LungVision AI-Augmented Fluoroscopic Navigation for Intraoperative Pulmonary Nodule Localization
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
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
入学 (実際)
段階
- 適用できない
連絡先と場所
研究場所
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Taiwan
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Taipei、Taiwan、台湾、114202
- Tri-Service General Hospital
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参加基準
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
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
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 |
|---|---|
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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.
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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.
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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 |
|---|---|---|
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Localization Success Rate
時間枠:Intraoperative
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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.
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Intraoperative
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協力者と研究者
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (実際)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
キーワード
その他の研究ID番号
- TSGH-LV-2026
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?
IPD プランの説明
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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