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Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization

Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebra...

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Autores principales: Proesmans, Silke, Raedt, Robrecht, Germonpré, Charlotte, Christiaen, Emma, Descamps, Benedicte, Boon, Paul, De Herdt, Veerle, Vanhove, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565796/
https://www.ncbi.nlm.nih.gov/pubmed/34746179
http://dx.doi.org/10.3389/fmed.2021.744157
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author Proesmans, Silke
Raedt, Robrecht
Germonpré, Charlotte
Christiaen, Emma
Descamps, Benedicte
Boon, Paul
De Herdt, Veerle
Vanhove, Christian
author_facet Proesmans, Silke
Raedt, Robrecht
Germonpré, Charlotte
Christiaen, Emma
Descamps, Benedicte
Boon, Paul
De Herdt, Veerle
Vanhove, Christian
author_sort Proesmans, Silke
collection PubMed
description Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebral metabolic rate of glucose (CMR(glc)) and standard uptake values (SUVs). Especially in the brain, these (semi-)quantitative measures can be affected by several physiological factors, such as blood glucose level, age, gender, and stress. Next to this inter- and intra-subject variability, the use of different PET acquisition protocols across studies has created a need for the standardization and harmonization of brain PET evaluation. In this study we present a framework for statistical voxel-based analysis of glucose uptake in the rat brain using histogram-based intensity normalization. Methods: [18F]-FDG PET images of 28 normal rat brains were coregistered and voxel-wisely averaged. Ratio images were generated by voxel-wisely dividing each of these images with the group average. The most prevalent value in the ratio image was used as normalization factor. The normalized PET images were voxel-wisely averaged to generate a normal rat brain atlas. The variability of voxel intensities across the normalized PET images was compared to images that were either normalized by whole brain normalization, or not normalized. To illustrate the added value of this normal rat brain atlas, 9 animals with a striatal hemorrhagic lesion and 9 control animals were intravenously injected with [18F]-FDG and the PET images of these animals were voxel-wisely compared to the normal atlas by group- and individual analyses. Results: The average coefficient of variation of the voxel intensities in the brain across normal [18F]-FDG PET images was 6.7% for the histogram-based normalized images, 11.6% for whole brain normalized images, and 31.2% when no normalization was applied. Statistical voxel-based analysis, using the normal template, indicated regions of significantly decreased glucose uptake at the site of the ICH lesion in the ICH animals, but not in control animals. Conclusion: In summary, histogram-based intensity normalization of [18F]-FDG uptake in the brain is a suitable data-driven approach for standardized voxel-based comparison of brain PET images.
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spelling pubmed-85657962021-11-04 Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization Proesmans, Silke Raedt, Robrecht Germonpré, Charlotte Christiaen, Emma Descamps, Benedicte Boon, Paul De Herdt, Veerle Vanhove, Christian Front Med (Lausanne) Medicine Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebral metabolic rate of glucose (CMR(glc)) and standard uptake values (SUVs). Especially in the brain, these (semi-)quantitative measures can be affected by several physiological factors, such as blood glucose level, age, gender, and stress. Next to this inter- and intra-subject variability, the use of different PET acquisition protocols across studies has created a need for the standardization and harmonization of brain PET evaluation. In this study we present a framework for statistical voxel-based analysis of glucose uptake in the rat brain using histogram-based intensity normalization. Methods: [18F]-FDG PET images of 28 normal rat brains were coregistered and voxel-wisely averaged. Ratio images were generated by voxel-wisely dividing each of these images with the group average. The most prevalent value in the ratio image was used as normalization factor. The normalized PET images were voxel-wisely averaged to generate a normal rat brain atlas. The variability of voxel intensities across the normalized PET images was compared to images that were either normalized by whole brain normalization, or not normalized. To illustrate the added value of this normal rat brain atlas, 9 animals with a striatal hemorrhagic lesion and 9 control animals were intravenously injected with [18F]-FDG and the PET images of these animals were voxel-wisely compared to the normal atlas by group- and individual analyses. Results: The average coefficient of variation of the voxel intensities in the brain across normal [18F]-FDG PET images was 6.7% for the histogram-based normalized images, 11.6% for whole brain normalized images, and 31.2% when no normalization was applied. Statistical voxel-based analysis, using the normal template, indicated regions of significantly decreased glucose uptake at the site of the ICH lesion in the ICH animals, but not in control animals. Conclusion: In summary, histogram-based intensity normalization of [18F]-FDG uptake in the brain is a suitable data-driven approach for standardized voxel-based comparison of brain PET images. Frontiers Media S.A. 2021-10-20 /pmc/articles/PMC8565796/ /pubmed/34746179 http://dx.doi.org/10.3389/fmed.2021.744157 Text en Copyright © 2021 Proesmans, Raedt, Germonpré, Christiaen, Descamps, Boon, De Herdt and Vanhove. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Proesmans, Silke
Raedt, Robrecht
Germonpré, Charlotte
Christiaen, Emma
Descamps, Benedicte
Boon, Paul
De Herdt, Veerle
Vanhove, Christian
Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization
title Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization
title_full Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization
title_fullStr Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization
title_full_unstemmed Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization
title_short Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization
title_sort voxel-based analysis of [18f]-fdg brain pet in rats using data-driven normalization
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565796/
https://www.ncbi.nlm.nih.gov/pubmed/34746179
http://dx.doi.org/10.3389/fmed.2021.744157
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