实用医学杂志 ›› 2021, Vol. 37 ›› Issue (15): 2007-2011.doi: 10.3969/j.issn.1006⁃5725.2021.15.020

• 医学检查与临床诊断 • 上一篇    下一篇

超声影像组学标签预测乳腺癌前哨淋巴结转移的价值

暴珞宁1,2, 王瑛3,陈东4,刘再毅1,2   

  1. 1 南方医科大学第二临床医学院(广州 510515);2 广东省人民医院(广东省医学科学院)放射科(广州 510080);3 广州医科大学附属第一医院超声科(广州 510120);4 昆明医科大学第三附属医院(云南省肿瘤 医院)超声科(昆明 650118)
  • 出版日期:2021-08-10 发布日期:2021-08-10
  • 通讯作者: 刘再毅 E⁃mail:zyliu@163.com
  • 基金资助:
    国家重点研发计划项目(编号:2017YFC1309100)

Ultrasound ⁃ based radiomics to predict sentinel lymph node metastasis in breast cancer 

BAO Luoning, WANG Ying, CHEN Dong, LIU Zaiyi.    

  1. The Second School of Clinical Medicine, Southern Medical University, Guang⁃ zhou 510515, China; * Department of Radiology, Guangdong Provincial People′s Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China

  • Online:2021-08-10 Published:2021-08-10
  • Contact: LIU Zaiyi E⁃mail: zyliu@163.com

摘要:

目的 探讨基于常规超声的影像组学标签在术前诊断乳腺癌前哨淋巴结转移的应用价值。 方法 收集 2020 1-10 194 例经我院诊治的乳腺癌患者的临床资料和术前超声图像,按超声检查时间 顺序,将患者分为训练集(n = 103)和验证集(n = 88)。通过 Image J 软件手动勾画病灶区域,使用 Pyradiomics从每个病灶区域中提取1 130个特征,采用多种方法逐步筛选特征,利用逻辑回归模型构建超声 影像组学标签。采用受试者工作特征(ROC)曲线、校准曲线和决策曲线等评估超声影像组学标签预测乳腺 癌前哨淋巴结转移的效能。结果 筛选出 6 个关键超声影像组学特征用于构建超声影像组学标签。该标 签在训练集和验证集中预测乳腺癌前哨淋巴结转移的 ROC 曲线下面积分别为 0.795(95%CI:0.708 ~ 0.882)、0.784(95%CI:0.688 ~ 0.881)。在校准曲线中,该标签在训练集和验证集里表现出好的校准度(P = 0.985、0.854),决策曲线分析进一步表明了该标签对临床决策有辅助作用。结论 基于常规超声的影像组 学标签可用于术前预测乳腺癌有无前哨淋巴结转移,为临床制定个体化的手术方式提供更多参考依据。

关键词:

超声图像, 影像组学, 乳腺癌, 前哨淋巴结, 预测模型

Abstract:

Objective To explore the value of a radiomics model based on ultrasound imaging in predict⁃ ing the sentinel lymph node status of breast cancer before surgery. Methods A total of 194 patients with early ⁃ stage breast cancer were retrospectively analyzed,all patients underwent preoperative breast ultrasound examina⁃ tion. According to the order of examination time,the patients were divided into training group(n = 103)and vali⁃ dation group(n = 88). Image J software was used to manually delineate the lesion area in the ultrasound image along the tumor boundary. Pyradiomics was used to extract 1 130 features from each lesion area,and the features were screened using three statistical methods. Finally,an ultrasound imaging radiomics model was built using a lo⁃ gistic regression model. To evaluate the performance and value of an ultrasound imaging radiomics model in predict⁃ ing sentinel lymph node status,the receive operating characteristic curve(ROC),calibration curve,and decision curve were used. Results To construct the ultrasound imaging radiomics model,6 key image features were cho⁃ sen. The area of under the ROC curve of the model in the training group and the validation group were 0.795(95% CI:0.708~0.882)and 0.784(95%CI:0.688~0.881),respectively. The calibration curve showed that the model had a good calibration in both the training and validation groups;Additionally,the decision curve analysis con⁃ firmed that the model could support clinical decision ⁃making. Conclusion Ultrasound ⁃ based imaging radiomics model is of great value in predicting the sentinel lymph node status of breast cancer before surgery.

Key words:

ultrasonic image, image omics, breast cancer, sentinel lymph node, prediction model