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Multiple linear analysis methods for the quantification of irreversibly binding radiotracers

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dc.contributor.authorKim, Su Jin-
dc.contributor.authorLee, Jae Sung-
dc.contributor.authorKim, Yu Kyeong-
dc.contributor.authorFrost, James-
dc.contributor.authorWand, Gary-
dc.contributor.authorMcCaul, Mary E-
dc.contributor.authorLee, Dong Soo-
dc.date.accessioned2010-06-24T05:13:12Z-
dc.date.available2010-06-24T05:13:12Z-
dc.date.issued2008-07-17-
dc.identifier.citationJ Cereb Blood Flow Metab. 28(12):1965-77en
dc.identifier.issn1559-7016 (Electronic)-
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18628777-
dc.identifier.urihttp://www.nature.com/jcbfm/journal/v28/n12/pdf/jcbfm200884a.pdf-
dc.identifier.urihttp://hdl.handle.net/10371/67774-
dc.description.abstractGjedde-Patlak graphical analysis (GPGA) has commonly been used to quantify the net accumulations (K(in)) of radioligands that bind or are taken up irreversibly. We suggest an alternative approach (MLAIR: multiple linear analysis for irreversible radiotracers) for the quantification of these types of tracers. Two multiple linear regression model equations were derived from differential equations of the two-tissue compartment model with irreversible binding. Multiple linear analysis for irreversible radiotracer 1 has a desirable feature for ordinary least square estimations because only the dependent variable C(T)(t) is noisy. Multiple linear analysis for irreversible radiotracer 2 provides K(in) from direct estimates of the coefficients of independent variables without the mediation of a division operation. During computer simulations, MLAIR1 provided less biased K(in) estimates than the other linear methods, but showed a high uncertainty level for noisy data, whereas MLAIR2 increased the robustness of estimation in terms of variability, but at the expense of increased bias. For real [(11)C]MeNTI positron emission tomography data, both methods showed good correlations, with parameters estimated using the standard nonlinear least squares method. Multiple linear analysis for irreversible radiotracer 2 parametric images showed remarkable image quality as compared with GPGA images. It also showed markedly improved statistical power for voxelwise comparisons than GPGA. The two MLAIR approaches examined were found to have several advantages over the conventional GPGA method.en
dc.language.isoen-
dc.publisherNature Publishing Groupen
dc.subjectBrain/radionuclide imagingen
dc.subjectComputer Simulationen
dc.subjectFluorine Radioisotopes/analysis/pharmacokineticsen
dc.subjectHumansen
dc.subject*Linear Modelsen
dc.subjectMaleen
dc.subjectModels, Theoreticalen
dc.subjectPositron-Emission Tomography/*methodsen
dc.subject*Radioisotopes/analysis/pharmacokineticsen
dc.subjectYoung Adulten
dc.titleMultiple linear analysis methods for the quantification of irreversibly binding radiotracersen
dc.typeArticleen
dc.contributor.AlternativeAuthor김서진-
dc.contributor.AlternativeAuthor이재성-
dc.contributor.AlternativeAuthor김유경-
dc.contributor.AlternativeAuthor이동수-
dc.identifier.doi10.1038/jcbfm.2008.84-
Appears in Collections:
College of Medicine/School of Medicine (의과대학/대학원)Nuclear Medicine (핵의학전공)Journal Papers (저널논문_핵의학전공)
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