Martin Simon S, Mastrodicasa Domenico, van Assen Marly, De Cecco Carlo N, Bayer Richard R, Tesche Christian, Varga-Szemes Akos, Fischer Andreas M, Jacobs Brian E, Sahbaee Pooyan, Griffith L Parkwood, Matuskowitz Andrew J, Vogl Thomas J, Schoepf U Joseph
Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260 (S.S.M., D.M., M.v.A., C.N.D.C., R.R.B., C.T., A.V.S., A.M.F., B.E.J., L.P.G., U.J.S.); Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany (S.S.M., T.J.V.); Stanford University School of Medicine, Department of Radiology, Stanford, Calif (D.M.); Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (C.N.D.C.); Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC (R.R.B.); Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany (C.T.); Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-University, Munich, Germany (C.T.); Siemens Medical Solutions USA, Malvern, Pa (P.S.); and Department of Emergency Medicine, Medical University of South Carolina, Charleston, SC (A.J.M.).
Radiol Cardiothorac Imaging. 2020 Jun 25;2(3):e190137. doi: 10.1148/ryct.2020190137. eCollection 2020 Jun.
To evaluate the additional value of noninvasive artificial intelligence (AI)-based CT-derived fractional flow reserve (CT FFR), derived from triple-rule-out coronary CT angiography for acute chest pain (ACP) in the emergency department (ED) setting.
AI-based CT FFR from triple-rule-out CT angiography data sets was retrospectively obtained in 159 of 271 eligible patients (102 men; mean age, 57.0 years ± 9.7 [standard deviation]) presenting to the ED with ACP. The agreement between CT FFR (≤ 0.80) and stenosis at triple-rule-out CT angiography (≥ 50%), as well as downstream cardiac diagnostic testing, was investigated. Furthermore, the predictive value of CT FFR for coronary revascularization and major adverse cardiac events (MACE) was assessed over a 1-year follow-up period.
CT FFR and triple-rule-out CT angiography demonstrated agreement in severity of coronary artery disease (CAD) in 52% (82 of 159) of all cases. CT FFR of 0.80 and less served as a better predictor for coronary revascularization and MACE than stenosis of 50% and greater at triple-rule-out CT angiography (odds ratio, 3.4; 95% confidence interval: 1.4, 8.2 vs odds ratio, 2.2; 95% confidence interval: 0.9, 5.3) ( < .01). In the subgroup of patients with additional noninvasive cardiac testing (94 of 159), there was higher agreement as to the presence or absence of significant disease with CT FFR (55%) than with coronary triple-rule-out CT angiography (47%) ( = .23).
CT FFR derived from triple-rule-out CT angiography was a better predictor for coronary revascularization and MACE and showed better agreement with additional diagnostic testing than triple-rule-out CT angiography. Therefore, CT FFR may improve the specificity in identifying patients with ACP with significant CAD in the ED setting and reduce unnecessary downstream testing.© RSNA, 2020See also the commentary by Ihdayhid and Ben Zekry in this issue.
评估基于非侵入性人工智能（AI）的CT衍生血流储备分数（CT FFR）在急诊科（ED）急性胸痛（ACP）三联排除冠状动脉CT血管造影中的附加价值。
回顾性分析了271例符合条件的因ACP就诊于ED的患者中的159例（102例男性；平均年龄57.0岁±9.7[标准差]），从三联排除CT血管造影数据集中获取基于AI的CT FFR。研究了CT FFR（≤0.80）与三联排除CT血管造影时的狭窄（≥50%）以及下游心脏诊断检查之间的一致性。此外，在1年的随访期内评估了CT FFR对冠状动脉血运重建和主要不良心脏事件（MACE）的预测价值。
在所有病例的52%（159例中的82例）中，CT FFR和三联排除CT血管造影在冠状动脉疾病（CAD）严重程度方面显示出一致性。与三联排除CT血管造影时50%及以上的狭窄相比，CT FFR为0.80及以下对冠状动脉血运重建和MACE是更好的预测指标（优势比，3.4；95%置信区间：1.4，8.2对比优势比，2.2；95%置信区间：0.9，5.3）（P<0.01）。在进行了额外非侵入性心脏检查的患者亚组（159例中的94例）中，CT FFR在疾病是否存在方面的一致性（55%）高于冠状动脉三联排除CT血管造影（47%）（P = 0.23）。
从三联排除CT血管造影得出的CT FFR对冠状动脉血运重建和MACE是更好的预测指标，并且与额外诊断检查的一致性比三联排除CT血管造影更好。因此，CT FFR可能会提高在ED环境中识别患有严重CAD的ACP患者的特异性，并减少不必要的下游检查。©RSNA，2020另见本期Ihdayhid和Ben Zekry的评论。
