# MammoCAT Advanced Full Field Digital Mammography System

> **NIH NIH R44** · FISCHER IMAGING, INC. · 2023 · $979,261

## Abstract

Project Summary
Breast cancer remains a leading cause of cancer related death among women in the United States.
Mammography, the only cost effective method approved for population screening of breast cancer, fails
to find cancer in many women and causes too many unnecessary call backs on the rest. Fischer Imaging
has developed proprietary “slot scanning” technology that significantly improves contrast and image
resolution of today’s mammography and lowers the radiation dose. Our technology also removes the
need for painful breast compression. These essential enhancements will improve clinical performance
by finding missed cancers and reducing unnecessary treatment while increasing patient compliance with
mammography recommendations. This proposal describes the development and feasibility bench
testing of MammoCAT™ DM, our first product, which will provide superior two view mammography.
This product is regulated as a Class II, 510k device and current procedure reimbursement by CMS and
private payors allows a facility with an average patient volume to pay off the device in about a year. A
key feature of MammoCAT DM will be upgradeability to MammoCAT DBT, our second product, which
will allow image capture over multiple angles to give it digital breast tomosynthesis capability.

## Key facts

- **NIH application ID:** 10580860
- **Project number:** 5R44CA268305-02
- **Recipient organization:** FISCHER IMAGING, INC.
- **Principal Investigator:** Shabbir Bakir Bambot
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $979,261
- **Award type:** 5
- **Project period:** 2022-03-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10580860

## Citation

> US National Institutes of Health, RePORTER application 10580860, MammoCAT Advanced Full Field Digital Mammography System (5R44CA268305-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10580860. Licensed CC0.

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