Abstract

An increasing number of studies have examined the role of coronary computed tomographic angiography (CCTA) in assessing patients with known or suspected coronary artery disease (CAD) relative to established evaluation approaches. The diagnostic and predictive value of stress electrocardiography, stress imaging, and invasive, selective coronary angiography (SCA) is documented by a large body of evidence, and their use to guide patient management is codified in clinical guidelines. To date, no convincing evidence suggests that the diagnostic or predictive value of CCTA is superior or even equivalent. Consequently, no first-line indications for CCTA exist.1,2 However, there may be niche applications where CCTA could be a potentially effective and cost-saving alternative to more established imaging techniques. Studies comparing CCTA with SCA have universally shown a high negative predictive value (NPV).3 As a result, a ‘negative’ CCTA excludes CAD with very high certainty if image quality is diagnostic and most coronary segments are well seen, particularly in populations with a low prevalence of CAD. A valid argument can be made that patients with low pre-test probability do not need testing at all. However, there are clinical scenarios in which SCA is often performed because proving the absence of CAD has important diagnostic or therapeutic implications, or because the diagnostic accuracy of conventional stress testing is reduced. Ghostine et al. 4 address the potential use of CCTA in one of these scenarios. The authors examined the role of 64-slice multidetector CCTA in non-invasively classifying symptomatic left ventricular (LV) dysfunction as ischaemic or non-ischaemic. They determined, in 93 consecutive heart failure patients without known CAD, the diagnostic accuracy of CCTA in predicting >50% diameter stenoses detected on SCA. Cardiomyopathy was classified as ischaemic if coronary stenoses were present in the left main coronary artery or the proximal left … *Corresponding author. Email: kantor.birgit{at}mayo.edu

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