A team of doctors at the Thomas Jefferson University Hospital, have released the outcomes of an investigation revealing the potential of a completely automated analysis of coronary CT angiography (cCTA) by the COR Analyzer System of Rcadia.
This system helps to safely exclude coronary artery disease (CAD) found in coronary branch vessels and arteries. The investigation results were discussed at the Annual meeting of the Radiological Society of North America (RSNA), which was held in Chicago.
Ethan Halpern, Principal Investigator of the Study and Associate Professor in the Department of Radiology at the University's Jefferson Medical College, has stated that the emerging utilization of cCTA in identifying CAD has created an increased requirement to identify new methods, facilitating research analysis. He mentioned that the investigation was carried out on 207 patients and its outcomes reveal that automated analysis of cCTA has a high negative value of prediction for the nonexistence of coronary disease and establishes its utilization as an ideal investigation tool to prioritize cases for final analysis.
The COR Analyzer System is an innovative clinical decision assistance system that automatically examines cCTA investigation. The analyzer detects the presence of 50% and more stenosis and then speeds up triage in the emergency section of the hospital. It also helps in bringing down needless admissions by eliminating CAD as a basis of chest pain and reduces the time required to treat assumed CAD victims. This instant warning of CAD suspects enables streamlining of workflow as well as giving priority during reading sequence in the cardiology and radiology departments.
The investigation assessed an improved version of the COR Analyzer System that examines coronary vessels as well as main coronary arteries. The evaluations made by the system were compared with the assessments of a proficient reader. The concluding clinical analysis diagnosed major stenosis in 48 cases. The COR Analyzer System showcased 92% sensitivity, specificity of 70% and 97% and 48% of positive predictive and negative predictive values respectively.
According to Shai Levanon, President and CEO of Rcadia, the validation of the potential of COR Analyzer in detecting and managing CAD has been successfully performed in 10 studies and has showcased greater potential in ruling out CAD. He added that their system not only enhances patient care but also avoids unnecessary expenses.
The COR Analyzer System is scheduled to be displayed this year at the ‘RSNA Quantitative Imaging Reading Room of the Future’.