Subregional Breast Density and Cancer Risk

描述（由申请人提供）：尽管已经确定了乳腺密度等强风险因素，但识别有乳腺癌风险的女性并不是当前女性健康临床模式的一部分。在乳房X光片上高比例的致密实质似乎会使患乳腺癌的风险增加4-6倍。即使经过20年的研究，这种联系的生物学原因仍不清楚。这项拟议研究的长期目标是确定最佳的全球或局部乳腺密度测量方法，用于高死亡率癌症的风险评估。本申请的目的是描述体积乳腺密度和密度形态的特定局部测量与浸润性癌症以及DCIS病例的癌症风险的关系，并发现血清、组织或临床生物标志物作为致密乳腺组织宏观分布的决定因素。中心假设是纤维腺体体积密度百分比的次区域测量与局部和整体乳腺癌风险更密切相关。很少有人知道乳腺组织中的致密组织的分布在女性癌症与那些没有，因为在体内描述致密组织的分布还没有。我们的第二个假设是，乳腺密度的特定生物标志物作为密度宏观结构的morphostats。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腺体积密度，称为单X射线吸收测定法（SXA）。我们的第一个具体目标是确定与随后的乳腺癌妇女接受乳房X线摄影致密乳腺体积的分区。这一目标的工作假设是，乳房的子区域可能是该区域局部癌症的风险预测因子，而不是整体乳腺密度。此外，分区密度可能是一个更强的风险预测一个女人的乳腺癌的风险比全球乳腺密度，由于排除了周围脂肪，包绕实质。我们的第二个具体目标是确定乳腺形态与风险和关键组织，血清和临床相关因素的关联，以测试乳腺密度的形态稳定性行为。已知密度的粗分布显示了女性之间以及女性的两个乳房之间的形态稳定性。我们的工作假设是，可能有一个特定的空间分布，或形态，致密组织与癌症的风险无关的密度的大小。我们的预期结果将包括：开发新的局部乳腺密度区域，这些区域将可用于未来使用我们的大型队列的研究，确认乳腺密度作为局部或全球风险因素，并确定最有可能的生物标志物候选人驱动乳腺密度形态测量。我们的研究结果将通过提供癌症风险标志物来智能地减少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。它将有助于降低高风险妇女的死亡率，通过更准确的识别和针对性地使用更敏感的成像和降低风险的策略。 公共卫生相关性：这项拟议的研究与公共卫生有关，因为它将试图通过从筛查乳腺X射线摄影图像中采取的措施，显着提高量化妇女患乳腺癌个人风险的能力。这与国家卫生研究院的使命有关，因为改善乳腺癌风险的措施将“大大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."