癌变·畸变·突变 ›› 2022, Vol. 34 ›› Issue (5): 361-365.doi: 10.3969/j.issn.1004-616x.2022.05.005

• 论著 • 上一篇    

人工智能辅助系统在宫颈病变细胞学诊断中的应用效果研究

郭晓, 刘颖, 王蕊, 廉亚丽, 杜芸   

  1. 河北医科大学第四医院细胞学室, 河北 石家庄 050011
  • 收稿日期:2022-06-13 修回日期:2022-09-09 发布日期:2022-10-09
  • 通讯作者: 杜芸
  • 作者简介:郭晓,E-mail:335754696@qq.com。
  • 基金资助:
    河北省重点研发计划项目-民生科技专项(20377723D)

Application of an artificial intelligence-assisted system in cytological diagnosis of cervical lesions

GUO Xiao, LIU Ying, WANG Rui, LIAN Yali, DU Yun   

  1. Department of Cytology, the Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, Hebei, China
  • Received:2022-06-13 Revised:2022-09-09 Published:2022-10-09

摘要: 目的:分析人工智能(AI)辅助系统在宫颈病变细胞学诊断中的应用效果。方法:收集宫颈液基薄层细胞学(TCT)标本2 719例,同时进行AI辅助阅片和人工阅片,比较两者的一致性。以活体组织检查结果为金标准,比较AI辅助阅片和人工阅片的准确性,诊断高级别病变及癌的敏感性、特异性及ROC曲线下面积。结果:AI辅助阅片和人工阅片的细胞学分级诊断结果基本一致。AI辅助阅片在诊断低级别病变及炎症的准确率高于人工阅片(P<0.01)。在诊断高级别病变及癌方面,AI辅助阅片敏感性为82.1%,高于人工阅片的敏感性48.3%;AI辅助阅片特异度为94.3%,略低于人工阅片的特异度95.0%;AI辅助阅片的ROC曲线下面积为0.882,大于人工阅片的ROC曲线下面积0.717(P<0.01)。结论:AI辅助阅片在宫颈癌诊断方面准确度较高,不仅能提高宫颈癌筛查的覆盖率,而且能提高筛查质量,能够在广大人群中得到广泛推广。

关键词: 宫颈癌, 人工智能, 液基细胞学, TBS诊断, 辅助阅片

Abstract: OBJECTIVE: To analyze the application effects of artificial intelligence (AI) in cytological diagnosis of cervical lesions.METHODS: 2 719 cervical TCT specimens were collected.AI-assisted and manual diagnoses were performed on all specimens to compare their consistency.Histopathological results were used as the gold standard.The accuracy,sensitivity,specificity and area under ROC curve of AI-assisted diagnosis and manual diagnosis were compared.RESULTS: The results of AI-assisted cytological grading diagnosis were basically consistent with results of manual diagnosis.AI-assisted diagnosis of low-grade lesions and inflammation was more accurate than manual radiography (P<0.01).In the diagnosis of high-grade lesions and cancer,the sensitivity of AI diagnosis was 82.1%,higher than 48.3% of manual diagnosis.The specificity of AI diagnosis was 94.3%,slightly lower than 95.0% of manual diagnosis.The area under ROC curve of AIassisted diagnosis (AUC=0.882) was larger than that of manual diagnosis (AUC=0.717),and the difference was statistically significant (P<0.01).CONCLUSION: AI-assisted diagnosis showed high accuracy in the diagnosis of cervical cancer,which should improve the coverage rate and the quality of cervical cancer screening in the general population.

Key words: cervical cancer, artificial intelligence, thinprep cytologic test, the bethesda system, assisted reading

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