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Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods
PURPOSE: Amyloid positron emission tomography (PET) with [(18)F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amylo...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542295/ https://www.ncbi.nlm.nih.gov/pubmed/37300571 http://dx.doi.org/10.1007/s00259-023-06279-0 |
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author | Jovalekic, Aleksandar Roé-Vellvé, Núria Koglin, Norman Quintana, Mariana Lagos Nelson, Aaron Diemling, Markus Lilja, Johan Gómez-González, Juan Pablo Doré, Vincent Bourgeat, Pierrick Whittington, Alex Gunn, Roger Stephens, Andrew W. Bullich, Santiago |
author_facet | Jovalekic, Aleksandar Roé-Vellvé, Núria Koglin, Norman Quintana, Mariana Lagos Nelson, Aaron Diemling, Markus Lilja, Johan Gómez-González, Juan Pablo Doré, Vincent Bourgeat, Pierrick Whittington, Alex Gunn, Roger Stephens, Andrew W. Bullich, Santiago |
author_sort | Jovalekic, Aleksandar |
collection | PubMed |
description | PURPOSE: Amyloid positron emission tomography (PET) with [(18)F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. METHODS: This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), Amyloid(IQ)) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. RESULTS: The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. CONCLUSION: This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06279-0. |
format | Online Article Text |
id | pubmed-10542295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-105422952023-10-03 Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods Jovalekic, Aleksandar Roé-Vellvé, Núria Koglin, Norman Quintana, Mariana Lagos Nelson, Aaron Diemling, Markus Lilja, Johan Gómez-González, Juan Pablo Doré, Vincent Bourgeat, Pierrick Whittington, Alex Gunn, Roger Stephens, Andrew W. Bullich, Santiago Eur J Nucl Med Mol Imaging Original Article PURPOSE: Amyloid positron emission tomography (PET) with [(18)F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. METHODS: This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), Amyloid(IQ)) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. RESULTS: The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. CONCLUSION: This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06279-0. Springer Berlin Heidelberg 2023-06-10 2023 /pmc/articles/PMC10542295/ /pubmed/37300571 http://dx.doi.org/10.1007/s00259-023-06279-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Jovalekic, Aleksandar Roé-Vellvé, Núria Koglin, Norman Quintana, Mariana Lagos Nelson, Aaron Diemling, Markus Lilja, Johan Gómez-González, Juan Pablo Doré, Vincent Bourgeat, Pierrick Whittington, Alex Gunn, Roger Stephens, Andrew W. Bullich, Santiago Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods |
title | Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods |
title_full | Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods |
title_fullStr | Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods |
title_full_unstemmed | Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods |
title_short | Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods |
title_sort | validation of quantitative assessment of florbetaben pet scans as an adjunct to the visual assessment across 15 software methods |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542295/ https://www.ncbi.nlm.nih.gov/pubmed/37300571 http://dx.doi.org/10.1007/s00259-023-06279-0 |
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