Assessment of Treatment Response of Nasopharyngeal Cancer Using Simultaneous 18F-FDG-PET and MRI

The overarching goal of this study is to develop PET/MR techniques for accurate assessment of treatment response during and immediately after chemoradiation therapy. The central hypothesis is that the GMR measured using a simultaneous PET/MR scanner can more accurately detect residual tumor than conventional SUV measures from PET alone. It is important to note that SUV depends on both tumor metabolic rate and tracer delivery, which makes the interpretation of SUV challenging. For instance, inflammatory tissue can have high SUV due to increased vascularity and vascular permeability and cannot be easily differentiated from tumor based on the SUV. Investigators hypothesize that inflammatory tissue will have lower GMR than residual tumor that contain highly proliferating cells with increased expression of glucose transporters (GLUT). Measuring GMR accurately will improve the specificity of PET while maintaining the high sensitivity of PET for detection of residual tumor. In order to test our hypothesis, investigators propose to conduct dynamic PET and MRI scans with NPC patients who are undergoing a conventional two-stage chemoradiation therapy at our institution; the first stage for 7-week chemoradiation therapy followed by the second stage for 3-month chemotherapy. A combination of PET/CT and nasopharynx MRI is currently obtained before the initiation of treatment and 3 months after completion of treatment to assess treatment response.

This study proposes to introduce PET/MR scans at the time of these exams (scan #1 for pre-treatment & scan #4 for 3 months after completion) and to add two additional PET/MR scans in between them; one immediately after the first stage of treatment (scan #2) and another one immediately after the second stage (scan #3). A primary clinical endpoint of this study is the treatment response assessed at 3 months after completion of treatment. A secondary endpoint is 6 month follow-up exam. Complete responder will be determined based on clinical and imaging assessment of residual tumor size at each endpoint.

It is hoped that preliminary data obtained from this study will be useful in planning larger studies to formally investigate the utility of GMR for detection of residual tumor and prediction of treatment response.