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基于CCTA的ΔCT-FFR对重度钙化冠状动脉功能学评估的临床价值分析OA北大核心CSTPCD

CCTA based clinical value analysis of ΔCT-FFR in evaluating coronary artery function in patients with severe calcification

中文摘要英文摘要

目的 探讨基于冠状动脉计算机断层扫描血管成像(CCTA)的血流储备分数(CT-FFR)和冠状动脉病变最严重狭窄处的近端与远端CT-FFR测量差值(ΔCT-FFR)对重度钙化冠状动脉功能学评估诊断效能的临床价值.方法 收集2018年1月-2019年6月解放军总医院心血管内科收治住院的107例冠心病(CAD)患者的149支血管进行回顾性分析.所有患者住院期间依次进行CCTA、CT-FFR、侵入性冠状动脉造影(ICA)和有创血流储备分数(FFR)检查.以单支冠状动脉钙化积分(CACS)≥100判断为血管水平的重度钙化,根据CACS水平将冠状动脉分为CACS≥100组(n=56)和CACS<100组(n=93).以FFR≤0.8作为诊断冠状动脉血流动力学异常的"金标准",ΔCT-FFR定义为冠状动脉病变最严重狭窄处近端与远端CT-FFR的测量差值.采用Pearson相关和Bland-Altman图评估血管水平CT-FFR与FFR值的相关性和一致性.通过ΔCT-FFR校正CT-FFR的检测结果,使用Delong检验比较不同诊断方法间受试者工作特征曲线(ROC)的曲线下面积(AUC),在血管水平分析其对重度钙化冠状动脉功能学评估诊断效能的增量价值.结果 在血管水平CT-FFR与FFR值具有较好的相关性(CACS≥100组:r=0.71,P<0.01;CACS<100组:r=0.73,P<0.01)和一致性(CACS≥100组:Mean=-0.01,P=0.25;CACS<100组:Mean=0,P=0.96).与CACS<100组比较,CACS≥100组FFR(0.80±0.08 vs.0.84±0.09,P=0.004)和CT-FFR值(0.81±0.06 vs.0.85±0.06,P<0.001)明显降低,ΔCT-FFR值(0.14±0.06 vs.0.09±0.06,P<0.001)明显增高.与CACS<100组比较,CACS≥100组CT-FFR的诊断效能明显下降[(AUC=0.792,95%CI 0.663~0.889)vs.(AUC=0.929,95%CI 0.856~0.972),P=0.04].经ΔCT-FFR校正诊断后,CACS≥100组CT-FFR的诊断效能较前明显提高[(AUC=0.876,95%CI 0.760~0.949)vs.(AUC=0.792,95%CI 0.663~0.889),P=0.02],与CACS<100组差异无统计学意义(P=0.37).结论 对于重度钙化冠状动脉,经ΔCT-FFR校正后,CT-FFR评估冠状动脉功能学的诊断效能明显提高.

Objective To investigate the clinical value of coronary computed tomography angiography(CCTA)based CT derived fractional flow reserve(CT-FFR)and ΔCT-FFR in improving the diagnostic efficiency for coronary abnormal hemodynamics in patients with severe calcification.Methods We retrospectively analyzed the clinical data of coronary artery disease(CAD)patients who underwent CCTA,CT-FFR,invasive coronary angiography(ICA)and FFR during hospitalization from January 2018 to June 2019 in Chinese PLA General Hospital.Severe calcification was defined as coronary artery calcium score(CACS)≥100 on single vessel level.A total of 107 CAD patients with 149 coronary arteries were included in the present study.The enrolled coronary arteries were assigned to CACS≥100 group(n=56)and CACS<100 group(n=93).CT-FFR was performed on the deep FFR platform based on machine learning(ML)algorithms and ΔCT-FFR was defined as CT-FFR difference between proximal and distal to the coronary lesion.The correlation and consistency between CT-FFR and FFR values were analyzed by Pearson and Bland-Altman methods.We attempted to analyze the incremental value of ΔCT-FFR for coronary functional evaluation,especial for coronary arteries with severe calcification,regarding FFR≤0.8 as the diagnostic gold standard.Comparison of receiver operating characteristic curves(ROC)between different diagnostic methods was presented by Delong test.Results Pearson and Bland-Altman analyses showed appreciable correlation(CACS≥100 group,r=0.71,P<0.01;CACS<100 group,r=0.73,P<0.01)and consistency(CACS≥100 group,Mean=-0.01,P=0.25;CACS<100 group,Mean=0,P=0.96)between CT-FFR and FFR values in both groups.FFR(0.80±0.08 vs.0.84±0.09,P=0.004)and CT-FFR(0.81±0.06 vs.0.85±0.06,P<0.001)levels were significant lower in CACS≥100 group than those in CACS<100 group,while ΔCT-FFR(0.14±0.06 vs.0.09±0.06,P<0.001)levels were significant higher in CACS≥100 group.Moreover,the diagnostic efficiency of CT-FFR in CACS≥100 group was inferior to that in CACS<100 group[AUC=0.792(95%CI 0.663-0.889)vs.AUC=0.929(95%CI 0.856-0.972),P=0.04],while it achieved significant improvement after ΔCT-FFR adjustment[AUC=0.876(95%CI 0.760-0.949)vs.AUC=0.792(95%CI 0.663-0.889),P=0.02]and was similar to that in CACS<100 group(P=0.37).Conclusion For coronary arteries with severe calcification,CT-FFR demonstrated significant incremental value in improving the diagnostic efficiency of coronary abnormal hemodynamics after ΔCT-FFR adjustment.

魏凯;王玺;何柏;赵子强;张威;荆晶;单冬凯

解放军总医院第一医学中心心血管内科,北京 100853解放军总医院第六医学中心心血管病医学部,北京 100048科亚医疗科技股份有限公司,北京 100176

临床医学

冠心病冠状动脉计算机断层扫描血管成像血流储备分数重度钙化

coronary artery diseasecoronary computed tomography angiographyfractional flow reservesevere calcification

《解放军医学杂志》 2024 (002)

144-151 / 8

This work was supported by the National Key Research and Development Program of China(2016YFC1300304) 国家重点研发计划(2016YFC1300304)

10.11855/j.issn.0577-7402.1849.2023.0818

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