Novel Imaging Methods to Determine Breast Density

确定乳房密度的新成像方法

基本信息

批准号：
8073096
负责人：
JOHN Alan SHEPHERD
金额：
$ 17.26万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至 2013-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8073096
关键词：
3-Dimensional Address Algorithms Biological Biopsy Breast Breast Cancer Risk Factor Calibration Cell Culture Techniques Clinical Coculture Techniques Coupled Databases Densitometry Development Devices Digital Mammography Dimensions Epithelium Fatty acid glycerol esters Fractals Harvest High Risk Woman Histocompatibility Testing Histology Image Imaging Techniques Investigation Lead Magic Magnetic Resonance Magnetic Resonance Imaging Magnetic Resonance Spectroscopy Mammary Gland Parenchyma Mammographic Density Mammography Mastectomy Measures Membrane Metabolic Methods Microtomy Organ Outcome Pattern Phospholipids Procedures Punch Biopsy Research Personnel Residual state Resolution Risk Risk Estimate Roentgen Rays Sampling Sectioning technique Slice Slide Specimen Spectrum Analysis Structure Sum Techniques Thea Plant Tissue Sample Tissues Translations Uncertainty Work attenuation breast density cancer risk cell type density imaging modality in vivo malignant breast neoplasm metabolic abnormality assessment novel programs spectroscopic imaging substantia spongiosa success two-dimensional

项目摘要

We propose to develop novel imaging techniques to quantity breast density and breast parenchymal patterns that can be used to further study the linkage of tissue composition and cancer risk. Breast density, as currently defined and measured, is a strong risk factor for breast cancer. The clinical measure of mammographic density is inadequate to study how the composition of breast tissue relates to cancer risk, especially on tissue specimens. We will develop the following: a Dual X-ray Absorptiometry (DXA) technique to quantify breast tissue composition on a clinical digital mammography device and a novel technique to quantify the projected parenchyma pattern using a combination of connectivity (Euler number) and fractal dimensions. These measures will be quantified in whole breast specimens and compared to current clinical measures of breast density (i.e., mammographic density and BI-RADS scores). In addition, we will extend these techniques to their use in thin (5 mm or less) breast tissue sections. Local measures of density and structure will be compared to whole breast measures by sectioning breasts specimens in their entirety and summing the local measures. Lastly, we will study if metabolic profiles measured using magnetic resonance magic angle spectroscopy (MR-MAS) correspond to specific pathological tissue types associated with dense breast (from Project 2) by histology analysis of the same samples. The results of this study may lead to (1) the implementation of new clinical measures of breast composition and risk in clinical mammograms, (2) novel compositional measures of density for thin tissue samples such as biopsy tissue, and (3) the identification of a metabolic signature that is specific to breast tissue type and applicable to new MR spectroscopic imaging techniques for a more sensitive and specific measure of risk.

我们建议开发出新的成像技术，以达到数量的乳房密度和乳房实质模式可以用来进一步研究组织组成和癌症风险的联系。据目前定义和测量，乳房密度是乳腺癌的强大危险因素。临床乳房X线摄影密度的度量不足以研究乳腺组织的组成如何与癌症风险，尤其是在组织标本上。我们将开发以下内容：双X射线吸收法（DXA）量化临床数字乳房X线摄影和新颖的乳腺组织组成的技术使用连接性组合（Euler编号）量化投影实质模式的技术和分形维度。这些措施将在整个乳房标本中进行量化，并与当前的乳房密度临床测量（即乳腺X线摄影密度和BI-RADS评分）。另外，我们将把这些技术扩展到它们在薄（5 mm或更少）的乳房组织切片中的使用中。本地措施通过将乳房的标本切开，将密度和结构与整个乳房测量进行比较完整并总结本地措施。最后，我们将研究是否使用磁性测量代谢谱共振魔法角光谱（MR-MAS）对应于相关的特定病理组织类型通过对相同样品的组织学分析，乳房（来自项目2）。这项研究的结果可能导致（1）实施新的乳房组成临床测量（2）薄组织样品（例如活检组织，以及（3）鉴定特定于乳腺组织类型的代谢特征和适用于新的MR光谱成像技术，以更灵敏，更具体的风险度量。