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Abstract #0994

Simultaneous FDG-PET and MRI-based connectivity analysis for the detection of epileptogenic zones in non-lesional epilepsy patients

Clara Lisazo1,2, Natalia Noemí Massaccesi Bove1,2, Daniela Zanchi3, María Paula Del Pópolo1,2, Daniel Fino1,2,4, Federico Julián González Nicolini1,4,5, Sergio Mosconi3, Pedro Pablo Ariza1,2, Trinidad Gonzalez Padín1,2, Raúl Otoya6, Roberto Isoardi3,5, Thomas Martin Doring7, and Sebastián Moguilner5,8
1MRI Department, Fundación Escuela de Medicina Nuclear, Mendoza, Argentina, 2MRI Department, Fundación Argentina para el Desarrollo en Salud, Mendoza, Argentina, 3Nuclear Medicine Department, Fundación Escuela de Medicina Nuclear, Mendoza, Argentina, 4Instituto Balseiro, Universidad Nacional de Cuyo, San Carlos de Bariloche, Argentina, 5GQNYCS, Comisión Nacional de Energía Atómica, Ciudad Autónoma de Buenos Aires, Argentina, 6Neuromed, Mendoza, Argentina, 7GE Healthcare, Rio de Janeiro, Brazil, 8Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States


Detecting epileptogenic zones (EZ) in subjects with non-lesional epilepsy can represent a challenge, and it involves the analysis of data from various diagnostic procedures. In this study, seed-based structural and functional connectivity matrices were obtained from DWI and resting-state fMRI for each patient and compared with a control group. Then, we assessed whether significantly different regions (p<0.001) coincided with foci of abnormal metabolism on PET images, and if these ROIs corresponded with the subject’s EZ. This reduced the false positive rate and improved specificity of the connectivity analysis, optimizing EZ localization in patients with non-lesional epilepsy.

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