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.
Circ Cardiovasc Imaging. 2013 Sep;6(5):655-64. doi: 10.1161/CIRCIMAGING.112.000250. Epub 2013 Aug 19.
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.
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.
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.
计算机断层扫描（CT）常用于冠状动脉造影，也可以识别斑块的高危特征。然而，CT 区分斑块成分的能力，以及根据公认的组织学定义对斑块进行分类的能力尚不清楚。
我们首先通过 57 例患者的 108 个斑块的体内 CT 与虚拟组织学血管内超声（VH-IVUS）的联合，确定了单个斑块成分的 CT 衰减范围。与对比衰减创建的斑块/对比衰减比值进行比较，发现每个成分的比值都有显著差异。在一个独立的 47 例验证队列中，这些斑块图与 VH-IVUS 确定的斑块成分体积显著相关（坏死核心：r=0.41，P=0.002；纤维斑块：r=0.54，P<0.001；钙化斑块：r=0.59，P<0.001；总斑块：r=0.62，P<0.001）。我们还将 VH-IVUS 和 CT 斑块图与 8 个死后冠状动脉 72 个（VH-IVUS）和 87 个（CT）节段的共定位组织学进行了比较。CT 检测钙化斑块（83%对 92%）、坏死核心（80%对 65%）和纤维粥样瘤（80%对 79%）的准确性与 VH-IVUS 相当。然而，尽管 VH-IVUS 可以识别薄帽纤维粥样瘤（TCFA），其诊断准确性在 74%至 82%之间（取决于使用的 TCFA 定义），但 CT 的空间分辨率却阻止了 TCFA 的直接识别。
基于对比调整衰减范围的 CT 衍生斑块图可以与 VH-IVUS 一样准确地定义单个斑块成分。然而，冠状动脉 CT 斑块图不能可靠地对斑块进行分类，也不能识别 TCFA，因此高危斑块可能被错误分类或忽略。
