基于三维冠状动脉造影定量分析和定量血流分数分析冠状动脉分叉病变分支血流灌注受损的影响因素及其风险预测模型  

Value of Three-dimensional Quantitative Coronary Angiography andμQuantitative Flow Ratio Methods on the Perfusion Disorder Evaluation of Side Branch in Patience With Side Branch Occlusion:Influencing Factors and Establishment of a Risk Prediction Model

作　　者：龙宇博 胡湖 黄承诚 周婷[1] 刘金武 郑昭芬[1] 荣晶晶 潘宏伟[1] LONG Yubo;HU Hu;HUANG Chengcheng;ZHOU Ting;LIU Jinwu;ZHENG Zhaofen;RONG Jingjing;PAN Hongwei(Department of Cardiology,Clinical Research Center for Heart Failure in Hunan Province,The First Affiliated Hospital of Hunan Normal University,Hunan Provincial People's Hospital,Changsha 410005,China;Department of Cardiology,Hunan Shaoyang Central Hospital,Shaoyang 422099,China)

机构地区：[1]湖南省人民医院(湖南师范大学附属第一医院),湖南省心力衰竭临床医学研究中心心血管内科,长沙410005 [2]湖南省邵阳市中心医院心血管内科,邵阳422099

出　　处：《中国循环杂志》2023年第12期1246-1253,共8页Chinese Circulation Journal

基　　金：国家自然科学基金面上项目(82070520);湖南省重点领域研发计划项目(2020SK2115);仁术基金重点培育项目(RS2022A04);湖南省自然科学基金科卫联合项目(2020JJ8014)。

摘　　要：目的:利用三维冠状动脉(冠脉)造影定量分析(3D-QCA)及基于Murray定律的定量血流分数(μQFR)探讨冠脉分叉病变中影响分支血流灌注的各项危险因素,并建立影响分支灌注受损的风险预测模型,为分叉病变经皮冠脉介入治疗(PCI)手术策略的制定提供参考。方法:连续纳入2022年10月至2023年4月于湖南省人民医院行冠脉造影检查的362例患者,非左主干分叉病变393处。收集患者的一般临床评估指标、冠脉分叉病变的解剖学指标以及分叉病变中代表分支血流灌注的μQFR等数据资料。393处分叉病变按照8:2比例随机划分为训练集和测试集,利用单因素Logistic回归筛选变量,通过多因素Logistic逐步回归分析评估分叉病变中分支灌注的影响因素,建立风险评估模型,并在测试集中进一步验证模型准确性。结果:多因素Logistic逐步回归结果显示,主支最大面积狭窄率、分叉核最大直径狭窄率、分支最狭窄管腔直径狭窄率、分支开口直径狭窄率及分支病变长度是分支可能存在血流灌注受损(μQFR<0.8)的独立预测因子(P均<0.05),由这5个变量建立术前分支灌注受损风险评估模型,模型的ROC曲线下面积为0.926(95%CI:0.896~0.958),灵敏度为0.864(95%CI:0.818~0.910),特异度为0.850(95%CI:0.780~0.920)。测试集验证结果显示,该模型ROC曲线下面积为0.897(95%CI:0.817~0.976),灵敏度为0.870(95%CI:0.756~0.936),特异度为0.923(95%CI:0.759~0.986)。结论:冠脉分叉病变中分支的血流灌注情况主要与主支和分支的多个解剖学因素相关,其中主支最大面积狭窄率、分叉核最大直径狭窄率、分支最狭窄管腔直径狭窄率、分支开口直径狭窄率及分支病变长度是分支存在灌注受损的独立预测因素;所建立的分支灌注受损风险评估模型具有良好的临床应用前景。Objectives:The risk factors affecting the blood perfusion of side branch(SB)in coronary bifurcation lesions were explored by the three-dimensional quantitative coronary angiography(3D-QCA)and the Murray's law based quantitative flow ratio(μQFR),and a risk prediction model affecting SB perfusion disorders was established to provide reference for the percutaneous coronary intervention(PCI)strategies of bifurcation lesions.Methods:From October 2022 to April 2023,393 bifurcation lesions were evaluated by coronary angiography in Hunan Provincial People's Hospital.The general clinical evaluation index of the patient,the anatomical index of coronary bifurcation lesion,and theμQFR representing branch perfusion in bifurcation lesion were collected.All samples were randomly divided into training set and test set at the 8:2 ratio.Univariate logistic regression was used to determine filter variables,and the influencing factors of branch perfusion in bifurcated lesions were evaluated by multivariate logistic regression analysis.A risk prediction model was established,and the accuracy of the model was further verified in the test set.Results:The maximum area stenosis rate,maximum lumen diameter stenosis rate of the bifurcation nucleus,ostia diameter stenosis rate,as well as the branch maximum diameter stenosis rate,and length of the bifurcation lesion are independent predictors of SB perfusion disorders(SBμQFR<0.8),P<0.05.A SB perfusion disorder risk prediction model was established based on the above five independent risk factors.The area under the ROC curve of the model was 0.926(95%CI:0.896-0.958),the sensitivity was 0.864(95%CI:0.818-0.910),and the specificity was 0.850(95%CI:0.780-0.920).This model was applied to the test set,the results showed that the area under the ROC curve of this model was 0.897(95%CI:0.817-0.976),the sensitivity was 0.870(95%CI:0.756-0.936),and the specificity was 0.923(95%CI:0.759-0.986).Conclusions:The blood perfusion of branches in coronary bifurcation lesions is mainly related to multiple an

关 键 词：冠状动脉分叉病变 分支灌注 基于Murray分叉定律的定量血流分数 三维冠状动脉造影定量分析 风险预测模型 

分 类 号：R54[医药卫生—心血管疾病]