[1]徐辉雄.精准医学时代甲状腺结节危险分层的“超声-细胞-基因”组学[J].介入放射学杂志,2020,29(10):963-967.
　XU Huixiong..“Ultrasound-cell-gene” omics for the risk stratification of thyroid nodules in the era of precision medicine[J].journal interventional radiology,2020,29(10):963-967.
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精准医学时代甲状腺结节危险分层的“超声-细胞-基因”组学()

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《介入放射学杂志》[ISSN:1008-794X/CN:31-1796/R]

卷:
29
期数:
2020年10
页码:
963-967
栏目:
专 论
出版日期:
2020-10-25

文章信息/Info

Title:
“Ultrasound-cell-gene” omics for the risk stratification of thyroid nodules in the era of precision medicine
作者:
徐辉雄
Author(s):
XU Huixiong.
Department of Medical Ultrasound， Affiliated Shanghai Tenth People’s Hospital， School of Medicine， Tongji University； Shanghai Research Center of Thyroid Diseases； Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment； National Clinical Researth Center of Interventional Medicine， Shanghai 510080， China
关键词:
【关键词】 甲状腺结节;  危险分层;  组学;  超声;  细胞学检查;  基因检测
文献标志码:
A
摘要:
【摘要】 甲状腺结节是危害人群健康的常见疾病，过度诊疗和诊疗不足的风险同时存在。如何有效地筛检出甲状腺癌患者，并对甲状腺癌的侵袭性进行精确分层，是当前亟待解决的关键临床和科学问题。“超声-细胞-基因”组学概念提出，有针对性地解决了当前超声灵敏度高而特异度低、细胞学检查存在大量无法诊断或不确定诊断结果、术前基因检测靶点单一且无法区分滤泡性肿瘤等难题。可以预期，“超声-细胞-基因”组学体系的建立和不断完善，将逐步使甲状腺结节危险分层方法实现早期、精确、直观、量化、易行的目标，同时也将为各种新型诊疗方案的选择提供重要依据。

参考文献/References:

