Suppr超能文献

计算机辅助评估乳腺癌中 MRI 形态学与免疫组织化学标志物或分子亚型之间的相关性。

Computer-aided evaluation of the correlation between MRI morphology and immunohistochemical biomarkers or molecular subtypes in breast cancer.

机构信息

Department of Radiology, Cancer Hospital of Shantou University Medical College, Guangdong, China.

Department of Ultrasound, Cancer Hospital of Shantou University Medical College, Guangdong, China.

出版信息

Sci Rep. 2017 Oct 23;7(1):13818. doi: 10.1038/s41598-017-14274-3.

Abstract

Studies using tumor circularity (TC), a quantitative MRI morphologic index, to evaluate breast cancer are scarce. The purpose of this study is to evaluate the correlation between TC and immunohistochemical biomarkers or molecular subtypes in breast cancer. 146 patients with 150 breast cancers were selected. All tumors were confirmed by histopathology and examined by 3.0T MRI. TC was calculated by computer-aided software. The associations between TC and patient age, tumor size, histological grade, molecular subtypes, and immunohistochemical biomarkers including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 were analyzed. TC correlated inversely with tumor size (r = -0.224, P < 0.001), ER (r = -0.490, P < 0.001) and PR (r = -0.484, P < 0.001). However, TC correlated positively with Ki67 (r = 0.332, P < 0.001) and histological grade (r = 0.309, P < 0.001). In multiple linear regression analysis, tumor size, ER, PR and Ki67 were independent influential factors of TC. Compared with HER2-overexpressed (61.6%), luminal A (54.7%) and luminal B (52.3%) subtypes, triple-negative breast cancer (TNBC) showed the highest score of TC (70.8%, P < 0.001). Our study suggests that TC can be used as an imaging biomarker to predict the aggressiveness of newly diagnosed breast cancers. TNBC seems to present as an orbicular appearance when comparing with other subtypes.

摘要

使用肿瘤圆度(TC)评估乳腺癌的研究很少。本研究旨在评估 TC 与乳腺癌免疫组织化学标志物或分子亚型之间的相关性。选择了 146 例 150 例乳腺癌患者。所有肿瘤均经组织病理学证实,并经 3.0T MRI 检查。通过计算机辅助软件计算 TC。分析 TC 与患者年龄、肿瘤大小、组织学分级、分子亚型以及包括雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体 2(HER2)和 Ki67 在内的免疫组织化学标志物之间的关系。TC 与肿瘤大小呈负相关(r=-0.224,P<0.001)、ER(r=-0.490,P<0.001)和 PR(r=-0.484,P<0.001)。然而,TC 与 Ki67 呈正相关(r=0.332,P<0.001)和组织学分级(r=0.309,P<0.001)。在多元线性回归分析中,肿瘤大小、ER、PR 和 Ki67 是 TC 的独立影响因素。与 HER2 过表达(61.6%)、腔 A(54.7%)和腔 B(52.3%)亚型相比,三阴性乳腺癌(TNBC)的 TC 评分最高(70.8%,P<0.001)。我们的研究表明,TC 可用作预测新诊断乳腺癌侵袭性的影像学生物标志物。与其他亚型相比,TNBC 似乎呈圆形外观。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c598/5653801/3ab28c7157dc/41598_2017_14274_Fig1_HTML.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