Abstract #2836

Cohort Stratification by Clinical Symptoms through Unsupervised Learning Reveals Metabolic and Microstructural Brain Alterations in Former American Football Players

Molly Faith Charney¹, Janna Kochsiek^2,3, Tyler C. Starr¹, Michael Alosco⁴, Brett Martin⁴, Huijun Liao¹, David Kaufmann^2,3, Lauren J. O'Donnell⁵, Sylvain Bouix², Fan Zhang⁵, Nikos Makris⁶, Martha Shenton^2,7, Robert Stern⁴, Inga Koerte^2,3, and Alexander P. Lin¹

¹Radiology, Brigham and Women's Hospital, Boston, MA, United States, ²Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, United States, ³Child and Adolescent Psychiatry, Ludwig-Maximilians-Universität, Munich, Germany, ⁴Boston University, Boston, MA, United States, ⁵Laboratory of Mathematics in Imaging, Brigham and Women's Hospital, Boston, MA, United States, ⁶Massachusetts General Hospital, Boston, MA, United States, ⁷VA Boston Healthcare System, Brockton, MA, United States

Chronic Traumatic Encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts. This study aims to characterize the differing clinical presentations of CTE using MR Spectroscopy and Diffusion Tensor Imaging. Unsupervised Learning was first used to divide a cohort of former NFL players into sub-groups based on the degree of mood/behavior symptoms and cognitive impairment relative to controls. The neurometabolite concentrations and measures of diffusivity were then compared between the sub-groups. Athletes with increased mood/behavior symptoms showed alterations reflective of neuroinflammation, whereas the cognitive impairment sub-group showed more neuronal and structural alterations.

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