consuming. Prior work by the sponsor team integrated CT-based planning with real-time bronchoscopic guidance and AI-based lesion characterization. The investigational system overlays guidance and voice prompts during bronchoscopy to standardize navigation and reduce errors.
Design: Prospective multicenter controlled study in ICUs/respiratory units. Approximately 100 adults undergoing clinically indicated bronchoscopy for severe pneumonia will be enrolled across ~10 centers in China. Procedures will be performed either with AI assistance or with standard bronchoscopy per site workflow. Outcomes include: (1) diagnostic agreement versus a predefined reference (primary); (2) navigation success/loss-of-path; (3) procedure time; and (4) adverse events (e.g., bleeding, hypoxemia, infection). Enrollment is planned to start in Sep 2025, with anticipated primary completion around Sep 2026.
Operations: Data will be collected using a standardized CRF and analyzed per a prespecified SAP. The investigational software is integrated with an endoscopic image processor developed with an industry partner; physicians can follow or ignore AI suggestions at their discretion. The study will generate evidence on effectiveness and safety to inform subsequent registration testing and scaling.