Identification of Interscalene Brachial Plexus Automatically on Ultrasonography Using a Deep Neural Network
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,126
- 试验地点
- 1
- 主要终点
- The distance of the lateral midpoints of the nerve sheath contours
研究概览
简要总结
The purpose of the study is to develop and validate an algorithm based on deep neural networks (DNNs) to identify interscalene brachial plexus on ultrasonography automatically.
详细描述
The investigators plan to develop a deep learning-based network to automatically identify interscalene brachial nerves on ultrasound images. The trained model will be validated on an independent dataset. The performance of the network will also be compared against practicing anesthesiologists.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
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
- •ASA physical status class I or II
- •scheduled for elective surgery
排除标准
- •skin lesion or infection of neck
- •any known peripheral neuropathy
- •brachial nerve plexus injury
- •previous injury or operation on neck
- •pregnancy
- •allergic to ultrasound gel
结局指标
主要结局
The distance of the lateral midpoints of the nerve sheath contours
时间窗: immediately after the procedure
between model predictions and the ground truth; between nonexpert anesthesiologist predictions and the ground truth
次要结局
- Accuracy, Sensitivity and specificity(immediately after the procedure)
- The percentage of the intersection over union(immediately after the procedure)
研究者
Xiao-Yu Yang, MD
Principal Investigator
Huashan Hospital
