Spatiotemporal Kernel Reconstruction for Linear Parametric Neurotransmitter PET Kinetic Modeling in Motion Correction Brain PET of Awake Rats.
4D reconstruction
brain
kinetic modeling
motion correction
positron emission tomography
rat
Journal
Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481
Informations de publication
Date de publication:
2022
2022
Historique:
received:
21
03
2022
accepted:
26
04
2022
entrez:
1
6
2022
pubmed:
2
6
2022
medline:
2
6
2022
Statut:
epublish
Résumé
The linear parametric neurotransmitter positron emission tomography (lp-ntPET) kinetic model can be used to detect transient changes (activation) in endogenous neurotransmitter levels. Preclinical PET scans in awake animals can be performed to investigate neurotransmitter transient changes. Here we use the spatiotemporal kernel reconstruction (Kernel) for noise reduction in dynamic PET, and lp-ntPET kinetic modeling. Kernel is adapted for motion correction reconstruction, applied in awake rat PET scans. We performed 2D rat brain phantom simulation using the ntPET model at 3 different noise levels. Data was reconstructed with independent frame reconstruction (IFR), IFR with HYPR denoising, and Kernel, and lp-ntPET kinetic parameters (
Identifiants
pubmed: 35645721
doi: 10.3389/fnins.2022.901091
pmc: PMC9133502
doi:
Types de publication
Journal Article
Langues
eng
Pagination
901091Informations de copyright
Copyright © 2022 Miranda, Bertoglio, Stroobants, Staelens and Verhaeghe.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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