从冠状动脉计算机断层扫描血管造影术中量化的冠状动脉周围脂肪衰减指数和冠状动脉斑块可识别导致缺血的病变。
Pericoronary fat attenuation index and coronary plaque quantified from coronary computed tomography angiography identify ischemia-causing lesions.
作者信息
Yan Hankun, Zhao Na, Geng Wenlei, Hou Zhihui, Gao Yang, Lu Bin
机构信息
Department of Radiology, Fu Wai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Department of Radiology, Fu Wai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
出版信息
Int J Cardiol. 2022 Jun 15;357:8-13. doi: 10.1016/j.ijcard.2022.03.033. Epub 2022 Mar 16.
BACKGROUND
The association between pericoronary fat attenuation index (FAI), plaque characteristics, and lesion-specific ischemia identified by fractional flow reserve (FFR) remains unclear.
METHODS
Coronary computed tomography angiography (CCTA) stenosis, FAI, plaque characteristics, FFR derived from computed tomography (FFR) and FFR were assessed in 280 vessels of 247 patients. Stenosis ≥50% was considered obstructive. Optimal thresholds of FAI and plaque variables were defined by the area under the receiver-operating characteristics curve (AUC) analysis. Ischemia was defined by FFR ≤ 0.80.
RESULTS
FAI ≥ -71.9 HU, low-attenuation plaque (LAP) ≥ 49.62 mm and aggregate plaque volume (APV) ≥ 28.91% predicted ischemia independent of other plaque characteristics. The addition of FAI ≥ -71.9 HU improved discrimination (AUC, 0.720 vs. 0.674, P = 0.035) and reclassification abilities (category-free net reclassification index [NRI], 0.470, P < 0.001; relative integrated discrimination improvement [IDI], 0.047, P < 0.001) of ischemia compared with stenosis evaluation alone, with further discrimination (AUC, 0.772 vs. 0.720, P = 0.028) and reclassification abilities (NRI, 0.385, P = 0.001; relative IDI, 0.077, P < 0.001) of ischemia by adding information regarding LAP ≥49.62 mm + APV ≥ 28.91%. And the diagnostic performance of combination approach was comparable to that of FFR alone (AUC, 0.772 vs. 0.762, P = 0.771).
CONCLUSIONS
Stenosis severity, FAI, plaque characteristics predicted lesion-specific ischemia. The combination of FAI and plaque assessment improved the discrimination of ischemia compared with stenosis assessment alone.
背景
冠状动脉周围脂肪衰减指数（FAI）、斑块特征与通过血流储备分数（FFR）确定的病变特异性缺血之间的关联仍不清楚。
方法
对247例患者的280支血管进行冠状动脉计算机断层扫描血管造影（CCTA）狭窄、FAI、斑块特征、计算机断层扫描衍生的FFR（CT-FFR）和FFR评估。狭窄≥50%被视为阻塞性。通过受试者操作特征曲线（AUC）分析确定FAI和斑块变量的最佳阈值。缺血定义为FFR≤0.80。
结果
FAI≥-71.9 HU、低密度斑块（LAP）≥49.62 mm和总斑块体积（APV）≥28.91%可独立于其他斑块特征预测缺血。与单独的狭窄评估相比，增加FAI≥-71.9 HU可提高缺血的辨别能力（AUC，0.720对0.674，P = 0.035）和重新分类能力（无类别净重新分类指数[NRI]，0.470，P < 0.001；相对综合辨别改善[IDI]，0.047，P < 0.001），通过添加关于LAP≥49.62 mm + APV≥28.91%的信息，缺血的辨别能力进一步提高（AUC，0.772对0.720，P = 0.028）和重新分类能力（NRI，0.385，P = 0.001；相对IDI，0.077，P < 0.001）。联合方法的诊断性能与单独的FFR相当（AUC，0.772对0.762，P = 0.771）。
结论
狭窄严重程度、FAI、斑块特征可预测病变特异性缺血。与单独的狭窄评估相比，FAI和斑块评估的联合提高了缺血的辨别能力。
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