Computer-aided simple triage (CAST) for coronary CT angiography (CCTA)
| Autor: | Eugene Walach, Dov Eilot, Roman Goldenberg, Eyal Ben-Ishai, Nathan Peled, Grigory Begelman |
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| Rok vydání: | 2012 |
| Předmět: |
Chest Pain
medicine.medical_specialty Cath lab Population Biomedical Engineering Health Informatics Coronary Artery Disease Coronary Angiography Chest pain Sensitivity and Specificity Coronary artery disease medicine Humans Radiology Nuclear Medicine and imaging Computer-aided simple triage Diagnosis Computer-Assisted education education.field_of_study business.industry General Medicine medicine.disease Computer Graphics and Computer-Aided Design Triage Computer Science Applications Coronary arteries Stenosis medicine.anatomical_structure Surgery Computer Vision and Pattern Recognition Radiology medicine.symptom business Software |
| Zdroj: | International Journal of Computer Assisted Radiology and Surgery. 7:819-827 |
| ISSN: | 1861-6429 1861-6410 |
| DOI: | 10.1007/s11548-012-0684-7 |
| Popis: | Following a recent introduction of computer-aided simple triage (CAST) as a new subclass of computer-aided detection/diagnosis (CAD), we present a CAST software system for a fully automatic initial interpretation of coronary CT angiography (CCTA). We show how the system design and diagnostic performance make it CAST-compliant and suitable for chest pain patient triage in emergency room (ER). The processing performed by the system consists of three major steps: segmentation of coronary artery tree, labeling of major coronary arteries, and detection of significant stenotic lesions (causing > 50% stenosis). In addition, the system performs an automatic image quality assessment to discards low-quality studies. For multiphase studies, the system automatically chooses the best phase for each coronary artery. Clinical evaluation results were collected in 14 independent trials that included more than 2000 CCTA studies. Automatic diagnosis results were compared with human interpretation of the CCTA and to cath lab results. The presented system performs a fully automatic initial interpretation of CCTA without any human interaction and detects studies with significant coronary artery disease. The system demonstrated higher than 90% per patient sensitivity and 40–70% per patient specificity. For the chest pain, ER population, the specificity was 60–70%, yielding higher than 98% NPV. The diagnostic performance of the presented CCTA CAD system meets the CAST requirements, thus enabling efficient, 24/7 utilization of CCTA for chest pain patient triage in ER. This is the first fully operational, clinically validated, CAST-compliant CAD system for a fully automatic analysis of CCTA and detection of significant stenosis. |
| Databáze: | OpenAIRE |
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