Abstract #0837

Super-resolution 3D MRSI for Mapping 2HG and Tumor Metabolism in Patients with Mutant IDH Glioma

Xianqi Li^1,2, Bernhard Strasser^1,2, Kourosh Jafari-Khouzani³, Bijaya Thapa^1,2, Julia Small^2,4, Daniel P Cahill^2,4, Jorg Dietrich^2,5, Tracy T Batchelor^2,5, and Ovidiu Andronesi^1,2

¹A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³iCAD, Nashua, NH, United States, ⁴Department of Neurosurgery, Massachusetts General Hospital, Charlestown, MA, United States, ⁵Department of Neurology, Massachusetts General Hospital, Charlestown, MA, United States

To improve the spatial resolution of 3D MRSI, a feature-based nonlocal means approach utilizing the structural information of high-resolution MR images is proposed. By estimating similarity between voxels using a feature vector that characterizes the laminar pattern of brain structures, a more accurate similarity measure is achieved compared to conventional upsampling methods. The preliminary results on simulated and in vivo data indicate the proposed method has great potential for clinically neuroimaging applications.

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