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Arterial input function derived from pairwise correlations between PET-image voxels
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2013 (English)In: Journal of Cerebral Blood Flow and Metabolism, ISSN 0271-678X, E-ISSN 1559-7016, Vol. 33, no 7, 1058-1065 p.Article in journal (Refereed) Published
Abstract [en]

A metabolite corrected arterial input function is a prerequisite for quantification of positron emission tomography (PET) data by compartmental analysis. This quantitative approach is also necessary for radioligands without suitable reference regions in brain. The measurement is laborious and requires cannulation of a peripheral artery, a procedure that can be associated with patient discomfort and potential adverse events. A non invasive procedure for obtaining the arterial input function is thus preferable. In this study, we present a novel method to obtain image-derived input functions (IDIFs). The method is based on calculation of the Pearson correlation coefficient between the time-activity curves of voxel pairs in the PET image to localize voxels displaying blood-like behavior. The method was evaluated using data obtained in human studies with the radioligands [C-11]flumazenil and [C-11]AZ10419369, and its performance was compared with three previously published methods. The distribution volumes (V-T) obtained using IDIFs were compared with those obtained using traditional arterial measurements. Overall, the agreement in V-T was good (similar to 3% difference) for input functions obtained using the pairwise correlation approach. This approach performed similarly or even better than the other methods, and could be considered in applied clinical studies. Applications to other radioligands are needed for further verification.

Place, publisher, year, edition, pages
2013. Vol. 33, no 7, 1058-1065 p.
Keyword [en]
HRRT, image-derived input function, PET, pharmacokinetic modeling, voxel correlation
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URN: urn:nbn:se:su:diva-92636DOI: 10.1038/jcbfm.2013.47ISI: 000321185800011OAI: diva2:641724


Available from: 2013-08-19 Created: 2013-08-14 Last updated: 2015-01-13Bibliographically approved

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Lansner, Anders
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Numerical Analysis and Computer Science (NADA)
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