Motivation: Glioblastoma (GBM) treatment planning is limited by standard imaging, as contrast-enhanced T1-weighted MRI often cannot capture the full extent of tumor infiltration. Improved imaging techniques are needed for more precise surgical and radiation therapy guidance. Goal(s): Our goal was to integrate high-resolution, whole-brain 3D spectroscopic MRI (sMRI) into clinical workflows, enabling comprehensive tumor visualization to guide treatment in GBM patients. Approach: We developed an EPSI-based sMRI workflow, sequence distribution through Siemens platforms, and inline processing to significantly reduce data output, integrating it with the Brain Imaging Collaboration Suite (BrICS) to streamline treatment planning. Results: Inline python modules (pyMIDAS) demonstrated similar output to MIDAS. Impact: Our work brings high-resolution, 3D metabolic imaging into clinical practice for glioblastoma, providing better tools for treatment planning. This advancement could lead to more effective therapies and new research opportunities in brain tumor management, benefiting patients with improved care options.
Sharghi et al. (Tue,) studied this question.