Automatic Segmentation of Mediastinal Lymph Nodes and Blood Vessels in Endobronchial Ultrasound (EBUS) Images Using a Deep Neural Network
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 50
- 试验地点
- 2
- 主要终点
- Capability
研究概览
简要总结
To evaluate the usefulness of Deep neural network (DNN) in the evaluation of mediastinal and hilar lymph nodes with Endobronchial ultrasound (EBUS). The study will explore the feasibility of DNN to identify lymph nodes and blood vessel examined with EBUS.
详细描述
Multi-center prospective feasibility study. The DNN model will be trained on ultrasound images with annotation to identifies lymph nodes and blood vessels examined with EBUS. The ability of the DNN to segment lymph nodes and vessels based on postoperative processing and static EBUS images will be evaluated in the first part of the study. In the second part of the study Real-time use of DNN in EBUS procedure will be evaluated.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Subjects referred to thoracic department in any of the participating hospitals with undiagnosed enlarged mediastinal and hilar lymph nodes.
- •Subjects have to be ≥ 18 years of age
排除标准
- •Pregnancy
- •Any patient that the Investigator feels is not appropriate for this study for any reason.
结局指标
主要结局
Capability
时间窗: 8 months
To explore if Deep neural network (DNN) has capability to segment lymph nodes and blood vessels from EBUS images
次要结局
- Precision(2 months)
- Dice similarity coefficient(2 months)
- Run-time(2 months)
- Adverse events(48 hours)
- Sensitivity(2 months)
- Specificity(2 months)