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dc.creatorMoreno-Ajona, D. (David)-
dc.creatorPrieto, E. (Elena)-
dc.creatorGrisanti-Vollbracht, F. (Fabiana)-
dc.creatorEsparragosa, I. (Inés)-
dc.creatorSánchez-Orduz, L. (Lizeth)-
dc.creatorGallego-Perez-Larraya, J. (Jaime)-
dc.creatorArbizu, J. (Javier)-
dc.creatorRiverol, M. (Mario)-
dc.identifier.citationMoreno-Ajona, D. (David); Prieto, E. (Elena); Grisanti-Vollbracht, F. (Fabiana); et al. "18F-FDG-PET Imaging Patterns in Autoimmune Encephalitis: Impact of Image Analysis on the Results". Diagnostics. 10 (6), 2020,es
dc.description.abstractBrain positron emission tomography imaging with 18Fluorine-fluorodeoxyglucose (FDG-PET) has demonstrated utility in suspected autoimmune encephalitis. Visual and/or assisted image reading is not well established to evaluate hypometabolism/hypermetabolism. We retrospectively evaluated patients with autoimmune encephalitis between 2003 and 2018. Patients underwent EEG, brain magnetic resonance imaging (MRI), cerebrospinal fluid (CSF) sampling and autoantibodies testing. Individual FDG-PET images were evaluated by standard visual reading and assisted by voxel-based analyses, compared to a normal database. For the latter, three different methods were performed: two based on statistical surface projections (Siemens syngo.via Database Comparison, and 3D-SSP Neurostat) and one based on statistical parametric mapping (SPM12). Hypometabolic and hypermetabolic findings were grouped to identify specific patterns. We found six cases with definite diagnosis of autoimmune encephalitis. Two cases had anti-LGI1, one had anti-NMDA-R and two anti-CASPR2 antibodies, and one was seronegative. 18F-FDG-PET metabolic abnormalities were present in all cases, regardless of the method of analysis. Medial–temporal and extra-limbic hypermetabolism were more clearly depicted by voxel-based analyses. We found autoantibody-specific patterns in line with the literature. Statistical surface projection (SSP) methods (Neurostat and syngo.via Database Comparison) were more sensitive and localized larger hypermetabolic areas. As it may lead to comparable and accurate results, visual analysis of FDG-PET studies for the diagnosis of autoimmune encephalitis benefits from voxel-based analysis, beyond the approach based on MRI, CSF sample and EEG.es_ES
dc.description.sponsorshipThis research received no external fundinges_ES
dc.subjectVoxel-based analysises_ES
dc.subjectAssisted analysises_ES
dc.subjectAutoimmune encephalitises_ES
dc.subjectLimbic encephalitises_ES
dc.title18F-FDG-PET Imaging Patterns in Autoimmune Encephalitis: Impact of Image Analysis on the Resultses_ES
dc.description.noteThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (

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