LungVision AI-Augmented Fluoroscopic Navigation for Intraoperative Pulmonary Nodule Localization

NCT07682012 | Completed

• 1 other identifier: TSGH-LV-2026
• Study Type: interventional
• Target: 14
• Locations: 1 country
• Sites: 1

Brief Summary

This prospective single-center pilot study evaluates the clinical feasibility, localization accuracy, and safety of the LungVision system-an AI-augmented fluoroscopic navigation platform-for real-time intraoperative localization of small pulmonary nodules during video-assisted thoracoscopic surgery (VATS). All enrolled patients underwent dual localization: preoperative marking via CT-guided dye injection or virtual bronchoscopic navigation (Broncus Archimedes), followed by intraoperative localization using the LungVision system. The primary outcome was localization success rate, defined as the proportion of patients achieving fluoroscopic tool-in-lesion confirmation. Secondary outcomes included complete resection rate, navigation time, total operative time, and perioperative complication rate.

Conditions

Lung Neoplasms; Pulmonary Nodule, Solitary; Carcinoma, Non-Small-Cell Lung

Keywords

Pulmonary Nodule Localization; Bronchoscopic Navigation, Fluoroscopic Navigation; Intraoperative Localization; Video-Assisted Thoracoscopic Surgery, VATS; AI-Augmented Navigation, LungVision

Outcome Measures

Primary Outcomes (1)

• Localization Success Rate

  Proportion of patients in whom successful intraoperative pulmonary nodule localization was achieved using the LungVision system, defined as fluoroscopic tool-in-lesion confirmation verified by the operating surgeon based on real-time AI-augmented fluoroscopic overlay. Localization was considered successful when the navigational tool tip was confirmed to be positioned within or immediately adjacent to the target nodule under fluoroscopic guidance prior to dye injection.

  Intraoperative

Study Arms (1)

LungVision AI-Augmented Fluoroscopic Navigation

EXPERIMENTAL

Patients underwent intraoperative pulmonary nodule localization using the LungVision system (Body Vision Medical, Israel), an AI-augmented fluoroscopic bronchoscopic navigation platform that integrates preoperative CT imaging with real-time C-arm fluoroscopy via machine learning-based image fusion. Under bronchoscopic guidance, the navigational tool was advanced toward the target lesion, and tool-in-lesion confirmation was verified under fluoroscopic overlay. Upon successful localization, indocyanine green (ICG) dye was injected transbronchially to mark the target nodule. All patients additionally received preoperative localization via CT-guided percutaneous dye injection or virtual bronchoscopic navigation (Broncus Archimedes Software System) as part of the dual-localization protocol. Subsequent video-assisted thoracoscopic surgery (VATS) was performed based on the combined localization findings.

Device: LungVision System; Device: Preoperative Dual Localization

Interventions

LungVision System DEVICE

The LungVision system is an AI-augmented fluoroscopic bronchoscopic navigation platform developed by Body Vision Medical (Israel). The system integrates preoperative CT imaging with real-time intraoperative C-arm fluoroscopy using machine learning-based image fusion to provide continuous tool-tip tracking and lesion overlay. The system guides the bronchoscopic navigational tool to the target pulmonary nodule without additional radiation beyond standard fluoroscopy. Upon tool-in-lesion confirmation, indocyanine green (ICG) dye is injected transbronchially for surgical marking prior to thoracoscopic resection.

LungVision AI-Augmented Fluoroscopic Navigation

Preoperative Dual Localization DEVICE

As part of the dual-localization protocol, all patients received preoperative localization via one of the following methods prior to LungVision intraoperative navigation: (1) CT-guided percutaneous dye injection using methylene blue, or (2) virtual bronchoscopic navigation using the Broncus Archimedes Software System. The choice of preoperative localization method was determined by the operating surgeon based on nodule characteristics and clinical judgment.

LungVision AI-Augmented Fluoroscopic Navigation

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age 18-65 years
• Scheduled to undergo thoracoscopic resection for solitary, subsolid, or ground-glass pulmonary nodules requiring localization
• Lesion characteristics and CT imaging indicating need for preoperative localization, as determined by the attending surgeon
• Able and willing to complete the study protocol
• Able to provide written informed consent

You may not qualify if:

• Age \>65 years
• Pregnancy
• Bleeding tendency or current use of anticoagulants
• Impaired consciousness or inability to communicate
• Cognitive impairment precluding autonomous consent

Sponsors & Collaborators

• Tri-Service General Hospital (TSGH): lead

Study Sites (1)

Tri-Service General Hospital

Taipei, Taiwan, 114202, Taiwan

Location

MeSH Terms

Conditions

Lung Neoplasms; Solitary Pulmonary Nodule; Carcinoma, Non-Small-Cell Lung

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases; Carcinoma, Bronchogenic; Bronchial Neoplasms

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Resident Doctor

Model Details: All enrolled patients underwent a dual-localization protocol within the same operative session. Preoperative localization was performed using either CT-guided percutaneous dye injection or virtual bronchoscopic navigation (Broncus Archimedes Software System), followed by intraoperative localization using the LungVision system. Each patient served as their own reference, allowing direct intraoperative comparison of localization findings. Thoracoscopic resection was subsequently performed based on the combined localization results.

Study Record Dates

• First Submitted: June 27, 2026
• First Posted: July 2, 2026
• Study Start: January 1, 2024
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: July 2, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)