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人工智能辅助肺部超声波用于肺胸部:诊断准确性与CT相比在紧急和重症监护中

İsmail Dal¹, Kemal Akyol²

¹Department of Thoracic Surgery, Faculty of Medicine, Kastamonu University, Kastamonu 37150, Turkey.

Tomography (Ann Arbor, Mich.)

|November 26, 2025

概括

人工智能 (AI) 显著增强肺部超声波 (LUS) 检测肺胸部 (PTX),实现近乎专家的准确性. 这种人工智能辅助的方法为重症监护机构提供了更快,更可靠的诊断工具.

科学领域:

医疗成像医学成像
人工智能的人工智能
关键护理医学关键护理医学

背景情况:

肺胸部 (PTX) 诊断在紧急和重症监护中至关重要.
肺部超声波 (LUS) 是CT的快速,无辐射的替代方案,但取决于操作者.
人工智能 (AI) 可能会标准化LUS解释并提高准确性.

研究的目的:

评估AI,特别是变压器模型在使用肺超声波检测肺胸部的性能.
为了比较PTX检测的不同AI模型 (ViT,DINOv2,RF,XGBoost) 和成像模式 (B模式,M模式) 的准确性.

主要方法:

使用CT作为参考对46名患者 (23名PTX,23名对照) 的回顾性分析.
提取 2760 B 模式和 M 模式的超声波框架.
在图像数据和视频特征上对变压器模型 (ViT,DINOv2) 和分类器 (RF,XGBoost) 的培训和测试.

主要成果:

变压器模型实现了高诊断准确度,B模式图像通常优于M模式.
在B模式 (90%准确度,80%灵敏度,100%特异性) 中,DINOv2在患者层面的分割场景中表现出强的表现.
人工智能模型,包括视频功能上的RF和XGBoost,在PTX检测中达到高达90%的准确性.

结论:

人工智能辅助的LUS大大改善了肺胸部检测,像DINOv2这样的变压器模型显示了接近专家的准确性.
在更大的多中心数据集上进行进一步的验证是必要的,以便在LUS中临床整合AI用于PTX诊断.

关键词:

人工智能的人工智能是人工智能.诊断成像诊断成像的使用应急服务的紧急服务.肺部胸部 (pneumothorax) 是一个疾病.关怀点的系统关怀点的系统超声波学超声波学超声波学

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