Determination of a pharmacokinetic model for [11C]-acetate in brown adipose tissue View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-12

AUTHORS

Marie Anne Richard, Denis P. Blondin, Christophe Noll, Réjean Lebel, Martin Lepage, André C. Carpentier

ABSTRACT

BACKGROUND: [11C]-acetate positron emission tomography is used to assess oxidative metabolism in various tissues including the heart, tumor, and brown adipose tissue. For brown adipose tissue, a monoexponential decay model is commonly employed. However, no systematic assessment of kinetic models has been performed to validate this model or others. The monoexponential decay model and various compartmental models were applied to data obtained before and during brown adipose tissue activation by cold exposure in healthy men. Quality of fit was assessed visually and by analysis of residuals, including the Akaike information criterion. Stability and accuracy of compartmental models were further assessed through simulations, along with sensitivity and identifiability of kinetic parameters. RESULTS: Differences were noted in the arterial input function between the warm and cold conditions. These differences are not taken into account by the monoexponential decay model. They are accounted for by compartmental models, but most models proved too complex to be stable. Two and three-tissue models with no more than four distinct kinetic parameters, including blood volume fraction, provided the best compromise between fit quality and stability/accuracy. CONCLUSION: For healthy men, a three-tissue model with four kinetic parameters, similar to a heart [11C]-palmitate model seems the most appropriate based on model stability and its ability to describe the main [11C]-acetate pathways in BAT cells. Further studies are required to validate this model in women and people with metabolic disorders. More... »

PAGES

31

Journal

TITLE

EJNMMI Research

ISSUE

1

VOLUME

9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13550-019-0497-6

DOI

http://dx.doi.org/10.1186/s13550-019-0497-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113043774

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30919091


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