CODEX1 TRIAL: Complete One-Stop-Shop Diagnosis Of Coronary Artery Disease On Computed Coronary Tomography Angiography: From the COMBINE-CT Study
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,000
- 试验地点
- 8
- 主要终点
- Diagnostic accuracy of CAD-RADS classification using the diagnostic software
研究概览
简要总结
The CODEX-1 study is a multicenter retrospective observational study designed to assess the diagnostic performance of a novel software application for coronary artery disease (CAD) evaluation. The application integrates automated stenosis detection, CT-derived fractional flow reserve (CT-FFR), and plaque quantification, all performed on-site. A total of 1,000 patients who previously underwent coronary computed tomography angiography (CCTA) and diagnostic invasive coronary angiography (ICA) and/or other non-invasive imaging will be included. The study compares the diagnostic outputs of the software to current clinical practice and expert adjudication, focusing on CAD-RADS categorization, prediction of the need for percutaneous coronary intervention (PCI), and reduction in unnecessary ICA procedures.
详细描述
Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide. Coronary computed tomography angiography (CCTA) has become a first-line diagnostic tool for patients with suspected CAD, and its utility can be further enhanced through the use of advanced software for automated assessment. The CODEX-1 study is a multicenter, retrospective, observational cohort study aimed at evaluating the diagnostic performance of a novel on-site software application integrating three key features: automated stenosis detection and CAD-RADS categorization, CT-derived fractional flow reserve (CT-FFR), and quantitative plaque analysis.
The study will include 1,000 patients who underwent CCTA for CAD assessment between 2019 and 2024 at four European centers. All participants also have comparator diagnostic data available, such as invasive coronary angiography (ICA), stress MRI, or CCTA analyzed using alternative methods. The software's output will be compared against current clinical practice and expert consensus, with a focus on diagnostic accuracy, inter-reader variability, and the potential to reduce unnecessary ICA procedures.
The study will not involve any patient intervention, and all data analyses will be performed offline using de-identified imaging datasets. The results are expected to provide evidence on the feasibility and accuracy of integrating multiple diagnostic tools into a single application, enabling faster and more consistent CAD diagnosis in clinical practice.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
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
- •Age 18 years or older
- •Underwent coronary computed tomography angiography (CCTA) for the diagnosis or assessment of coronary artery disease (CAD) between 2019 and 2024
- •Availability of comparator diagnostic data within 1 month before or after the CCTA, such as: Invasive coronary angiography (ICA), Stress MRI, Alternative CCTA analysis software, Documented clinical events
排除标准
- •- Insufficient image quality to determine coronary stenosis or assess CAD parameters in routine clinical use
研究组 & 干预措施
Cohort_1
Patients who underwent coronary computed tomography angiography (CCTA) between 2019 and 2024 for the assessment or diagnosis of coronary artery disease (CAD), with available comparator diagnostic data such as invasive coronary angiography (ICA) and/or other non-invasive imaging. No interventions are performed as part of this study
干预措施: Diagnostic Software Application for CAD Assessment (Device)
结局指标
主要结局
Diagnostic accuracy of CAD-RADS classification using the diagnostic software
时间窗: At study completion (expected March 2025)
Accuracy of the CAD-RADS category assigned by the software compared to expert adjudication using invasive coronary angiography (ICA) and/or other non-invasive imaging.
Reproducibility of CAD-RADS classification using the diagnostic software
时间窗: At study completion (expected March 2025)
Assessment of inter-reader and intra-reader reproducibility in CAD-RADS classification using the software, evaluated via kappa statistics and intraclass correlation coefficients (ICC), stratified by reader experience.
次要结局
- User satisfaction with the diagnostic software application(After completion of image analysis (expected March 2025))
- Accuracy of the software in predicting the need for percutaneous coronary intervention (PCI)(At study completion (expected March 2025))
- Proportion of invasive coronary angiographies (ICA) without PCI potentially avoidable based on software analysis(At study completion (expected March 2025))