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Autoren: Gonzalez-Escamilla, Gabriel
Miederer, Isabelle
Grothe, Michel J.
Schreckenberger, Mathias
Muthuraman, Muthuraman
Groppa, Sergiu
Titel: Metabolic and amyloid PET network reorganization in Alzheimer’s disease : differential patterns and partial volume effects
Online-Publikationsdatum: 10-Mai-2021
Erscheinungsdatum: 2021
Sprache des Dokuments: Englisch
Zusammenfassung/Abstract: Alzheimer’s disease (AD) is a neurodegenerative disorder, considered a disconnection syndrome with regional molecular pattern abnormalities quantifiable by the aid of PET imaging. Solutions for accurate quantification of network dysfunction are scarce. We evaluate the extent to which PET molecular markers reflect quantifiable network metrics derived through the graph theory framework and how partial volume effects (PVE)-correction (PVEc) affects these PET-derived metrics 75 AD patients and 126 cognitively normal older subjects (CN). Therefore our goal is twofold: 1) to evaluate the differential patterns of [18F]FDG- and [18F]AV45-PET data to depict AD pathology; and ii) to analyse the effects of PVEc on global uptake measures of [18F]FDG- and [18F]AV45-PET data and their derived covariance network reconstructions for differentiating between patients and normal older subjects. Network organization patterns were assessed using graph theory in terms of “degree”, “modularity”, and “efficiency”. PVEc evidenced effects on global uptake measures that are specific to either [18F]FDG- or [18F]AV45-PET, leading to increased statistical differences between the groups. PVEc was further shown to influence the topological characterization of PET-derived covariance brain networks, leading to an optimised characterization of network efficiency and modularisation. Partial-volume effects correction improves the interpretability of PET data in AD and leads to optimised characterization of network properties for organisation or disconnection.
DDC-Sachgruppe: 610 Medizin
610 Medical sciences
Veröffentlichende Institution: Johannes Gutenberg-Universität Mainz
Organisationseinheit: FB 04 Medizin
Veröffentlichungsort: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-5879
Version: Published version
Publikationstyp: Zeitschriftenaufsatz
Nutzungsrechte: CC BY
Informationen zu den Nutzungsrechten: https://creativecommons.org/licenses/by/4.0/
Zeitschrift: Brain imaging and behavior
15
Seitenzahl oder Artikelnummer: 190
204
Verlag: Springer
Verlagsort: New York, NY u.a.
Erscheinungsdatum: 2021
ISSN: 1931-7565
URL der Originalveröffentlichung: https://doi.org/10.1007/s11682-019-00247-9
DOI der Originalveröffentlichung: 10.1007/s11682-019-00247-9
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