Breast cancer is the 2nd most common cancer among American women, roughly 1 in 8 women will develop breast cancer, and ultimately about 1 in 36 women will die of the disease. Mammographic screening is a vital tool in detecting cancer early, but particularly for women with dense breasts (~50% of women) it is significantly less effective. Currently 31 out of 50 states require informing women of their breast density, which implies an increased risk of cancer, reduced mammographic sensitivity, and likely no recommendation for further screening. Ultrasound is a supplemental screening technique that has good sensitivity in dense breasts, is inexpensive, and is widely available, but unfortunately, it has high rates of false positives. Electrical impedance tomography (EIT) is a second attractive modality that is low-cost and has shown promise for cancer detection and in differentiating fibrocystic tissues from other tissues ? which could aid ultrasound?s ability to distinguish cancer. In this project, we aim to combine ultrasound and EIT to improve ultrasound?s ability to detect cancer. The technologies will be combined using an automated whole breast ultrasound (AWB-US), which based on our recent studies should significantly improve EIT?s accuracy by ensuring accurate control over the domain shape and incorporating spatial data obtained from the ultrasound imaging. Thus a combined AWB-US/EIT system may significantly reduce the number of false positives of AWB-US. A series of realistic, dense-breast phantoms will be used to evaluate the system, and a small pilot study of five women will prepare us for a larger clinical study.
The Specific Aims of this project are to 1) Build an electrode array and walls into iVu Imaging?s AWB-US system so that the AWB-US and EIT systems are integrated and 2) Perform a series of realistic, dense-breast phantom experiments and collect data from 5 women with screen positive findings scheduled for biopsy. The women will be imaged with the AWS-US/EIT system prior to a scheduled breast biopsy of a suspicious lesion, and in-vivo electrical impedance measurements taken during the biopsy will provide ground-truth tissue conductivity values. Accuracy of phantom and tissue conductivities from EIT imaging will be quantified and used to assess the accuracy of AWB-US/EIT?s reconstructions ? which should provide initial evidence that this combined system can reduce false positives. Dartmouth?s previously developed EIT and US/EIT technology (including breast EIT systems); expertise in EIT and medical applications, and close collaboration with Dartmouth?s medical center gives this project a unique and strong opportunity for success. A positive end of this project will be a fully functional AWB- US/EIT system that yields accurate reconstructions of lesion conductivities. This will put us in a great position to administer a larger study to verify the potential this technology has to standard AWB-US imaging, and thus be an important improvement in breast cancer screening.

Public Health Relevance

Breast cancer is a global problem with approximately 1 in 8 women in the United States being diagnosed, and the current standard screening using X-ray mammography has disadvantages especially for women with the common trait of having dense breasts (~50% of women). Currently 31 out of 50 states require informing women of their breast density, which implies an increased risk of cancer, reduced mammographic sensitivity, and likely no recommendation for further screening. This project aims to combine two low-cost, non-ionizing technologies (ultrasound and electrical impedance tomography) to produce a technology to significantly improve the screening for these millions of women.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Research Grants (R03)
Project #
1R03EB027224-01A1
Application #
9744388
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
King, Randy Lee
Project Start
2019-06-01
Project End
2021-03-31
Budget Start
2019-06-01
Budget End
2020-03-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Dartmouth College
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
03755