[1]贺 芳,肖际东,郭 阳.人工智能S-detect技术在超声BI-RADS 4类乳腺肿块中的应用价值[J].医学信息,2023,36(17):115-118.[doi:10.3969/j.issn.1006-1959.2023.17.022]
　HE Fang,XIAO Ji-dong,GUO Yang.Application Value of Artificial Intelligence S-detect Technology in Ultrasound BI-RADS 4 Breast Masses[J].Journal of Medical Information,2023,36(17):115-118.[doi:10.3969/j.issn.1006-1959.2023.17.022]
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人工智能S-detect技术在超声BI-RADS 4类乳腺肿块中的应用价值()

医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年17期
页码:
115-118
栏目:
论著
出版日期:
2023-09-01

文章信息/Info

Title:
Application Value of Artificial Intelligence S-detect Technology in Ultrasound BI-RADS 4 Breast Masses
文章编号:
1006-1959（2023）17-0115-04
作者:
贺 芳; 肖际东; 郭 阳
（1.长沙市第三医院超声科，湖南 长沙 410035；2.中南大学湘雅三医院超声科，湖南 长沙 410013；3.哈尔滨医科大学第一临床医学院，黑龙江 哈尔滨 150007）
Author(s):
HE Fang; XIAO Ji-dong; GUO Yang
(1.Department of Diagnostic Ultrasound,the Third Hospital of Changsha,Changsha 410035,Hunan,China;2.Department of Diagnostic Ultrasound,the Third Xiangya Hospital of Central South University,Changsha 410013,Hunan,China;3.The First Clinical Medical College of Harbin Medical University,Harbin 150007,Heilongjiang,China)
关键词:
BI-RADS 4类; S-detect技术; 人工智能; 乳腺肿块
Keywords:
BI-RADS 4 category; S-detect technology; Artificial intelligence; Breast mass
分类号:
R737.9
DOI:
10.3969/j.issn.1006-1959.2023.17.022
文献标志码:
A
摘要:
目的 探究人工智能S-detect技术在超声BI-RADS 4类乳腺肿块中的应用价值。方法 选取2018年2月-2020年2月在中南大学湘雅三医院进行乳腺超声检查的女性患者73例作为研究对象，同时进行了S-detect检测。以组织学病理结果为金标准，分析S-detect技术在辅助常规超声前后在BI-RADS 4类乳腺肿块中诊断效能。结果 以组织学病理结果为金标准，常规超声对76例乳腺肿块进行BI-RADS分类的正确率为72.37%、S-detect检测的正确率为71.05%，二者结合诊断的正确率为81.58%。常规超声、S-detect检测及S-detect辅助超声的受试者工作特征曲线下面积分别为0.724、0.746和0.838，后者具有最佳的AUC值（P＜0.05）。结论 S-detect技术能有效提高常规超声对BI-RADS 4类乳腺肿块的诊断效能，减少不必要肿块活检。
Abstract:
Objective To explore the application value of artificial intelligence S-detect technology in ultrasound BI-RADS 4 breast masses.Methods A total of 73 female patients who underwent breast ultrasound examination in the Third Xiangya Hospital of Central South University from February 2018 to February 2020 were selected as the research objects, and S-detect detection was performed at the same time. The diagnostic efficacy of S-detect technique in BI-RADS 4 breast masses before and after conventional ultrasound was analyzed with histopathological results as the gold standard.Results With the histopathological results as the gold standard, the accuracy of BI-RADS classification of 76 cases of breast masses by conventional ultrasound was 72.37%, the accuracy of S-detect detection was 71.05%, and the accuracy of combined diagnosis was 81.58%. The area under the receiver operating characteristic curve of conventional ultrasound, S-detect detection and S-detect assisted ultrasound were 0.724, 0.746 and 0.838, respectively, and the last one had the best AUC value (P<0.05).Conclusion S-detect technology can effectively improve the diagnostic efficiency of conventional ultrasound for BI-RADS 4 breast masses, and reduce unnecessary mass biopsy.

参考文献/References:

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更新日期/Last Update: 1900-01-01