Suppr超能文献

桥本甲状腺炎合并甲状腺乳头状癌的术前超声特征对中央区淋巴结转移的预测。

Sonographic Characteristics of Papillary Thyroid Carcinoma With Coexistent Hashimoto's Thyroiditis in the Preoperative Prediction of Central Lymph Node Metastasis.

机构信息

Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China.

Research Center of Ultrasonography, The Second Xiangya Hospital, Central South University, Changsha, China.

出版信息

Front Endocrinol (Lausanne). 2021 Mar 15;12:556851. doi: 10.3389/fendo.2021.556851. eCollection 2021.

Abstract

The purpose of this study was to evaluate the usefulness of the sonographic characteristics of papillary thyroid carcinoma (PTC) with Hashimoto's thyroiditis (HT) for predicting central lymph node metastasis (CLNM). One hundred thirty-three patients who underwent thyroidectomy and central cervical lymph node dissection for PTC with coexistent HT were retrospectively analyzed. All PTCs with HT were preoperatively evaluated by ultrasound (US) regarding their nodular number, size, component, shape, margin, echogenicity, calcification, capsule contact with protrusion, vascularity and contrast enhanced ultrasound (CEUS) parameters. Univariate analysis demonstrated that patients with PTCs with HT and CLNM more frequently had age ≤ 45 years, size > 10 mm, a wider than tall shape, microcalcification, hypo-enhancement and peak intensity index < 1 than those without CLNM (all <0.05). Binary logistic regression analysis demonstrated that size > 10 mm and CEUS hypo-enhancement were independent characteristics for the presence of CLNM. Our study indicated that preoperative US characteristics could offer help in predicting CLNM in PTCs with coexistent HT.

摘要

本研究旨在评估桥本甲状腺炎(HT)合并甲状腺乳头状癌(PTC)的超声特征在预测中央淋巴结转移(CLNM)中的作用。回顾性分析了 133 例因 PTC 合并 HT 而行甲状腺切除术和中央颈部淋巴结清扫术的患者。所有合并 HT 的 PTC 均在术前通过超声(US)评估结节数量、大小、成分、形状、边缘、回声、钙化、与突出物的包膜接触、血管生成和对比增强超声(CEUS)参数。单因素分析表明,有 CLNM 的 HT 合并 PTC 患者的年龄≤45 岁、大小>10mm、宽高比>1、微钙化、低增强和峰值强度指数<1 的比例高于无 CLNM 者(均<0.05)。二元逻辑回归分析表明,大小>10mm 和 CEUS 低增强是 CLNM 存在的独立特征。本研究表明,术前 US 特征有助于预测合并 HT 的 PTC 中的 CLNM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b4/8008373/41a414786eda/fendo-12-556851-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验