超声新技术在预测乳腺癌分子标志物中的应用进展

摘要/Abstract

中图分类号:

R737.9

罗婷, 周建桥. 超声新技术在预测乳腺癌分子标志物中的应用进展[J]. 诊断学理论与实践, 2020, 19(03): 325-328.

参考文献39

[1]	Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020[J]. CA Cancer J Clin, 2020, 70(1):7-30. doi:10.3322/caac.21590 URL
[2]	Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68(6):394-424. doi:10.3322/caac.21492 URL
[3]	Prat A, Pineda E, Adamo B, et al. Clinical implications of the intrinsic molecular subtypes of breast cancer[J]. Breast, 2015, 24( Suppl 2):S26-S35.
[4]	Tremont A, Lu J, Cole JT. Endocrine therapy for early breast cancer: Updated review[J]. Ochsner J, 2017, 17(4):405-411.
[5]	Ma CX, Bose R, Ellis MJ. Prognostic and predictive biomarkers of endocrine responsiveness for estrogen receptor positive breast cancer[J]. Adv Exp Med Biol, 2016, 882:125-154.
[6]	Asif HM, Sultana S, Ahmed S, et al. HER-2 positive breast cancer-a mini-review[J]. Asian Pac J Cancer Prev, 2016, 17(4):1609-1615. doi:10.7314/APJCP.2016.17.4.1609 URL
[7]	Moasser MM, Krop IE. The evolving landscape of HER2 targeting in breast cancer[J]. Jama Oncol, 2015, 1(8):1154-1161. doi:10.1001/jamaoncol.2015.2286pmid:26204261
[8]	Wang W, Wu J, Zhang P, et al. Prognostic and predictive value of Ki-67 in triple-negative breast cancer[J]. Oncotarget, 2016, 7(21):31079-31087. doi:10.18632/oncotarget.9075pmid:27145269
[9]	Mb A, Sb E, Fl G, et al. AJCC cancer staging manual[M]. 8th ed. New York: Springer, 2016:589-628.
[10]	中国抗癌协会乳腺癌专业委员会. 中国抗癌协会乳腺癌诊治指南与规范(2019年版)[J]. 中国癌症杂志, 2019, 29(8):609-679.
[11]	彭晓静, 李奥, 叶新华, 等. 应变式弹性成像与剪切波弹性成像技术鉴别诊断乳腺良恶性病灶的价值比较[J]. 中华医学超声杂志(电子版), 2016, 13(12):942-947. doi:10.3877/cma.j.issn.1672-6448.2016.12.013
[12]	You Y, Song Y, Li SX, et al. Quantitative and qualitative evaluation of breast cancer prognosis: A sonographic elastography study[J]. Med Sci Monit, 2019, 25:9272-9279. doi:10.12659/MSM.918806 URL
[13]	Hayashi M, Yamamoto Y, Sueta A, et al. Associations between elastography findings and clinicopathological factors in breast cancer[J]. Medicine (Baltimore), 2015, 94(50):e2290. doi:10.1097/MD.0000000000002290 URL
[14]	Chang JM, Park IA, Lee SH, et al. Stiffness of tumours measured by shear-wave elastography correlated with subtypes of breast cancer[J]. Eur Radiol, 2013, 23(9):2450-2458. doi:10.1007/s00330-013-2866-2pmid:23673574
[15]	Youk JH, Gweon HM, Son EJ, et al. Shear-wave elastography of invasive breast cancer: correlation between quantitative mean elasticity value and immunohistochemi-cal profile[J]. Breast Cancer Res Treat, 2013, 138(1):119-126. doi:10.1007/s10549-013-2407-3 URL
[16]	Brocklehurst D, Wilde CE, Finbow JA, et al. Relative importance of estrogen and progesterone receptor assays as prognostic indicators in primary breast cancer: a short-term study[J]. Clin Chem, 1989, 35(2):238-240. pmid:2914367
[17]	Au FWF, Ghai S, Lu FI, et al. Quantitative shear wave elastography: correlation with prognostic histologic features and immunohistochemical biomarkers of breast cancer[J]. Acad Radiol, 2015, 22(3):269-277. doi:10.1016/j.acra.2014.10.007 URL
[18]	Choi WJ, Kim HH, Cha JH, et al. Predicting prognostic factors of breast cancer using shear wave elastography[J]. Ultrasound Med Biol, 2014, 40(2):269-274. doi:10.1016/j.ultrasmedbio.2013.09.028 URL
[19]	Gonzalez-Sistal A, Baltasar-Sánchez A, Menéndez P, et al. Breastfeeding and immunohistochemical expression of ki-67, p53 and BCL2 in infiltrating lobular breast carcinoma[J]. PloS One, 2016, 11(3):e151093.
[20]	Raja R, Kale S, Thorat D, et al. Hypoxia-driven osteopontin contributes to breast tumor growth through modulation of HIF1α-mediated VEGF-dependent angiogenesis[J]. Oncogene, 2014, 33(16):2053-2064. doi:10.1038/onc.2013.171pmid:23728336
[21]	Cao Y, Guangqi E, Wang E, et al. VEGF exerts an angiogenesis-independent function in cancer cells to promote their malignant progression[J]. Cancer Res, 2012, 72(16):3912-3918.
