Feindel Seminar Series: Hyperpolarized MRI: Visualize Metabolism - As It Happens

About this event

Hyperpolarized MRI: Visualize Metabolism - As It Happens Paul Weavers, General Manager, NVision Metabolism is central to human health and disease, yet capturing its dynamics in vivo has long remained a challenge. Hyperpolarized magnetic resonance imaging (HP MRI) overcomes this by considerably enhancing the signal of 13C-labeled molecules (such as [1-13C]pyruvate), transforming MRI into a real-time, non-invasive tool for metabolic imaging. This talk will describe the motivation for utilizing hyperpolarized carbon, the types of metabolic readouts we can expect from the technique, some examples from the literature, and a technological context for where the field is now. Hyperpolarized pyruvate has been applied across a variety of applications, a selected few are described here: Multiple Sclerosis (MS): Research in EAE and Cuprizone mouse models utilizes hyperpolarized (HP) MRI to monitor neuroinflammation in vivo. The technology detects elevated pyruvate-to-lactate conversion, which reflects glycolytic shifts in disease. This metabolic readout allows for the non-invasive monitoring of therapeutic responses to immunomodulatory drugs—such as dimethyl fumarate and fingolimod—that are often invisible on standard anatomical MRI. Traumatic Brain Injury (TBI): Investigations using controlled cortical impact (CCI) models track secondary injury by simultaneously measuring pyruvate-to-bicarbonate conversion (a proxy for mitochondrial function) and pyruvate-to-lactate conversion (a marker of neuroinflammation). Studies have demonstrated that this technology can evaluate the efficacy of anti-inflammatory interventions, such as CSF1-R inhibitor (e.g., PLX5622) administration, which leads to microglial depletion and a normalization of elevated lactate levels. Aging/Alzheimer’s: In preclinical models of cognitive impairment induced by high-fat diets, HP-MRI detects metabolic alterations (increased lactate-to-pyruvate ratios) as early as 3 months, well before behavioral deficits manifest at 6 months. Furthermore, recent studies are establishing healthy human cerebral metabolic baselines across different age groups to enable the differentiation of normal age-related metabolic changes from early pathological signatures associated with neurodegeneration. PDAC Staging: Research differentiates molecular subtypes of pancreatic ductal adenocarcinoma (PDAC), such as the aggressive Quasi-mesenchymal (QM) subtype versus the classical subtype, based on their distinct metabolic activities. Additionally, studies using patient-derived xenografts have shown that tumor p53 status determines the response to LDHA inhibitors (like FX11); lactate levels decrease in sensitive subtypes but increase in resistant ones, providing a potential tool for targeted therapy assessment. Ovarian Cancer: Studies leveraging patient-derived organoid (PDO) models indicate that HP-MRI outperforms conventional FDG-PET in disease characterization. HP-MRI captures distinct metabolic profiles (specifically distinguishing between high-OXPHOS and low-OXPHOS tumors) that FDG-PET fails to detect. This capability enables more precise monitoring of variable chemotherapy responses (e.g., carboplatin) in ovarian cancer. GBM Subtyping: Studies have shown that the lactate-to-pyruvate signal ratio can effectively predict treatment response to radiation in glioblastoma models with different genotypes. These sub-types express differing levels of c-Myc, which acts to reduce the effectiveness of radiation in killing cancer cells. Knocking down c-Myc in a resistant tumor increases the effectiveness of radiation in killing the cancer cells. Higher lactate levels correspond to more resistant tumors. For more information, visit the web page