摘要
胸膜超声作为肺部超声的一部分,简便、高效,是评估和监测呼吸系统疾病的重要有效手段。常规技术包括胸膜的静态和动态评估,如胸膜形态、厚度、运动情况、胸膜下改变及胸腔积液,这与呼吸系统各疾病的病理生理存在密切联系。因此,不同呼吸系统疾病表现为不同的胸膜改变,可以帮助医生快速区分肺水肿、慢性阻塞性肺疾病、肺炎、肺栓塞、肺间质纤维化等疾病。胸膜超声在胸腔积液和周围型肺占位的定性及定量评估中,展现出独特优势。超声新技术如斑点追踪技术、超声造影、弹性成像、深度学习算法等的应用,使得胸膜超声进入新阶段。随着技术的进步,胸膜超声展示出巨大应用潜力,特别是动态征象的人工智能识别、三维模型计算胸腔积液量、周围型肺结节的人工智能识别及定性诊断等,可能会更加高效地提供临床信息和改变诊疗模式。本文就胸膜超声在呼吸系统疾病中的应用现状及未来发展趋势作一综述。
As a part of lung ultrasound,pleural ultrasound is a simple,efficient,important,and effective tool in the assessment and monitoring of respiratory diseases.Routine techniques include static and dynamic assessment of the pleura,such as pleural morphology,thickness,motion,subpleural changes,and pleural effusion,which are closely related to the pathophysiology of various respiratory diseases.Therefore,different respiratory diseases show different pleural changes,which can help us to quickly differentiate between diseases such as pulmonary edema,chronic obstructive pulmonary disease,pneumonia,pulmonary embolism,and interstitial fibrosis.Pleural ultrasound demonstrates unique advantages in the qualitative and quantitative assessment of pleural effusion and peripheral lung occupations.New ultrasound technologies such as speckle tracking technology,ultrasonography,elastography,and the application of deep learning algorithms have brought pleural ultrasound into a new phase.With the advancement of technology,pleural ultrasound demonstrates great potential for application,especially artificial intelligence(AI)recognition of dynamic signs,3D models calculation of pleural effusion volume,AI recognition of peripheral lung nodules,and qualitative diagnosis,which may provide clinical information and change the diagnostic and treatment modes more efficiently.In this review,the status and future development of pleural ultrasound application in respiratory diseases are discussed.
作者
孙哲
马姣姣
张波
Sun Zhe;Ma Jiaojiao;Zhang Bo(Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100730,China;Department of Ultrasound,China-Japan Friendship Hospital,Beijing 100029,China;National Center for Respiratory Medicine,State Key Laboratory of Respiratory Health and Multimorbidity,National Clinical Research Center for Respiratory Diseases,Institute of Respiratory Medicine,Chinese Academy of Medical Sciences,Center of Respiratory Medicine,China-Japan Friendship Hospital,Beijing 100029,China)
出处
《首都医科大学学报》
北大核心
2023年第6期966-972,共7页
Journal of Capital Medical University
基金
中央高水平医院临床科研业务费资助项目(2022-NHLHCRF-LX-01-0205)。
关键词
超声
胸膜
呼吸系统疾病
ultrasound
pleura
respiratory diseases