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

• Published in: NeuroImage (Orlando, Fla.) Vol. 84; pp. 225 - 235
• Main Authors: Jiao, Jieqing, Searle, Graham E., Tziortzi, Andri C., Salinas, Cristian A., Gunn, Roger N., Schnabel, Julia A.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01-01-2014; Elsevier; Elsevier Limited
• Subjects: Algorithms; Biological and medical sciences; Brain; Brain - diagnostic imaging; Brain - metabolism; Carbon Isotopes - pharmacokinetics; Computer Simulation; Data processing; Dopamine; Economic models; Female; Fundamental and applied biological sciences. Psychology; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Male; Medical imaging; Methods; Models, Neurological; Monitoring systems; Motion correction; Neuroimaging - methods; Neuroreceptor imaging; Noise; Oxazines - pharmacokinetics; PET; Pharmacokinetic modelling; Positron-Emission Tomography - methods; Radiopharmaceuticals - pharmacokinetics; Receptors, Dopamine D3 - antagonists & inhibitors; Receptors, Dopamine D3 - metabolism; Reproducibility of Results; Sensitivity and Specificity; Spatio-Temporal Analysis; Spatio-temporal registration; Subtraction Technique; Time Factors; Vertebrates: nervous system and sense organs; Young Adult; Motion correction; Spatio-temporal registration; Pharmacokinetic modelling; Neuroreceptor imaging; PET; Imaging; Models
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2013.08.031

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.
•A novel motion correction algorithm is presented for dynamic PET neuroimaging studies.•A data driven pharmacokinetic model is used as the temporal regulariser.•It improves spatial realignment and receptor outcome measures in dopamine D3 studies.•The image based method is applicable to all PET tracers.