RATIONALE AND OBJECTIVES: We investigated if 16-slice multidetector row computed tomography (MDCT) allows correct classification of coronary plaques into calcified or noncalcified and further subclassification of noncalcified plaques into either lipid-rich with a necrotic core or fibrous. MATERIALS AND METHODS: Coronary arteries of 30 isolated hearts were filled postmortem with a contrast medium and scanned with a 16-slice MDCT imager (Light Speed 16 pro, GEMS, Milwaukee, WI). Imaging parameters: collimation 16 x 0.625 mm, pitch 0.325, tube voltage 120 kV, tube current 250 mA, and gantry rotation time 500 milliseconds. The images were reformatted perpendicular to the axis of the coronary arteries (AW 4.2 software, GEMS) and analyzed by establishing attenuation profiles of the coronary cross sections (ImageJ 1.33n software, NIH, Bethesda, MD). Results were compared with the correlating histopathologic sections of the arteries. RESULTS: Analysis of 195 CT cross-sections showed a sensitivity and specificity for the correct classification of calcified plaques of 100% and 97.3% and for noncalcified plaques of 80.8% and 95.1%, respectively. The attenuation of epicardial fat ranged from -119 Hounsfield units (HU) to 23 HU (median -71 HU), and from 93 HU to 625 HU (308 HU) for the contrast medium. Calcified plaques showed an attenuation between 333 HU and 1944 HU (1,089 HU), noncalcified plaques between 26 HU and 124 HU (52 HU). Further subclassification of noncalcified plaques showed attenuation values between 26 HU and 67 HU (median 44 HU) for lipid-rich plaques with a necrotic core and from 37 HU to 124 HU (median 67 HU) for fibrous plaques. CONCLUSIONS: Coronary atherosclerotic plaques can be reliably identified and classified as either calcified or noncalcified by 16-slice MDCT in postmortem studies. Further differentiation of noncalcified plaques in either lipid-rich or fibrous is not reliably feasible because of substantial overlap of the attenuation.
RATIONALE AND OBJECTIVES: We investigated if 16-slice multidetector row computed tomography (MDCT) allows correct classification of coronary plaques into calcified or noncalcified and further subclassification of noncalcified plaques into either lipid-rich with a necrotic core or fibrous. MATERIALS AND METHODS: Coronary arteries of 30 isolated hearts were filled postmortem with a contrast medium and scanned with a 16-slice MDCT imager (Light Speed 16 pro, GEMS, Milwaukee, WI). Imaging parameters: collimation 16 x 0.625 mm, pitch 0.325, tube voltage 120 kV, tube current 250 mA, and gantry rotation time 500 milliseconds. The images were reformatted perpendicular to the axis of the coronary arteries (AW 4.2 software, GEMS) and analyzed by establishing attenuation profiles of the coronary cross sections (ImageJ 1.33n software, NIH, Bethesda, MD). Results were compared with the correlating histopathologic sections of the arteries. RESULTS: Analysis of 195 CT cross-sections showed a sensitivity and specificity for the correct classification of calcified plaques of 100% and 97.3% and for noncalcified plaques of 80.8% and 95.1%, respectively. The attenuation of epicardial fat ranged from -119 Hounsfield units (HU) to 23 HU (median -71 HU), and from 93 HU to 625 HU (308 HU) for the contrast medium. Calcified plaques showed an attenuation between 333 HU and 1944 HU (1,089 HU), noncalcified plaques between 26 HU and 124 HU (52 HU). Further subclassification of noncalcified plaques showed attenuation values between 26 HU and 67 HU (median 44 HU) for lipid-rich plaques with a necrotic core and from 37 HU to 124 HU (median 67 HU) for fibrous plaques. CONCLUSIONS:Coronary atherosclerotic plaques can be reliably identified and classified as either calcified or noncalcified by 16-slice MDCT in postmortem studies. Further differentiation of noncalcified plaques in either lipid-rich or fibrous is not reliably feasible because of substantial overlap of the attenuation.
Authors: Lorenzo Mannelli; Lawrence MacDonald; Marcello Mancini; Marina Ferguson; William P Shuman; Monica Ragucci; Serena Monti; Dongxiang Xu; Chun Yuan; Lee M Mitsumori Journal: Eur Radiol Date: 2014-12-24 Impact factor: 5.315
Authors: Margaret N Holme; Georg Schulz; Hans Deyhle; Timm Weitkamp; Felix Beckmann; Johannes A Lobrinus; Farhad Rikhtegar; Vartan Kurtcuoglu; Irene Zanette; Till Saxer; Bert Müller Journal: Nat Protoc Date: 2014-05-22 Impact factor: 13.491
Authors: Rolf Symons; Justin Z Morris; Colin O Wu; Amir Pourmorteza; Mark A Ahlman; João A C Lima; Marcus Y Chen; Marissa Mallek; Veit Sandfort; David A Bluemke Journal: Radiology Date: 2016-09-16 Impact factor: 11.105
Authors: Wisnumurti Kristanto; Peter M A van Ooijen; Jaap M Groen; Rozemarijn Vliegenthart; Matthijs Oudkerk Journal: Int J Cardiovasc Imaging Date: 2011-04-21 Impact factor: 2.357
Authors: Lorenzo Mannelli; Lee M Mitsumori; Marina Ferguson; Dongxiang Xu; Baocheng Chu; Kelley R Branch; William P Shuman; Chun Yuan Journal: Eur Radiol Date: 2012-08-21 Impact factor: 5.315