An observational study in Coronary Artery Disease, Atherosclerosis and Myocardial Ischemia, sponsored by Instituto de Investigación Biomédica de Salamanca. Recruiting at 4 sites in 3 countries. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-04-21.
Sponsored by Instituto de Investigación Biomédica de Salamanca · Observational
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.
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.
5,600 studies on the registry are indexed under Coronary Artery Disease; 958 are open to participants now.
This study's planned enrollment of 1,000 is above the median of 336 across 1,947 observational studies indexed under Coronary Artery Disease.
Browse Coronary Artery Disease studies →Instituto de Investigación Biomédica de Salamanca is the lead sponsor of 20 studies on the registry; 15 are open to participants now.
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Retrospective cohort of 1,000 adult patients who underwent coronary computed tomography angiography (CCTA) between 2019 and 2024 for the diagnosis or assessment of coronary artery disease (CAD), at four academic hospitals in Spain, the Netherlands, and France. All patients have comparator diagnostic data available, such as invasive coronary angiography (ICA) and/or other non-invasive imaging. No new data collection or interventions will be performed, and all analyses will be conducted offline on de-identified datasets
Exclusion Criteria:
- Insufficient image quality to determine coronary stenosis or assess CAD parameters in routine clinical use
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
Device: Diagnostic Software Application for CAD Assessment
A novel on-premises diagnostic software integrating automated coronary stenosis detection, CT-derived fractional flow reserve (CT-FFR), and plaque quantification for evaluation of coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) datasets.
Diagnostic accuracy of CAD-RADS classification using the diagnostic software
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.
Time frame: At study completion (expected March 2025)
Reproducibility of CAD-RADS classification using the diagnostic software
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.
Time frame: At study completion (expected March 2025)
User satisfaction with the diagnostic software application
User satisfaction will be evaluated using a standardized 5-point Likert scale questionnaire completed by radiologists and cardiac imagers. The scale ranges from 1 (Very dissatisfied) to 5 (Very satisfied). Higher scores indicate greater satisfaction with the usability and performance of the software.
Time frame: After completion of image analysis (expected March 2025)
Accuracy of the software in predicting the need for percutaneous coronary intervention (PCI)
Comparison between PCI recommendations generated by the software application (based on CCTA and CT-FFR analysis) and actual PCI decisions made in clinical practice.
Time frame: At study completion (expected March 2025)
Proportion of invasive coronary angiographies (ICA) without PCI potentially avoidable based on software analysis
Percentage of ICA procedures not followed by PCI that could have been avoided based on retrospective evaluation with the diagnostic software.
Time frame: At study completion (expected March 2025)
Plan to share: Yes — De-identified individual participant data (IPD), including imaging datasets and related diagnostic parameters, may be shared for additional analyses in compliance with GDPR and FAIR data principles. Data will be stored in secure, GDPR-compliant repositories and may be made available upon reasonable request following project completion and publication of main results.
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Instituto de Investigación Biomédica de Salamanca