Lesion Composition and Quantitative Imaging Analysis on Breast Cancer Diagnosis

项目摘要/摘要。乳房致密的女性并未被证明受益于癌症的增加 检测容积式数字乳房断层合成(DBT)，但可能受益于较低的召回率。DBT筛选 活检率与2D数字乳房X光检查相似；首次筛查的活检率更高，此后筛查的活检率更低 根据年龄和乳房密度进行调整。在美国，71%的活组织检查不能确诊为乳腺癌 在接受乳腺癌筛查的40-79岁女性中。为了解决不必要的高比率 活检，一种使用FDA批准的乳房成像方案的创新方式已经开发出来，以获得 多光谱图像测量可疑乳腺病变的脂肪/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组分 组织。该建议旨在通过结合L/W/P生物组织来提高活检产量(BI-RADS-PPV3 生物标志物与定量形态和纹理图像分析。这一组合的构图和 可疑乳房病变的物理描述称为q3cb。在当前版本中添加q3CB的好处 可能已经包括计算机辅助检测的DBT筛查/诊断成像范例是未知的。 这项研究旨在比较临床读者研究中使用和不使用q3CB时的预期活检率。 并探索如何将q3CB与现有技术相结合。中心假设是生物学上的 乳腺组织中L/W/P组分结合组织形态和质地分析 与传统的DBT解释相比，这些特征将产生显著更高的乳腺癌特异性 独自一人。目的是为了更好地识别可疑的乳房病变，这些病变需要在 目前建议做活组织检查的女性。长期目标是减少不必要的活组织检查，增加 活检率。我们提出这项研究的理由是，对乳腺病变的生物学L/W/P描述将 有助于做出更具体的活检决定，并更好地了解癌症类型。具体地说，该项目 目标是1)开发q3CB病变特征，用于区分乳腺癌病变和良性病变，使用 对建议接受活检的妇女进行600次预期获得的DBT检查；2)进行临床 Reader研究比较放射科医生在不使用和不使用DT的情况下对标准护理FFDM或DBT的表现 包括q3CB签名；3)调查q3CB病变签名在筛查范例中的用途 在评估恶性肿瘤的任务中提高对CADE识别的可疑病变的敏感性和特异性 以及它们与癌症亚型的关联；探索性的)探索增加的敏感性 双能量DBT在探索病变大小、成分和乳房的模体研究中的特异性 密度。本研究的创新之处在于对脂质/水/蛋白质损伤成分进行了全面表征 DBT及其与临床放射科医生配对的现有计算机辅助诊断程序的补充 为这项独特的新兴技术的临床翻译提供准备的证据。

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.