A novel framework for quantifying metabolic brain health - Project Summary An emerging theme in personalized medicine is the central role of metabolic dysfunction in disease and treatment response. As metabolic changes occur earlier than morphological changes, there are significant and untapped opportunities to incorporate metabolic markers into medical imaging. While medical imaging is an indispensable resource for the diagnosis and prognosis of disease, we do not have a way to reliably, repeatably, and non- invasively image metabolic abnormalities. Despite the mounting evidence that metabolism is involved in disease onset, treatment response and resistance, and prognosis, crucial metabolic information is left unexplored and uncharacterized. To facilitate a new paradigm in medical imaging and clinical decision making, I propose the development of a novel investigative approach termed “metaboloradiomics.” Metaboloradiomics will incorporate non-invasive metabolic imaging with conventional morphological imaging into a metabolism driven -omics model. By overcoming the existing challenges of clinical magnetic resonance spectroscopy data collection, analysis, and integration, combined with a suite of innovative computational tools, my vision is to enable an entirely new approach to magnetic resonance imaging that will enable researchers and clinicians to routinely characterize the role of metabolism in disease. The proposed research will facilitate a paradigm shift in magnetic resonance- based medical imaging and is ideally suited to the New Innovator Award mechanism. These methods will be applicable to a wide range of diseases, spanning the missions of multiple NIH Institutes and Centers. As a new investigator, my cross-disciplinary background in chemistry and biomedical engineering, combined with immersion in a clinical radiology department, has provided me with a unique skillset and specific expertise to execute this high-risk and high-impact research.