[22]	Guo R, Lu G, Qin B, et al. Ultrasound imaging technologies for breast cancer detection and management: A review[J]. Ultrasound Med Biol, 2018, 44(1):37-70. doi:10.1016/j.ultrasmedbio.2017.09.012 URL
[23]	Vraka I, Panourgias E, Sifakis E, et al. Correlation between contrast-enhanced ultrasound characteristics (qua-litative and quantitative) and pathological prognostic factors in breast cancer[J]. In Vivo, 2018, 32(4):945-954. doi:10.21873/invivo.11333 URL
[24]	Cao XL, Bao W, Zhu SG, et al. Contrast-enhanced ultrasound characteristics of breast cancer: Correlation with prognostic factors[J]. Ultrasound Med Biol, 2014, 40(1):11-17. doi:10.1016/j.ultrasmedbio.2013.08.014 URL
[25]	Wan CF, Du J, Fang H, et al. Enhancement patterns and parameters of breast cancers at contrast-enhanced US: Correlation with prognostic factors[J]. Radiology, 2012, 262(2):450-459. doi:10.1148/radiol.11110789 URL
[26]	Putti TC, El-Rehim DM A, Rakha EA, et al. Estrogen receptor-negative breast carcinomas: a review of morphology and immunophenotypical analysis[J]. Mod Pathol, 2004, 18(1):26-35. doi:10.1038/modpathol.3800255 URL
[27]	Zhao LX, Liu H, Wei Q, et al. Contrast-enhanced ultrasonography features of breast malignancies with different sizes: Correlation with prognostic factors[J]. Biomed Res Int, 2015, 2015:613831.
[28]	Zhao YX, Liu S, Hu YB, et al. Diagnostic and prognostic values of contrast-enhanced ultrasound in breast cancer: a retrospective study[J]. Onco Targets Ther, 2017, 10:1123-1129. doi:10.2147/OTT.S124134 URL
[29]	Lichtenbeld HC, Barendsz-Janson AF, Essen HV, et al. Angiogenic potential of malignant and non-malignant human breast tissues in anin vivoangiogenesis model[J]. Int J Cancer, 1998, 77(3):455-459. pmid:9663610
[30]	Ji CL, Li X, He Y, et al. Quantitative parameters of contrast-enhanced ultrasound in breast invasive ductal carcinoma: The correlation with pathological prognostic factors[J]. Clin Hemorheol Microcirc, 2017, 66(4):333-345. doi:10.3233/CH-170251 URL
[31]	Szabó BK, Saracco A, Tánczos E, et al. Correlation of contrast-enhanced ultrasound kinetics with prognostic factors in invasive breast cancer[J]. Eur Radiol, 2013, 23(12):3228-3236. doi:10.1007/s00330-013-2960-5 URL
[32]	Nie M, Qin YC, Zhu JF, et al. Correlation between ultrasonic features and expression levels of C-erbB-2, VEGF and nm23 in breast cancer[J]. Oncol Lett, 2018, 16(2):1701-1707.
[33]	朱琳, 张丽华, 吴道明, 等. 超声光散射成像系统对各种病理类型乳腺病变的诊断价值[J]. 中国超声医学杂志, 2016, 32(10):883-886.
[34]	Mostafa A, Vavadi H, Uddin KMS, et al. Diffuse optical tomography using semiautomated coregistered ultrasound measurements[J]. J Biomed opt, 2017, 22(12):1-12. doi:10.1117/1.JBO.22.12.121610pmid:29260537
[35]	Kim MJ, Su MY, Yu HJ, et al. US-localized diffuse optical tomography in breast cancer: comparison with pharmacokinetic parameters of DCE-MRI and with pathologic biomarkers[J]. BMC Cancer, 2016, 16(1):50. doi:10.1186/s12885-016-2086-7 URL
[36]	Zhi WX, Wang Y, Chang C, et al. US-guided diffuse optical tomography: Clinicopathological features affect total hemoglobin concentration in breast cancer[J]. Trasl Oncol, 2018, 11(4):845-851.
[37]	Zhu Q, Hegde PU, Ricci A, et al. Early-stage invasive breast cancers: potential role of optical tomography with US localization in assisting diagnosis[J]. Radiology, 2010, 256(2):367-378. doi:10.1148/radiol.10091237 URL
[38]	Choi JS, Kim MJ, Youk JH, et al. US-Guided optical tomography: Correlation with clinicopathologic variables in breast cancer[J]. Ultrasound Med Biol, 2013, 39(2):233-240. doi:10.1016/j.ultrasmedbio.2012.09.014pmid:23219038
[39]	Brown JQ, Wilke LG, Geradts J, et al. Quantitative optical spectroscopy: A robust tool for direct measurement of breast cancer vascular oxygenation and total hemoglobin contentin vivo[J]. Cancer Res, 2009, 69(7):2919-2926 doi:10.1158/0008-5472.CAN-08-3370 URL

