Suppr超能文献

乳腺癌脑转移的表观扩散系数直方图可预测其生物学亚型和进展。

Apparent diffusion coefficient histogram in breast cancer brain metastases may predict their biological subtype and progression.

机构信息

Department of Radiology, Gangnam Severance Hospital, Yonsei University, College of Medicine, Seoul, Korea.

Department of Biomedical Engineering, Hanyang University, Seoul, Korea.

出版信息

Sci Rep. 2018 Jul 2;8(1):9947. doi: 10.1038/s41598-018-28315-y.

Abstract

Our aims for this study were to investigate the relationship between diffusion weighted image (DWI) parameters of brain metastases (BMs) and biological markers of breast cancer, and moreover, to assess whether DWI parameters accurately predict patient outcomes. DWI data for 34 patients with BMs from breast cancer were retrospectively reviewed. Apparent diffusion coefficient (ADC) histogram parameters were calculated from all measurable BMs. Two region of interest (ROI) methods are used for the analysis: from the largest BM or from all measurable BMs per one patient. ADC histogram parameters were compared between positive and negative groups depending on ER/PR and HER2 statuses. Overall survival analysis after BM (OSBM) and BM-specific progression-free survival (BMPFS) was analyzed with ADC parameters. Regardless of ROI methods, 25th percentile of ADC histogram was significantly lower in the ER/PR-positive group than in the ER/PR-negative group (P < 0.05). Using ROIs from all measurable BMs, Peak location, 50th percentile, 75th percentile, and mean value of ADC histogram were also significantly lower in the ER/PR-positive group than in the ER/PR-negative group (P < 0.05). However, there was no significant difference between HER2-postive and negative group. On univariate analysis, using ROIs from all measurable BMs, lower 25th percentile, 50th percentile and mean of ADC were significant predictors for poor BMPFS. ADC histogram analysis may have a prognostic value over ER/PR status as well as BMPFS.

摘要

我们本研究的目的是探讨脑转移瘤(BMs)的弥散加权图像(DWI)参数与乳腺癌生物学标志物之间的关系,并且评估 DWI 参数是否能准确预测患者预后。回顾性分析了 34 例来自乳腺癌的 BMs 的 DWI 数据。从所有可测量的 BMs 计算表观扩散系数(ADC)直方图参数。分析采用了两种感兴趣区(ROI)方法:从最大的 BM 或每个患者的所有可测量的 BM。根据 ER/PR 和 HER2 状态,将 ADC 直方图参数在阳性和阴性组之间进行比较。使用 ADC 参数对 BM 后总体生存分析(OSBM)和 BM 特异性无进展生存(BMPFS)进行分析。无论 ROI 方法如何,在 ER/PR 阳性组中,ADC 直方图的第 25 百分位都明显低于 ER/PR 阴性组(P<0.05)。使用所有可测量的 BMs 的 ROI,ADC 直方图的峰位置、第 50 百分位、第 75 百分位和平均值在 ER/PR 阳性组也明显低于 ER/PR 阴性组(P<0.05)。然而,在 HER2 阳性和阴性组之间没有显著差异。在单变量分析中,使用所有可测量的 BMs 的 ROI,ADC 的较低第 25 百分位、第 50 百分位和平均值是 BMPFS 不良的显著预测因素。ADC 直方图分析可能具有比 ER/PR 状态更重要的预后价值,以及 BMPFS。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af41/6028481/e78c27c6cd15/41598_2018_28315_Fig1_HTML.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