Validation of a spatially variant resolution model for small animal brain PET studies.


Journal

Biomedical physics & engineering express
ISSN: 2057-1976
Titre abrégé: Biomed Phys Eng Express
Pays: England
ID NLM: 101675002

Informations de publication

Date de publication:
06 05 2020
Historique:
entrez: 14 1 2021
pubmed: 15 1 2021
medline: 6 11 2021
Statut: epublish

Résumé

In small animal positron emission tomography (PET) studies, given the spatial resolution of preclinical PET scanners, quantification in small regions can be challenging. Moreover, in scans where animals are placed away from the center of the field of view (CFOV), e.g. in simultaneous scans of multiple animals, quantification accuracy can be compromised due to the loss of spatial resolution towards the edge of the FOV. Here, we implemented a spatially variant resolution model to improve quantification in small regions and to allow simultaneous scanning of multiple animals without compromising quantification accuracy. The scanner's point spread function (PSF) was characterized across the FOV and modelled using a spatially variant and asymmetric Gaussian function. The spatially variant PSF (SVPSF) was then used for resolution modelling in the iterative reconstruction. To assess the image quality, a line source phantom in a cold and warm background, as well as mouse brain [

Identifiants

pubmed: 33444262
doi: 10.1088/2057-1976/ab8c13
doi:

Substances chimiques

Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article Research Support, Non-U.S. Gov't Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

045001

Auteurs

Alan Miranda (A)

Molecular Imaging Center Antwerp, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium.

Articles similaires

Robotic Surgical Procedures Animals Humans Telemedicine Models, Animal

Odour generalisation and detection dog training.

Lyn Caldicott, Thomas W Pike, Helen E Zulch et al.
1.00
Animals Odorants Dogs Generalization, Psychological Smell

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages
Animals TOR Serine-Threonine Kinases Colorectal Neoplasms Colitis Mice

Classifications MeSH