留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

超声影像组学术前预测乳腺癌腋窝淋巴结转移的研究进展

高远菁 朱庆莉 姜玉新

高远菁, 朱庆莉, 姜玉新. 超声影像组学术前预测乳腺癌腋窝淋巴结转移的研究进展[J]. 协和医学杂志, 2021, 12(6): 989-993. doi: 10.12290/xhyxzz.2021-0187
引用本文: 高远菁, 朱庆莉, 姜玉新. 超声影像组学术前预测乳腺癌腋窝淋巴结转移的研究进展[J]. 协和医学杂志, 2021, 12(6): 989-993. doi: 10.12290/xhyxzz.2021-0187
GAO Yuanjing, ZHU Qingli, JIANG Yuxin. Research Progress of Ultrasound Radiomics in Predicting Axillary Lymph Node Metastasis of Breast Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(6): 989-993. doi: 10.12290/xhyxzz.2021-0187
Citation: GAO Yuanjing, ZHU Qingli, JIANG Yuxin. Research Progress of Ultrasound Radiomics in Predicting Axillary Lymph Node Metastasis of Breast Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(6): 989-993. doi: 10.12290/xhyxzz.2021-0187

超声影像组学术前预测乳腺癌腋窝淋巴结转移的研究进展

doi: 10.12290/xhyxzz.2021-0187
基金项目: 

中国医学科学院医学与健康科技创新工程项目 2020-I2M-C & T-B-033

详细信息
    通讯作者:

    朱庆莉  电话:010-69155494,E-mail:zqlpumch@126.com

  • 中图分类号: R445.1;R737.9

Research Progress of Ultrasound Radiomics in Predicting Axillary Lymph Node Metastasis of Breast Cancer

Funds: 

CAMS Innovation Fund for Medical Science 2020-I2M-C & T-B-033

More Information
    Corresponding author: ZHU Qingli  Tel: 86-10-69155494, E-mail: zqlpumch@126.com
  • 摘要: 乳腺癌已成为全球女性发病率最高的恶性肿瘤,是全球广泛关注的重点疾病。乳腺癌腋窝淋巴结转移的术前准确评估对于手术治疗决策至关重要,而传统的腋窝超声对少量和微转移淋巴结识别困难,无法满足精准治疗需求。近年来,随着人工智能和影像学技术的快速发展,影像组学方法可提取人眼难以识别的深层次图像信息,在医学影像领域得到了广泛应用。本文介绍超声影像组学术前预测乳腺癌淋巴结转移的研究进展,并对该领域的未来发展进行展望。
    作者贡献:高远菁负责文献检索、数据分析及论文初稿撰写; 朱庆莉负责论文初稿修订; 姜玉新负责论文审校。
    利益冲突:
  • [1] DeSantis C, Ma J, Bryan L, et al. Breast cancer statistics, 2013[J]. CA Cancer J Clin, 2014, 64: 52-62. doi:  10.3322/caac.21203
    [2] 李贺, 郑荣寿, 张思维. 2014年中国女性乳腺癌发病与死亡分析[J]. 中华肿瘤杂志, 2018, 40: 166-171. doi:  10.3760/cma.j.issn.0253-3766.2018.03.002

