Value of S-Detect technique for diagnosing breast tumors by well-experienced and less-experienced ultrasound physicians

CAO Li; ZHANG Huiping; ZHOU Yuqing; ZHOU Zhuying

doi:10.19732/j.cnki.2096-6210.2022.04.015

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Value of S-Detect technique for diagnosing breast tumors by well-experienced and less-experienced ultrasound physicians

更新时间：2025-12-15

- Value of S-Detect technique for diagnosing breast tumors by well-experienced and less-experienced ultrasound physicians
- Vol. 31, Issue 4, Pages: 439-443(2022)
- 作者机构：
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- DOI：10.19732/j.cnki.2096-6210.2022.04.015
  CLC：
- Published Online：28 August 2022，
  
  Published：28 August 2022
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曹力,张会萍,周毓青,等. 不同年资超声科医师应用S-Detect技术诊断乳腺结节的价值研究[J]. 肿瘤影像学, 2022, 31(4): 439-443 https://doi.

org/10.19732/j.cnki.2096-6210.2022.04.015
曹力,张会萍,周毓青,等. 不同年资超声科医师应用S-Detect技术诊断乳腺结节的价值研究[J]. 肿瘤影像学, 2022, 31(4): 439-443 https://doi. DOI： 10.19732/j.cnki.2096-6210.2022.04.015.

org/10.19732/j.cnki.2096-6210.2022.04.015 DOI：

摘要

目的：

对比分析不同年资超声科医师应用人工智能（artificial intelligence，AI）S-Detect技术诊断乳腺结节的诊断效能，探讨S-Detect技术的临床应用价值。

方法：

对2020年710月在上海市长宁区妇幼保健院行乳腺结节手术的100例患者（144例结节），分别由1名高年资副主任医师和1名低年资主治医师行常规临床超声诊断，按照乳腺影像报告和数据系统（Breast Imaging Reporting and Data System，BI-RADS）分类标准，以分类结果4A诊断为良性结节，＞4A诊断为恶性结节；并分别应用S-Detect技术评价结节，以纵切及横切两次结果均为可能良性诊断为良性结节，否则诊断为恶性结节。以病理学检查结果为金标准，对比分析常规超声检查及S-Detect技术2名医师的诊断效能及一致性。

结果：

144个乳腺结节中，良性结节124个，恶性结节20个。使用常规超声检查高年资医师及低年资医师的受试者工作特征（receiver operating characteristic，ROC）曲线的曲线下面积（area under curve，AUC）分别为0.868和0.690；S-Detect技术高年资医师及低年资医师的AUC分别为0.877和0.893；常规超声检查低年资医师的AUC与其他三者差异有统计学意义（

＜0.01）。常规超声检查高年资医师及低年资医师组内相关系数（intraclass correlation coefficient，ICC）为0.736，具有中度一致性；S-Detect技术高年资医师及低年资医师ICC为0.928，具有高度一致性。

结论：

临床不同年限超声科医师工作经验对于乳腺结节的鉴别诊断有影响，但是AI技术可以降低经验对诊断结果的影响。S-Detect技术值得临床推广。

Abstract

Objective:

To compare the diagnostic efficiencies of artificial intelligence (AI) S-Detect technique for diagnosing breast tumors using by a well-experienced ultrasound physician and a less-

experienced one and to explore the value of S-Detect technique for clinical application.

Methods:

A total of 100 patients (with 144 breast masses) who underwent breast tumor surgery in Shanghai Changning Maternity and Infant Health Hospital were included in this study and were examined by a well-experienced ultrasound physician and a less-experienced one using conventional ultrasound with Breast Imaging Reporting and Data System (BI- RADS) classification (BI-RADS ＞4A was considered as malignant) and S-Detect technique (benign nodules were diagnosed if the results of both the longitudinal and transverse were possibly benign; otherwise

malignant nodules were diagnosed) respectively. With pathological results as golden standards

the diagnostic efficiencies and consistency of conventional ultrasound and S-Detect technique were analyzed and compared.

Results:

Among 144 breast tumors

124 were benign and 20 were malignant. Area under curves (AUCs) of receiver operating characteristic (ROC) curves of conventional ultrasound of the well-experienced ultrasound physician and the less-experienced one were 0.868 and 0.690 respectively; AUCs of S-Detect technique of those physicians were 0.877and 0.893 respectively. AUC of conventional ultrasound classification of the less-experienced ultrasound physician was significantly lower than the other three (

＜0.01). The diagnostic results of two ultrasound physicians using conventional ultrasound were moderately consistent with intraclass correlation coefficient (ICC) as 0.736; and the diagnostic results of two ultrasound physicians using S-Detect were highly consistent with ICC as 0.928.

Conclusion:

The work experience of ultrasound physicians with different clinical working years has influence on the differential diagnosis of breast nodules

but AI technology can reduce the influence of experience on the diagnosis results. S-Detect technique is worth to be popularized clinically.

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