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(申请人提供)：通过胶片屏幕乳房X光照相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重要信息，还为定制乳房筛查方法和确定治疗反应提供重要信息。到目前为止，乳房密度的临床潜力还没有完全实现，部分原因是缺乏标准的、可重复的、客观的和自动化的临床密度测量。目前，美国放射学会乳腺影像报告和数据系统(BI-RADS)4类定性评估是临床上应用最广泛的密度测量方法，但它是主观的，需要训练有素的放射科医生，并不总是有报道，而S在评估治疗反应中微小但潜在有意义的密度变化的能力有限。我们和其他人已经在全视野数字乳房摄影(FFDM)上开发了有前景的自动化乳房摄影测量方法，包括面积、体积和变异密度测量，并显示了它们与乳腺癌的关系。到目前为止，还没有研究比较自动密度测量或它们的组合在同一女性的ffdm图像上的性能，以便为临床使用的最佳测量方法(S)提供参考。由于美国超过85%的乳房X光检查是FFDM，因此需要开发密度测量方法，并在FFDM环境中进行检查，以转换为今天的临床护理使用。我们建议检查和比较FFDM的乳房X光检查措施与乳腺癌的相关性，并评估它们在2006年至2015年期间在梅奥诊所和旧金山乳房X光检查登记处接受FFDM乳房筛查实践的35-75岁女性中检测更年期和激素治疗的变化的能力。具体地说，我们建议1)检索诊断前(或对照的相应日期)、BI-RADS密度和大型嵌套病例对照研究中的协变量，2800例乳腺癌和5600例匹配对照，并估计所有图像上的自动化面积、体积和变异密度测量；2)检查最早和多次后续乳房X光检查中的乳腺密度测量与乳腺癌的关联，并评估这些关联是否因年龄、浸润性乳腺癌与原位乳腺癌和ER、PR-2定义的亚型而不同；3)评估500例健康围绝经期妇女、1000例开始激素治疗的围绝经期或绝经后妇女以及1000例开始内分泌治疗的乳腺癌患者的绝经和治疗相关密度测量的变化。该方案将回答：1)哪种自动密度测量或测量组合在FFDM环境中作为乳腺癌的风险因素和检测治疗反应中密度的变化在临床上最有用？2)密度测量在年轻女性和老年女性以及特定类型的乳腺癌中是否表现相似？3)与单项测量相比，多项乳房密度测量是否能改善风险关联？这项建议将影响全美的乳房密度评估，使临床实践标准化，并有机会将密度测量整合到个性化的风险评估和筛查中。