Research on New Intelligent Diagnosis and Treatment Technologies for Early Lung Cancer Based on Multimodal Imaging Bronchoscopy Navigation
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 92
- 试验地点
- 1
- 主要终点
- Diagnostic positive yield
研究概览
简要总结
To verify the clinical effectiveness and safety of the airway tree navigation system constructed by artificial intelligence (AI) in the navigation diagnosis of peripheral pulmonary nodules (PPLs).
详细描述
Early diagnosis and treatment of lung cancer is of great significance, in which navigated tracheoscopic biopsy is an important tool for confirming the diagnosis of early lung cancer. Conventional navigation software realizes airway reconstruction and guides biopsy by recognizing differences in HU values on computed tomography scans. It is difficult for conventional navigation software to recognize the reconstruction due to the special characteristics of small airways that are susceptible to interference and collapse. Therefore, an AI deep learning approach can realize accurate construction of small airways and guide accurate biopsy. This study intends to validate the clinical effectiveness and safety of the AI-constructed airway tree navigation system in the navigational diagnosis of peripheral pulmonary nodules (PPLs).
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- Single (Participant)
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Aged 18 years or above.
- •Patients with one or more peripheral lung nodules suspected to be lung cancer or poorly absorbing lesions on conventional anti-infective therapy.
- •Patients with nodule diameters ≤30 mm (diameters mentioned in the text are the average of the maximum and minimum diameters).
- •The nodules were pure ground glass nodules, partially solid nodules, or solid nodules.
- •The nodule is surrounded by lung parenchyma and is not visible in the bronchial lumen above the segment.
排除标准
- •Preoperative judgment that it is difficult for the patient to benefit from bronchoscopic biopsy (e.g., high risk of bleeding due to perivascular encasement of the lesion, difficulty in reaching the airway adjacent to the lesion due to previous lung surgery, etc.).
- •Those with incomplete clinical data.
- •Those with missing visits after biopsy.
研究组 & 干预措施
New navigation system group
The new AI-constructed airway tree navigation system (SARS-pro) was used for preoperative navigation path planning. The SARS-pro navigation system was independently developed by the research group based on a conventional augmented reality optical navigation system (LungPro; Bronchus Company).
干预措施: Preoperative navigation path planning using the SARS-pro navigation system (Diagnostic Test)
Old navigation system group
Preoperative navigation path planning was performed using the old VBN system (LungPro; Bronchus Company).
干预措施: Preoperative navigation path planning using the VBN navigation system (Diagnostic Test)
结局指标
主要结局
Diagnostic positive yield
时间窗: One month after the patients were enrolled
After biopsy by navigational bronchoscopy, the biopsy tissue was tested for lung cancer pathology. A positive diagnosis was defined when the pathology report was a neoplastic lesion (benign or malignant tumor). A positive diagnosis was also made if the pathology report was a granulomatous lesion (with tuberculosis or fungus). If the pathology was reported as an inflammatory cell infiltration or other non-specific inflammation in the lungs, the subject underwent another pathology biopsy after at least 3 months of follow-up to rule out false-positive results due to a change in the site of the lesion.
次要结局
- Adverse events(3 days after navigational tracheoscopic biopsy)
研究者
Jisong Zhang
Doctor of Medicine
Sir Run Run Shaw Hospital