[1]王美文,王艳春,肖沪生,等.S-Detect技术在乳腺超声检查中的诊断性能[J].中国医学物理学杂志,2020,37(4):450-455.[doi:DOI:10.3969/j.issn.1005-202X.2020.04.010]
　WANG Meiwen,WANG Yanchun,XIAO Husheng,et al.Diagnostic performances of S-Detect technique in breast ultrasound examination[J].Chinese Journal of Medical Physics,2020,37(4):450-455.[doi:DOI:10.3969/j.issn.1005-202X.2020.04.010]
点击复制

S-Detect技术在乳腺超声检查中的诊断性能()
分享到：

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第4期
页码:
450-455
栏目:
医学影像物理
出版日期:
2020-04-29

文章信息/Info

Title:
Diagnostic performances of S-Detect technique in breast ultrasound examination
文章编号:
1005-202X（2020）04-0450-06
作者:
王美文; 王艳春; 肖沪生; 任亚娟; 徐芳
上海中医药大学附属龙华医院超声医学科， 上海 200232
Author(s):
WANG Meiwen;  WANG Yanchun;  XIAO Husheng;  REN Yajuan;  XU Fang
Department of Ultrasound Medicine, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200232, China
关键词:
乳腺肿块; S-Detect技术; 计算机辅助诊断
Keywords:
Keywords: breast mass;  S-Detect technique;  computer-aided diagnosis
分类号:
R318；R445.1
DOI:
DOI:10.3969/j.issn.1005-202X.2020.04.010
文献标志码:
A
摘要:
目的：分析S-Detect技术在乳腺超声检查中的诊断性能。方法：选择2018年6月~12月接受检查的的女性患者175例，共纳入192个乳腺肿块。分别通过超声医生和S-Detect技术来评估其对乳腺超声检查结果的一致性。比较两者的诊断性能，包括敏感性、特异性、阳性预测值、阴性预测值、准确性和接受者操作特征曲线下面积。结果：192个乳腺肿块中，恶性72个（37.5%），良性120个（62.5%）。对于4a类良性肿块，相比超声医生，S-Detect技术具有较高的良性评估率。S-Detect技术的特异性、阳性预测值、准确性和接受者操作特征曲线下面积显著高于超声医生，而诊断敏感度、阴性预测值低于超声医生（P<0.05）。超声医生和S-Detect技术的最终评估结果显示中度一致（κ=0.58）。结论：S-Detect技术可作为提高乳腺超声诊断特异性的一种辅助诊断手段，可指导乳腺肿块的诊断。
Abstract:
Abstract: Objective To evaluate the diagnostic performance of S-Detect technique in breast ultrasound examination. Methods A total of 175 female patients receiving ultrasound examination from June to December 2018 were enrolled in the study, with a total of 192 breast masses. The consistency of the diagnostic results obtained by ultrasound doctors and S-Detect technique was evaluated, and the diagnostic performances including sensitivity, specificity, positive predictive value, negative predictive value, accuracy and area under receiver operating characteristic curve were compared. Results Among 192 breast masses, there were 72 (37.5%) of malignant masses and 120 (62.5%) of benign masses. For 4a benign masses, S-Detect technique had a benign assessment rate higher than ultrasound doctors. The specificity, positive predictive value, accuracy and area under receiver operating characteristic curve of S-Detect technique were significantly higher than those of ultrasound doctors, while the diagnostic sensitivity and negative predictive value were lower than those of ultrasound doctors (P<0.05). There was a moderate agreement in the diagnostic results evaluated by ultrasound doctors and S-Detect technique (κ=0.58). Conclusion S-Detect technique can be used as an additional diagnostic tool to improve the specificity of breast ultrasound examination and provide guidance for the diagnosis of breast masses.

相似文献/References:

[1]王孝义,邢素霞,王瑜,等.基于自适应能量偏移场无边缘主动轮廓模型的乳腺肿块分割与分类方法研究[J].中国医学物理学杂志,2020,37(8):1010.[doi:DOI:10.3969/j.issn.1005-202X.2020.08.014]
　WANG Xiaoyi,XING Suxia,WANG Yu,et al.Breast mass image segmentation and classification based on adaptive energy offset field-CV[J].Chinese Journal of Medical Physics,2020,37(4):1010.[doi:DOI:10.3969/j.issn.1005-202X.2020.08.014]
[2]梁楠,赵政辉,周依,等.基于滑动块的深度卷积神经网络乳腺X线摄影图像肿块分割算法[J].中国医学物理学杂志,2020,37(12):1513.[doi:DOI:10.3969/j.issn.1005-202X.2020.12.008]
　LIANG Nan,ZHAO Zhenghui,et al.An algorithm of mass segmentation in mammogram by using deep convolutional neural network based on sliding patch[J].Chinese Journal of Medical Physics,2020,37(4):1513.[doi:DOI:10.3969/j.issn.1005-202X.2020.12.008]

备注/Memo

备注/Memo:
【收稿日期】2019-11-02 【基金项目】国家自然科学基金青年科学基金（81503413） 【作者简介】王美文，博士，初级医师，研究方向：浅表器官超声诊断，E-mail: 414500048@qq.com 【通信作者】徐芳，主任医师，研究方向：心脏超声诊断，E-mail: xf_818@126.com
更新日期/Last Update: 2020-04-29