    Li H, Zheng RS, Zhang SW, et al. Incidence and mortality of female breast cancer in China, 2014[J]. Zhonghua Zhongliu Zazhi, 2018, 40: 166-171. doi:  10.3760/cma.j.issn.0253-3766.2018.03.002
    [3] Harbeck N, Gnant M. Breast cancer[J]. Lancet, 2017, 389: 1134-1150. doi:  10.1016/S0140-6736(16)31891-8
    [4] de Boer M, van Deurzen CH, van Dijck JA, et al. Micrometastases or isolated tumor cells and the outcome of breast cancer[J]. N Engl J Med, 2009, 361: 653-663. doi:  10.1056/NEJMoa0904832
    [5] Napel S, Mu W, Jardim-Perassi BV, et al. Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats[J]. Cancer, 2018, 124: 4633-4649. doi:  10.1002/cncr.31630
    [6] Giuliano AE, Ballman KV, McCall L, et al. Effect of Axillary Dissection vs No Axillary Dissection on 10-Year Overall Survival Among Women With Invasive Breast Cancer and Sentinel Node Metastasis: The ACOSOG Z0011 (Alliance) Randomized Clinical Trial[J]. JAMA, 2017, 318: 918-926. doi:  10.1001/jama.2017.11470
    [7] Lyman GH, Somerfield MR, Bosserman LD, et al. Sentinel Lymph Node Biopsy for Patients With Early-Stage Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline Update[J]. J Clin Oncol, 2017, 35: 561-564.
    [8] Valente SA, Levine GM, Silverstein MJ, et al. Accuracy of predicting axillary lymph node positivity by physical examination, mammography, ultrasonography, and magnetic resonance imaging[J]. Ann Surg Oncol, 2012, 19: 1825-1830. doi:  10.1245/s10434-011-2200-7
    [9] Alvarez S, Añorbe E, Alcorta P, et al. Role of sonography in the diagnosis of axillary lymph node metastases in breast cancer: a systematic review[J]. AJR Am J Roentgenol, 2006, 186: 1342-1348. doi:  10.2214/AJR.05.0936
    [10] Cools-Lartigue J, Meterissian S. Accuracy of axillary ultrasound in the diagnosis of nodal metastasis in invasive breast cancer: a review[J]. World J Surg, 2012, 36: 46-54. doi:  10.1007/s00268-011-1319-9
    [11] Engohan-Aloghe C, Hottat N, Noël JC. Accuracy of lymph nodes cell block preparation according to ultrasound features in preoperative staging of breast cancer[J]. Diagn Cytopathol, 2010, 38: 5-8. http://www.onacademic.com/detail/journal_1000033827615110_890a.html
    [12] Chen X, He Y, Wang J, et al. Feasibility of using negative ultrasonography results of axillary lymph nodes to predict sentinel lymph node metastasis in breast cancer patients[J]. Cancer Med, 2018, 7: 3066-3072. doi:  10.1002/cam4.1606
    [13] Zhu Y, Zhou W, Jia XH, et al. Preoperative Axillary Ultrasound in the Selection of Patients With a Heavy Axillary Tumor Burden in Early-Stage Breast Cancer: What Leads to False-Positive Results?[J]. J Ultrasound Med, 2018, 37: 1357-1365. doi:  10.1002/jum.14545
    [14] Ahmed M, Jozsa F, Baker R, et al. Meta-analysis of tumour burden in pre-operative axillary ultrasound positive and negative breast cancer patients[J]. Breast Cancer Res Treat, 2017, 166: 329-336. doi:  10.1007/s10549-017-4405-3
    [15] Bevilacqua JL, Kattan MW, Fey JV, et al. Doctor, what are my chances of having a positive sentinel node? A validated nomogram for risk estimation[J]. J Clin Oncol, 2007, 25: 3670-3679. doi:  10.1200/JCO.2006.08.8013
    [16] Chue KM, Yong WS, Thike AA, et al. Predicting the likelihood of additional lymph node metastasis in sentinel lymph node positive breast cancer: validation of the Memorial Sloan-Kettering Cancer Centre (MSKCC) nomogram[J]. J Clin Pathol, 2014, 67: 112-119. doi:  10.1136/jclinpath-2013-201524
    [17] Rouzier R, Uzan C, Rousseau A, et al. Multicenter prospective evaluation of the reliability of the combined use of two models to predict non-sentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: the MSKCC nomogram and the Tenon score. Results of the NOTEGS study[J]. Br J Cancer, 2017, 116: 1135-1140. doi:  10.1038/bjc.2017.47
    [18] Barranger E, Coutant C, Flahault A, et al. An axilla scoring system to predict non-sentinel lymph node status in breast cancer patients with sentinel lymph node involvement[J]. Breast Cancer Res Treat, 2005, 91: 113-119. doi:  10.1007/s10549-004-5781-z
    [19] Coutant C, Rouzier R, Fondrinier E, et al. Validation of the Tenon breast cancer score for predicting non-sentinel lymph node status in breast cancer patients with sentinel lymph node metastasis: a prospective multicenter study[J]. Breast Cancer Res Treat, 2009, 113: 537-543. doi:  10.1007/s10549-008-9967-7
    [20] Han L, Zhu Y, Liu Z, et al. Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer[J]. Eur Radiol, 2019, 29: 3820-3829. doi:  10.1007/s00330-018-5981-2
    [21] van Griethuysen JJM, Fedorov A, Parmar C, et al. Computational Radiomics System to Decode the Radiographic Phenotype[J]. Cancer Res, 2017, 77: e104-e107. doi:  10.1158/0008-5472.CAN-17-0339
    [22] Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data[J]. Radiology, 2016, 278: 563-577. doi:  10.1148/radiol.2015151169
    [23] Fung AD, Collins JA, Campassi C, et al. Performance characteristics of ultrasound-guided fine-needle aspiration of axillary lymph nodes for metastatic breast cancer employing rapid on-site evaluation of adequacy: analysis of 136 cases and review of the literature[J]. Cancer Cytopathol, 2014, 122: 282-291. doi:  10.1002/cncy.21384
    [24] Lee SE, Sim Y, Kim S, et al. Predictive performance of ultrasonography-based radiomics for axillary lymph node metastasis in the preoperative evaluation of breast cancer[J]. Ultrasonography, 2021, 40: 93-102. doi:  10.14366/usg.20026
    [25] Gao Y, Luo Y, Zhao C, et al. Nomogram based on radiomics analysis of primary breast cancer ultrasound images: prediction of axillary lymph node tumor burden in patients[J]. Eur Radiol, 2021, 31: 928-937. doi:  10.1007/s00330-020-07181-1
    [26] Yu FH, Wang JX, Ye XH, et al. Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer[J]. Eur J Radiol, 2019, 119: 108658. doi:  10.1016/j.ejrad.2019.108658
    [27] Qiu X, Jiang Y, Zhao Q, et al. Could Ultrasound-Based Radiomics Noninvasively Predict Axillary Lymph Node Metastasis in Breast Cancer?[J]. J Ultrasound Med, 2020, 39: 1897-1905. doi:  10.1002/jum.15294
    [28] Tibshirani R. Regression Shrinkage and Selection Via the Lasso[J]. J R Stat Soc Series B Stat Methodol, 1996, 58: 267-288. http://www.stat.ohio-state.edu/~yklee/882/yongganglasso.pdf
    [29] Koelliker SL, Chung MA, Mainiero MB, et al. Axillary lymph nodes: US-guided fine-needle aspiration for initial staging of breast cancer--correlation with primary tumor size[J]. Radiology, 2008, 246: 81-89. doi:  10.1148/radiol.2463061463
    [30] Bevers TB, Helvie M, Bonaccio E, et al. Breast Cancer Screening and Diagnosis, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology[J]. J Natl Compr Canc Netw, 2018, 16: 1362-1389. doi:  10.6004/jnccn.2018.0083
    [31] Zhou LQ, Wu XL, Huang SY, et al. Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning[J]. Radiology, 2020, 294: 19-28. doi:  10.1148/radiol.2019190372
    [32] Sun Q, Lin X, Zhao Y, et al. Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region[J]. Front Oncol, 2020, 10: 53. doi:  10.3389/fonc.2020.00053
    [33] Cheon H, Kim HJ, Kim TH, et al. Invasive Breast Cancer: Prognostic Value of Peritumoral Edema Identified at Preoperative MR Imaging[J]. Radiology, 2018, 287: 68-75. doi:  10.1148/radiol.2017171157
    [34] Zhou J, Zhan W, Dong Y, et al. Stiffness of the surround-ing tissue of breast lesions evaluated by ultrasound elastography[J]. Eur Radiol, 2014, 24: 1659-1667. doi:  10.1007/s00330-014-3152-7
    [35] Zheng X, Yao Z, Huang Y, et al. Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer[J]. Nat Commun, 2020, 11: 1236. doi:  10.1038/s41467-020-15027-z
    [36] Guo X, Liu Z, Sun C, et al. Deep learning radiomics of ultrasonography: Identifying the risk of axillary non-sentinel lymph node involvement in primary breast cancer[J]. EBioMedicine, 2020, 60: 103018. doi:  10.1016/j.ebiom.2020.103018
    [37] 索静峰, 张麒, 常婉英, 等. 依托弹性与B型双模态超声影像组学的腋窝淋巴结转移评价[J]. 中国医疗器械杂志, 2017, 41: 313-316. doi:  10.3969/j.issn.1671-7104.2017.05.001

