An Automated System for Breast Cancer Biomarker Analysis

用于乳腺癌生物标志物分析的自动化系统

• 批准号: 7271911
• 负责人: JOHN J HEINE
• 金额: $ 25.14万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-03 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7271911
• 关键词: Accounting; Address; Adjuvant; Adjuvant Study; Age; Algorithms; Area; Biological; Biological Markers; Breast; Breast Cancer Risk Factor; Calibration; Case-Control Studies; Computing Methodologies; Coupled; Data; Data Collection; Data Set; Data Storage and Retrieval; Detection; Development; Diagnostic; Digital Mammography; Disease Management; Dissection; Electronics; Eligibility Determination; Engineering; Ensure; Environment; Family history of; Film; Financial compensation; Foundations; Future; Goals; Hormonal; Hormone replacement therapy; Hormones; Image; Indium; Industry; Institution; Intervention; Kansas; Knowledge; Lesion; Location; Malignant Neoplasms; Mammary Gland Parenchyma; Mammographic Density; Mammography; Maps; Measurement; Measures; Medical center; Metabolic; Methods; Metric; Modification; Monitor; Nature; Noise; Numbers; Odds Ratio; Output; Pathology; Patients; Photons; Physics; Principal Investigator; Procedures; Property; Publishing; Qualifying; Quality Control; Radiation; Range; Rate; Reporting; Reproducibility; Reproductive History; Research; Research Design; Research Personnel; Risk; Risk Factors; Screening procedure; Sensitivity and Specificity; Signal Transduction; Sister; Site; Solid; Somatotropin; Source; Staging; Standardization; Standards of Weights and Measures; Structure; System; Tamoxifen; Techniques; Thick; Time; Tissues; Today; Tube; Uncertainty; Variant; Wichita; Woman; Work; attenuation; base; breast density; cancer risk; case control; cholesterol-binding protein; computer code; data integration; density; design; detector; digital; improved; innovation; malignant breast neoplasm; parity; programs; quality assurance; response; solid state; statistics; tool; transmission process; two-dimensional; voltage

DESCRIPTION (provided by applicant): Research has long implicated breast density as an important risk factor for breast cancer (BC). Compared to other risk factors, such as age, family history, hormone exposure, parity, etc., breast density shows an equivalent or greater association with BC risk, with odd ratios ranging from two through six or higher. Nevertheless, the breast density-BC risk association is complicated by several facts. First, dense mammographic tissue is present, to some degree, in the vast majority of women. Second, reported associations between breast density measures and BC risk show broad variability across studies, third, breast tissue is a biomarker both for BC risk and for past and present hormonal interactions. Moreover, currently there are no universally applied or accepted standards for measuring breast density. In this work we will build on our previous work in calibrated tissue metrics and the automated analysis of digitized mammograms and fully develop an approach for automatically assessing tissue-risk in mammograms acquired with the General Electric Senographe 2000D full field digital mammography (FFDM) system. The aim is to standardize the output images so that each pixel is calibrated to the amount of dense tissue that the x-ray beam passed through above the related detector location (above the pixel). The work includes comparing volumetric with calibrated two-dimensional measures. Our previous work in this area will be modified and built into a total tool for assessing density in the research environment. The resulting tissue metrics will be validated in terms of sensitivity and specificity with a case-control study. In order to better understand and quantify the breast tissue density-risk associations, large multi-center serial based studies will be necessary in the future. However, this will first require understanding the calibration stability over time, as well as designing the appropriate quality assurance procedures as proposed here. The intra-imager serial stability and the inter-imager concordance will be assessed by performing the same calibration on two similar FFDM systems located at the Pi's site and another site (Via Christi Regional Medical Center, Wichita, Kansas). The serial comparisons will be made with robust methods applied in industry for monitoring serial quality control. This work will produce a calibrated automated density assessment package that may be easily implemented across institutions without modifications for use in the FFDM systems that is tailored for tissue-related risk research.

描述（由申请人提供）：长期以来，研究将乳房密度作为乳腺癌的重要危险因素（BC）。与其他危险因素（例如年龄，家族病史，激素暴露，均等等）相比，乳房密度与BC风险相同或更大的关联，奇数比率为2至六个或更高。然而，乳房密度BC风险关联因几个事实而变得复杂。首先，在某种程度上，绝大多数女性都存在着密集的乳房X线摄影组织。其次，报道的乳房密度度量与BC风险之间的关联在研究中显示出广泛的差异，第三，乳腺组织是BC风险的生物标志物，也是过去和现在的激素相互作用。此外，目前尚无普遍应用或接受的标准来测量乳房密度。在这项工作中，我们将基于我们先前在校准组织指标上的工作以及对数字乳房X线照片的自动分析，并充分开发一种方法，以自动评估使用通用电气SENographe 2000D Full Full Field数字乳腺摄影（FFDM）系统中自动评估乳房X线照片的组织风险。目的是标准化输出图像，以便将每个像素校准到X射线束穿过相关检测器位置（像素上方）上方的密集组织量。这项工作包括将体积与校准的二维测量进行比较。我们以前在该领域的工作将被修改并内置为用于评估研究环境中密度的全部工具。通过病例对照研究，将根据敏感性和特异性来验证所得的组织指标。为了更好地理解和量化乳腺组织密度风险的关联，将来需要大型多中心串行研究。但是，这将首先需要了解随着时间的流逝的校准稳定性，并设计此处提出的适当质量保证程序。将通过对位于PI站点和另一个站点的两个类似的FFDM系统进行相同的校准来评估IMIMAGER内部序列稳定性和Inter-Imager Coonistance（通过堪萨斯州Wichita的Christi Regional Medical Center）进行相同的校准。串行比较将使用在行业中应用的强大方法进行监控，以监视串行质量控制。这项工作将产生校准的自动密度评估包，可以轻松地在机构之间实施，而无需对FFDM系统进行修改，该系统是针对组织相关的风险研究量身定制的。