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Abstract #0650

Identification of Quantitative Susceptibility Biomarkers for First Episode Psychosis using XGBoost

Pamela Franco1,2, Cristian Montalba1,2,3, Raul Caulier-Cisterna1,2, Marisleydis García1,2,4, Alonso González5,6, Juan Undurraga5,7, Nicolás Crossley2,5, Cristian Tejos1,2,4, and Sergio Uribe1,2,3
1Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile, 2Millennium Institute for Intelligent Healthcare Engineering - iHEALTH, Pontificia Universidad Catolica de Chile, Santiago, Chile, 3Radiology Department, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile, 4Electrical Engineering Department, School of Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile, 5Department of Psychiatry, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile, 6School of Medicine, Universidad Finis Terrae, Santiago, Chile, 7Pharmacovigilance, Instituto Psiquiátrico Dr J. Horwitz Barak, Santiago, Chile

Synopsis

Keywords: Psychiatric Disorders, Quantitative Susceptibility mappingSeveral studies have demonstrated altered neurochemicals in deep-brain nuclei of psychosis patients. These alterations suggest a dopamine dysfunction in subcortical areas. QSM images quantify magnetic susceptibility changes in the brain. These changes are usually associated with iron concentrations and co-factor in dopamine pathways of the neurons. We propose a method based on machine learning to discriminate between psychosis patients and healthy controls by looking at the magnetic susceptibility of 9 deep gray matter nuclei, obtaining a precision of 91.6%.

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