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LungVision AI-Augmented Fluoroscopic Navigation for Intraoperative Pulmonary Nodule Localization

2026年6月27日 更新者: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.

調査の概要

詳細な説明

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.

研究の種類

介入

入学 (実際)

14

段階

  • 適用できない

連絡先と場所

このセクションには、調査を実施する担当者の連絡先の詳細と、この調査が実施されている場所に関する情報が記載されています。

研究場所

    • Taiwan
      • Taipei、Taiwan、台湾、114202
        • Tri-Service General Hospital

参加基準

研究者は、適格基準と呼ばれる特定の説明に適合する人を探します。これらの基準のいくつかの例は、人の一般的な健康状態または以前の治療です。

適格基準

就学可能な年齢

  • 大人
  • 高齢者

健康ボランティアの受け入れ

はい

説明

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

研究計画

このセクションでは、研究がどのように設計され、研究が何を測定しているかなど、研究計画の詳細を提供します。

研究はどのように設計されていますか?

デザインの詳細

  • 主な目的:処理
  • 割り当て:なし
  • 介入モデル:単一グループの割り当て
  • マスキング:なし(オープンラベル)

武器と介入

参加者グループ / アーム
介入・治療
実験的: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.

この研究は何を測定していますか?

主要な結果の測定

結果測定
メジャーの説明
時間枠
Localization Success Rate
時間枠: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

協力者と研究者

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研究記録日

これらの日付は、ClinicalTrials.gov への研究記録と要約結果の提出の進捗状況を追跡します。研究記録と報告された結果は、国立医学図書館 (NLM) によって審査され、公開 Web サイトに掲載される前に、特定の品質管理基準を満たしていることが確認されます。

主要日程の研究

研究開始 (実際)

2024年1月1日

一次修了 (実際)

2024年12月31日

研究の完了 (実際)

2024年12月31日

試験登録日

最初に提出

2026年6月27日

QC基準を満たした最初の提出物

2026年6月27日

最初の投稿 (実際)

2026年7月2日

学習記録の更新

投稿された最後の更新 (実際)

2026年7月2日

QC基準を満たした最後の更新が送信されました

2026年6月27日

最終確認日

2026年6月1日

詳しくは

本研究に関する用語

個々の参加者データ (IPD) の計画

個々の参加者データ (IPD) を共有する予定はありますか?

いいえ

IPD プランの説明

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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米国FDA規制医薬品の研究

いいえ

米国FDA規制機器製品の研究

いいえ

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