Literature DB >> 26323854

Age-related changes in FDG brain uptake are more accurately assessed when applying an adaptive template to the SPM method of voxel-based quantitative analysis.

Axel Van Der Gucht1, Antoine Verger2,3,4, Eric Guedj5,6, Grégoire Malandain7, Gabriela Hossu8,9, Yalcin Yagdigul2, Véronique Roch2,3,4, Sylvain Poussier2,3,4, Louis Maillard4,10, Gilles Karcher2,4,11, Pierre-Yves Marie2,4,12.   

Abstract

INTRODUCTION: The impact of age is crucial and must be taken into account when applying a voxel-based quantitative analysis on brain images from [¹⁸F]-fluorodeoxyglucose Positron Emission Tomography (FDG-PET). This study aimed to determine whether age-related changes in brain FDG-PET images are more accurately assessed when the conventional statistical parametric mapping (SPM) normalization method is used with an adaptive template, obtained from analysed PET images using a Block-Matching (BM) algorithm to fit with the characteristics of these images.
METHODS: Age-related changes in FDG-PET images were computed with linear models in 84 neurologically healthy subjects (35 women, 19 to 82-year-old), and compared between results provided by the SPM normalization algorithm applied on its dedicated conventional template or on the adaptive BM template. A threshold P value of 0.05 was used together with a family-wise error correction.
RESULTS: The age-related changes in FDG-PET images were much more apparent when computed with the adaptive template than with the conventional template as evidenced by: (1) stronger correlation coefficients with age for the overall frontal and temporal uptake values (respective R² values of 0.20 and 0.07) and (2) larger extents of involved areas (13 and 5% of whole brain template volume, respectively), leading to reveal several age-dependent areas (especially in dorsolateral prefrontal, inferior temporal/fusiform and primary somatosensory cortices).
CONCLUSION: Age-related changes in brain FDG uptake may be more accurately determined when applying the SPM method of voxel-based quantitative analysis on a template that best fits the characteristics of the analysed TEP images.

Entities:  

Keywords:  18F-fluorodeoxyglucose; Age; Block-Matching algorithm; Positron emission tomography; Spatial normalization; Statistical parametric mapping

Mesh:

Substances:

Year:  2015        PMID: 26323854     DOI: 10.1007/s12149-015-1022-2

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


  6 in total

1.  Quantitative SPM Analysis Involving an Adaptive Template May Be Easily Applied to [18F]FDG PET Images of the Rat Brain.

Authors:  Sylvain Poussier; Fatiha Maskali; Gaelle Vexiau; Antoine Verger; Henri Boutley; Gilles Karcher; Emmanuel Raffo; Pierre-Yves Marie
Journal:  Mol Imaging Biol       Date:  2017-10       Impact factor: 3.488

2.  Physiological Whole-Brain Distribution of [18F]FDOPA Uptake Index in Relation to Age and Gender: Results from a Voxel-Based Semi-quantitative Analysis.

Authors:  Sinn-Rithy Toch; Sylvain Poussier; Emilien Micard; Marc Bertaux; Axel Van Der Gucht; Elodie Chevalier; Pierre-Yves Marie; Eric Guedj; Antoine Verger
Journal:  Mol Imaging Biol       Date:  2019-06       Impact factor: 3.488

3.  18F-THK 5351 and 11C-PiB PET of the Thai normal brain template.

Authors:  Chanisa Chotipanich; Supaporn Kongthai; Anchisa Kunawudhi; Chetsadaporn Promteangtrong; Attapon Jantarato
Journal:  Asia Ocean J Nucl Med Biol       Date:  2021

4.  The pons as reference region for intensity normalization in semi-quantitative analysis of brain 18FDG PET: application to metabolic changes related to ageing in conventional and digital control databases.

Authors:  A Verger; M Doyen; J Y Campion; Eric Guedj
Journal:  EJNMMI Res       Date:  2021-03-24       Impact factor: 3.138

5.  Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain 18F-FDG digital PET scans.

Authors:  Elise Mairal; Matthieu Doyen; Thérèse Rivasseau-Jonveaux; Catherine Malaplate; Eric Guedj; Antoine Verger
Journal:  EJNMMI Res       Date:  2020-11-30       Impact factor: 3.138

6.  Evaluation of factors influencing 18F-FET uptake in the brain.

Authors:  Antoine Verger; Carina Stegmayr; Norbert Galldiks; Axel Van Der Gucht; Philipp Lohmann; Gabriele Stoffels; Nadim J Shah; Gereon R Fink; Simon B Eickhoff; Eric Guedj; Karl-Josef Langen
Journal:  Neuroimage Clin       Date:  2017-11-08       Impact factor: 4.881

  6 in total

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