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本文引用的文献

1
Breast density (BD) assessment with digital breast tomosynthesis (DBT): Agreement between Quantra™ and 5th edition BI-RADS.使用数字乳腺断层合成(DBT)评估乳腺密度(BD):Quantra™与第5版乳腺影像报告和数据系统(BI-RADS)之间的一致性
Breast. 2016 Dec;30:185-190. doi: 10.1016/j.breast.2016.10.003. Epub 2016 Oct 19.
2
Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.基于BI-RADS的乳腺纤维腺组织量磁共振成像主观视觉评估的观察者间及观察者内一致性:与自动定量评估的比较
Eur Radiol. 2016 Nov;26(11):3917-3922. doi: 10.1007/s00330-016-4274-x. Epub 2016 Apr 23.
3
Comparison of Dixon Sequences for Estimation of Percent Breast Fibroglandular Tissue.用于估计乳腺纤维腺体组织百分比的狄克逊序列比较
PLoS One. 2016 Mar 24;11(3):e0152152. doi: 10.1371/journal.pone.0152152. eCollection 2016.
4
Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.基于数字乳腺断层合成图像的乳腺体积密度全自动定量评估:初步结果及与数字乳腺X线摄影和磁共振成像的比较
Radiology. 2016 Apr;279(1):65-74. doi: 10.1148/radiol.2015150277. Epub 2015 Oct 21.
5
Preliminary assessment of dispersion versus absorption analysis of high spectral and spatial resolution magnetic resonance images in the diagnosis of breast cancer.高光谱和空间分辨率磁共振图像的色散与吸收分析在乳腺癌诊断中的初步评估
J Med Imaging (Bellingham). 2015 Apr;2(2):024502. doi: 10.1117/1.JMI.2.2.024502. Epub 2015 May 7.
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Comparative analysis of image-based phenotypes of mammographic density and parenchymal patterns in distinguishing between BRCA1/2 cases, unilateral cancer cases, and controls.基于乳腺X线密度和实质模式的影像学表型在区分BRCA1/2病例、单侧癌症病例和对照中的比较分析。
J Med Imaging (Bellingham). 2014 Oct;1(3):031009. doi: 10.1117/1.JMI.1.3.031009. Epub 2014 Nov 13.
7
B1 and T1 mapping of the breast with a reference tissue method.采用参考组织法对乳腺进行B1和T1映射。
Magn Reson Med. 2016 Apr;75(4):1565-73. doi: 10.1002/mrm.25751. Epub 2015 May 27.
8
Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?磁共振成像中背景实质强化、纤维腺体量的定性评估以及乳腺X线密度与乳腺癌风险相关吗?
Radiology. 2015 Aug;276(2):371-80. doi: 10.1148/radiol.2015142304. Epub 2015 May 12.
9
Breast segmentation and density estimation in breast MRI: a fully automatic framework.乳腺MRI中的乳腺分割与密度估计:一个全自动框架。
IEEE J Biomed Health Inform. 2015 Jan;19(1):349-57. doi: 10.1109/JBHI.2014.2311163.
10
Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study.计算机提取的乳腺X线纹理模式特征与BRCA1/2突变状态之间的关系:一项横断面研究。
Breast Cancer Res. 2014;16(4):424. doi: 10.1186/s13058-014-0424-8. Epub 2014 Aug 23.

基于高光谱和空间分辨率磁共振成像的乳腺密度估计

Breast density estimation from high spectral and spatial resolution MRI.

作者信息

Li Hui, Weiss William A, Medved Milica, Abe Hiroyuki, Newstead Gillian M, Karczmar Gregory S, Giger Maryellen L

机构信息

University of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.

出版信息

J Med Imaging (Bellingham). 2016 Oct;3(4):044507. doi: 10.1117/1.JMI.3.4.044507. Epub 2016 Dec 28.

DOI:10.1117/1.JMI.3.4.044507
PMID:28042590
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5193119/
Abstract

A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists' breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 ([Formula: see text]) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 ([Formula: see text]) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 ([Formula: see text]) was observed between HiSS-based breast density estimations and radiologists' BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy.

摘要

本文提出了一种用于高光谱和空间分辨率(HiSS)磁共振成像的三维乳腺密度估计方法。招募了22名患者(根据机构审查委员会批准的符合《健康保险流通与责任法案》的方案)进行高危乳腺癌筛查。每位患者均接受了标准护理临床数字X线乳房造影、磁共振扫描以及HiSS扫描。乳腺密度估计算法包括乳腺掩膜生成、乳腺皮肤去除以及乳腺百分比密度计算。使用相关性分析和一致性界限确定基于HiSS的密度估计的用户间和用户内变异性。还对基于HiSS的密度估计与放射科医生的乳腺影像报告和数据系统(BI-RADS)密度评级之间进行了相关性分析。左右乳腺密度估计之间的相关系数为0.91([公式:见原文])。组内相关系数为0.99([公式:见原文]),表明基于HiSS的乳腺密度估计的用户间变异性具有高可靠性。基于HiSS的乳腺密度估计与放射科医生的BI-RADS之间观察到中等相关系数0.55([公式:见原文])。总之,开发了一种使用来自乳腺MRI的HiSS光谱数据的客观密度估计方法。这项初步研究显示出的高再现性以及低用户间和低用户内变异性表明,这种基于HiSS的密度指标在诸如乳腺癌风险评估和治疗效果监测等需要乳腺密度的项目中可能具有潜在益处。