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

基本信息

批准号：
8693976
负责人：
KARLA M KERLIKOWSKE
金额：
$ 58.05万
依托单位：
MAYO CLINIC ROCHESTER
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-01 至 2018-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8693976
关键词：
Adjuvant Therapy Age American College of Radiology Area Aromatase Inhibitors Breast 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 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 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 public health relevance radiologist response screening

项目摘要

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）：通过胶片乳房 X 光检查评估的乳房密度是乳腺癌最强的危险因素之一，不仅为风险评估提供重要信息，而且还为调整乳房筛查方法和确定对治疗的反应提供重要信息。迄今为止，乳腺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、客观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 类定性评估是最广泛使用的临床密度测量，但它是主观的，需要训练有素的放射科医生，并不总是报告，而且有限其能够评估反应疗法中微小但可能有意义的密度变化。我们和其他人在全视野数字乳房X线摄影（FFDM）上开发了有前途的自动化乳房X线摄影测量，包括面积、体积和变化密度测量，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测量或其组合在同一女性的 FFDM 图像上的性能，以告知在临床环境中使用的最佳测量方法。由于美国超过 85% 的乳房 X 光检查采用 FFDM，因此需要在 FFDM 环境中开发和检查密度测量，以转化为当今临床护理中的使用。我们建议检查和比较 FFDM 的乳房 X 光检查措施与乳腺癌的关联，并评估其检测梅奥诊所和旧金山乳房 X 光检查登记处乳房筛查实践中接受 FFDM 的 35-75 岁女性对更年期和激素治疗的反应变化的能力2006年至2015年间。具体来说，我们建议 1) 在一项针对 2800 例乳腺癌病例和 5600 例匹配对照的大型巢式病例对照研究中检索诊断前的连续数字乳房 X 光检查（或对照的相应日期）、BI-RADS 密度和协变量，并估计所有图像的自动面积、体积和变化密度测量； 2) 检查最早和多次后续乳房 X 光检查的乳腺密度测量值与乳腺癌的关联，并评估这些关联是否因年龄、浸润性乳腺癌与原位乳腺癌以及 ER、PR 和 HER-2 定义的亚型而异； 3) 评估 500 名健康围绝经期妇女、1000 名开始激素治疗的围绝经期或绝经后妇女以及 1000 名开始内分泌治疗的乳腺癌病例的 FFDM 密度测量与绝经期和治疗相关的变化。该协议将回答： 1) 在 FFDM 环境中，哪种自动密度测量或测量组合在临床上最有用，作为乳腺癌的危险因素，并用于检测治疗反应中的密度变化？ 2) 密度测量在年轻女性与老年女性以及特定类型乳腺癌中的表现是否相似？ 3) 与单一测量相比，多种乳房密度测量是否可以改善风险关联？该提案将影响整个美国的乳腺密度评估，从而实现临床实践的标准化，并有机会将密度测量纳入个性化风险评估和筛查。