Physicians at Thomas Jefferson University Hospital reported on results of a study demonstrating the potential for fully automated interpretation of coronary CT angiography (cCTA) by Rcadia's COR Analyzer® System to safely rule out coronary artery disease (CAD) in the major coronary arteries as well as branch vessels. The study was presented in Chicago at the Radiological Society of North America (RSNA) Annual Meeting.

"The emergence of cCTA in detecting CAD is creating a growing need for new methods to facilitate study analysis," said Ethan Halpern, MD, Associate Professor in the Dept. of Radiology at the University's Jefferson Medical College and the study's principal investigator. "The results of the study, performed on 207 cases, show that automated interpretation of cCTA has a high negative predictive value for the absence of coronary disease and demonstrate its potential as an effective preliminary analysis tool to triage cases for final interpretation."

The COR Analyzer® System is a unique clinical decision support tool that performs fully automatic analysis of Coronary CT Angiography (cCTA) studies. The system, which rapidly identifies the presence of significant (50 percent and over) stenosis, is designed to accelerate triage in the emergency department. It assists in reducing unnecessary admissions by ruling out CAD as a cause of chest pain and shortens time to treatment of suspected CAD patients. In the radiology and cardiology department settings, the immediate indication of suspected significant CAD provided by the COR Analyzer, allows workflow optimization and prioritization of reading sequence.

The study evaluated an enhanced version of the system that assesses coronary branch vessels in addition to main coronary arteries. In the study, COR Analyzer assessments of 207 cCTA examinations were compared with the evaluations of an expert reader. The final clinical interpretation identified 48 patients with significant stenosis. The COR Analyzer demonstrated a sensitivity of 92 percent and a negative predictive value of 97 percent. The specificity was 70 percent, and positive predictive value was 48 percent in the study.

"The potential of the COR Analyzer to fill a key need in CAD detection and management has been validated in more than 10 studies," said Shai Levanon, President and CEO of Rcadia. "The ability to support rapid decisions to rule out CAD has demonstrated great potential both to improve patient care and reduce unnecessary costs."

Two additional studies were presented at RSNA by researchers at the Medical University of South Carolina. One study followed 247 patients for one year after the COR Analyzer ruled out significant stenosis and found that none had a subsequent coronary event. The second study demonstrated the potential of the COR Analyzer to increase the performance of inexperienced readers.

The COR Analyzer is also being presented this year at the "RSNA Quantitative Imaging Reading Room of the Future."

Source: Rcadia Medical Imaging