NCT04482114已完成不适用
Detection and Volumetry of Pulmonary Nodules on Ultra-low Dose Chest CT Scan With Deeplearning Image Reconstruction Algorithm (DLIR)
适应症
干预措施
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 70
- 试验地点
- 2
- 主要终点
- Diagnostic accuracy
研究概览
简要总结
evaluate the diagnostic performance of ultra-low dose CT using deep learning-based reconstruction in the detection of pulmonary nodules.
详细描述
- Background: Lung cancer is the leading cause of cancer deaths. Patients with pulmonary nodules often undergo multiple computed tomography (CT) examinations for diagnostic and follow-up purposes.
- Purpose: The main objective of this study is to evaluate the diagnostic performance of ultra-low dose CT using deep learning-based reconstruction in the detection of pulmonary nodules.
- Abstract: Despite recent advances, lung cancer remains the most commonly diagnosed cancer and the leading cause of cancer death worldwide because it is often diagnosed at advanced stages that are not surgically curable. Nevertheless, early detection of lung cancer allows surgical resection, offers curative treatment and the best chance of survival. There is currently no screening program in France, but individual screening can be carried out depending on risk factors. Many pulmonary nodules are discovered each year, most of which are benign. The challenge is to distinguish malignant lesions from the multitude of benign lesions. One of the most effective criteria is the doubling time of the nodules which leads to multiple follow-up examinations requiring ionizing radiation to assess the size and growth of the nodules. Great efforts are currently being made by CT manufacturers in order to reduce the radiation with equivalent diagnostic performance. Patients who were referred to our department for an unenhanced low-dose chest CT (LD CT) for pulmonary nodules check-up or follow-up, and had consented to participate in the study, will undergo an additional ultra-low dose acquisition (ULDCT, <0,25 mSv, similar to standard two-view chest X-Ray) with deep learning-based reconstruction (DLIR). The main objective of this study is to evaluate the diagnostic performance between ULD and LD CT protocols for the detection of pulmonary nodules. The impact of dose reduction will be assessed in this context. The data from each examination will be blindly interpreted from the results of the other one. No follow-up will be required for the study.
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 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age ≥ 18 years old,
- •Patient referred for non-enhanced chest CT for lung nodule check-up or follow-up,
- •Affiliation to a social security program,
- •Ability of the subject to understand and express opposition
排除标准
- •Age <18 years old,
- •Person under guardianship or curatorship,
- •Pregnant woman,
- •Any contraindications to CT
研究组 & 干预措施
ultra-low dose CT
Other
All the examinations are part of the routine care. Addition of the ULD CT protocol does not require injection of contrast agent and does not extend the duration of the examination.
干预措施: ULD CT (Radiation)
结局指标
主要结局
Diagnostic accuracy
时间窗: Day 0
The study aimed to investigate the diagnostic accuracy (Sensibility and Specificity) of ultra-low dose CT using DLIR reconstruction for the detection of pulmonary nodules in comparison with the low dose CT reference protocol.
次要结局
- Pulmonary nodules volume(Day 0)
- Image quality(Day 0)
研究者
研究点 (2)
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