title: Atherosclerotic plaque composition and classification identified by coronary computed tomography: assessment of computed tomography-generated plaque maps compared with virtual histology intravascular ultrasound and histology.
abstract: BACKGROUND
  Computed tomography (CT) is used routinely for coronary angiography, and higher-risk features of plaques can also be identified. However, the ability of CT to discriminate individual plaque components and classify plaques according to accepted histological definitions is unknown.
  
  
  RESULTS
  We first determined CT attenuation ranges for individual plaque components using combined in vivo CT coregistered with virtual histology intravascular ultrasound (VH-IVUS) in 108 plaques from 57 patients. Comparison with contrast attenuation created plaque/contrast attenuation ratios that were significantly different for each component. In a separate validation cohort of 47 patients, these Plaque Maps correlated significantly with VH-IVUS-determined plaque component volumes (necrotic core: r=0.41, P=0.002; fibrous plaque: r=0.54, P<0.001; calcified plaque: r=0.59, P<0.001; total plaque: r=0.62, P<0.001). We also assessed VH-IVUS and CT Plaque Maps against coregistered histology in 72 (VH-IVUS) and 87 (CT) segments from 8 postmortem coronary arteries. The diagnostic accuracy of CT to detect calcified plaque (83% versus 92%), necrotic core (80% versus 65%), and fibroatheroma (80% versus 79%) was comparable with VH-IVUS. However, although VH-IVUS could identify thin-cap fibroatheromas (TCFA) with a diagnostic accuracy of between 74% and 82% (depending on the TCFA definition used), the spatial resolution of CT prevented direct identification of TCFA.
  
  
  CONCLUSIONS
  CT-derived Plaque Maps based on contrast-adjusted attenuation ranges can define individual plaque components with a similar accuracy to VH-IVUS ex vivo. However, coronary CT Plaque Maps could not reliably classify plaques and identify TCFA, such that high-risk plaques may be misclassified or overlooked.
authors: Division of Cardiovascular Medicine, and Centre for Applied Medical Statistics, University of Cambridge, Cambridge, United Kingdom; and Papworth Hospital NHS Foundation Trust, Cambridge, United Kingdom.
authors: Daniel R
authors: DR
authors: Obaid
authors: Patrick A
authors: PA
authors: Calvert
authors: Deepa
authors: D
authors: Gopalan
authors: Richard A
authors: RA
authors: Parker
authors: Stephen P
authors: SP
authors: Hoole
authors: Nick E J
authors: NE
authors: West
authors: Martin
authors: M
authors: Goddard
authors: James H F
authors: JH
authors: Rudd
authors: Martin R
authors: MR
authors: Bennett
mesh_terms: D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000145:classification / Q000000981:diagnostic imaging* / Q000473:pathology; D003331:Coronary Vessels / Q000000981:diagnostic imaging* / Q000473:pathology; D005355:Fibrosis; D006801:Humans; D016014:Linear Models; D061330:Multidetector Computed Tomography; D009336:Necrosis; D058226:Plaque, Atherosclerotic; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012307:Risk Factors; D018084:Ultrasonography, Interventional; D061205:Vascular Calcification / Q000000981:diagnostic imaging / Q000473:pathology
keywords: atherosclerosis; imaging