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

PURPOSE: Digital PET cameras markedly improve sensitivity and spatial resolution of brain (18)F-FDG PET images compared to conventional cameras. Our study aimed to assess whether specific control databases are required to improve the diagnostic performance of these recent advances. METHODS: We retro...

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Autores principales: Mairal, Elise, Doyen, Matthieu, Rivasseau-Jonveaux, Thérèse, Malaplate, Catherine, Guedj, Eric, Verger, Antoine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704892/
https://www.ncbi.nlm.nih.gov/pubmed/33258085
http://dx.doi.org/10.1186/s13550-020-00733-y
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author Mairal, Elise
Doyen, Matthieu
Rivasseau-Jonveaux, Thérèse
Malaplate, Catherine
Guedj, Eric
Verger, Antoine
author_facet Mairal, Elise
Doyen, Matthieu
Rivasseau-Jonveaux, Thérèse
Malaplate, Catherine
Guedj, Eric
Verger, Antoine
author_sort Mairal, Elise
collection PubMed
description PURPOSE: Digital PET cameras markedly improve sensitivity and spatial resolution of brain (18)F-FDG PET images compared to conventional cameras. Our study aimed to assess whether specific control databases are required to improve the diagnostic performance of these recent advances. METHODS: We retrospectively selected two groups of subjects, twenty-seven Alzheimer's Disease (AD) patients and twenty-two healthy control (HC) subjects. All subjects underwent a brain (18)F-FDG PET on a digital camera (Vereos, Philips®). These two group (AD and HC) are compared, using a Semi-Quantitative Analysis (SQA), to two age and sex matched controls acquired with a digital PET/CT (Vereos, Philips®) or a conventional PET/CT (Biograph 6, Siemens®) camera, at group and individual levels. Moreover, individual visual interpretation of SPM T-maps was provided for the positive diagnosis of AD by 3 experienced raters. RESULTS: At group level, SQA using digital controls detected more marked hypometabolic areas in AD (+ 116 cm(3) at p < 0.001 uncorrected for the voxel, corrected for the cluster) than SQA using conventional controls. At the individual level, the accuracy of SQA for discriminating AD using digital controls was higher than SQA using conventional controls (86% vs. 80%, p < 0.01, at p < 0.005 uncorrected for the voxel, corrected for the cluster), with higher sensitivity (89% vs. 78%) and similar specificity (82% vs. 82%). These results were confirmed by visual analysis (accuracies of 84% and 82% for digital and conventional controls respectively, p = 0.01). CONCLUSION: There is an urgent need to establish specific digital PET control databases for SQA of brain (18)F-FDG PET images as such databases improve the accuracy of AD diagnosis.
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spelling pubmed-77048922020-12-02 Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans Mairal, Elise Doyen, Matthieu Rivasseau-Jonveaux, Thérèse Malaplate, Catherine Guedj, Eric Verger, Antoine EJNMMI Res Original Research PURPOSE: Digital PET cameras markedly improve sensitivity and spatial resolution of brain (18)F-FDG PET images compared to conventional cameras. Our study aimed to assess whether specific control databases are required to improve the diagnostic performance of these recent advances. METHODS: We retrospectively selected two groups of subjects, twenty-seven Alzheimer's Disease (AD) patients and twenty-two healthy control (HC) subjects. All subjects underwent a brain (18)F-FDG PET on a digital camera (Vereos, Philips®). These two group (AD and HC) are compared, using a Semi-Quantitative Analysis (SQA), to two age and sex matched controls acquired with a digital PET/CT (Vereos, Philips®) or a conventional PET/CT (Biograph 6, Siemens®) camera, at group and individual levels. Moreover, individual visual interpretation of SPM T-maps was provided for the positive diagnosis of AD by 3 experienced raters. RESULTS: At group level, SQA using digital controls detected more marked hypometabolic areas in AD (+ 116 cm(3) at p < 0.001 uncorrected for the voxel, corrected for the cluster) than SQA using conventional controls. At the individual level, the accuracy of SQA for discriminating AD using digital controls was higher than SQA using conventional controls (86% vs. 80%, p < 0.01, at p < 0.005 uncorrected for the voxel, corrected for the cluster), with higher sensitivity (89% vs. 78%) and similar specificity (82% vs. 82%). These results were confirmed by visual analysis (accuracies of 84% and 82% for digital and conventional controls respectively, p = 0.01). CONCLUSION: There is an urgent need to establish specific digital PET control databases for SQA of brain (18)F-FDG PET images as such databases improve the accuracy of AD diagnosis. Springer Berlin Heidelberg 2020-11-30 /pmc/articles/PMC7704892/ /pubmed/33258085 http://dx.doi.org/10.1186/s13550-020-00733-y Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Research
Mairal, Elise
Doyen, Matthieu
Rivasseau-Jonveaux, Thérèse
Malaplate, Catherine
Guedj, Eric
Verger, Antoine
Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans
title Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans
title_full Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans
title_fullStr Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans
title_full_unstemmed Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans
title_short Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain (18)F-FDG digital PET scans
title_sort clinical impact of digital and conventional pet control databases for semi-quantitative analysis of brain (18)f-fdg digital pet scans
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704892/
https://www.ncbi.nlm.nih.gov/pubmed/33258085
http://dx.doi.org/10.1186/s13550-020-00733-y
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