Literature DB >> 23247191

Graphic plot analysis for estimating binding potential of translocator protein (TSPO) in positron emission tomography studies with [¹⁸F]FEDAA1106.

Yoko Ikoma1, Akihiro Takano, Andrea Varrone, Christer Halldin.   

Abstract

PURPOSE: [(18)F]FEDAA1106 is expected to be used for evaluating the regional density of the peripheral benzodiazepine receptor (also called TSPO) in several neurodegenerative disorders. Regarding the quantification, direct binding potential (BP(ND)) has been reported to be preferable because of the variation of nondisplaceable distribution volume (V(ND)) among individuals. However, the precise calculation of BP(ND) is difficult in small regions or at voxel levels due to noise. Recently, a new graphical analysis (GA) was proposed to estimate V(ND) in a direct way. In this paper, we evaluated two types of GA for reliable quantification of BP(ND) in PET study with [(18)F]FEDAA1106 using computer simulations and human data.
METHODS: In the simulations, time-activity curves were generated with various rate constants and noise levels, and the errors of BP(ND) estimated by GA were analyzed by comparing with true values calculated from rate constants given for the simulations. Thereafter, in a human study with [(18)F]FEDAA1106 for healthy volunteers, BP(ND) was estimated by two types of GA for region-of-interest (ROI) data. Parametric images of BP(ND) were generated by two types of GA with or without wavelet-denoising.
RESULTS: Simulations showed that BP(ND) by GA was well correlated with true values, despite an underestimation. GA reduced unreasonable estimates compared with a conventional nonlinear least-square fitting (NLS), although larger variation of BP(ND) estimates was observed. In a ROI-based analysis of data obtained in a human study, BP(ND)s estimated by GA were well correlated with those generated by NLS, though they were underestimated. Parametric BP(ND) images by GA could be improved with wavelet-denoising.
CONCLUSION: Graphical analysis could provide BP(ND) values with high stability and simple calculation in both ROI-based and voxel-based analyses of [(18)F]FEDAA1106 data.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23247191     DOI: 10.1016/j.neuroimage.2012.12.009

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  4 in total

1.  In vivo imaging of the 18-kDa translocator protein (TSPO) with [18F]FEDAA1106 and PET does not show increased binding in Alzheimer's disease patients.

Authors:  Andrea Varrone; Patrik Mattsson; Anton Forsberg; Akihiro Takano; Sangram Nag; Balázs Gulyás; Jacqueline Borg; Ronald Boellaard; Nabil Al-Tawil; Maria Eriksdotter; Torsten Zimmermann; Marcus Schultze-Mosgau; Andrea Thiele; Anja Hoffmann; Adriaan A Lammertsma; Christer Halldin
Journal:  Eur J Nucl Med Mol Imaging       Date:  2013-02-22       Impact factor: 9.236

Review 2.  Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

Authors:  Seongho Seo; Su Jin Kim; Dong Soo Lee; Jae Sung Lee
Journal:  Neurosci Bull       Date:  2014-09-28       Impact factor: 5.203

3.  Simplified estimation of binding parameters based on image-derived reference tissue models for dopamine transporter bindings in non-human primates using [18F]FE-PE2I and PET.

Authors:  Ikuo Odano; Andrea Varrone; Tetsuo Hosoya; Kazuya Sakaguchi; Balázs Gulyás; Parasuraman Padmanabhan; Krishna Kanta Ghosh; Chang-Tong Yang; Ilonka Guenther; Zhimin Wang; Raymond Serrano; Nevil Ghislain Chimon; Christer Halldin
Journal:  Am J Nucl Med Mol Imaging       Date:  2017-12-20

4.  Dynamic image denoising for voxel-wise quantification with Statistical Parametric Mapping in molecular neuroimaging.

Authors:  Stergios Tsartsalis; Benjamin B Tournier; Christophe E Graf; Nathalie Ginovart; Vicente Ibáñez; Philippe Millet
Journal:  PLoS One       Date:  2018-09-05       Impact factor: 3.240

  4 in total

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