国际医学放射学杂志2018，Vol.41Issue(3)：272-276,5.DOI:10.19300/j.2018.L6229zt
FFRCT诊断冠心病的初步应用体会
Preliminary experience of applying FFRCTderived from coronary computed tomography angiography in coronary artery disease
摘要
Abstract
Objective To preliminarily investigate the diagnostic performance of computed tomography angiography derived noninvasive fractional flow reserve(FFRCT)for myocardial ischemia in patients with coronary artery disease(CAD)by comparing to that of invasive fractional flow reserve(FFR).Methods Twenty patients(13 male,7 female;mean age 64.72± 8.01 years)with suspected or known CAD underwent coronary CT angiography(CCTA)and invasive FFR within one week after CCTA during February 2017 to December 2017 in our hospital.Using invasive FFR as the golden standard,the FFRCT values were measured by 1D cFFR software,and FFRCTdiagnostic performance(sensitivity,specificity,positive predictive value, negative predictive value, and accuracy)was assessed for CAD patients with myocardial ischemia. The receiver operating characteristic(ROC)curves of FFRCTand CCTA were compared for the diagnostic accuracy.Pearson correlation and Bland-Altman consistency were used for comparing the diagnostic correlation and consistency between FFRCTand FFR. Results On a per-lesion basis,for the FFRCT,the sensitivity,specificity,positive predictive value,negative predictive value, and accuracy were 93.5%,86.2%,87.9%,92.6%,and 90.0%,respectively;and for the CCTA,were 83.9%,79.3%,82.1%, 81.2%,and 81.7%,respectively.The areas under the ROC curve of FFRCTand CCTA were 0.960 and 0.892,respectively.The FFRCTand FFR had a high consistency and correlation in the ischemia diagnosis(r=0.973,P<0.001).Conclusion FFRCThas promising diagnostic value for CAD patients with myocardial ischemia.关键词
冠心病/血流储备分数/冠状动脉CT血管成像/FFRCTKey words
Coronary artery disease/Fractional flow reserve/Coronary computed tomography angiography/FFRCT分类
医药卫生引用本文复制引用
易妍,王怡宁,吴炜,徐橙,金征宇..FFRCT诊断冠心病的初步应用体会[J].国际医学放射学杂志,2018,41(3):272-276,5.基金项目
国家重点研发计划项目(2016YFC1300402) （2016YFC1300402）
国家自然科学基金面上项目(81471725) （81471725）
北京市科技专项(Z171100001117136) （Z171100001117136）
