Development of Quantitative Multi-Contrast Molecular Imaging

The Problem There are a number of important yet unanswered biological questions about how cells and molecules behave in the body (in vivo). Although researchers have discovered a large amount of information by using cutting edge tools to map individual cells down to the genome, in many cases we still don't understand how populations of cells actually interact and behave in the body. Several imaging techniques have been developed that allow monitoring of cells over time in vivo, but the techniques that offer the best quality images do not provide quantitative information, limiting our observations. Additionally, although we have developed technologies to image various different types of contrast agents like gadolinium (Gd) or iron oxide, almost all studies only use one agent at a time. The Solution Magnetic resonance imaging (MRI) is well known for its ability to image a large variety of materials, from human tissue to concrete. It can also be used to track individual cells and molecules that have been labeled with a contrast agent. This program will develop and evaluate MRI-based quantitative measurements of biological agents tagged with superparamagnetic iron oxide (SPIO) in combination with a special Gd agent that can indicate when cells are dying, also known as apoptosis. My project will have three distinct steps in it. In the first step, we will optimize a special type of MRI pulse sequence called magnetic resonance fingerprinting (MRF). Our lab has implemented this technique for imaging both SPIO and Gd, but right now it is not fast enough to use in vivo preclinically. We will therefore work to make this technique faster and even more accurate. The second step of the program will use MRF to look at SPIO-labeled cells and the Gd contrast agent that measures apoptosis. Because this agent is modified in cells that are dying, it has two unique forms - a) the version that gets trapped only in dying cells, and b) the precursor form of the probe that can get into any cells but will eventually be cleared. We will use MRF to distinguish between the different versions of the probe and still measure the labeled cells to see if there is a response to e.g. cancer therapy. The last part of the program will be to optimize the specialized data analysis for this project. We will look at an emerging type of automated analysis called radiomics, which can be used to automatically pick out important features in large amounts of imaging data that are not obvious to the human eye. The Impact This program of research describes a coherent sequence of projects that will develop and validate novel tools for simultaneous MRI-based quantification of two types of cells and molecules labeled with SPIO or Gd. This work will result in advanced imaging technologies that have broad applicability in a number of biological fields and can improve understanding of basic immunological behavior, particularly with respect to cancer therapies.