Treatment Planning using Physiologic MRI Data

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DESCRIPTION (provided by applicant): This application requests support to integrate physiologic magnetic resonance imaging (MRI) methods to better describe and delineate glioblastoma multiforme (GBM) brain tumors in preparation for radiation therapy treatment. We hypothesize that the use of these imaging methods will result in more precise radiotherapy treatment planning. The proposed research is based upon extensive preliminary data indicating chemical shift imaging (CSI), perfusion and diffusion imaging and MR-based hypoxia mapping add additional information about tumor physiology that can be incorporated into a treatment plan with the goal of decreasing the rate of tumor recurrence. Although regions of abnormality on T2 MRI are known to correlate with microscopic spread of tumor, some of this abnormality represents edema without malignant cells while other areas may contain a high concentration of malignant cells that should be incorporated into the treatment boost volume. While most malignant brain tumors recur within the radiation treatment fields, 20- 25% of recurrences occur outside of these fields. For this reason, we expect that in at least 25% of patients there will be a boost volume discrepancy > 10%. We anticipate that at least some of these out-of-field recurrences could be predicted by the use of the imaging techniques. Thus, the imaging techniques will be used to identify "high-risk subvolumes" within each tumor, which may be at high risk of recurrence. After completing radiotherapy, patients will be followed with serial physiologic MRI scans; the study endpoint being the first recurrence. The SPECIFIC AIMS are: 1) Create maps of hypoxia within individual tumors using blood oxygen level dependent (BOLD) MRI combined with carbogen breathing. 2) Probe the proliferative potential of tumors using chemical-shift imaging (CSI). 3) Assess the angiogenic features of a tumor using contrast enhanced perfusion MRI. 4) Assess the cellularity of a tumor using diffusion-weighted MRI. 5) Compare the locations and areas of maps created in AIMS 1-4. 6) Generate clinical target volumes (CTV's) from the regions defined by AIM 5.