Li Hui, Weiss William A, Medved Milica, Abe Hiroyuki, Newstead Gillian M, Karczmar Gregory S, Giger Maryellen L
University of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
J Med Imaging (Bellingham). 2016 Oct;3(4):044507. doi: 10.1117/1.JMI.3.4.044507. Epub 2016 Dec 28.
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.
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。