Pulmonary Nodule Localization Under Thoracoscopic Surgery- a Machine Learning Based Retrospective Analysis and Prospective Validation
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 50
- 试验地点
- 1
- 主要终点
- Nodule detection
研究概览
简要总结
Localization is the key for successful excision of small target nodules under thoracoscopy, but the procedure also brings risks to patients. However, the criteria is still unclear. The investigators will validate the prediction model produced by institutional retrospective analysis in the prospective cohort.
详细描述
Excision of targeted lung nodules during thoracoscopy sometimes needs placing a mark before surgery. The procedure of mark placement (localization) could probably cause damages to the patients. However, the criteria for patient selection is still not clear. Through respective analysis, the investigators have set up a prediction model and wish to validate this model prospectively.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 20 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≧ 20 years
- •Lung nodule size ≦2cm on the pre-operative computed tomography (CT)
- •Nodulectomy is performed under thoracoscopy
排除标准
- •Age < 20 years
- •Lung nodule size > 2cm on CT or in the final pathology report
- •Open surgery for nodulectomy
结局指标
主要结局
Nodule detection
时间窗: During surgery
Whether the nodule could be detected by conventional visualization or palpation
次要结局
未报告次要终点
研究者
Tu, Yuan-Kun
president
E-DA Hospital