Automated Density Measures for Estimating Breast Cancer Risk and Therapy Response

用于估计乳腺癌风险和治疗反应的自动密度测量

• 批准号: 8913697
• 负责人: KARLA M KERLIKOWSKE
• 金额: $ 63.59万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8913697
• 关键词: Adjuvant Therapy; Age; American College of Radiology; Area; Aromatase Inhibitors; Breast Cancer Detection; Breast Cancer Risk Factor; Categories; Clinic; Clinical; Congresses; Data; Diagnosis; Digital Mammography; Discrimination; Disease; ERBB2 gene; Environment; Estrogens; Ethnic Origin; Film; Frequencies; Geographic state; Goals; Health; Image; In Situ; Individual; Information Systems; Malignant Neoplasms; Mammography; Measures; Menopause; Methods; Modality; Monitor; Nested Case-Control Study; Outcome; Performance; Perimenopause; Postmenopause; Progestins; Protocols documentation; Race; Reporting; Risk; Risk Assessment; Risk Factors; Roentgen Rays; San Francisco; Standardization; State Government; Surrogate Markers; Tamoxifen; Time; Training; Translating; Tumor Subtype; Variant; Woman; age group; base; breast density; breast imaging; cancer recurrence; cancer risk; cancer therapy; case control; clinical care; clinical practice; density; digital; digital imaging; hormone therapy; improved; malignant breast neoplasm; mammography registry; older women; radiologist; response; screening

DESCRIPTION (provided by applicant): Breast density assessed from film-screen mammography is one of the strongest risk factors for breast cancer and provides important information not only for risk assessment, but also for tailoring breast screening approaches and determining response to therapies. To date, the clinical potential of breast density has not been fully realized, in part due to lack of a standard, reproducible, objective and automated clinical density measure. Currently, the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) 4-category qualitative assessment is the most widely used clinical density measure, but it is subjective, requires a trained radiologist, is not always reported, and s limited in its ability to assess small, but potentially meaningful changes in density in response t therapies. We and others have developed promising automated mammographic measures on full field digital mammography (FFDM), including area, volumetric and variation density measures, and shown their associations with breast cancer. To date, studies have not compared the performance of automated density measures or their combination on FFDM images from the same women, to inform the best measure(s) for use in the clinical setting. Since over 85% of mammography in the US is FFDM, density measures need to be developed and examined in the FFDM environment to translate for use in today's clinical care. We propose to examine and compare the association of mammographic measures from FFDM with breast cancer and evaluate their ability to detect changes in response to menopause and hormone therapies among women ages 35-75 receiving FFDM within the Mayo Clinic and San Francisco Mammography Registry breast screening practices between 2006-2015. Specifically, we propose 1) To retrieve serial, digital mammograms prior to diagnosis (or corresponding date for controls), BI-RADS density and covariates on a large nested case-control study of 2800 incident breast cancers and 5600 matched controls, and to estimate automated area, volumetric and variation density measures on all images; 2) To examine the association of breast density measures from both the earliest and multiple subsequent mammograms with breast cancer and to assess whether these associations differ by age, invasive vs. in situ breast cancer and ER, PR and HER-2 defined subtypes; and 3) To estimate menopause- and therapy-related changes in density measures on FFDM from 500 healthy perimenopausal women, 1000 peri or postmenopausal women initiating hormone therapy, and 1000 breast cancer cases initiating endocrine therapy. This protocol will answer: 1) Which automated density measure or combination of measures are most clinically useful in the FFDM environment as a risk factor for breast cancer and for detecting changes in density in response to therapy? 2) Do density measures perform similarly in younger vs. older women and for specific types of breast cancer? And 3) Do multiple measures of breast density improve risk associations compared to a single measure? This proposal will impact breast density assessment across the US, allowing for standardization in clinical practice and opportunities to integrate density measures into individualized risk assessment and screening.

描述（由申请人提供）：乳房乳房X线摄影评估的乳房密度是乳腺癌的最强风险因素之一，不仅为风险评估提供了重要的信息，而且还提供了调整乳房筛查方法并确定对治疗疗法的反应的重要信息。迄今为止，乳房密度的临床潜力尚未完全实现，部分原因是缺乏标准，可重复的，客观和自动化的临床密度度量。目前，美国放射学乳房成像报告和数据系统（BI-RADS）4类定性评估是最广泛使用的临床密度度量，但它是主观的，需要训练有素的放射科医生，并且并不总是有报道，并且在评估响应疗法中的密度较小但潜在的有意义的变化方面的能力有限。我们和其他人在全田数字乳房X线摄影（FFDM）上制定了有希望的自动乳腺X线摄影测量，包括面积，体积和变异密度度量，并显示了它们与乳腺癌的关联。迄今为止，研究尚未比较自动密度度量的性能或与同一女性的FFDM图像的组合，以告知最佳措施在临床环境中使用。由于在美国，超过85％的乳房X线摄影是FFDM，因此需要在FFDM环境中制定和检查密度措施，以翻译以在当今的临床护理中使用。我们建议检查和比较FFDM的乳腺X线摄影测量与乳腺癌的关联，并评估其在2006年至2015年之间在Mayo Clinic和Sanfrancisco乳房摄影术中接受FFDM的35-75岁妇女中对更年期和激素疗法的响应能力。具体而言，我们提出1）在诊断之前（或对照组的相应日期），BI-RADS密度和协变量在大型嵌套的病例对照研究中检索串行，数字乳房X线照片（或相应的日期），对2800个事件乳腺癌和5600个匹配的对照组进行了大型嵌套病例对照研究，以及估计所有图像上所有图像的自动化区域，大量和变体密度度量； 2）检查最早和多个随后的乳房X线照片与乳腺癌的乳房密度测量的关联，并评估这些关联是否因年龄而有所不同，侵入性与原位乳腺癌以及ER和ER，PR和HER-2定义了亚型； 3）估计500名健康的上绝经妇女，1000名或绝经后妇女开始激素治疗的FFDM的更年期和治疗相关的密度度变化，以及1000例开始内分泌治疗的乳腺癌病例。该方案将回答：1）在FFDM环境中，哪种自动密度度量或措施组合作为乳腺癌的危险因素以及检测响应治疗的密度变化？ 2）密度度量在年轻女性和特定类型的乳腺癌中的密度度量是否相似？ 3）与单一度量相比，多种乳房密度的度量可以改善风险关联吗？该建议将影响整个美国的乳房密度评估，从而使临床实践中的标准化以及将密度措施纳入个性化的风险评估和筛查的机会。