Development of Protein MRI Contrast Agent for Precision Imaging Lung Fibrosis - 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.
