首页|尘肺病影像学及AI辅助诊断技术的研究进展

尘肺病影像学及AI辅助诊断技术的研究进展

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职业性尘肺病(尘肺病)是我国危害最严重的职业病病种.相关文献报道尘肺病占所有职业病报告总数的80％左右.根据GBZ 70-2015《职业性尘肺病的诊断》标准,诊断尘肺病主要依据粉尘接触史、职业健康监护资料及技术质量合格的X线后前位胸片,参照尘肺标准片进行诊断与分期.X线胸片是既往尘肺病诊断研究最多的影像技术,在尘肺病早期鉴别诊断方面技术相对落后.随着影像学检查技术及人工智能技术的进步,尘肺病影像研究逐渐向早期、精准诊断方向发展.计算机体层摄影(又称计算机断层扫描技术,computed tomography,CT)、人工智能辅助诊断、磁共振成像(magnetic resonance imaging,MRI)、正电子发射断层显像-X线计算机体层成像仪(positron emission tomography-computed tomography,PET-CT)辅助检查手段成为近年来尘肺病辅助诊断研究的热点,通过查阅、梳理文献,对相关研究内容进行综述.总结各类检查技术优点及应用中存在的问题,提出未来尘肺病影像学及辅助诊断方面可能面临的挑战,为未来尘肺病影像学及辅助诊断技术研究方向提供参考依据.
Research progress of imaging and AI-assisted diagnosis of pneumoconiosis
Occupational pneumoconiosis is the most serious occupational disease in China.Relevant literature reports that pneumoconiosis accounts for about 80％of all occupational disease reports.According to GBZ 70-2015"diagnosis of occupational pneumoconiosis",the diagnosis of pneumoconiosis is mainly based on the dust exposure history,occupational health monitoring data and technical quality qualified X-ray posterior anterior chest film,with reference to pneumoconiosis standard film for diagnosis and staging.Chest X-ray is the most studied imaging technology in the diagnosis of pneumoconiosis in the past,and the technology in the early differential diagnosis of pneumoconiosis is relatively backward.With the progress of imaging technology and artificial intelligence technology,pneumoconiosis imaging research is gradually developing towards early and accurate diagnosis.Computed tomography(CT),artificial intelligence assisted diagnosis,magnetic resonance imaging(MRI),positron emission tomography X-ray computed tomography(PET-CT)assisted examination methods have become a hot spot in the research of pneumoconiosis assisted diagnosis in recent years.Through consulting and combing the literature,this paper reviews the relevant research content.This paper summarizes the advantages of various examination technologies and the problems existing in their application,and puts forward the possible challenges in the imaging and auxiliary diagnosis of pneumoconiosis in the future,so as to provide reference for the research direction of imaging and auxiliary diagnosis technology of pneumoconiosis in the future.

PneumoconiosisImagingDigital radiographyComputed tomographyPositron emission tomography computed tomographyMagnetic resonance imagingArtificial intelligence aided diagnosisNeural network

王宁宁、靳毅、王成霞、刘真、刘肖、王燕停

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淄博市职业病防治院放射科,山东淄博 255000

淄博市中心医院放射科,山东淄博 255000

济宁医学院临床医学院,山东济宁 272013

尘肺病 影像学 数字化X线摄影 计算机断层扫描 正电子发射断层显像-X线计算机体层成像仪 磁共振成像 人工智能辅助诊断 神经网络

山东省医药卫生科技发展计划

202009010872

2024

职业与健康
天津市疾病预防控制中心 中华预防医学会

职业与健康

CSTPCD
影响因子：0.737
ISSN：1004-1257
年,卷(期)：2024.40(6)
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