心外膜脂肪影像分割量化方法及其临床应用的研究进展  

Research progress on imaging segmentation and quantification methods for epicardial adipose tissue and its clinical applications

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作  者:屈俊达 杨敏福[2] 李春林[1] 孙立伟 高赫 张旭[1] Qu Junda;Yang Minfu;Li Chunlin;Sun Liwei;Gao He;Zhang Xu(School of Biomedical Engineering,Capital Medical University,Beijing 100069,China;Department of Nuclear Medicine,Beijing Chaoyang Hospital,Capital Medical University,Beijing 100020,China)

机构地区:[1]首都医科大学生物医学工程学院,北京100069 [2]首都医科大学附属北京朝阳医院核医学科,北京100020

出  处:《首都医科大学学报》2025年第1期99-105,共7页Journal of Capital Medical University

基  金:国家自然科学基金项目(62171300,82272036,62301343)。

摘  要:心外膜脂肪(epicardial adipose tissue,EAT)是紧邻冠状动脉和心肌的脂肪组织,通过自分泌或旁分泌活性因子对机体造成生理和病理性的改变。EAT被认为是心血管疾病的诊断标志物和潜在的治疗靶点,分割量化EAT具有重要意义。本文从传统影像、图谱及人工智能三个方面介绍EAT分割量化方法的演变过程,并对自动量化的EAT指标在心血管疾病诊疗中的研究进展进行综述。Epicardial adipose tissue(EAT)is a type of fat tissue that is closely adjacent to the coronary arteries and myocardium,and it caused physiological and pathological changes to the body through the secretion of autocrine and paracrine active factors.EAT is regarded as a diagnostic marker and a potential therapeutic target for cardiovascular diseases,and it is of great significance to segment and quantify EAT.This article introduced the evolution of the EAT segmentation and quantification methods from the aspects of traditional imaging,atlas,and artificial intelligence.Furthermore,it reviewed the research progresses on automatically quantified EAT indices in the diagnosis and treatment of cardiovascular diseases.

关 键 词:心外膜脂肪 分割及量化 深度学习 临床应用 

分 类 号:R318[医药卫生—生物医学工程] TP18[医药卫生—基础医学]

 

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