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术前 MRI 乳腺癌瘤周水肿:一项具有组织病理学复查的解读性研究,旨在了解肿瘤微环境。

Peritumoral edema in breast cancer at preoperative MRI: an interpretative study with histopathological review toward understanding tumor microenvironment.

机构信息

Department of Pathology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, South Korea.

Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, South Korea.

出版信息

Sci Rep. 2021 Jun 21;11(1):12992. doi: 10.1038/s41598-021-92283-z.

DOI:10.1038/s41598-021-92283-z
PMID:34155253
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8217499/
Abstract

Peritumoral edema (PE) of breast cancer at T2-weighted MR images is considered a poor prognostic sign and may represent the microenvironment surrounding the tumor; however, its histopathological mechanism remains unclear. The purpose of the study was to identify and describe detailed histopathological characteristics associated with PE at preoperative breast MRI in breast cancer patients. This retrospective study included breast cancer patients who had undergone preoperative MRI and surgery between January 2011 and December 2012. Two radiologists determined the presence of PE in consensus based on the signal intensity surrounding the tumor at T2-weighted images. The following detailed histopathological characteristics were reviewed by two breast pathologists using four-tiered grades; lymphovascular invasion, vessel ectasia, stromal fibrosis, growth pattern, and tumor budding. Tumor necrosis and tumor infiltrating lymphocytes were assessed using a percent scale. Baseline clinicopathological characteristics, including age and histologic grade, were collected. The associations between detailed histopathologic characteristics and PE were examined using multivariable logistic regression with odds ratio (OR) calculation. A total of 136 women (median age, 49 ± 9 years) were assessed; among them 34 (25.0%) had PE. After adjustment of baseline clinicopathological characteristics that were significantly associated with PE (age, T stage, N stage, histologic grade, and subtype, all Ps < 0.05), lymphovascular invasion (P = 0.009), vessel ectasia (P = 0.021), stromal fibrosis (P = 0.024), growth pattern (P = 0.036), and tumor necrosis (P < 0.001) were also associated with PE. In comparison with patients without PE, patients with PE were more likely to have a higher degree of lymphovascular invasion (OR, 2.9), vessel ectasia (OR, 3.3), stromal fibrosis (OR, 2.5), lesser degree of infiltrative growth pattern (OR, 0.4), and higher portion of tumor necrosis (OR, 1.4). PE of breast cancer at MRI is associated with detailed histopathological characteristics of lymphovascular invasion, vessel ectasia, stromal fibrosis, growth pattern, and tumor necrosis, suggesting a relevance for tumor microenvironment.

摘要

乳腺癌 T2 加权磁共振成像中的瘤周水肿(PE)被认为是预后不良的标志,可能代表肿瘤周围的微环境;然而,其组织病理学机制尚不清楚。本研究的目的是在术前乳腺 MRI 中识别和描述与乳腺癌患者 PE 相关的详细组织病理学特征。这项回顾性研究纳入了 2011 年 1 月至 2012 年 12 月期间接受术前 MRI 和手术的乳腺癌患者。两位放射科医生根据 T2 加权图像上肿瘤周围的信号强度,一致确定 PE 的存在。两位乳腺病理学家使用四级评分系统评估以下详细的组织病理学特征:淋巴管血管侵犯、血管扩张、间质纤维化、生长模式和肿瘤芽生。使用百分比评估肿瘤坏死和肿瘤浸润淋巴细胞。收集基线临床病理特征,包括年龄和组织学分级。使用多变量逻辑回归和比值比(OR)计算来检查详细组织病理学特征与 PE 之间的关系。共评估了 136 名女性(中位年龄 49±9 岁);其中 34 名(25.0%)有 PE。在调整与 PE 显著相关的基线临床病理特征(年龄、T 分期、N 分期、组织学分级和亚型,均 P<0.05)后,淋巴管血管侵犯(P=0.009)、血管扩张(P=0.021)、间质纤维化(P=0.024)、生长模式(P=0.036)和肿瘤坏死(P<0.001)也与 PE 相关。与无 PE 的患者相比,有 PE 的患者更有可能具有更高程度的淋巴管血管侵犯(OR,2.9)、血管扩张(OR,3.3)、间质纤维化(OR,2.5)、浸润性生长模式程度较低(OR,0.4)和更高比例的肿瘤坏死(OR,1.4)。MRI 显示乳腺癌的 PE 与淋巴管血管侵犯、血管扩张、间质纤维化、生长模式和肿瘤坏死等详细组织病理学特征相关,提示与肿瘤微环境有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc12/8217499/96120f48b668/41598_2021_92283_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc12/8217499/0075ded38714/41598_2021_92283_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc12/8217499/96120f48b668/41598_2021_92283_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc12/8217499/0075ded38714/41598_2021_92283_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc12/8217499/96120f48b668/41598_2021_92283_Fig2_HTML.jpg

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