Real-Time AI-Augmented Fluoroscopic Navigation for Intraoperative Pulmonary Nodule Localization: Prospective Observational Pilot Study.
Authors
Affiliations (5)
Affiliations (5)
- Division of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan.
- Department of Thoracic Surgery, School of Medicine, College of Medicine, National Defense Medical University, Taipei, Taiwan.
- Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan.
- Taichung Armed Forces General Hospital, Taichung, Taiwan.
- Digital Medical Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan.
Abstract
The integration of AI into intraoperative surgical imaging represents an emerging frontier in digital health. Despite advances in preoperative computed tomography (CT)-based surgical planning, real-time translation of imaging data into actionable intraoperative guidance remains limited by CT-to-body divergence-a fundamental information gap between preoperative digital models and the dynamic surgical field. This divergence, driven by lung deflation under anesthesia and positional changes, represents a critical digital-to-physical registration challenge that current preoperative imaging workflows fail to address in real time. This study aimed to evaluate the clinical feasibility, localization success, and safety of the LungVision system-an AI-augmented fluoroscopic navigation platform-for real-time intraoperative localization of small pulmonary nodules during thoracoscopic surgery. A prospective single-center study enrolled 14 patients with pulmonary nodules requiring localization prior to thoracoscopic resection between January 2024 and December 2024. The platform comprises a passive radiopaque positioning board, an AI-powered computing unit for real-time image processing, and a tablet-based interface for procedural planning and augmented visualization. All patients received dual localization with either preoperative CT-guided dye injection or Archimedes virtual bronchoscopic navigation followed by intraoperative localization with the LungVision system and video-assisted thoracoscopic surgery. Demographic data, lesion characteristics, procedural performance, and procedure-related complications were recorded. The mean patient age was 57.2 (SD 9.2) years, and 92.9% (13/14) were nonsmokers. Most nodules were peripherally located (12/14, 85.7%), with a mean diameter of 9.3 (SD 5.3) mm and a mean CT attenuation of -320.1 (SD 334.9) Hounsfield units. LungVision successfully localized all target lesions intraoperatively, with a mean navigation time of 38.6 (SD 19.5) minutes. Complete resection was achieved in all cases, and 71.4% (10/14) of nodules were pathologically malignant. No intraoperative or localization-related complications were observed. The system was integrated into the existing operating room without additional infrastructure modifications. In this prospective study, the LungVision system achieved successful intraoperative localization of small, hypodense pulmonary nodules using a bronchoscopic approach integrated with conventional C-arm fluoroscopy. These findings support the feasibility of the technique and provide preliminary evidence on its use in thoracoscopic resection workflows. Larger studies are needed to further evaluate its clinical performance and implementation in diverse practice settings. ClinicalTrials.gov NCT07682012; https://clinicaltrials.gov/study/NCT07682012.