A linear model for estimation of neurotransmitter response profiles from dynamic PET data

Marc D. Normandin, Wynne K Schiffer, Evan D. Morris

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


The parametric ntPET model (p-ntPET) estimates the kinetics of neurotransmitter release from dynamic PET data with receptor-ligand radiotracers. Here we introduce a linearization (lp-ntPET) that is computationally efficient and can be applied to single scan data. lp-ntPET employs a non-invasive reference region input function and extends the LSRRM of Alpert et al. (2003) using basis functions to characterize the time course of neurotransmitter activation. In simulation studies, the temporal precision of neurotransmitter profiles estimated by lp-ntPET was similar to that of p-ntPET (standard deviation ~3min for responses early in the scan) while computation time was reduced by several orders of magnitude. Violations of model assumptions such as activation-induced changes in regional blood flow or specific binding in the reference tissue have negligible effects on lp-ntPET performance. Application of the lp-ntPET method is demonstrated on [ 11C]raclopride data acquired in rats receiving methamphetamine, which yielded estimated response functions that were in good agreement with simultaneous microdialysis measurements of extracellular dopamine concentration. These results demonstrate that lp-ntPET is a computationally efficient, linear variant of ntPET that can be applied to PET data from single or multiple scan designs to estimate the time course of neurotransmitter activation.

Original languageEnglish (US)
Pages (from-to)2689-2699
Number of pages11
Issue number3
StatePublished - Feb 1 2012

Bibliographical note

Funding Information:
M.D. Normandin acknowledges the support of the L.A. Geddes Fellowship and the Society of Nuclear Medicine Student Fellowship . E.D. Morris acknowledges the support of NIH grant R21 AA015077 and the Whitaker Foundation grants RG 02-0126 and TF 04-0034 .


  • Basis functions
  • Compartmental modeling
  • Dopamine
  • Neurotransmitter
  • PET
  • Reference region
  • Tracer kinetics


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