# Development of Protein MRI Contrast Agent for Precision Imaging Lung Fibrosis

> **NIH NIH R61** · GEORGIA STATE UNIVERSITY · 2024 · $401,613

## Abstract

Summary
Lung diseases, such as interstitial lung diseases, including idiopathic pulmonary fibrosis (IPF), chronic
obstructive pulmonary disease (COPD), and acute viral infection, are major leading causes of death worldwide.
There is a pressing unmet medical need to develop noninvasive imaging methodologies and contrast agents to
detect early stages of lung fibrosis, and to stage fibrosis severity and heterogeneous expression of collagen.
MRI is potentially the best imaging modality for early detection and monitoring of lung disease progression and
regression8-10 due to its advantage of not using harmful ionizing radiation, which reduces safety concerns for
increased accessibility to patient populations, including children and pregnant women, and its superior ability to
longitudinally characterize tissue properties. However, lung imaging by MRI, especially in small animals,
encounters many unique difficulties11-13 including respiratory cardiac motion, the relatively low tissue density, and
short relaxation times. A collagen-targeted MRI contrast agent overcoming these challenges will address the
critical unmet medical need for lung fibrosis imaging. Dr. Yang (PI) at Georgia State University has pioneered a
novel class of protein-based MRI contrast agents (ProCAs) targeting molecular biomarkers. ProCA32.collagenL
specifically targets collagen and is tailored to lung imaging, exhibiting strong specificity to overexpressed collagen in
patient lung fibrosis tissues with high translational potential. The goal of this R61/R33 Catalyze application is to
create stable and homogeneous ProCA32.collagenL for monitoring lung fibrosis progression by
ProCA32.collagenL enabled precision MRI. In R61 phase, we will develop homogenous collagen-targeted protein
MRI contrast agents for precision Imaging of lung fibrosis. Various biophysical methods will be performed to
ensure homogenous and strong stability of formulated Gd-ProCA32.collagenL complex. Our Go / No-Go
milestones is to identify stable Gd-ProCA32.collagenL with desired homogeneity. In R33 Phase, we first aim to
evaluate in vivo imaging capability of lung fibrosis for early detection using multiple mouse models. Quantitative
mapping of fibrosis remodeling using established radio-histological methodology. We then aim to evaluate pMRI’s
ability to monitor drug treatment response in vivo. We will define histopathologic and radiologic signatures of lung
fibrosis and their treatment changes and improve sensitivity using machine learning AI methodology. Our
transformative product will open a new avenue for non-invasive longitudinal early diagnosis and monitoring of
lung fibrosis treatment with disease activity by pMRI without radiation.

## Key facts

- **NIH application ID:** 10900297
- **Project number:** 1R61HL173984-01
- **Recipient organization:** GEORGIA STATE UNIVERSITY
- **Principal Investigator:** Jenny J. Yang
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $401,613
- **Award type:** 1
- **Project period:** 2024-05-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10900297

## Citation

> US National Institutes of Health, RePORTER application 10900297, Development of Protein MRI Contrast Agent for Precision Imaging Lung Fibrosis (1R61HL173984-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10900297. Licensed CC0.

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