MAMMOGRAPHIC DENSITIES AND RISK OF BREAST CANCER

描述：(改编自调查人员摘要)的长期目标 这项提议是为了改进测量乳房组织的方法。 我们称之为“乳房X光照相密度”的特征 与患乳腺癌的风险密切相关。这些改进的方法将是 完全自动化，不需要观察者，并将测量体积， 而不是乳房相关组织的投影面积。 不同个体的钼靶致密乳房组织可能具有相似的 投影面积，但在厚度和数量上有很大的不同。 因为我们预计相关组织的数量会更直接 与乳腺癌风险相关的预测面积，我们认为 测量体积将是乳腺癌的一个更强的风险因素。 投影面积。评估放射致密乳房组织的体积 作为乳腺癌的一个危险因素，我们必须在以下条件下获得前瞻性的图像 控制条件，我们已经开发了一个校准装置和一个 厚度计将被整合到现场成像期间 乳房X光检查以评估乳房组织的成分和厚度。 我们将在选定的乳房X光照相地点安装校准设备，以及 将其纳入所有乳房X光检查对象的检查中。案件将会是 被诊断为组织学证实的浸润性乳腺癌的受试者。一 对照将从相同的乳房X光摄影科挑选，并与年龄匹配 到案子里去。总共将招募800对病例对照。这个 本项目中要解决的假设是：1)自动测量 乳房中X光摄影致密组织的体积将产生更大的 风险的梯度比预测面积大。2)乳房X线片的体积密度 乳房组织将与其他风险因素更密切地关联在一起 乳腺癌比投射面积大。3)结合的统计模型 体积、投影面积和其他乳房X光检查特征将导致改进 与单独的百分比密度相比，乳腺癌风险的预测。

DESCRIPTION: (Adapted from the Investigator's Abstract) The long term goal of this proposal is to develop improved methods of measuring the breast tissue characteristics that we refer to as "mammographic densities" and have found to be strongly related to risk of breast cancer. These improved methods will be fully automated, will not require an observer, and will measure the volume, rather than the projected area, of the relevant tissues in the breast. Mammographically dense breast tissue in different individuals may have similar projected areas, but differ substantially in thickness and thus in quantity. Because we expect the quantity of the relevant tissue to be more directly related to risk of breast cancer than the projected area, we believe that measurement of volume will be a stronger risk factor for breast cancer than is the projected area. To assess the volume of radiologically dense breast tissue as a risk factor for breast cancer we must acquire images prospectively under controlled conditions, and we have developed a calibration device and a thickness gauge that will be incorporated into the field imaged during mammography to assess breast tissue composition and thickness. We will install the calibration device in selected mammography sites, and include it in the examination of all subjects having mammography. Cases will be subjects diagnosed with histologically verified invasive breast cancer. One control will be selected from the same mammography department, and age-matched to the case. A total of 800 case control pairs will be recruited. The hypotheses to be addressed in this project are: 1) Automated measurement of the volume of mammographically dense tissue in the breast will create larger gradients in risk than projected area. 2) The volume of mammographically dense breast tissue will be more strongly associated with other risk factors for breast cancer than the projected area. 3) Statistical models that combine volume, projected area, and other mammographic features will result in improved prediction of breast cancer risk compared to percent density alone.