Detecting Mammographically-Occult Cancer in Women with Dense Breasts

检测乳腺致密女性的乳房X线隐匿性癌症

• 批准号: 9296809
• 负责人: ROBERT M NISHIKAWA
• 金额: $ 20.23万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-03 至 2019-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9296809
• 关键词: Adipose tissue; Biological Markers; Biopsy; Breast; Clinical; Computers; Consult; Data Set; Development; Discriminant Analysis; Equilibrium; Eye; Financial cost; Future; Goals; Human; Image; Individual; Laws; Left; Letters; Magnetic Resonance Imaging; Malignant Neoplasms; Mammary Gland Parenchyma; Mammography; Maps; Notification; Physicians; ROC Curve; Radon; Research; Risk; Scheme; Specificity; Structure; Techniques; Testing; Tissues; Training; Ultrasonography; Validation; Woman; Women Physicians; base; breast density; cost; density; high risk; imaging biomarker; imaging modality; malignant breast neoplasm; novel; quantitative imaging; radiologist; screening

Most women in the USA who have dense breast tissue at screening mammography receive a letter notifying them that they have dense breasts and, therefore, mammography is less effective for them and could be associated with an increased risk of breast cancer. The letter advises women to talk with their physician whether they should have additional screening with ultrasound or magnetic resonance imaging (MRI). The benefit of additional screening is the possibility of detecting a mammographically occult cancer. However, the likelihood of detecting a cancer is not known, making it a difficult decision for the woman to balance the uncertain potential benefit against the known costs. These known costs are financial (as some states do not cover the supplemental screen) and the risk of an unnecessary biopsy, as the specificity of ultrasound and MRI are lower than mammography. The goal of our research is to develop imaging biomarkers for mammographically occult breast cancers on screening mammograms of women with dense breasts. This would allow women to know whether it is likely that they have a mammographically occult cancer that may be imaged with ultrasound or MRI. Our approach is to use a new and novel technique called a Radon Cumulative Distribution Transform (RadonCDT) to compare the structure of the left and right breasts. The RadonCDT is a non-linear technique the maps structures, which are created by the adipose and fibroglandular tissue, from the right breast to the left breast. Since the left and right breasts are generally symmetric, the presence of a mammographically occult cancer may produce subtle changes to the symmetry. These subtle differences are not visible to the human eye, but through the RadonCDT transform may become more apparent. We will develop the imaging biomarkers on a dataset of 150 mammographically occult cancer cases (clinical cases read as normal, but the woman has breast cancer detected on her next screening mammogram) and 150 normal cases (clinical cases read as normal and the woman does not have breast cancer detected on her next two screening mammograms). We will apply the RadonCDT to the images and then image features will be extracted from the transformed images. We anticipate that we will need less than 10 features. We will use a stepwise linear discriminant analysis to choose the best set of features from the full set of features extracted. We will use a linear discriminant classifier to merge the features so that the cases can be classified as containing a mammographically occult breast cancer or not. We will use a three-way cross validation to reduce bias. That is, we will divide the full dataset into three subsets, one for developing and selecting the features, one for training the classifier, and one for testing. Finally, we will use an independent dataset of 100 cases to validate the classifier. If we are successful, then up to 14 million women each year who have dense breasts will have needed information upon which to base her decision for getting supplemental screening.

大多数在筛查乳房 X 光检查时乳腺组织致密的美国女性都会收到一封通知信 他们认为自己的乳房致密，因此乳房 X 光检查对他们来说效果较差，可能会 与乳腺癌风险增加有关。这封信建议女性与她们的医生交谈 他们是否应该接受超声波或磁共振成像 (MRI) 的额外筛查。这 额外筛查的好处是有可能检测到乳房X光检查隐匿性癌症。然而， 检测出癌症的可能性尚不清楚，这使得女性很难做出平衡的决定 相对于已知成本，不确定的潜在收益。这些已知的成本是财务成本（因为有些州没有 覆盖补充屏幕）以及不必要的活检的风险，因为超声和 MRI 的特异性 低于乳房X光检查。我们研究的目标是开发成像生物标志物 乳房X光检查隐匿性乳腺癌对致密乳房女性的乳房X光检查进行筛查。这 可以让女性知道她们是否有可能患有乳房X光检查隐匿性癌症 通过超声波或 MRI 成像。我们的方法是使用一种称为氡累积的新技术 分布变换（RadonCDT）来比较左右乳房的结构。 RadonCDT 是 非线性技术映射由脂肪和纤维腺组织创建的结构， 右乳房到左乳房。由于左右乳房通常是对称的，因此存在 乳房X光检查隐匿性癌症可能会对对称性产生微妙的变化。这些细微的差别是 人眼不可见，但通过RadonCDT变换可能会变得更加明显。我们将 在 150 个乳腺 X 光检查隐匿性癌症病例（临床病例）的数据集上开发成像生物标志物 读数正常，但该妇女在下次筛查乳房 X 光检查中检测到乳腺癌）和 150 正常病例（临床病例视为正常，并且该妇女在下次检查时未检测到乳腺癌） 两次筛查性乳房X光检查）。我们将 RadonCDT 应用于图像，然后图像特征将是 从转换后的图像中提取。我们预计需要的功能少于 10 个。我们将使用一个 逐步线性判别分析，从提取的全套特征中选择最佳特征集。 我们将使用线性判别分类器来合并特征，以便将案例分类为 是否含有乳房X光检查隐匿性乳腺癌。我们将使用三向交叉验证 减少偏见。也就是说，我们将完整的数据集分为三个子集，一个用于开发和选择 特征，一种用于训练分类器，一种用于测试。最后，我们将使用一个包含 100 个数据的独立数据集 案例来验证分类器。如果我们成功的话，每年将有多达 1400 万女性患有密集型 乳房将获得所需的信息来决定是否进行补充筛查。