Stanford Cancer Institute

SCI Innovation Award

March 2024

Nancy Pham, MD, clinical assistant professor, radiology, Quynh-Thu Le, MD, Katharine Dexter McCormick and Stanley McCormick Memorial Professor, Dimitrios Colevas, MD, professor of medicine (oncology), Nancy Fischbein, MD, professor of radiology, and Michael Iv, MD, clinical associate professor, radiology, have been granted an SCI Innovation Award for their project, “Integration of MR perfusion and metabolic imaging biomarkers with circulating EBV-DNA for predicting treatment response and prognostication in patients with nasopharyngeal cancer.” Pham is a neuroradiologist using imaging approaches to treating patients with head and neck cancer (HNC). Le studies the role of tumor hypoxia in HNC and investigates approaches to regenerate salivary glands after radiation damage. She has led multicenter clinical trials to test novel drugs in HNC. Colevas is a medical oncologist with expertise in new drug development and multimodality treatment of HNC and has served as the principal investigators on multiple clinical trials. Fischbein has 30 years of experience in the evaluation and management of patients with nasopharyngeal cancer and has expertise in perfusion imaging in HNC. Iv’s research focuses on neuro-oncologic imaging and the implementation of a 3D quantitative brain tumor analysis pipeline.

Nasopharyngeal cancer (NPC) is the second leading cause of death among patients with head and neck cancer. Although it can be treated with chemoradiation, the cancer often recurs in up to 30% of patients. It is currently difficult to identify patients with risk of recurrence for several reasons. First, the current staging system for NPC is not very accurate and does not include all factors necessary to predict recurrence. Second, non-invasive approaches to predict recurrence in NPC are still lacking. And finally, the current imaging tests for NPC are suboptimal. Novel imaging techniques have the potential to improve diagnosis, treatment, and surveillance. One promising approach is MR perfusion imaging, which can measure blood flow through the tumor and can identify patients at highest risk for recurrence. With the support of the SCI Innovation Award, Pham, Le, Colevas, Fischbein and Iv will evaluate the performance of three different MR perfusion imaging techniques. They will also determine whether combining these approaches with other standard of care tests, such as blood tests and PET/CT scans, can help detect early signs of cancer recurrence.