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个体化快速心律失常虚拟介入手术体系的建立与临床应用价值研究
引用本文:曹 威,于 阳,冯 薇,王召军,张英涛,承恒达,曲秀芬.个体化快速心律失常虚拟介入手术体系的建立与临床应用价值研究[J].现代生物医学进展,2019,19(11):2116-2119.
作者姓名:曹 威  于 阳  冯 薇  王召军  张英涛  承恒达  曲秀芬
作者单位:哈尔滨医科大学附属第二医院心内科;哈尔滨医科大学附属第一医院心内科;哈尔滨工业大学计算机学院
基金项目:黑龙江省教育厅科研基金项目(12511295)
摘    要:目的:建立个体化快速心律失常虚拟介入手术体系定位手术靶点并分析其临床应用价值。方法:收集2011年1月-2013年1月在我院进行射频消融手术治疗的室性早搏和房室折返性心动过速患者共120例,(其中室性早搏40例,房室折返性心动过速80例),平均年龄40.6±9.7岁,获取数字新电机记录18导体表心电图(ECG)、数字食道调搏图、心脏CT成像原始数据,并记录手术靶点。所有采集心电图和CT数据进行多模式序列识别系统的计算机辅助诊断(CAD)处理,然后再对处理后的数据进行分析。两名心内科医生人工对心电图进行分析定位,并不告知患者的临床资料及射频消融手术最终靶点定位结果,按照室性早搏和房室旁路的诊断定位标准进行诊断,随后两名医师对处理后的心电图进行诊断,再次得出诊断结果,以术中成功消融靶点定位诊断为金标准,分析,个体化快速心律失常虚拟介入手术体系定位手术靶点的特异性、敏感性、阳性预测值,阴性预测值等指标。结果:ECG+CAD组诊断准确度高于单独ECG组,ECG组ROC曲线下面积(Az)=0.742,95%可信区间0.652-0.832];ECG+CAD组:Az=0.934,95%可信区间0.882-0.985];ECG+CAD组:精确度0.908;敏感性:0.905;特异性:0.923;阳性预测值:0.818;阴性预测值:0.934,较单独ECG组明显提高。结论:与单独体表心电图定位诊断相比,虚拟介入手术体系显著提高快速心律失常诊靶点定位的准确度,临床应用价值更高。

关 键 词:室性早搏,房室折返性心动过速,心电图,计算机辅助诊断
收稿时间:2019/4/30 0:00:00
修稿时间:2019/5/24 0:00:00

Establishment of Individualized Virtual Interventional System for Tachyarrhythmia and Its Clinical Application Value
CAO Wei,YU Yang,FENG Wei,WANG Zhao-jun,ZHANG Ying-tao,CHEN Heng-d,QU Xiu-fen.Establishment of Individualized Virtual Interventional System for Tachyarrhythmia and Its Clinical Application Value[J].Progress in Modern Biomedicine,2019,19(11):2116-2119.
Authors:CAO Wei  YU Yang  FENG Wei  WANG Zhao-jun  ZHANG Ying-tao  CHEN Heng-d  QU Xiu-fen
Institution:The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150001, China;The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150001, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China
Abstract:ABSTRACT Objective: To establish individualized virtual interventional system for tachyarrhythmia to evaluate its location the surgical target and analyze its clinical application value. Methods: A total of 120 patients with premature ventricular beats and atrioventricular reentrant tachycardia (including 40 cases of premature ventricular beats and 80 cases of atrioventricular reentrant tachycardia) underwent radiofrequency ablation in our hospital from January 2011 to January 2013, with an average age of 40.6±9.7 years. New digital motor was used to record 18 conductor surface electrocardiogram (ECG), digital esophageal pacing map, raw data of cardiac CT imaging and surgical targets. All collected ECG and CT data were processed by computer aided diagnosis (CAD) of multi-pattern sequence recognition system, and then the processed data were analyzed. Two cardiologists analyzed and positioned the ECG artificially without informing the clinical data and the final target location results of radiofrequency ablation. They diagnosed the ECG according to the diagnostic and positioning criteria of premature ventricular beats and atrioventricular bypass. Then two physicians diagnosed the treated ECG and got the diagnostic results again. The gold standard was the successful target positioning diagnosis during the operation. The specificity, sensitivity, positive predictive value and negative predictive value of this method were obtained to evaluate the clinical value of individualized virtual interventional system for tachyarrhythmia. Results: The diagnostic accuracy of ECG+CAD group was higher than that of ECG group alone, the area under ROC curve (Az) = 0.742, 95% confidence interval 0.652-0.832]; ECG+CAD group: Az = 0.934, 95% confidence interval 0.882-0.985]; ECG+CAD group: accuracy 0.908; sensitivity: 0.913; specificity: 0.905; positive predictive value: 0.818; negative predictive value: 0.934, significantly higher than that of ECG group alone. Conclusion: Compared with body surface electrocardiogram alone, virtual interventional surgery system significantly improves the accuracy of target location and diagnosis of tachyarrhythmia, it has higher clinical application value.
Keywords:Premature ventricular beats(PVCs)  Atrioventricular reentrant tachycardia (AVRT)  Electrocardiogram (ECG)  Computer- aided diagnosis (CAD)
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