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β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3

INTRODUCTION: The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to eva...

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Autores principales: Bourgeat, Pierrick, Doré, Vincent, Burnham, Samantha C., Benzinger, Tammie, Tosun, Duygu, Li, Shenpeng, Goyal, Manu, LaMontagne, Pamela, Jin, Liang, Rowe, Christopher C, Weiner, Michael W., Morris, John C, Masters, Colin L, Fripp, Jurgen, Villemagne, Victor L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9550562/
https://www.ncbi.nlm.nih.gov/pubmed/35917917
http://dx.doi.org/10.1016/j.neuroimage.2022.119527
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author Bourgeat, Pierrick
Doré, Vincent
Burnham, Samantha C.
Benzinger, Tammie
Tosun, Duygu
Li, Shenpeng
Goyal, Manu
LaMontagne, Pamela
Jin, Liang
Rowe, Christopher C
Weiner, Michael W.
Morris, John C
Masters, Colin L
Fripp, Jurgen
Villemagne, Victor L
author_facet Bourgeat, Pierrick
Doré, Vincent
Burnham, Samantha C.
Benzinger, Tammie
Tosun, Duygu
Li, Shenpeng
Goyal, Manu
LaMontagne, Pamela
Jin, Liang
Rowe, Christopher C
Weiner, Michael W.
Morris, John C
Masters, Colin L
Fripp, Jurgen
Villemagne, Victor L
author_sort Bourgeat, Pierrick
collection PubMed
description INTRODUCTION: The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies. METHODS: All Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer’s respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in (11)C-PiB-(18)F-Florbetapir pairs and longitudinal consistency were evaluated. RESULTS: The smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for (18)F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used. CONCLUSIONS: FWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined.
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spelling pubmed-95505622022-11-15 β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3 Bourgeat, Pierrick Doré, Vincent Burnham, Samantha C. Benzinger, Tammie Tosun, Duygu Li, Shenpeng Goyal, Manu LaMontagne, Pamela Jin, Liang Rowe, Christopher C Weiner, Michael W. Morris, John C Masters, Colin L Fripp, Jurgen Villemagne, Victor L Neuroimage Article INTRODUCTION: The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies. METHODS: All Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer’s respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in (11)C-PiB-(18)F-Florbetapir pairs and longitudinal consistency were evaluated. RESULTS: The smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for (18)F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used. CONCLUSIONS: FWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined. 2022-11-15 2022-07-30 /pmc/articles/PMC9550562/ /pubmed/35917917 http://dx.doi.org/10.1016/j.neuroimage.2022.119527 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Article
Bourgeat, Pierrick
Doré, Vincent
Burnham, Samantha C.
Benzinger, Tammie
Tosun, Duygu
Li, Shenpeng
Goyal, Manu
LaMontagne, Pamela
Jin, Liang
Rowe, Christopher C
Weiner, Michael W.
Morris, John C
Masters, Colin L
Fripp, Jurgen
Villemagne, Victor L
β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
title β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
title_full β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
title_fullStr β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
title_full_unstemmed β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
title_short β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
title_sort β-amyloid pet harmonisation across longitudinal studies: application to aibl, adni and oasis3
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9550562/
https://www.ncbi.nlm.nih.gov/pubmed/35917917
http://dx.doi.org/10.1016/j.neuroimage.2022.119527
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