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Software development for quantitative analysis of brain amyloid PET
INTRODUCTION: Centiloid (CL) scaling has become a standard quantitative measure in amyloid PET because it allows the direct comparison of results across sites, even when different analytical methods or PET tracers are used. METHODS: In the present study, we developed new standalone software to easil...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933769/ https://www.ncbi.nlm.nih.gov/pubmed/35134278 http://dx.doi.org/10.1002/brb3.2499 |
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author | Matsuda, Hiroshi Yamao, Tensho |
author_facet | Matsuda, Hiroshi Yamao, Tensho |
author_sort | Matsuda, Hiroshi |
collection | PubMed |
description | INTRODUCTION: Centiloid (CL) scaling has become a standard quantitative measure in amyloid PET because it allows the direct comparison of results across sites, even when different analytical methods or PET tracers are used. METHODS: In the present study, we developed new standalone software to easily handle a pipeline for accurate calculation of the CL scale for the five currently available amyloid PET tracers—(11)C‐PiB, (18)F‐florbetapir, (18)F‐flutemetamol, (18)F‐florbetaben, and (18)F‐NAV4694. This pipeline requires reorientation and coregistration of PET and MRI, anatomic standardization of coregistered PET to a standardized space using a warping parameter for coregistered MRI, application of standard volumes of interest (VOIs) to the warped PET, calculation of the standardized uptake value ratio (SUVR) for the target VOIs, and finally conversion of the SUVR to the CL scale. The PET data for these tracers were collected from the publicly available Global Alzheimer's Association Interactive Network (GAAIN) repository. We also developed software to map Z‐scores for the statistical comparison of a patient's PET data with a negative control database obtained from young healthy controls in the GAAIN repository. RESULTS: When whole cerebellum or whole cerebellum plus brainstem was chosen as the reference area, an excellent correlation was found between the CL scale calculated by this software and the CL scale published by GAAIN. There were no significant differences in the detection performance of significant amyloid accumulation using Z‐score mapping between each (18)F‐labeled tracer and (11)C‐PiB. The cutoff CL values providing the most accurate detection of regional amyloid positivity in Z‐score mapping were 11.8, 14.4, 14.7, 15.6, and 17.7 in the posterior cingulate gyrus and precuneus, frontal cortex, temporal cortex, parietal cortex, and striatum, respectively. CONCLUSION: This software is able to not only provide reliable calculation of the global CL scale but also detect significant local amyloid accumulation in an individual patient. |
format | Online Article Text |
id | pubmed-8933769 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89337692022-03-24 Software development for quantitative analysis of brain amyloid PET Matsuda, Hiroshi Yamao, Tensho Brain Behav Original Articles INTRODUCTION: Centiloid (CL) scaling has become a standard quantitative measure in amyloid PET because it allows the direct comparison of results across sites, even when different analytical methods or PET tracers are used. METHODS: In the present study, we developed new standalone software to easily handle a pipeline for accurate calculation of the CL scale for the five currently available amyloid PET tracers—(11)C‐PiB, (18)F‐florbetapir, (18)F‐flutemetamol, (18)F‐florbetaben, and (18)F‐NAV4694. This pipeline requires reorientation and coregistration of PET and MRI, anatomic standardization of coregistered PET to a standardized space using a warping parameter for coregistered MRI, application of standard volumes of interest (VOIs) to the warped PET, calculation of the standardized uptake value ratio (SUVR) for the target VOIs, and finally conversion of the SUVR to the CL scale. The PET data for these tracers were collected from the publicly available Global Alzheimer's Association Interactive Network (GAAIN) repository. We also developed software to map Z‐scores for the statistical comparison of a patient's PET data with a negative control database obtained from young healthy controls in the GAAIN repository. RESULTS: When whole cerebellum or whole cerebellum plus brainstem was chosen as the reference area, an excellent correlation was found between the CL scale calculated by this software and the CL scale published by GAAIN. There were no significant differences in the detection performance of significant amyloid accumulation using Z‐score mapping between each (18)F‐labeled tracer and (11)C‐PiB. The cutoff CL values providing the most accurate detection of regional amyloid positivity in Z‐score mapping were 11.8, 14.4, 14.7, 15.6, and 17.7 in the posterior cingulate gyrus and precuneus, frontal cortex, temporal cortex, parietal cortex, and striatum, respectively. CONCLUSION: This software is able to not only provide reliable calculation of the global CL scale but also detect significant local amyloid accumulation in an individual patient. John Wiley and Sons Inc. 2022-02-08 /pmc/articles/PMC8933769/ /pubmed/35134278 http://dx.doi.org/10.1002/brb3.2499 Text en © 2022 The Authors. Brain and Behavior published by Wiley Periodicals LLC https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Matsuda, Hiroshi Yamao, Tensho Software development for quantitative analysis of brain amyloid PET |
title | Software development for quantitative analysis of brain amyloid PET |
title_full | Software development for quantitative analysis of brain amyloid PET |
title_fullStr | Software development for quantitative analysis of brain amyloid PET |
title_full_unstemmed | Software development for quantitative analysis of brain amyloid PET |
title_short | Software development for quantitative analysis of brain amyloid PET |
title_sort | software development for quantitative analysis of brain amyloid pet |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933769/ https://www.ncbi.nlm.nih.gov/pubmed/35134278 http://dx.doi.org/10.1002/brb3.2499 |
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