Untreated Virtual Imaging Control (UVIC)
funded by the National Institutes of Health (www.nih.gov).
The UVIC grant proposal integrates mathematical modeling of tumor proliferation and invasion with advanced cancer imaging methods. The goals of our project are twofold:
1) To impact current clinical challenges with treatment of gliomas
2) provide tools for the development of new therapies for these challenging cancers.
Our first goal is to develop image-based response metrics based on the growth kinetics of each patient’s tumor, as seen on both anatomical imaging (MR) and functional imaging (PET and advanced MR). We will use mathematical modeling to develop a patient-specific UVIC that quantifies the dynamics of each patient’s tumor system. We will then test the UVIC model against a novel set of paired PET and MR images at multiple time-points (five on average) for each of 20 glioblastoma patients.
The overall goal of this project is to extend the UVIC model to the early response assessment of individual patients in clinical trials. This will provide a tool for the development of much-needed therapies that are more effective for gliomas.
The core investigators include
Kristin Swanson – University of Washington
Paul Kinahan – Image Research Lab (IRL) University of Washington