Improved whole-brain spectroscopic MRI for radiation therapy planning

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Identifying the extent of brain tumor margins for radiation treatment planning remains a challenging task due to the infiltrative nature of these tumors and limitations in current standard imaging methods. Multiple studies including our own have demonstrated that an MR technique for detecting metabolites in tissue, MR spectroscopic imaging or spectroscopic MRI (sMRI), can detect areas of infiltrating tumor with a high degree of sensitivity and specificity, enabling better radiation treatment of areas that lead to early recurrence and extending life. sMRI enables the identification of tumor extent that is marked by increased Choline/N-Acetylaspartate ratios, including regions that are not detectable by diagnostic MRI and that are normally left untreated. By allowing these previously undetected regions to be treated, sMRI has the potential to improve the efficacy of radiation treatment and significantly delay recurrence. In our 3-site sMRI-guided radiation dose escalation pilot study which was completed in 2019, we were able to demonstrate feasibility and safety. Survival analysis of all 30 GBM patients shows a promising median overall survival (OS) of 23 months compared to 16 months OS for GBM patients receiving standard-of-care. Our trial has been approved as a National Clinical Trial Network (ECOG-ACRIN) trial (EAF211). This is a great opportunity to disseminate this technique with staff support from ACRIN and American College of Radiology (ACR). We will achieve the goal in the renewal funding period of our current project by leveraging diverse expertise at three research sites and collaboration with Siemens Healthineers to engineer and validate technological improvements needed to improve sMRI acquisition, analysis, and clinical integration. These improvements include: (1) updated rapid and motion-robust sMRI for improved image quality; (2) new accelerated data processing pipelines to return Cho/NAA ratio maps to PACS for clinically timely radiology reporting; (3) new processing, display, and analysis methods that will present metabolite maps in an efficient manner with a clinician-friendly interface that enables integration with radiation treatment planning software systems; and (4) development of new tools to predict the optimal baseline RT planning strategies using sMRI. The completion of this study will provide robust sMRI acquisition methods and software tools that are ready to be deployed in clinical use and which will help guide important treatment decisions.