Oncology
Characterize tumor models and predict responses to novel interventions in vivo
Metabolic imaging distinguishes ovarian cancer subtypes and detects their early and variable responses to treatment. Chia et al. 2024. Oncogene.
Challenge
Leverage HP MRI data to empower your basic biomedical research
Approach
Map these critical metabolic fluxes in vivo with metabolic imaging agents
Outcome
Use these real-time insights to precisely characterize tumor models and predict responses to novel interventions
- Assessment of early response to neoadjuvant chemotherapy in multi-site high-grade serous ovarian cancer using hyperpolarized-13C MRI. Beer et al. 2025. EJNMMI Res.
Exploratory study demonstrating the potential of hyperpolarized [1-13C]pyruvate to monitor early response to neoadjuvant chemotherapy in patients with high-grade serous ovarian cancer.
- Metabolic Imaging Detects Resistance to PI3Kα Inhibition Mediated by Persistent FOXM1 Expression in ER+ Breast Cancer. Ros et al. 2020. Cancer Cell.
Hyperpolarized [1-13C]pyruvate provides a window into metabolic signaling to enable in vivo validation of resistance mechanisms to PI3Kα inhibitors in ER-positive breast cancer models.
