The challenge of improving risk assessment in asymptomatic individuals: the additive prognostic value of electron beam tomography?

The detection of atherosclerosis has changed considerably over the past few decades, with an ever-increasing array of diagnostic tools available to the researcher and practicing clinician. For many decades, traditional risk factor assessment was the mainstay for prognostication, forming a basis for preventive strategies aimed at risk reduction. More recently, new laboratory markers (e.g., C-reactive protein), as well as cardiac imaging techniques (e.g., electron beam computed tomography [EBCT]), are being advocated as optimal tools for the detection of subclinical disease and as predictors of obstructive coronary artery disease (CAD) and worsening prognosis. Electron beam computed tomography is attractive due to the ease of measurement of coronary calcium as compared with other measures, such as carotid intimal medial thickness. Considerable previous evidence suggests that the extent of coronary calcification is strongly related to plaque burden, but is less reliable for detecting vulnerable plaque (1,2). Calcification of the coronary artery occurs as part of the development of atherosclerosis and is not present in a normal vessel wall. As an emerging technique, EBCT has merit but also disadvantages that temper our enthusiasm for its widespread clinical use (2). Recently, the American College of Cardiology in association with the American Heart Association (AHA) presented an updated technology evaluation on the use of EBCT for the diagnosis of CAD in symptomatic patients, for risk assessment in asymptomatic individuals and for serial monitoring of drug therapy (2,3). Other reviews on EBCT have been published by the AHA Prevention V Conference and Blue Cross/Blue Shield Technology Evaluation Center (Chicago, Illinois). From either the payer perspective or that of medical societies, there is consensus that widespread use of EBCT for disease or risk assessment is not supported by current data (2,3). When examining the predictive accuracy of EBCT, the weight and quality of the evidence are dependent on the rigor with which the data are analyzed, as well as its comparative accuracy in relation to other noninvasive techniques (2). This editorial comment highlights the current state of evidence on EBCT, including examples from the Arad report (4) in this issue of the Journal.