Suppr超能文献

计算机断层扫描成像中淋巴结形态作为乳腺癌患者腋窝淋巴结转移的预测指标

Lymph node shape in computed tomography imaging as a predictor for axillary lymph node metastasis in patients with breast cancer.

作者信息

Kutomi Goro, Ohmura Tousei, Satomi Fukino, Takamaru Tomoko, Shima Hiroaki, Suzuki Yasuyo, Otokozawa Seiko, Zembutsu Hitoshi, Mori Mitsuru, Hirata Koichi

机构信息

First Department of Surgery, School of Medicine, Sapporo Medical University, Sapporo, Hokkaido 060-8543, Japan.

Department of Public Health, School of Medicine, Sapporo Medical University, Sapporo, Hokkaido 060-8556, Japan.

出版信息

Exp Ther Med. 2014 Aug;8(2):681-685. doi: 10.3892/etm.2014.1787. Epub 2014 Jun 16.

Abstract

The aim of the present study was to evaluate whether preoperative computed tomography (CT) is a useful modality for the diagnosis of axillary lymph node metastasis. The axillary lymph node status was examined in patients with primary breast cancer who had undergone surgery. In total, 75 patients were analyzed with preoperative contrast CT images, following which the patients underwent an intraoperative sentinel lymph node biopsy to determine possible predictors of axillary lymph node metastasis. The lymph node shape was classified into three groups, which included fat-, clear-and obscure-types. Multivariate analysis revealed that clear-type lymph nodes in preoperative contrast CT imaging may be an independent predictor of lymph node metastasis (odds ratio, 15; P=0.003). Therefore, the results indicated that preoperative CT examination is useful to predict axillary lymph node metastasis.

摘要

本研究的目的是评估术前计算机断层扫描(CT)是否是诊断腋窝淋巴结转移的有用方法。对接受手术的原发性乳腺癌患者的腋窝淋巴结状态进行了检查。总共对75例患者的术前增强CT图像进行了分析,随后这些患者接受了术中前哨淋巴结活检,以确定腋窝淋巴结转移的可能预测因素。淋巴结形态分为三组,包括脂肪型、清晰型和模糊型。多因素分析显示,术前增强CT成像中的清晰型淋巴结可能是淋巴结转移的独立预测因素(比值比,15;P=0.003)。因此,结果表明术前CT检查有助于预测腋窝淋巴结转移。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a9/4079443/d50eed91670f/ETM-08-02-0681-g00.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验