| 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
|
| [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. |
Supported by:
Beijing Renhe Information Technology Co. Ltd
Submit
Review
Office
Email Alert
RSS
DownLoad: