BACKGROUND: Noninvasive characterization of coronary atherosclerotic plaque is limited with current computed tomography (CT) techniques. Dual-energy CT (DECT) has the potential to provide additional attenuation data for better differentiation of plaque components. OBJECTIVE: We attempted to characterize coronary atherosclerotic plaque with DECT. METHODS: Seven human coronary arteries acquired at autopsy were scanned consecutively at 80 and 140 kVp with CT. Vessels were perfused with saline, and data were acquired before and after contrast agent injection. Lesions were identified, and attenuation measurements were made from CT image quadrants. CT quadrants were classified as densely calcified, fibrocalcific, fibrous, lipid-rich, or normal vessel wall, corresponding to matched histology images. Attenuation values at each peak tube voltage were compared within plaque types for both noncontrast and contrast scans. Further, dual-energy index (DEI) values computed from attenuation were analyzed for classification of plaque. RESULTS: In 14 lesions, a total of 56 quadrants were identified. Histology results classified 8 (14%) as densely calcified, 8 (14%) as fibrocalcific, 9 (16%) as fibrous, 5 (9%) as lipid-rich, and 25 (45%) as normal vessel wall. Calcified lesions attenuated significantly more at 80 kVp in both contrast and noncontrast scans, whereas fibrous plaque attenuated more at 80 kVp only for contrast-enhanced scans. No differences were found for lipid-rich plaques. Using DEI values, only densely calcified plaques could be distinguished from other plaque types except fibrocalcific plaques in contrast images. CONCLUSIONS: Only densely calcified and fibrocalcific plaques showed a true change in attenuation at 80 versus 140 kVp. Therefore, calcified plaques could be distinguished from noncalcified plaques with DECT, but further classification of plaque types was not possible.
BACKGROUND: Noninvasive characterization of coronary atherosclerotic plaque is limited with current computed tomography (CT) techniques. Dual-energy CT (DECT) has the potential to provide additional attenuation data for better differentiation of plaque components. OBJECTIVE: We attempted to characterize coronary atherosclerotic plaque with DECT. METHODS: Seven human coronary arteries acquired at autopsy were scanned consecutively at 80 and 140 kVp with CT. Vessels were perfused with saline, and data were acquired before and after contrast agent injection. Lesions were identified, and attenuation measurements were made from CT image quadrants. CT quadrants were classified as densely calcified, fibrocalcific, fibrous, lipid-rich, or normal vessel wall, corresponding to matched histology images. Attenuation values at each peak tube voltage were compared within plaque types for both noncontrast and contrast scans. Further, dual-energy index (DEI) values computed from attenuation were analyzed for classification of plaque. RESULTS: In 14 lesions, a total of 56 quadrants were identified. Histology results classified 8 (14%) as densely calcified, 8 (14%) as fibrocalcific, 9 (16%) as fibrous, 5 (9%) as lipid-rich, and 25 (45%) as normal vessel wall. Calcified lesions attenuated significantly more at 80 kVp in both contrast and noncontrast scans, whereas fibrous plaque attenuated more at 80 kVp only for contrast-enhanced scans. No differences were found for lipid-rich plaques. Using DEI values, only densely calcified plaques could be distinguished from other plaque types except fibrocalcific plaques in contrast images. CONCLUSIONS: Only densely calcified and fibrocalcific plaques showed a true change in attenuation at 80 versus 140 kVp. Therefore, calcified plaques could be distinguished from noncalcified plaques with DECT, but further classification of plaque types was not possible.
Authors: Dipanjan Pan; Ewald Roessl; Jens-Peter Schlomka; Shelton D Caruthers; Angana Senpan; Mike J Scott; John S Allen; Huiying Zhang; Grace Hu; Patrick J Gaffney; Eric T Choi; Volker Rasche; Samuel A Wickline; Roland Proksa; Gregory M Lanza Journal: Angew Chem Int Ed Engl Date: 2010-12-10 Impact factor: 15.336
Authors: Tony DeFrance; Eric Dubois; Dan Gebow; Alex Ramirez; Florian Wolf; Gudrun M Feuchtner Journal: Int J Cardiovasc Imaging Date: 2009-11-07 Impact factor: 2.357
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: Dipanjan Pan; Carsten O Schirra; Angana Senpan; Anne H Schmieder; Allen J Stacy; Ewald Roessl; Axel Thran; Samuel A Wickline; Roland Proska; Gregory M Lanza Journal: ACS Nano Date: 2012-03-08 Impact factor: 15.881