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AI赋能肺部超声在新生儿呼吸窘迫综合征诊疗中的应用价值与研究进展

陆涵,  左莉莉,  陈筱青

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文章导航 > 中华全科医学  > 2026 >  24(5): 829-832
陆涵, 左莉莉, 陈筱青. AI赋能肺部超声在新生儿呼吸窘迫综合征诊疗中的应用价值与研究进展[J]. 中华全科医学, 2026, 24(5): 829-832. doi: 10.16766/j.cnki.issn.1674-4152.004501
引用本文: 陆涵, 左莉莉, 陈筱青. AI赋能肺部超声在新生儿呼吸窘迫综合征诊疗中的应用价值与研究进展[J]. 中华全科医学, 2026, 24(5): 829-832. doi: 10.16766/j.cnki.issn.1674-4152.004501
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LU Han, ZUO Lili, CHEN Xiaoqing. Application value and research progress of AI-assisted lung ultrasound in the diagnosis and treatment of neonatal respiratory distress syndrome[J]. Chinese Journal of General Practice, 2026, 24(5): 829-832. doi: 10.16766/j.cnki.issn.1674-4152.004501
Citation: LU Han, ZUO Lili, CHEN Xiaoqing. Application value and research progress of AI-assisted lung ultrasound in the diagnosis and treatment of neonatal respiratory distress syndrome[J]. Chinese Journal of General Practice, 2026, 24(5): 829-832. doi: 10.16766/j.cnki.issn.1674-4152.004501
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AI赋能肺部超声在新生儿呼吸窘迫综合征诊疗中的应用价值与研究进展

doi: 10.16766/j.cnki.issn.1674-4152.004501
  • 1.

    南京医科大学第一附属医院儿科，江苏 南京 210029

  • 2.

    南京医科大学第一附属医院儿童保健科

基金项目: 

江苏省卫生健康委员会医学科研重点项目 K2023007

江苏省妇幼保健协会科研课题重点项目 FYX202508

江苏省人民医院临床能力提升工程项目 JSPH-MC-2023-30

详细信息
    通讯作者:

    陈筱青，E-mail：chenxq2002@foxmail.com

  • 中图分类号: R563.8  R445.1

Application value and research progress of AI-assisted lung ultrasound in the diagnosis and treatment of neonatal respiratory distress syndrome

  • 1.

    Department of Oncology (Division Ⅱ), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China

    摘要
  • 摘要: 新生儿呼吸窘迫综合征(NRDS)是早产儿中最具代表性的危重疾患之一, 因肺泡表面活性物质(PS)缺乏引起, 是早产儿死亡的主要呼吸系统病因之一。传统诊断依赖胸部X线, 但因辐射暴露与图像不稳定性构成临床局限。目标导向的重症超声(POCUS)应用价值已在重症医学领域获得广泛认可。作为重要核心模块的肺部超声(LUS)具有无辐射、床旁实时参与评估的技术特点, 在NRDS的诊断与综合管理中表现出显著优势。LUS不仅能快速准确诊断NRDS, 还能有效鉴别暂时性呼吸增快症、肺炎、气胸及胎粪吸入综合征等相似疾病。人工智能(AI)、大数据及5G技术的发展为LUS带来新机遇。AI通过深度学习和图像识别算法, 显著提高了LUS图像分析的效率与精确度, 使得NRDS的诊断更为高效、精准。大数据为新生儿个体化治疗方案提供证据链支持, 进一步优化治疗策略。5G技术则为参与LUS远程会诊提供核心保障, 尤其在资源匮乏地区, AI赋能LUS可以实现更为高效、高阶的远程诊疗, 多维度改善NRDS早产儿的全系统综合性管理。本文旨在分析AI赋能LUS在NRDS诊断和治疗中的应用价值, 并探讨相关技术的最新研究进展。

     

    Abstract: Neonatal respiratory distress syndrome (NRDS) is one of the most critical and representative diseases in preterm infants, primarily caused by a deficiency of pulmonary surfactant (PS), and it remains one of the leading respiratory causes of mortality in this population.Traditional diagnosis relies on chest X-ray, but its clinical utility is limited due to radiation exposure and image variability.Point-of-care critical ultrasound (POCUS) has gained widespread recognition in critical care medicine for its diagnostic value.As a core component, lung ultrasound (LUS) offers distinct advantages in the diagnosis and comprehensive management of NRDS, owing to its radiation-free nature and real-time bedside assessment capabilities.It not only enables rapid and accurate diagnosis of NRDS but also effectively differentiates it from similar conditions such as transient tachypnea of the newborn, pneumonia, pneumothorax, and meconium aspiration syndrome.Advancements in artificial intelligence (AI), big data, and 5G technology have opened new opportunities for LUS.AI, through deep learning and image recognition algorithms, significantly enhances the efficiency and precision of LUS image analysis, making the diagnosis of NRDS more efficient and accurate.Big data provides an evidence-based chain to support individualized treatment plans for newborns, further optimizing therapeutic strategies.Meanwhile, 5G technology offers robust support for remote LUS consultations, particularly in resource-limited areas.AI-powered LUS enables more efficient and advanced remote diagnostics and treatment, improving the comprehensive, system-wide management of preterm infants with NRDS across multiple dimensions.This review aims to summarize the application value of AI-powered LUS in the diagnosis and treatment of NRDS and explore the latest research advancements in related technologies.

     

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  • 收稿日期:  2025-11-04
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