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LungVision AI-Augmented Fluoroscopic Navigation for Intraoperative Pulmonary Nodule Localization

27. juni 2026 opdateret af: Hsiang Teng, Tri-Service General Hospital (TSGH)

Clinical Feasibility, Localization Accuracy, and Safety of the LungVision System for Intraoperative Localization of Small Pulmonary Nodules During Thoracoscopic Surgery: A Prospective Single-Center Pilot Study

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.

Studieoversigt

Detaljeret beskrivelse

Lung cancer is the leading cause of cancer-related mortality worldwide, and accurate intraoperative localization of small pulmonary nodules is critical for guiding thoracoscopic resection. Conventional localization methods, including CT-guided percutaneous dye injection and virtual bronchoscopic navigation, carry limitations such as radiation exposure, pneumothorax risk, and dependence on pre-procedural planning without real-time intraoperative feedback.

The LungVision system (Body Vision Medical, Israel) is an AI-augmented fluoroscopic bronchoscopic navigation platform that integrates preoperative CT imaging with real-time C-arm fluoroscopy via machine learning-based image fusion. The system provides continuous intraoperative tool-tip tracking and lesion overlay without additional radiation beyond standard fluoroscopy, enabling real-time navigational feedback during bronchoscopic procedures.

This prospective, single-center, single-arm pilot study was conducted at the Department of Thoracic Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. A total of 14 patients with small pulmonary nodules requiring preoperative localization prior to video-assisted thoracoscopic surgery (VATS) were enrolled between January and December 2024. Each patient underwent dual localization: preoperative marking via CT-guided percutaneous dye injection or virtual bronchoscopic navigation (Broncus Archimedes Software System), followed by intraoperative localization using the LungVision system with ICG dye injection under fluoroscopic guidance.

The primary outcome was localization success rate, defined as the proportion of patients achieving fluoroscopic tool-in-lesion confirmation using the LungVision system. Secondary outcomes included complete resection rate (confirmed by pathological examination), navigation time, total operative time, and perioperative complication rate assessed up to 30 days postoperatively. Thoracoscopic resection was performed based on the combined localization findings, and all resected specimens were submitted for histopathological analysis.

This study was approved by the Institutional Review Board of Tri-Service General Hospital (IRB No.: A202303004) and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment.

Undersøgelsestype

Interventionel

Tilmelding (Faktiske)

14

Fase

  • Ikke anvendelig

Kontakter og lokationer

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Studiesteder

    • Taiwan
      • Taipei, Taiwan, Taiwan, 114202
        • Tri-Service General Hospital

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ja

Beskrivelse

Inclusion Criteria:

  • 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

Exclusion Criteria:

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

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Behandling
  • Tildeling: N/A
  • Interventionel model: Enkelt gruppeopgave
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: LungVision AI-Augmented Fluoroscopic Navigation
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.
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.
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.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Localization Success Rate
Tidsramme: Intraoperative
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

Samarbejdspartnere og efterforskere

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Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

1. januar 2024

Primær færdiggørelse (Faktiske)

31. december 2024

Studieafslutning (Faktiske)

31. december 2024

Datoer for studieregistrering

Først indsendt

27. juni 2026

Først indsendt, der opfyldte QC-kriterier

27. juni 2026

Først opslået (Faktiske)

2. juli 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

2. juli 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

27. juni 2026

Sidst verificeret

1. juni 2026

Mere information

Begreber relateret til denne undersøgelse

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

Individual participant data (IPD) will not be shared publicly. This decision is based on the small sample size (n=14), potential re-identification risk of participants, and institutional data governance policies of Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. Aggregated, de-identified summary data supporting the findings of this study are available from the corresponding author upon reasonable request.

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