KCT0005065已完成未知
A multi-center, retrospective pivotal trial to evaluate the efficacy of artificial intelligence-based pulmonary nodule detection software ‘VUNO Med – Lung CAD’ in thoracic CT
Vuno0 个研究点目标入组 855 人开始时间: 待定最近更新:
适应症
试验速览
- 阶段
- 未知
- 状态
- 已完成
- 发起方
- 入组人数
- 855
研究概览
简要总结
暂无简介。
研究设计
- 研究类型
- Interventional Study
入排标准
- 年龄范围
- 19(Year) 至 o Limit（—）
- 性别
- All
入选标准
- •1) Adults at the age 19 or above who had a thoracic CT scan within the period from Jan 2012 to Jun 2018
- •2) Patients whose thoracic CT scan showed no or 1 to 5 pulmonary nodules with the long-axis diameter from 4 mm to 30 mm
排除标准
- •1) Women who was pregnant or breast-feeding on the date of the thoracic CT scan
- •2) Patients who had been diagnosed with cancers other than lung cancer within 5 years
- •3) Patients who had any of following medical records:
- •?-Severe pulmonary fibrosis
- •?-Diffuse bronchiectasis
- •?-Extensive pulmonary consolidation
- •?-Massive pleural effusion
- •?-Active or latent tuberculosis
- •4) Patients whose thoracic CT scans difficult to be read due to any reasons described as below:
- •?-Images not fully showing regions of interest (e.g., when it is unable to see both lungs, when at least one slice above lung apex and both adrenal glands are not included.)
- •?-Images with a severe artifact due to the patient movement or technical problems
- •?-Images of slice thickness exceeded 5 mm
- •?-Images with interslice gaps
- •?-Images not using standard reconstruction kernel
- •?- Images that structures of lung and mediastinum are not fully evaluated due to poor resolution
- •5) Patients who are otherwise considered to be not suitable for participating in the study by the investigator
研究者
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