    Suo JF, Zhang L, Chang WY, et al. Evaluation of Axillary Lymph Node Metastasis by Using Radiomics of Dual-modal Ultrasound Composed of Elastography and B-mode[J]. Zhongguo Yiliao Qixie Zazhi, 2017, 41: 313-316. doi:  10.3969/j.issn.1671-7104.2017.05.001
    [38] Turner RR, Chu KU, Qi K, et al. Pathologic features associated with nonsentinel lymph node metastases in patients with metastatic breast carcinoma in a sentinel lymph node[J]. Cancer, 2000, 89: 574-581. doi:  10.1002/1097-0142(20000801)89:3<574::AID-CNCR12>3.0.CO;2-Y
    [39] Li Q, Bai H, Chen Y, et al. A Fully-Automatic Multiparametric Radiomics Model: Towards Reproducible and Prognostic Imaging Signature for Prediction of Overall Survival in Glioblastoma Multiforme[J]. Sci Rep, 2017, 7: 14331. doi:  10.1038/s41598-017-14753-7
    [40] Ford RA, Price Ⅱ WN. Privacy and Accountability in Black-Box Medicine[EB/OL]. (2016-07-14)[2021-02-08]. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2758121.
  • 加载中
计量
  • 文章访问数:  716
  • HTML全文浏览量:  181
  • PDF下载量:  84
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-02-08
  • 录用日期:  2021-03-05
  • 网络出版日期:  2021-10-25
  • 刊出日期:  2021-11-30

目录

    /

    返回文章
    返回

    【温馨提醒】近日,《协和医学杂志》编辑部接到作者反映,有多名不法人员冒充期刊编辑发送见刊通知,鼓动作者添加微信,从而骗取版面费的行为。特提醒您,本刊与作者联系的方式均为邮件通知或电话,稿件进度通知邮箱为:mjpumch@126.com,编辑部电话为:010-69154261,请提高警惕,谨防上当受骗!如有任何疑问,请致电编辑部核实。谢谢!