Abstract #0994

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

Clara Lisazo^1,2, Natalia Noemí Massaccesi Bove^1,2, Daniela Zanchi³, María Paula Del Pópolo^1,2, Daniel Fino^1,2,4, Federico Julián González Nicolini^1,4,5, Sergio Mosconi³, Pedro Pablo Ariza^1,2, Trinidad Gonzalez Padín^1,2, Raúl Otoya⁶, Roberto Isoardi^3,5, Thomas Martin Doring⁷, and Sebastián Moguilner^5,8

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

Synopsis

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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