［1］ Siegel RL， Miller KD， Jemal A. Cancer statistics， 2020［J］. CA Cancer J Clin，2020， 70：7- 30.
［2］ Durante C， Grani G， Lamartina L， et al. The diagnosis and management of thyroid nodules： areview［J］. JAMA， 2018， 319：914- 924.
［3］ Alexander EK， Kennedy GC， Baloch ZW， et al. Preoperative diagnosis of benign thyroid nodules with indeterminate cytology［J］. N Engl J Med， 2012， 367：705- 715
［4］ Haugen BR， Alexander EK， Bible KC， et al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer： the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer［J］. Thyroid， 2016， 26：1- 133.
［5］ Xing M， Haugen BR， Schlumberger M. Progress in molecular- based management of differentiated thyroid cancer［J］. Lancet，2013， 381：1058- 1069.
［6］ Brito JP， Gionfriddo MR， Al Nofal A， et al. The accuracy of thyroid nodule ultrasound to predict thyroid cancer： systematic review and meta- analysis［J］. J Clin Endocrinol Metab， 2014，99：1253- 1263.
［7］ Gharib H， Papini E， Garber JR， et al. American Association of Clinical Endocrinologists， American College of Endocrinology， and Associazione Medici Endocrinologi medical guidelines for clinical practice for the diagnosis and management of thyroid nodules： 2016 update［J］. Endocr Pract， 2016， 22：622- 639.
［8］ Tessler FN， Middleton WD， Grant EG， et al. ACR thyroid imaging， reporting and data system（TI- RADS）： white paper of the ACR TI- RADS Committee［J］. J Am Coll Radiol， 2017， 14：587- 595.
［9］ Zhao CK， Zheng JY， Sun LP， et al. BRAFV600E mutation analysis in fine- needle aspiration cytology specimens for diagnosis of thyroid nodules： the influence of false- positive and false- negative results［J］. Cancer Med， 2019， 8：5577- 5589.
［10］ Chen J， Li XL， Zhao CK， et al. Conventional ultrasound， immu-nohistochemical factors and BRAFV600E mutation in predicting central cervical lymph node metastasis of papillary thyroid carcinoma［J］. Ultrasound Med Biol， 2018， 44：2296- 2306.
［11］ Chen J， Li XL， Zhang YF， et al. Ultrasound validation of predictive model for central cervical lymph node metastasis in papillary thyroid cancer on BRAF［J］. Future Oncol， 2020， 16：1607- 1618
［12］ 贺亚萍， 徐辉雄. 超声引导细针穿刺抽吸活组织检查联合分子标志物诊断甲状腺肿瘤的进展［J］. 中华医学超声杂志（电子版）， 2015， 12： 753- 756
［13］ Shi H， Guo LH， Zhang YF， et al. Suspicious ultrasound and clinicopathological features of papillary thyroid carcinoma predict the status of TERT promoter［J］. Endocrine， 2020， 68：349- 357. ［14］ Akkus Z，Cai J， BoonrodA， et al. A survey of deep- learning applications in ultrasound： artificial intelligence–powered ultrasound for improving clinical workflow［J］. J Am Coll Radiol，2019， 16（9 Pt B）：1318- 1328.
［15］ 郭 翌， 周世崇， 余锦华， 等. 影像组学的前沿研究与未来挑战［J］. 肿瘤影像学， 2017， 26：81- 83.
［16］ Ma J， Wu F， Zhu J， et al. A pre- trained convolutional neural network based method for thyroid nodule diagnosis［J］. Ultrasonics， 2017， 73：221- 230.
［17］ Li H， Weng J， Shi Y， et al. An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images［J］. Sci Rep， 2018， 8：6600.
［18］ Wang Y， Yue W， Li X， et al. Comparison study of radiomics and deep learning- based methods for thyroid nodules classifi- cation using ultrasound images［J］. IEEE Access， 2020， 8： 52010- 52017.
［19］ Zhao CK， Ren TT， Yin YF， et al. A comparative analysis of two machine learning- based diagnostic patterns with ACR TI- RADS for thyroid nodules： diagnostic performance and unnecessary biopsy rate［J］. Thyroid， 2020， ［online ahead of print］.
［20］ Sultan R， Levy S， Sulanc E， et al. Utility of Afirma gene expression classifier for evaluation of indeterminate thyroid nodules and correlation with ultrasound risk assessment： single institutional experience［J］. Endocr Pract， 2020， 26：543- 551.
［21］ Wei S， Veloski C， Sharda P， et al. Performance of the Afirma genomic sequencing classifier versus gene expression classifier： an institutional experience［J］. Cancer Cytopathol， 2019， 127：720- 724.
［22］ Jug R， Foo WC， Jones C， et al. High- risk and intermediate- high- risk results from the ThyroSeq v2 and v3 thyroid genomic classifier are associated with neoplasia： independent performance assessment at an academic institution［J］. Cancer Cytopathol，2020， 128：563- 569.
［23］ Xu JM， Xu XH， Xu HX， et al. Conventional US， US elasticity imaging， and acoustic radiation force impulse imaging in the prediction of malignancy in thyroid nodules［J］. Radiology， 2014， 272：577- 586.
［24］ Yue W， Qi L， Wang DD， et al. US- guided microwave ablation of low- risk papillary thyroid microcarcinoma： long- term results of a prospective study［J］. J Clin Endocrinol Metab， 2020， 105：1791-1800.
［25］ Yue WW， Wang SR， Lu F， et al. Radiofrequency ablation vs. microwave ablation for patients with benign thyroid nodules： a propensity score matching study［J］. Endocrine， 2017， 55：485- 495.
［26］ Ma J， Wu F， Jiang T， et al. Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images［J］. Med Phys， 2017， 44：1678- 1691.
［27］ Li X， Zhang S， Zhang Q， et al. Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images： a retrospective， multicohort， diagnostic study［J］. Lancet Oncol， 2019， 20：193- 201.

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备注/Memo

备注/Memo:
（收稿日期：2020- 08- 12）
（本文编辑：边 佶）
更新日期/Last Update: 2020-10-19