# Improved cancer screening with synthetic and stationary 3D mammography

> **NIH NIH F30** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $49,576

## Abstract

PROJECT SUMMARY/ABSTRACT
Motivation and clinical relevance: Early detection is the key to surviving breast cancer. This project aims to
complete the development of an experimental carbon nanotube-enabled x-ray imaging device for breast cancer
screening. Best described as stationary digital breast tomosynthesis (sDBT), this unique approach to 3D breast
imaging has been shown in pre-clinical testing to collect higher quality information than the commercially-
available 3D mammography systems currently in use. As such, it has the potential to improve the early detection
of cancer. However, as with all 3D imaging, the images presented to the reader are the product of extensive
computer processing. For 3D breast imaging, the final and crucial step is the presentation of a synthetic
mammogram. Purpose and hypotheses: The purpose of this project is to integrate synthetic mammography
into the image processing capability of the sDBT system, thereby providing a complete clinical tool. We
hypothesize that (1) the quality of the sDBT synthetic mammogram will be greater than the quality of synthetic
mammograms from available 3D mammography systems and (2) readers will prefer the sDBT synthetic
mammogram over standard mammograms when interpreting diagnostically-important image features. Methods:
To test these hypotheses, the research will involve two specific aims. First, phantom-based experimentation will
be used to develop image processing algorithms that optimize the quality of information generated by sDBT and
displayed as a synthetic mammogram. Quantitative image quality metrics (detectability indices) will be used for
optimization, with images from commercially-available 2D and 3D mammography devices providing references
for comparison. Second, the clinical utility of the optimized synthetic mammogram will be tested in reader studies,
when applied to a library of sDBT images that have been collected previously in human trials. These studies will
quantify reader performance (diagnostic accuracy) and preference, when interpreting clinically-important image
features, such as masses and microcalcifications, in a head-to-head comparison of sDBT synthetic
mammograms to standard mammograms. Project value: Since trials assessing the value of 3D mammography
should include a synthetic mammogram, this project will have a direct clinical impact. It will provide the foundation
for continued human testing of this promising high-resolution imaging system, which has the potential to improve
breast cancer detection. Training Plan: It is anticipated that this project will require two years, forming the core
of the dissertation work to complete a PhD in Biomedical Engineering. It will be carried out in a basic research
lab with scientists and computer programmers and will also involve working with patient data, under the
supervision of physician-scientists and radiologists. Since this project combines basic experimentation with a
direct clinical application, it should prov...

## Key facts

- **NIH application ID:** 10069315
- **Project number:** 5F30CA235892-03
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Andrew Connor Puett
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $49,576
- **Award type:** 5
- **Project period:** 2019-01-01 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10069315

## Citation

> US National Institutes of Health, RePORTER application 10069315, Improved cancer screening with synthetic and stationary 3D mammography (5F30CA235892-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10069315. Licensed CC0.

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