Combined Breast Tomosynthesis and Near Infrared Spectroscopy for Cancer Detection

乳腺断层合成和近红外光谱相结合用于癌症检测

• 批准号: 8816057
• 负责人: Kelly Michaelsen
• 金额: $ 4.81万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-22 至 2016-03-21
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8816057
• 关键词: Advanced Development; Applications Grants; Biological; Breast; Breast Cancer Detection; Cancer Detection; Characteristics; Clinical; Clinical Research; Computer software; Data; Diagnosis; Digital Breast Tomosynthesis; Disease; Doctor of Philosophy; Doctor' s Degree; Fellowship; Funding; Future; Goals; Health; Hemoglobin; Histopathology; Image; Imaging Techniques; Institution; Knowledge; Lesion; Link; Lipids; Malignant - descriptor; Malignant Neoplasms; Mammary Gland Parenchyma; Measurement; Metabolic; Metabolism; Methods; Microscopic; Modality; Monitor; NIH Program Announcements; Nature; Near-Infrared Spectroscopy; Normal tissue morphology; Optics; Pathologic; Pathology; Patient Participation; Patients; Performance; Predictive Value; Predoctoral Individual National Research Service Award; Property; Recovery; Resolution; Roentgen Rays; Scanning; Screening for cancer; System; Tissues; Water; breast imaging; contrast imaging; cost; density; design; experience; imaging system; improved; insight; interest; malignant breast neoplasm; novel; optical imaging; tomography

DESCRIPTION (provided by applicant): This grant application responds to Program Announcement Number PA-11-110 (Ruth L. Kirschstein National Research Service Awards for Individual Predoctoral MD/PhD and Other Dual Doctoral Degree Fellows) by proposing a study on the differences in optical signatures between healthy and malignant breast tissue using a combined Near Infrared (NIR) spectral tomography (NIRST) and digital breast tomosynthesis (DBT) system. This is a single exam platform that synergistically combines the functional parameters obtained through NIRST with the high-resolution three-dimensional structural information available from DBT for breast cancer surveillance. This study aims to examine and eliminate several potential barriers to clinical implementation and subject participation as well a optimize system performance for detection of cancer. Through clinical exams of both healthy and diseased breasts, this project will examine relationships between optical scattering parameters, X-ray density and other DBT characteristics with the goal of estimating optical scattering from the DBT, eliminating the need for optical hardware for scattering measurements. Optical phantoms will independently verify contrast recovery linearity and scatter estimation. The study will analyze the effects of breast compression levels during the NIRST/DBT exam on optical tissue signatures in both healthy and diseased subjects, by performing combined scans at two compression levels. Determination of optical contrast levels between a region of interest (ROI) and background will be characterized for each subject at each compression level and DBT images at each level will also be compared. The focus of this part of the study is to identify what compression level can most accurately identify lesions and evaluate the necessity of full compression exams. Furthermore, comparisons between pathologic results and NIRST/DBT images of subjects with disease will be performed in order to further understand the biological origins of the optical property measurements. By the end of the proposed funding period, we expect to have developed an increased knowledge of the nature of tissue scattering, the effects of breast compression and the underlying histopathology of breast cancer that creates image contrast. These advances will direct optimization of the hardware and software components of NIRST/DBT system to increase the likelihood of significantly improved ROC characteristics and positive predictive value of a combined system compared to DBT alone while simultaneously minimizing system cost and complexity.

描述（由申请人提供）：本拨款申请响应计划公告号 PA-11-110（Ruth L. Kirschstein 个人博士前 MD/PhD 和其他双博士学位研究员国家研究服务奖），提出一项使用近红外 (NIR) 光谱断层扫描 (NIRST) 和数字乳房断层合成相结合的健康和恶性乳腺组织之间光学特征差异的研究 （DBT）系统。这是一个单一的检查平台，它将通过 NIRST 获得的功能参数与 DBT 提供的高分辨率三维结构信息协同结合起来，用于乳腺癌监测。本研究旨在检查并消除临床实施和受试者参与的几个潜在障碍，并优化癌症检测的系统性能。通过对健康和患病乳房的临床检查，该项目将检查光学散射参数、X 射线密度和其他 DBT 特性之间的关系，目的是估计 DBT 的光学散射，从而消除对光学硬件进行散射测量的需要。光学模型将独立验证对比度恢复线性度和散射估计。该研究将通过在两个压缩水平上进行组合扫描，分析 NIRST/DBT 检查期间乳房压缩水平对健康和患病受试者光学组织特征的影响。确定感兴趣区域 (ROI) 和背景之间的光学对比度水平将针对每个压缩级别的每个受试者进行表征，并且还将比较每个级别的 DBT 图像。这部分研究的重点是确定什么压缩级别可以最准确地识别病变并评估全面压缩检查的必要性。此外，还将对患病受试者的病理结果和 NIRST/DBT 图像进行比较，以进一步了解光学特性测量的生物学起源。在拟议的资助期结束时，我们预计将对组织散射的性质、乳房压缩的影响以及产生图像对比度的乳腺癌的潜在组织病理学有更多的了解。这些进步将直接优化 NIRST/DBT 系统的硬件和软件组件，与单独的 DBT 相比，增加组合系统显着改善 ROC 特性和阳性预测值的可能性，同时最大限度地降低系统成本和复杂性。