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Jiao, J.* ; Searle, G.E.* ; Tziortzi, A.C.* ; Salinas, C.A.* ; Gunn, R.N.* ; Schnabel, J.A.*

Spatio-temporal pharmacokinetic model based registration of 4D PET neuroimaging data.

Neuroimage 84, 225-235 (2014)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
In dynamic positron emission tomography (PET) neuroimaging studies, where scan durations often exceed 1h, registration of motion-corrupted dynamic PET images is necessary in order to maintain the integrity of the physiological, pharmacological, or biochemical information derived from the tracer kinetic analysis of the scan. In this work, we incorporate a pharmacokinetic model, which is traditionally used to analyse PET data following any registration, into the registration process itself in order to allow for a groupwise registration of the temporal time frames. The new method is shown to achieve smaller registration errors and improved kinetic parameter estimates on validation data sets when compared with image similarity based registration approaches. When applied to measured clinical data from 10 healthy subjects scanned with [11C]-(+)-PHNO (a dopamine D3/D2 receptor tracer), it reduces the intra-class variability on the receptor binding outcome measure, further supporting the improvements in registration accuracy. Our method incorporates a generic tracer kinetic model which makes it applicable to different PET radiotracers to remove motion artefacts and increase the integrity of dynamic PET studies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Motion Correction ; Neuroreceptor Imaging ; Pet ; Pharmacokinetic Modelling ; Spatio-temporal Registration
ISSN (print) / ISBN 1053-8119
e-ISSN 1095-9572
Zeitschrift NeuroImage - a Journal of Brain Function
Quellenangaben Band: 84, Heft: , Seiten: 225-235 Artikelnummer: , Supplement: ,
Verlag Elsevier
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute for Machine Learning in Biomed Imaging (IML)