Strategy for the formation of parametric images under conditions of low injected radioactivity applied to PET studies with the irreversible monoamine oxidase A tracers [11C]clorgyline and deuterium-substituted [11C]clorgyline

Jean Logan, Joanna S. Fowler, Yu Shin Ding, Dinko Franceschi, Gene Jack Wang, Nora D. Volkow, Christoph Felder, David Alexoff

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

The construction of parametric positron emission tomography images of enzyme or receptor concentration obtained using irreversibly binding radiotracers presents problems not usually encountered with reversibly binding radiotracers. Difficulties are most apparent in brain regions having low blood flow and/or high enzyme or receptor concentration and are exacerbated with noisy data. This is especially true when minimal doses of radiotracer are administered. A comparison was recently reported of the irreversible monoamine oxidase A (MAO A) radiotracers [11C]clorgyline (CLG) and deuterium-substituted [11C]clorgyline (CLG-D) in the human brain using region of interest (ROI) analysis in which the authors observed an unexpected loss of image contrast with CLG-D compared with CLG. In order to more fully investigate patterns of binding of these irreversibly binding radiotracers, a strategy was devised to reduce noise in the generation of parametric images of the model term related to enzyme or receptor concentration. The generalized linear least squares (GLLS) method of Feng et al. (1995), a rapid linear method that is unbiased, was used for image-wide parameter estimation. Since GLLS can fail in the presence of large amounts of noise, local voxels were grouped within the image to increase the signal, and the GLLS method was combined with the standard nonlinear estimation methods when necessary. Voxels were grouped together depending on their proximity and whether they fell within a specified range of the time-integrated image. It was assumed that voxels meeting both criteria are functionally related. Simulations reflecting varying enzyme concentrations were performed to assess precision and accuracy of parameter estimates in the presence of varying amounts of noise. Using this approach, images were generated of the combination parameter λk3 (λ = K1/k2, where K1 and k2 are plasma-to-tissue and tissue-to-plasma transport constants, respectively) that is related to enzyme concentration as well as images of the transport constant K1 for individual subjects. Reasonably high-quality images of both K1 and λk3 were obtained for CLG and CLG-D for individual subjects even with low injected doses averaging 6 mCi. While there were no differences in the K1 images, the λk3 images revealed the loss of contrast previously reported for CLG-D using the ROI analysis. This method should be generalizable to other tracers and should facilitate the analysis of group differences.

Original languageEnglish
Pages (from-to)1367-1376
Number of pages10
JournalJournal of Cerebral Blood Flow and Metabolism
Volume22
Issue number11
DOIs
StatePublished - 1 Nov 2002
Externally publishedYes

Keywords

  • Kinetic modeling
  • Monoamine oxidase
  • PET
  • Parametric images

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