Metabolic and amyloid PET network reorganization in Alzheimer’s disease: differential patterns and partial volume effects
- Publication type:
- Journal article
- Metadata:
-
- Abstract
- <jats:title>Abstract</jats:title><jats:p>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 [<jats:sup>18</jats:sup>F]FDG- and [<jats:sup>18</jats:sup>F]AV45-PET data to depict AD pathology; and ii) to analyse the effects of PVEc on global uptake measures of [<jats:sup>18</jats:sup>F]FDG- and [<jats:sup>18</jats:sup>F]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 [<jats:sup>18</jats:sup>F]FDG- or [<jats:sup>18</jats:sup>F]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.</jats:p>
- Autoren
- Gabriel Gonzalez-Escamilla
- Isabelle Miederer
- Michel J Grothe
- Mathias Schreckenberger
- Muthuraman Muthuraman
- Sergiu Groppa
- DOI
- 10.1007/s11682-019-00247-9
- eISSN
- 1931-7565
- ISSN
- 1931-7557
- Ausgabe der Veröffentlichung
- 1
- Zeitschrift
- Brain Imaging and Behavior
- Sprache
- en
- Online publication date
- 2020
- Paginierung
- 190 - 204
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Herausgeber
- Springer Science and Business Media LLC
- Herausgeber URL
- http://dx.doi.org/10.1007/s11682-019-00247-9
- Datum der Datenerfassung
- 2021
- Titel
- Metabolic and amyloid PET network reorganization in Alzheimer’s disease: differential patterns and partial volume effects
- Ausgabe der Zeitschrift
- 15
Data source: Crossref
- Other metadata sources:
-
- Author's licence
- CC-BY
- Autoren
- Gabriel Gonzalez-Escamilla
- Isabelle Miederer
- Michel J Grothe
- Mathias Schreckenberger
- Muthuraman Muthuraman
- Sergiu Groppa
- Hosting institution
- Universitätsbibliothek Mainz
- Sammlungen
- JGU-Publikationen
- Resource version
- Published version
- DOI
- 10.1007/s11682-019-00247-9
- File(s) embargoed
- false
- Open access
- true
- ISSN
- 1931-7565
- Zeitschrift
- Brain imaging and behavior
- Schlüsselwörter
- 610 Medizin
- 610 Medical sciences
- Sprache
- eng
- Open access status
- Open Access
- Paginierung
- 190 - 204
- Datum der Veröffentlichung
- 2021
- Public URL
- https://openscience.ub.uni-mainz.de/handle/20.500.12030/5888
- Herausgeber
- Springer
- Herausgeber URL
- https://doi.org/10.1007/s11682-019-00247-9
- Datum der Datenerfassung
- 2021
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2021
- Zugang
- Public
- Titel
- Metabolic and amyloid PET network reorganization in Alzheimer’s disease : differential patterns and partial volume effects
- Ausgabe der Zeitschrift
- 15
Files
gonzalez-escamilla_gabriel-metabolic_and_-20210503155811443.pdf
Data source: OPENSCIENCE.UB