Subregional Breast Density and Cancer Risk

描述(由申请人提供)：尽管已经确定了乳房密度等强烈的风险因素，但识别乳腺癌风险女性并不是当前女性健康临床范例的一部分。乳房X光照片上高比例的致密实质似乎使患乳腺癌的风险增加了4-6倍。即使经过20年的研究，这种联系的生物学原因也不清楚。这项拟议研究的长期目标是确定用于高死亡率癌症风险评估的最佳全球或局部乳房密度测量方法。本应用的目的是描述特定局部测量的乳腺体积密度和密度形态与浸润性癌症和DCIS病例的癌症风险的关系，并发现血清、组织或临床生物标记物作为致密乳腺组织宏观分布的决定因素。中心假设是，分区域测量纤维腺体积密度百分比与局部和全球乳腺癌风险的相关性更强。由于致密组织分布的活体描述尚不清楚，对癌症女性与非癌症女性乳房组织内致密组织的分布情况知之甚少。我们的第二个假设是，乳房密度的特定生物标志物作为密度宏观结构的形态恒定器。我们的方法是独特的，因为我们将使用一种新的逐像素测量乳房体积密度的方法，称为单次X射线吸光度(SXA)。我们的第一个具体目标是确定与接受乳房X光检查的女性继发乳腺癌相关的致密乳房体积的亚区。这一目标的工作假设是，与全球乳房密度相比，乳房区域可能是该地区局部癌症的更强风险预测因子。此外，与整体乳房密度相比，分区域密度可能是女性患乳腺癌风险的更强的风险预测因子，这是因为排除了包裹实质的外围脂肪。我们的第二个具体目标是确定乳房形态与风险的关系以及与关键组织、血清和临床的相关性，以测试乳房密度的形态恒定行为。众所周知，密度的粗略分布显示了女性之间以及女性两个乳房之间的形态特征。我们的工作假设是，致密组织可能存在特定的空间分布或形态，与癌症风险相关，与密度的大小无关。我们的预期结果将包括：开发局部乳房密度的新区域，用于未来使用我们的大队列进行研究；确认乳房密度是局部或全球风险因素，以及确定最有可能驱动乳房密度形态测量的生物标志物候选对象。我们的发现将通过提供癌症风险标记物来智能地降低极低风险女性的筛查频率，从而降低接受乳房X光检查的女性的伤害风险。它将有助于通过更准确地识别和定向使用更敏感的成像和减少风险策略来降低高危妇女的死亡率。 公共卫生相关性：这项拟议的研究与公共健康相关，因为它将试图显著提高通过筛查乳房X光检查图像来量化女性个人乳腺癌风险的能力。这与美国国立卫生研究院的使命相关，因为改进的乳腺癌风险衡量标准将“显著提高国家保护和改善健康的能力”。

DESCRIPTION (provided by applicant): Identifying women at risk for breast cancer is not part of the current clinical paradigm for women's health even though strong risk factors, such as breast density, have been identified. A high percentage of dense parenchyma on mammograms appears to give a 4-6 fold risk to develop breast cancer. The biological cause for the association is unclear even after 20 years of study. The long-term goal of this proposed research is to determine the best global or local measure of breast density for risk assessment of high-mortality cancers. The objective of this application is to describe the relationship of specific local measures of volume breast density and density morphology to cancer risk for invasive cancers as well as DCIS cases, and to discover what serum, tissue, or clinical biomarkers act as a determinant of the macro distribution of dense breast tissue. The central hypothesis is that subregional measurements of the percent fibroglandular volume density are more strongly associated with local and global breast cancer risk. Very little is known of the distribution of dense tissue within breast tissue in women with cancer versus those without because an in vivo description of dense tissue distribution has not been available. Our secondary hypothesis is that specific biomarkers of breast density act as morphostats for density macro structure. Our approach is unique in that we will be using a novel pixel-by-pixel measure of volumetric breast density called Single X-ray Absorptiometry (SXA). Our first specific aim is to identify subregions of dense breast volume associated with subsequent breast cancer in women undergoing mammography. The working hypothesis for this aim is that subregions of the breast may be stronger risk predictor of local cancer in that region than global breast density. In addition, subregional density may be a stronger risk predictor of a woman's risk of breast cancer than global breast density due to the exclusion of peripheral adipose that envelopes the parenchyma. Our second specific aim is to Identify the association of breast morphology to risk and to key tissue, serum, and clinical correlates to test the morphostatic behavior of breast density. The coarse distribution of density is known to show morphostatic qualities between women as well as between a woman's two breasts. Our working hypothesis is that there may be a particular spatial distribution, or morphology, of dense tissue that is associated with cancer risk independent of the magnitude of the density. Our expected outcome will include: development of new regions of local breast density that will be made available for future studies using our large cohort, confirmation of breast density as either a local or global risk factor, and the identification of the most likely biomarker candidates driving breast density morphometry. Our findings will reduce the risks of harms for women undergoing mammography by providing a cancer risk marker to intelligently reduce the screening frequency of very low risk women. It will aid in the decreased mortality of high risk women by their more accurate identification and targeting for use of more sensitive imaging and risk reduction strategies. PUBLIC HEALTH RELEVANCE: The proposed research is relevant to the public health because it will attempt to significantly improve the ability to quantify a woman's personal risk of breast cancer using measures taken from her screening mammography images. This is relevant to the NIH's mission because improved measures of breast cancer risk will "advance significantly the Nation's capacity to protect and improve health."