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dc.contributor.authorEl Fakhri, G.
dc.contributor.authorTrott, Cathryn
dc.contributor.authorSitek, A.
dc.contributor.authorBonab, A.
dc.contributor.authorAlpert, N.
dc.date.accessioned2017-01-30T11:36:37Z
dc.date.available2017-01-30T11:36:37Z
dc.date.created2014-11-19T01:13:30Z
dc.date.issued2013
dc.identifier.citationEl Fakhri, G. and Trott, C. and Sitek, A. and Bonab, A. and Alpert, N. 2013. Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences. Molecular Imaging and Biology. 15 (6): pp. 666-674.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/13354
dc.description.abstract

Purpose: With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions.Procedures: To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) (brain metabolism) and 11C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously. Results: The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3±1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9±3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation. Conclusions: Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals can be separated into components based on the differences in the kinetics, provided their kinetic behaviors are distinct.

dc.publisherSpringer New York LLC
dc.relation.urihttp://link.springer.com/article/10.1007/s11307-013-0631-1
dc.subjectBrain imaging
dc.subjectQuantitation
dc.subjectDynamic PET
dc.titleDual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences
dc.typeJournal Article
dcterms.source.volume15
dcterms.source.number6
dcterms.source.startPage666
dcterms.source.endPage674
dcterms.source.issn1536-1632
dcterms.source.titleMolecular Imaging and Biology
curtin.accessStatusFulltext not available


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