Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI
Abstract INTRODUCTION The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid...
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| Aineistotyyppi: | Artikkeli |
| Kieli: | English |
| Julkaistu: |
Wiley
2023-04-01
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| Sarja: | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| Aiheet: | |
| Linkit: | https://doi.org/10.1002/dad2.12434 |
| _version_ | 1827353805255081984 |
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| author | William Coath Marc Modat M. Jorge Cardoso Pawel J. Markiewicz Christopher A. Lane Thomas D. Parker Ashvini Keshavan Sarah M. Buchanan Sarah E. Keuss Matthew J. Harris Ninon Burgos John Dickson Anna Barnes David L. Thomas Daniel Beasley Ian B. Malone Andrew Wong Kjell Erlandsson Benjamin A. Thomas Michael Schöll Sebastien Ourselin Marcus Richards Nick C. Fox Jonathan M. Schott David M. Cash for the Alzheimer's Disease Neuroimaging Initiative |
| author_facet | William Coath Marc Modat M. Jorge Cardoso Pawel J. Markiewicz Christopher A. Lane Thomas D. Parker Ashvini Keshavan Sarah M. Buchanan Sarah E. Keuss Matthew J. Harris Ninon Burgos John Dickson Anna Barnes David L. Thomas Daniel Beasley Ian B. Malone Andrew Wong Kjell Erlandsson Benjamin A. Thomas Michael Schöll Sebastien Ourselin Marcus Richards Nick C. Fox Jonathan M. Schott David M. Cash for the Alzheimer's Disease Neuroimaging Initiative |
| author_sort | William Coath |
| collection | DOAJ |
| description | Abstract INTRODUCTION The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI). METHODS We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian‐mixture‐modelling–derived cutpoints for Aβ PET positivity were converted. RESULTS The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM‐based Centiloids. Linear adjustment produced a WM‐based cutpoint of 18.1. DISCUSSION Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed. HIGHLIGHTS Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results. Centiloid values can be influenced by differences in acquisition. We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort. Whole cerebellum referenced values could be reliably transformed to Centiloids. White matter referenced values may be less generalizable between datasets. |
| first_indexed | 2024-03-08T03:33:21Z |
| format | Article |
| id | doaj.art-89fc878da77c45b0abc21824ecd8a625 |
| institution | Directory Open Access Journal |
| issn | 2352-8729 |
| language | English |
| last_indexed | 2024-03-08T03:33:21Z |
| publishDate | 2023-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| spelling | doaj.art-89fc878da77c45b0abc21824ecd8a6252024-02-10T14:10:32ZengWileyAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring2352-87292023-04-01152n/an/a10.1002/dad2.12434Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRIWilliam Coath0Marc Modat1M. Jorge Cardoso2Pawel J. Markiewicz3Christopher A. Lane4Thomas D. Parker5Ashvini Keshavan6Sarah M. Buchanan7Sarah E. Keuss8Matthew J. Harris9Ninon Burgos10John Dickson11Anna Barnes12David L. Thomas13Daniel Beasley14Ian B. Malone15Andrew Wong16Kjell Erlandsson17Benjamin A. Thomas18Michael Schöll19Sebastien Ourselin20Marcus Richards21Nick C. Fox22Jonathan M. Schott23David M. Cash24for the Alzheimer's Disease Neuroimaging InitiativeDementia Research Centre UCL Queen Square Institute of Neurology London UKSchool of Biomedical Engineering and Imaging Sciences King's College London London UKSchool of Biomedical Engineering and Imaging Sciences King's College London London UKCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering UCL London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKSorbonne Université, Institut du Cerveau ‐ Paris Brain Institute ‐ ICM, Inserm, CNRS, AP‐HP, Hôpital Pitié Salpêtrière, Inria Aramis project‐team Paris FranceInstitute of Nuclear Medicine University College London Hospitals London UKInstitute of Nuclear Medicine University College London Hospitals London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKSchool of Biomedical Engineering and Imaging Sciences King's College London London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKMRC Unit for Lifelong Health and Ageing at UCL London UKInstitute of Nuclear Medicine University College London Hospitals London UKInstitute of Nuclear Medicine University College London Hospitals London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKSchool of Biomedical Engineering and Imaging Sciences King's College London London UKMRC Unit for Lifelong Health and Ageing at UCL London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKDementia Research Centre UCL Queen Square Institute of Neurology London UKAbstract INTRODUCTION The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI). METHODS We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian‐mixture‐modelling–derived cutpoints for Aβ PET positivity were converted. RESULTS The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM‐based Centiloids. Linear adjustment produced a WM‐based cutpoint of 18.1. DISCUSSION Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed. HIGHLIGHTS Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results. Centiloid values can be influenced by differences in acquisition. We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort. Whole cerebellum referenced values could be reliably transformed to Centiloids. White matter referenced values may be less generalizable between datasets.https://doi.org/10.1002/dad2.12434Alzheimer's diseaseamyloid betacentiloidflorbetapirpositron emission tomography/magnetic resonance imaging |
| spellingShingle | William Coath Marc Modat M. Jorge Cardoso Pawel J. Markiewicz Christopher A. Lane Thomas D. Parker Ashvini Keshavan Sarah M. Buchanan Sarah E. Keuss Matthew J. Harris Ninon Burgos John Dickson Anna Barnes David L. Thomas Daniel Beasley Ian B. Malone Andrew Wong Kjell Erlandsson Benjamin A. Thomas Michael Schöll Sebastien Ourselin Marcus Richards Nick C. Fox Jonathan M. Schott David M. Cash for the Alzheimer's Disease Neuroimaging Initiative Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring Alzheimer's disease amyloid beta centiloid florbetapir positron emission tomography/magnetic resonance imaging |
| title | Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI |
| title_full | Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI |
| title_fullStr | Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI |
| title_full_unstemmed | Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI |
| title_short | Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI |
| title_sort | operationalizing the centiloid scale for 18f florbetapir pet studies on pet mri |
| topic | Alzheimer's disease amyloid beta centiloid florbetapir positron emission tomography/magnetic resonance imaging |
| url | https://doi.org/10.1002/dad2.12434 |
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