Quantification and characterization of obstructive coronary plaques using 64-slice computed tomography: A comparison with intravascular ultrasound

Jin Hur, Youngjin Kim, Hye Jeong Lee, Ji Eun Nam, Kyu Ok Choe, Jae Seung Seo, Donghoon Choi, Jung Sun Kim, Byoung Wook Choi

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Abstract

PURPOSE: The aim of this study was to determine the diagnostic accuracy of 64-slice computed tomography (CT) coronary angiography in the quantification and characterization of obstructive coronary plaques in comparison with intravascular ultrasound (IVUS). MATERIALS AND METHODS: Thirty-nine patients were selected who underwent both CT coronary angiography (CTCA) and IVUS. For each stenotic site (n = 61), the maximum vessel cross-sectional area, lumen cross-sectional area, plaque area, and percentage of luminal obstruction were measured. Plaque composition was analyzed according to IVUS (plaque echogenicity and classified into several types: calcified, mixed, fibrous, and soft plaques) and CTCA criteria (Hounsfield units [HU]). The correlation between CTCA and IVUS measurements was determined using Pearson correlation coefficient. The statistical significance of differences in the CT densities of plaques among plaque types determined by IVUS was assessed using the Scheffe method. RESULTS: The correlation coefficients for the measurements of the lumen, vessel, plaque area, and percentage of luminal obstruction were r = 0.712, r = 0.654, r = 0.753, and r = 0.799, respectively. The mean CT density values for soft (n = 10), fibrous (n = 11), mixed (n = 31), and calcified plaques (n = 9) were 54 ± 13 HU, 82 ± 17 HU, 162 ± 57 HU, and 392 ± 155 HU, respectively. Computed tomography density measurements were not significantly different between soft and fibrous plaques (P = 0.224). CONCLUSIONS: Sixty-four-slice CTCA is a noninvasive modality that allows quantification of coronary artery plaques. However, reliable classification of noncalcified plaques as vulnerable or stable plaques based on CT density measurements is currently limited.

Original languageEnglish
Pages (from-to)186-192
Number of pages7
JournalJournal of Computer Assisted Tomography
Volume33
Issue number2
DOIs
Publication statusPublished - 2009 Mar 1

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All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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