超声新技术在预测乳腺癌分子标志物中的应用进展

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献39

相关文章15

编辑推荐

Metrics

本文评价

[1]	刁雪红, 申艳, 陈林, 詹嘉, 方靓, 蔡剑飞, 陈悦.超声微血流成像技术在临床缓解期类风湿性关节炎诊断中的应用[J]. 诊断学理论与实践, 2022, 21(05): 575-580.
[2]	王之倩, 李敏, 于一飞, 周建桥.21-羟化酶缺陷先天性肾上腺皮质增生患者睾丸肾上腺残基瘤超声特征分析[J]. 诊断学理论与实践, 2022, 21(05): 588-591.
[3]	何亲羽, 王伟, 陈立芬, 张雪蕾, 董治亚.LHCGR基因突变致家族性男性性早熟2例报告及文献复习[J]. 诊断学理论与实践, 2022, 21(05): 598-605.
[4]	陈志敏, 何浩岚.艾滋病合并马尔尼菲篮状菌病的诊治现状[J]. 诊断学理论与实践, 2022, 21(04): 425-430.
[5]	沈银忠.《人类免疫缺陷病毒感染/艾滋病合并结核分枝杆菌感染诊治专家共识》解读[J]. 诊断学理论与实践, 2022, 21(04): 431-436.
[6]	顾炫, 柳俊.超声筛查鉴别胰腺实性假乳头状瘤与胰腺导管腺癌的研究分析[J]. 诊断学理论与实践, 2022, 21(04): 504-508.
[7]	王文涵, 夏蜀珺, 詹维伟.长链非编码RNA ENST00000489676在超声评估甲状腺乳头状癌颈部淋巴结转移中的应用[J]. 诊断学理论与实践, 2022, 21(04): 514-519.
[8]	陈宏, 沈银忠.人类免疫缺陷病毒感染/艾滋病合并结核病的诊治进展[J]. 诊断学理论与实践, 2022, 21(04): 530-534.
[9]	何新, 陈慧, 冯炜炜.机器学习算法在辅助超声诊断附件肿块良恶性中的应用研究进展[J]. 诊断学理论与实践, 2022, 21(04): 541-546.
[10]	徐子真, 李擎天, 刘湘帆, 李莉, 李惠, 王也飞, 吴洁敏, 陈宁, 梁璆荔, 陈松立, 戴健敏, 宋珍, 丁磊.实验诊断学在线课程的建立和实践[J]. 诊断学理论与实践, 2022, 21(04): 547-550.
[11]	杜燕然, 焦景, 任芸芸, 周建桥.超声影像组学技术在评估胎肺成熟度中的应用[J]. 诊断学理论与实践, 2022, 21(03): 326-330.
[12]	桂燕萍, 陈晔芬, 施仲伟, 许燕.超声心动图右室面积变化分数筛查左心室射血分数降低的心力衰竭患者心脏同步性研究[J]. 诊断学理论与实践, 2022, 21(03): 331-335.
[13]	徐琛莹, 李嫣然, 倪晓枫, 徐上妍, 林青.超声预测老年甲状腺乳头状癌患者颈部淋巴结转移的效能及相关超声征象分析[J]. 诊断学理论与实践, 2022, 21(03): 343-348.
[14]	赵然, 詹维伟, 侯怡卿.计算机辅助诊断系统辅助超声诊断甲状腺弥漫性病变合并结节良恶性的应用价值[J]. 诊断学理论与实践, 2022, 21(03): 390-394.
[15]	王晨琛, 方跃华, 施仲伟, 屈雪蒸.25例主动脉瓣成形术后一年的超声心动图评价[J]. 诊断学理论与实践, 2022, 21(03): 395-398.