Calibrated measures for breast density estimation.

Breast density is a significant breast cancer risk factor measured from mammograms. Evidence suggests that the spatial variation in mammograms may also be associated with risk. We investigated the variation in calibrated mammograms as a breast cancer risk factor and explored its relationship with other measures of breast density using full field digital mammography (FFDM). A matched case-control analysis was used to assess a spatial variation breast density measure in calibrated FFDM images, normalized for the image acquisition technique variation. Three measures of breast density were compared between cases and controls: (a) the calibrated average measure, (b) the calibrated variation measure, and (c) the standard percentage of breast density (PD) measure derived from operator-assisted labeling. Linear correlation and statistical relationships between these three breast density measures were also investigated. Risk estimates associated with the lowest to highest quartiles for the calibrated variation measure were greater in magnitude [odds ratios: 1.0 (ref.), 3.5, 6.3, and 11.3] than the corresponding risk estimates for quartiles of the standard PD measure [odds ratios: 1.0 (ref.), 2.3, 5.6, and 6.5] and the calibrated average measure [odds ratios: 1.0 (ref.), 2.4, 2.3, and 4.4]. The three breast density measures were highly correlated, showed an inverse relationship with breast area, and related by a mixed distribution relationship. The three measures of breast density capture different attributes of the same data field. These preliminary findings indicate the variation measure is a viable automated method for assessing breast density. Insights gained by this work may be used to develop a standard for measuring breast density.

乳腺密度是通过乳腺X线摄影测量出的一个重要的乳腺癌风险因素。有证据表明，乳腺X线摄影中的空间变异可能也与风险相关。我们研究了校准后的乳腺X线摄影中的变异作为一种乳腺癌风险因素，并利用全视野数字化乳腺X线摄影（FFDM）探索了它与其他乳腺密度测量方法的关系。 采用匹配的病例 - 对照分析来评估校准后的FFDM图像中的一种空间变异乳腺密度测量方法，该方法针对图像采集技术的差异进行了归一化。比较了病例组和对照组之间的三种乳腺密度测量方法：（a）校准后的平均测量值，（b）校准后的变异测量值，以及（c）由操作人员辅助标记得出的乳腺密度（PD）的标准百分比测量值。还研究了这三种乳腺密度测量值之间的线性相关性和统计关系。 与校准后的变异测量值从最低到最高四分位数相关的风险估计值在幅度上[比值比：1.0（参照），3.5，6.3和11.3]大于标准PD测量值四分位数的相应风险估计值[比值比：1.0（参照），2.3，5.6和6.5]以及校准后的平均测量值[比值比：1.0（参照），2.4，2.3和4.4]。这三种乳腺密度测量值高度相关，与乳腺面积呈反比关系，并且通过混合分布关系相互关联。 这三种乳腺密度测量方法捕捉到了同一数据域的不同属性。这些初步研究结果表明，变异测量值是一种可行的评估乳腺密度的自动化方法。这项工作所获得的见解可用于制定乳腺密度测量的标准。