# Coupling Advanced Computational Analyses for Mammography and SHG Imaging for Early Detection of Breast Cancer Tissue Microenvironment Disruptions Accompanying Tumorigenesis

> **NIH NIH R15** · UNIVERSITY OF MAINE ORONO · 2020 · $418,484

## Abstract

Summary
 The breast tumor microenvironment plays a key role in the early development of cancer. An
improved understanding of the tumor microenvironment will support the early detection of disease and the
development of novel, more effective therapies. Current radiological interpretation of mammograms is
based on identifying breast lesions and assessing their potential malignancy and lethality. The biomedical
research community has yet to correlate the mammographic signatures of microenvironment alterations and
loss of tissue homeostasis accompanying, or even preceding tumorigenesis.
 The PI recently used a novel and powerful computational technique to demonstrate that tissue
disruption and loss of homeostasis can be quantitatively and objectively assessed from standard clinical
mammography. These preliminary findings pertain only to single diagnostic mammograms; the proposed
AREA project will analyze longitudinal sequences of mammograms over multiple years prior to, and
approaching the year of diagnosis, thus revealing the progression of healthy breast tissue microenvironment
towards a disrupted state. It is hypothesized that the tissue disorganization signature present in
mammographic data is associated with tissue disruption and loss of tissue homeostasis in the
microenvironment. Team members will verify this hypothesis by imaging breast tissue samples to
characterize, at the cellular level, disruption of collagen structures associated to tumor microenvironment
alterations accompanying tumorigenesis.
 This project's specific aims include: 1) verifying that mammographic tissue disruption
accompanies and perhaps even precedes tumor development; 2) developing an in silico model of
microcalcification growth into mammographic breast tissue environment, 3) improving the computational
efficiency of our data analysis, and 4) linking morphological features of the breast tumor microenvironment
imaged by mammography to cellular-scale alterations imaged by second harmonic generation microscopy.
 The proposed research will advance the education and career preparation of undergraduates within
Maine's only biomedical engineering program, nurture a growing partnership among the University of
Maine, Spectrum Healthcare Partners and Maine Medical Research Institute, introduce two UMaine faculty
to biomedical research, and support the early career development of two assistant professors.

## Key facts

- **NIH application ID:** 10046750
- **Project number:** 1R15CA246335-01A1
- **Recipient organization:** UNIVERSITY OF MAINE ORONO
- **Principal Investigator:** Andre Khalil
- **Activity code:** R15 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $418,484
- **Award type:** 1
- **Project period:** 2020-09-07 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10046750

## Citation

> US National Institutes of Health, RePORTER application 10046750, Coupling Advanced Computational Analyses for Mammography and SHG Imaging for Early Detection of Breast Cancer Tissue Microenvironment Disruptions Accompanying Tumorigenesis (1R15CA246335-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10046750. Licensed CC0.

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