AIMS: To assess plaque characteristics by multi-detector computed tomography angiography in patients with known coronary artery disease and to compare these findings with those obtained with intravascular ultrasound-derived radiofrequency analysis of plaque composition. METHODS AND RESULTS: By computed tomography, lesions were classified on the basis of Hounsfield Units as non-calcified, calcified, or mixed. By intravascular ultrasound-derived radiofrequency analysis, plaques were classified according to the relative composition of components with specific backscatter characteristics (necrotic core, fibrous, fibro-fatty, calcium). Thin cap fibroatheroma (defined as necrotic core component >10% without evidence of fibrotic cap, calcium >5%, remodelling index >1.05) was considered as vulnerable plaque. Seventy-eight plaques were analysed. By computed tomography, 22 plaques were classified as non-calcified and 56 as mixed. A higher incidence of mixed plaques was observed among lesions causing unstable angina and non-ST elevation myocardial infarction compared to stable angina (76% vs 38%, p=0.04). Plaque composition by radiofrequency analysis was significantly different between mixed and non-calcified plaques by computed tomography. The calcium content was 6.0+/-3.2% vs 2.5+/-1.8% (p=0.001), necrotic core was 14.0+/-6.9% vs 7.5+/-5.6% (p=0.03) and fibrous tissue was 59.0+/-7.5% vs 67.0+/-5.9% (p=0.03), for mixed vs non-calcified plaques, respectively. Positive, negative predictive value and diagnostic accuracy for detection of vulnerable plaque by computed tomography was 77, 54 and 59%. CONCLUSIONS: Mixed plaque by computed tomography correlates with plaque composition as determined by intravascular ultrasound-derived radiofrequency analysis. However, the present diagnostic accuracy of computed tomography is not high enough to support its use for non invasive detection of vulnerable coronary plaque.
AIMS: To assess plaque characteristics by multi-detector computed tomography angiography in patients with known coronary artery disease and to compare these findings with those obtained with intravascular ultrasound-derived radiofrequency analysis of plaque composition. METHODS AND RESULTS: By computed tomography, lesions were classified on the basis of Hounsfield Units as non-calcified, calcified, or mixed. By intravascular ultrasound-derived radiofrequency analysis, plaques were classified according to the relative composition of components with specific backscatter characteristics (necrotic core, fibrous, fibro-fatty, calcium). Thin cap fibroatheroma (defined as necrotic core component >10% without evidence of fibrotic cap, calcium >5%, remodelling index >1.05) was considered as vulnerable plaque. Seventy-eight plaques were analysed. By computed tomography, 22 plaques were classified as non-calcified and 56 as mixed. A higher incidence of mixed plaques was observed among lesions causing unstable angina and non-ST elevation myocardial infarction compared to stable angina (76% vs 38%, p=0.04). Plaque composition by radiofrequency analysis was significantly different between mixed and non-calcified plaques by computed tomography. The calcium content was 6.0+/-3.2% vs 2.5+/-1.8% (p=0.001), necrotic core was 14.0+/-6.9% vs 7.5+/-5.6% (p=0.03) and fibrous tissue was 59.0+/-7.5% vs 67.0+/-5.9% (p=0.03), for mixed vs non-calcified plaques, respectively. Positive, negative predictive value and diagnostic accuracy for detection of vulnerable plaque by computed tomography was 77, 54 and 59%. CONCLUSIONS: Mixed plaque by computed tomography correlates with plaque composition as determined by intravascular ultrasound-derived radiofrequency analysis. However, the present diagnostic accuracy of computed tomography is not high enough to support its use for non invasive detection of vulnerable coronary plaque.
Authors: Michiel A de Graaf; Alexander Broersen; Pieter H Kitslaar; Cornelis J Roos; Jouke Dijkstra; Boudewijn P F Lelieveldt; J Wouter Jukema; Martin J Schalij; Victoria Delgado; Jeroen J Bax; Johan H C Reiber; Arthur J Scholte Journal: Int J Cardiovasc Imaging Date: 2013-02-16 Impact factor: 2.357