Abstract #0516

Estimation of Brain Tissue Composition and Voxel Location in MR Spectroscopy Using Neural Networks

Eduardo Coello¹, Molly F. Charney¹, Tyler C. Starr¹, Huijun Liao¹, Marcia Louis², and Alexander P. Lin¹

¹Radiology, Brigham and Women's Hospital, Boston, MA, United States, ²Electrical and Computer Engineering, Boston University, Boston, MA, United States

This work presents a machine learning method to estimate the tissue partial volumes of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), in a given MR spectroscopy voxel, providing an alternative to the standard time‑intensive MRI segmentation pipeline. The tissue composition was determined from quantified metabolic concentrations using a neural networks regression model. Moreover, a classification model was trained to determine the brain region corresponding to a measured spectrum from both metabolic components and tissue volumes.

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