Lesion Composition and Quantitative Imaging Analysis on Breast Cancer Diagnosis

项目概要/摘要。患有致密乳腺癌的妇女没有被证明会因癌症增加而受益 体积数字乳腺断层合成摄影（DBT）的检测，但可能受益于较低的召回率。DBT筛查 活检率与2D数字乳腺X射线摄影相似;首次筛查检查较高，之后较低， 根据年龄和乳腺密度进行调整。在美国，71%的活检不会导致乳腺癌诊断 在40-79岁接受乳腺癌筛查的女性中。为了解决不必要的高比率问题， 活检，一种使用FDA批准的乳腺成像协议的创新方法已经开发出来， 多光谱图像来测量可疑乳腺病变的脂质/水/蛋白质（L/W/P）组成。 与正常或良性乳腺组织相比，恶性乳腺组织具有独特的L/W/P组成分数 组织.该提案旨在通过结合L/W/P生物学技术， 生物标志物的定量形态学和纹理图像分析。这种组合物和 对可疑乳腺病变的物理描述称为q3 CB。将q3 CB添加到电流中的好处 DBT筛查/诊断成像范例，可能已经包括计算机辅助检测，是未知的。 本研究旨在比较临床阅片师研究中使用和不使用q3 CB的预期活检率 并探索q3 CB如何与现有技术联合收割机结合。核心假设是， 乳腺组织中的L/W/P组分结合形态和组织结构分析 这些特征将产生比传统DBT解释更高的乳腺癌特异性 一个人其目的是更好地确定可疑的乳腺病变，需要活检的恶性肿瘤， 目前建议进行活检的女性。长期目标是减少不必要的活检， 活检率。我们提出这项研究的理由是，乳腺病变的生物学L/W/P描述将 导致更具体的活检决定和更好地了解癌症类型。具体而言，该项目 目的是：1）开发q3 CB病变特征，用于区分乳腺癌病变和良性病变，使用 600例推荐接受活检的女性前瞻性获得的DBT检查; 2）进行临床 比较放射科医生在标准FFDM或DBT（无和有）上的表现的阅片人研究 包括q3 CB特征; 3）研究q3 CB病变特征在筛选范例中的效用， 在评估恶性肿瘤的任务中，提高CADE识别的可疑病变的灵敏度和特异性 以及与癌症亚型的关联;探索性）探索增加的敏感性 双能量DBT在体模研究中的特异性和特异性， 密度的本研究的创新之处在于， DBT以及它如何补充现有的计算机辅助诊断程序与临床放射科医生配对 为这项独特的新兴技术的临床转化提供证据。

Project Summary/Abstract. Women with dense breast have not been shown to benefit by increased cancer detection of volumetric digital breast tomosynthesis (DBT) but may benefit by lower recall rates. DBT screening biopsy rates are similar to 2D digital mammography; higher for first screening exams, lower thereafter with adjustment for age and breast density. In the U.S., 71% of biopsies do not result in a breast cancer diagnosis among women ages 40-79 who undergo breast cancer screening. To address the high rate of unnecessary biopsies, an innovative way to use FDA-approved breast imaging protocols has been developed to acquire multispectral images to measure the lipid/water/protein (L/W/P) composition of suspicious breast lesions. Malignant breast tissue has unique L/W/P composition fractions when compared to normal or benign breast tissue. This proposal aims to increase biopsy yield (BI-RADS-PPV3) through combining L/W/P biological biomarkers with quantitative morphological and textural image analysis. This combination of composition and physical descriptions of suspicious breast lesions is called q3CB. The benefits of adding q3CB to the current DBT screening/diagnostic imaging paradigm, that may already include computer aided detection, is not known. This study is designed to compare the expected biopsy yield with and without q3CB in a clinical reader study and explore how q3CB may be combine with existing technologies. The central hypothesis is that biological L/W/P fractions in breast tissue in combination with analysis of morphological and textural tissue characteristics will yield significantly higher breast cancer specificity than conventional interpretation of DBT alone. The objective is to better identify suspicious breast lesions that need to be biopsied for malignancy in women currently recommended for biopsy. The long-term goal is to reduce unnecessary biopsies and increase biopsy yield. Our rationale for the proposed research is that biological L/W/P descriptions of breast lesions will lead to more specific biopsy decisions and a better understanding of cancer types. Specifically, the project aims are 1) develop q3CB lesion signatures for distinguishing breast cancer lesions from benign lesions, using 600 prospectively-acquired DBT exams of women recommended to undergo biopsy; 2) conduct a clinical reader study to compare radiologists' performance on standard-of-care FFDM or DBT without and with the inclusion of q3CB signatures; 3) Investigate the utility of q3CB lesion signatures in a screening paradigm to improve sensitivity and specificity on CADe-identified suspicious lesions in the tasks of assessing malignancy as well as in associating with their association with cancer subtypes; Exploratory) explore the added sensitivity and specificity of dual-energy DBT in phantom studies that explore lesion size, composition, and breast density. The innovation of this study is the full characterization of lipid/water/protein lesion composition with DBT and how it complements existing computer aided diagnostic programs paired with clinical radiologists providing evidence ready for clinical translation of this unique and emerging technology.