Study Examines Prognostic Value of Semiautomated Coronary Plaque Quantification

June 4, 2013—Mathijs O. Versteylen, MD, et al published a study in the Journal of the American College of Cardiology (JACC) that investigated whether a semiautomated plaque quantification algorithm provides additional prognostic value for the development of acute coronary syndromes (ACS) compared with conventional reading from cardiac computed tomography angiography (CCTA).

The investigators described the study as including 1,650 patients who were examined using 64-slice CCTA and followed up for ACS (mean, 26 ± 10 months). Coronary artery disease was evaluated in 24 patients who had ACS and 101 random controls who were selected from 993 patients with coronary artery disease but without coronary event. These patients were evaluated using conventional reading and semiautomated software. Conventional reading evaluated calcium score, luminal stenosis, and morphology; the semiautomated software quantified plaque volume, burden area (defined as plaque area divided by vessel area times 100%), noncalcified percentage, attenuation, and remodeling. The Framingham risk score was used to calculate clinical risk profile.

There were no significant differences in conventional reading parameters reported between controls and patients who had ACS. Semiautomated plaque quantification showed that compared to controls, ACS patients had higher total plaque volume (median, 94 mm³ vs. 29 mm³) and total noncalcified volume (28 mm³ vs. 4 mm³, P ≤ .001 for both); in addition, per-plaque maximal volume (median, 56 mm³ vs. 24 mm³), noncalcified percentage (62% vs. 26%), and plaque burden (57% vs. 36%) in ACS patients were shown to be significantly higher (P < .01 for all). The results further showed that a receiver-operating characteristic model predicting for ACS incorporating FRS and conventional CCTA reading had an area under the curve of 0.64; a second model also incorporating semiautomated plaque quantification had an area under the curve of 0.79 (P < .05).

As summarized in JACC, the study concluded that the semiautomated plaque quantification algorithm identified parameters that were predictive for acute coronary syndromes. These provided incremental prognostic value over clinical risk profile and conventional CT reading. The authors suggest that this tool may improve risk stratification in patients undergoing CCTA.