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.

Public Health Relevance

This project aims to improve breast cancer screening by optimizing a new imaging system. This new system combines breast tomosynthesis, which uses X-rays to produces high resolution three dimensional images, with near infrared imaging, which provides information about tissue metabolism, such as the amount of hemoglobin, water and lipids that are present. Combining these two imaging techniques may make it easier to distinguish cancer from normal tissue during a breast cancer screening exam.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
1F30CA168079-01A1
Application #
8457475
Study Section
Special Emphasis Panel (ZRG1-F15-P (20))
Program Officer
Damico, Mark W
Project Start
2013-03-22
Project End
2017-03-21
Budget Start
2013-03-22
Budget End
2014-03-21
Support Year
1
Fiscal Year
2013
Total Cost
$47,232
Indirect Cost
Name
Dartmouth College
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
03755
Michaelsen, Kelly E; Krishnaswamy, Venkataramanan; Shi, Linxi et al. (2016) Effects of breast density and compression on normal breast tissue hemodynamics through breast tomosynthesis guided near-infrared spectral tomography. J Biomed Opt 21:91316
Michaelsen, Kelly E; Krishnaswamy, Venkataramanan; Shi, Linxi et al. (2015) Calibration and optimization of 3D digital breast tomosynthesis guided near infrared spectral tomography. Biomed Opt Express 6:4981-91
Mastanduno, Michael A; Xu, Junqing; El-Ghussein, Fadi et al. (2014) Sensitivity of MRI-guided near-infrared spectroscopy clinical breast exam data and its impact on diagnostic performance. Biomed Opt Express 5:3103-15
Michaelsen, Kelly E; Krishnaswamy, Venkataramanan; Shenoy, Adele et al. (2014) Anthropomorphic breast phantoms with physiological water, lipid, and hemoglobin content for near-infrared spectral tomography. J Biomed Opt 19:026012