论著摘要 |【MR】由MammaPrint,Oncotype DX和PAM50基因测定的研究版本给出的用于预测乳腺癌复发风险的MR成像影像学特征研究(双语版)

2017-12-21 15:00:37 admin 1

MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays

发表日期: 2016.05.05   来源:Radiology. 2016 Nov;281(2):382-391.

作者:

Hui Li1 , Yitan Zhu1, Elizabeth S. Burnside1, Karen Drukker1, Katherine A. Hoadley1, Cheng Fan1 , Suzanne D. Conzen1, Gary J. Whitman1, MD, Elizabeth J. Sutton1, Jose M. Net1, Marie Ganott1 , Erich Huang1, Elizabeth A. Morris1, Charles M. Perou1, Yuan Ji1, Maryellen L. Giger1.

作者介绍:

1. From the Depts of Radiology (H.L., K.D., M.L.G.) and Public Health Sciences (Y.J.), The Univ of Chicago, 5841 S Maryland Ave , MC 2026, Chicago, IL 60637; Program of Computational Genomics & Medicine, NorthShore Univ HealthSystem, Evanston, Ill (Y.Z., Y.J.); Dept of Radiology, Univ of Wisconsin-Madison , Madison, Wis (E.S.B.); Lineberger Comprehensive Cancer Ctr, Univ of North Carolina, Chapel Hill, NC (K.A.H., C.F., C.M.P.); Dept of Medicine, Section of Hematology & Oncology , The Univ of Chicago, Chicago, Ill (S.D.C.); Dept of Diagnostic Radiology, The Univ of Texas MD Anderson Cancer Ctr, Houston, Tex (G.J.W.); Dept of Radiology, Memorial Sloan-Kettering Cancer Ctr , New York, NY (E.J.S., E.A.M.); Dept of Radiology, Univ of Miami Sylvester Comprehensive Cancer Ctr, Miami, Fla (J.M.N.); Dept of Radiology , Univ of Pittsburgh Medical Ctr, Pittsburgh, Pa (M.G.); and Div of Cancer Treatment and Diagnosis, National Cancer Inst, Biometric Research Branch, Bethesda, Md (E.H.).

摘要

Abstact

目的

研究计算机提取的乳腺磁共振(MR)成像表型与MammaPrint,Oncotype DX和PAM50的多基因测定之间的关系,以评价影像学在评估乳腺癌复发风险中的作用。

Purpose

To investigate relationships between computer-extracted breast magnetic resonance (MR) imaging phenotypes with multigene assays of MammaPrint, Oncotype DX, and PAM50 to assess the role of radiomics in evaluating the risk of breast cancer recurrence.

材料和方法

分析来自国家癌症研究所癌症成像存档的84个身份,多机构乳腺MR检查的机构审查委员会批准的回顾性数据集,以及来自癌症基因组图谱的临床,组织病理学和基因组数据。 经活检证实浸润性乳腺癌的数据集包括74例(88%)导管,8例(10%)小叶和2例(2%)混合型癌。 其中,73例(87%)为雌激素受体阳性,67例(80%)为孕酮受体阳性,19例(23%)为人表皮生长因子受体2阳性。 对于每种情况,MR图像的计算机化放射学检查产生了计算机提取的大小,形状,边缘形态,增强纹理和动力学评估的肿瘤表型。 进行回归和受体操作特征分析,以评估相对于多基因测定分类的MR放射性特征的预测能力。

Material and Methods

Analysis was conducted on an institutional review board–approved retrospective data set of 84 deidentified, multi-institutional breast MR examinations from the National Cancer Institute Cancer Imaging Archive, along with clinical, histopathologic, and genomic data from The Cancer Genome Atlas. The data set of biopsy-proven invasive breast cancers included 74 (88%) ductal, eight (10%) lobular, and two (2%) mixed cancers. Of these, 73 (87%) were estrogen receptor positive, 67 (80%) were progesterone receptor positive, and 19 (23%) were human epidermal growth factor receptor 2 positive. For each case, computerized radiomics of the MR images yielded computer-extracted tumor phenotypes of size, shape, margin morphology, enhancement texture, and kinetic assessment. Regression and receiver operating characteristic analysis were conducted to assess the predictive ability of the MR radiomics features relative to the multigene assay classifications.

结果

多元线性回归分析显示影像学特征与多基因测定复发评分之间的显着关联(R2 = 0.25-0.32,r = 0.5-0.56,P<0.0001)。 重要的辐射特征包括肿瘤大小和增强纹理,这表明肿瘤异质性。使用影像组学在区分好预后和差预后的任务中,对于MammaPrint,Oncotype DX,PAM50基于亚型的复发风险的面积,以及基于亚型和增殖的PAM50复发风险,接收机工作特性曲线值为0.88(标准误差,0.05),0.76(标准误差,0.06),0.68(标准误差,0.08)和0.55(标准误差,0.09),后者显示与机会的统计差异。

Results

Multiple linear regression analyses demonstrated significant associations (R2 = 0.25–0.32, r = 0.5–0.56, P < .0001) between radiomics signatures and multigene assay recurrence scores. Important radiomics features included tumor size and enhancement texture, which indicated tumor heterogeneity. Use of radiomics in the task of distinguishing between good and poor prognosis yielded area under the receiver operating characteristic curve values of 0.88 (standard error, 0.05), 0.76 (standard error, 0.06), 0.68 (standard error, 0.08), and 0.55 (standard error, 0.09) for MammaPrint, Oncotype DX, PAM50 risk of relapse based on subtype, and PAM50 risk of relapse based on subtype and proliferation, respectively, with all but the latter showing statistical difference from chance.

结论

定量乳腺MR成像影像学显示了在评估乳腺癌复发风险中基于图像的表型具有很大的前景。

Conclusions

Quantitative breast MR imaging radiomics shows promise for image-based phenotyping in assessing the risk of breast cancer recurrence.

阅读原文:PMID: 27144536   PMID: PMC5069147DOI: 10.1016/j.radonc.2017.04.016


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