by Kerri Glover
Business Development & Marketing Services
A new automated computer system shows promise in enhancing the ability
of coronary CT angiography (cCTA) to rule out significant stenosis
(narrowing) of coronary arteries in patients with chest pain at low to
moderate risk of coronary artery disease (CAD).
Several million patients are hospitalized each year to definitely
determine whether they suffer from CAD. The new computer system
enhances the ability to quickly exclude significant narrowing or
blockage of the heart vessels through use of cCTA and thus has
significant potential to assist in reducing unnecessary
hospitalizations. The results, the first peer-reviewed published
analysis of a fully automated, computer supported cCTA coronary
stenosis detection system, appears online in European Radiology.
“Computer aided detection has been integrated into clinical practice
for a number of diseases, but surprisingly to date not to CAD,” said
Joseph Schoepf, M.D., professor of radiology and cardiology, director
of cardiovascular imaging at MUSC, and lead investigator in the study.
“CAD is the most important socioeconomic health care problem in the
western world and there is an urgent need for new methods to improve
timely and accurate detection and reduce costs.”
CAD is estimated to affect approximately 16 million Americans, causes
1.2 million heart attacks, and more than 450,000 deaths. The direct
costs of CAD are estimated at more than $87 billion. Several million
patients with chest pain for whom CAD is ultimately ruled out are
admitted to the hospital from emergency departments each year, at a
cost of more than $10 billion.
cCTA is being used increasingly as a non-invasive procedure for
coronary blood vessel analysis, particularly as a means to rule out
significant disease in patients with atypical presentation. However,
successful interpretation of cCTA requires considerable expertise. “The
findings of this study suggest that if used as a ‘second reader,’ the
high negative predictive value demonstrated by this system may enhance
the confidence and efficiency of excluding significant stenosis based
on a normal or near-normal cCTA study,” Schoepf noted.
In the study led by Schoepf and others at MUSC, researchers evaluated
the system, called the COR Analyzer, with cCTA in patients who also
underwent invasive coronary catheter angiography due to suspected CAD.
The system was developed by Rcadia Medical Imaging and is FDA cleared.
In the study, none of the patients who were cleared by the system were
found to have significant stenosis by invasive coronary catheter
angiography (100 percent negative predictive value). Moreover, the
researchers found that the system had relatively high accuracy overall
in detecting significant stenosis.
“Use of computer aided algorithms for other diseases are effective in
ruling out disease but have been complicated by the sometimes
overwhelming number of false positives,” Schoepf continued. “Compared
to computer systems developed for other diseases, the performance of
the algorithm evaluated here is comparatively high; particularly, the
low number of false positives along with the 100 percent sensitivity
and 100 percent negative predictive value on a per patient basis appear
The study investigated 59 patients without known prior CAD who had been
referred for invasive coronary catheter angiography due to atypical
chest pain or an abnormal cardiac blood flow study. In the study, 19 of
59 patients had significant (50 percent vessel narrowing or more)
coronary stenosis and significant stenosis was ruled out in 40 patients
based on invasive coronary catheter angiography. The COR Analyzer
correctly identified all 19 patients with significant stenosis in any
vessel, and correctly excluded significant stenosis in 26 of 40
patients. The negative predictive value was 100 percent on a per
patient basis, while the algorithm had 100 percent sensitivity, 65
percent specificity, and 58 percent positive predictive value compared
with invasive coronary catheter angiography. The COR Analyzer System
automatically processes images acquired on cCTA and generates
comprehensive results and corresponding reports within minutes. The
system’s algorithm determines the presence of significant lesions (more
than 50 percent stenosis) in the coronary arteries and visualizes the
results through the use of detection marks to indicate the location of
Using the system as a second reader, a physician in an emergency room
setting may find reassuring verification of his or her exclusion of
significant stenosis based on a normal or near-normal cCTA study. “This
may be particularly helpful in on-call situations where relatively
inexperienced trainees are increasingly called upon to rule out
significant coronary artery stenosis in patients with acute chest pain
using CT,” the researchers observed.
The paper is titled, “Automated Computer-Aided Stenosis Detection at Coronary CT Angiography: initial experience” [http://dx.doi.org/10.1007/s00330-009-1644-7].
In addition to Schoepf, the authors on the study included Elisabeth
Arnoldi, Mulugeta Gebregziabher, Luis Ramos-Duran, Peter L. Zwerner,
Philip Costello, and Christian Thilo from MUSC, Roman Goldenberg,
Rcadia Medical Systems, and Konstantin Nikolau and Max Reiser from
Ludwig-Maximilians University (Munich, Germany).
Friday, Nov. 13, 2009