基于大数据的儿科超声心动图标准参考体系建设  

Establishment of normal reference system in pediatric echocardiography based on BigData

作　　者：李昊旻[1] 俞劲[2] 王雨虹 段会龙[3] 叶菁菁[2] 李建华[1] 舒强[1] Li Haomin;Yu Jin;Wang Yuhong;Duan Huilong;Ye Jingjing;Li Jianhua;Shu Qiang((Heart Center, Children′s Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China;Department of Ultrasound, Children′s Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China;College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China)

机构地区：[1]浙江大学医学院附属儿童医院心脏中心,杭州310052 [2]浙江大学医学院附属儿童医院超声科,杭州310052 [3]浙江大学生物医学工程与仪器科学学院,杭州310027

出　　处：《中华超声影像学杂志》2019年第3期185-191,共7页Chinese Journal of Ultrasonography

基　　金：国家自然科学基金(81871456);国家重点研发计划(2016YFC0901905).

摘　　要：目的基于长期积累的儿科心脏超声报告大数据构建儿科超声心动图标准参考体系。方法利用自然语言处理技术从过去5年积累的71 831份超声心动图报告中提取结构化的各种测量指标,以其中12 732份标记为正常的报告中的5项测量值(主动脉内径、左心房内径、左室舒张末期内径、左冠状动脉内径、右冠状动脉内径)为基础,利用局部加权回归分别对参考值和标准方差值进行建模,建立基于年龄/性别以及体表面积的两个标准Z值体系,并利用4 459例具有体表面积数据的案例对该Z值体系进行评估。结果两个Z值体系显示出良好的正态分布特性,同时与目前国际上最广泛人群建立的美国儿科心脏网络(PHN)Z值体系具有显著相关性,其中基于体表面积的Z值体系R=0.954,基于年龄/性别的Z值体系R=0.895。相关结果发布为一个在线的Z值计算器(http://hdb.nbscn.org/zscore)。结论临床大数据的利用能够更快、更好地构建儿科超声心动图标准参考体系。Objective To establish a pediatric echocardiographic normal reference system based on clinical BigData and overcome limitations such as insufficient sample size and diverse in methods of normalization. Methods Measurements were extracted from total 71 831 pediatric echocardiography reports in the past 5 years by using the Natural Language Processing (NLP) technology. Among them, a total of 12 732 reports were labeled as normal and were used to establish the normal reference system. A local regression (LOESS) approach was used to optimize both the reference value and variance across 5 growth variables (aortic diameter, left atrium diameter, left ventricle end-diastolic endocardial diameter, left main coronary artery diameter, and right main coronary artery diameter). Two Z scores adjusted for age/sex and body surface area (BSA) were established respectively. In addition, 4 459 echocardiography reports with BSA information were used to evaluate these two Z scores. Results Two Z scores generated from 4 459 reports showed pretty good normal distribution. There were close strong correlations among two Z scores with Z scores generated based on the Pediatric Heart Network (PHN). The average correlation coefficient between BSA-adjust Z scores and PHN Z scores was 0.954. The average correlation coefficient between age/sex-adjust Z scores and PHN Z scores was 0.895. The results of this project were available as Z score calculator using the following link: http://hdb.nbscn.org/zscore. Conclusions BigData provides a more efficient and better approach to establish normal reference systems in pediatric echocardiography.

关 键 词：超声心动描记术 标准参考体系 儿童 大数据 Z值 

分 类 号：R725.4[医药卫生—儿科] R540.45[医药卫生—临床医学]