PROJECT SUMMARY/ABSTRACT This project proposes to develop methods for automated, real-time, single-voxel magnetic resonance spectroscopy (MRS) in brain tumors, integrate these methods with a clinical MRI system, evaluate their performance, and distribute them as open-source tools to the research community. MRS can provide metabolic information noninvasively for assessment of tumor phenotype and therapeutic response. Single-voxel MRS methods provide the best quality and most reliable data, but require the scanner operator to have a high skill level and expertise to produce good quality results. The need for this expert involvement in both acquisition and processing remains a critical barrier to the translation of MRS methods to clinical research sites without spectroscopy experts and to clinical practice. The first part of this project is to develop a method for 3D voxel placement using image guidance, integrate this method with a clinical MR system, and evaluate its performance. In the second part, we will automate our advanced MRS methods. In the third part, we will create real-time, automatic quantification tool specific to the obtained MRS data that will provide clinically interpretable results. We identified collaborators, the brain cancer researchers and clinicians, who will be early adopters and beta-testers of our tools. Successful completion of this project will improve data robustness and quality, eliminating the need for the expert interaction at the time of the scan and enabling adoption of MRS in multi- site clinical trials and clinical practice.

PROJECT NARRATIVE Magnetic resonance spectroscopy (MRS) can provide metabolic information noninvasively for assessment of tumor type and treatment response in any body part. The clinical impact of MRS has been limited by the technical expertise required to make these measurements. This research project will develop and evaluate automated tools to make MRS measurements easier and more robust for both research and clinical uses.