Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Matsuda, Hiroshi, Yamao, Tensho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
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
_version_ 1784671728858824704
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
work_keys_str_mv AT matsudahiroshi softwaredevelopmentforquantitativeanalysisofbrainamyloidpet
AT yamaotensho softwaredevelopmentforquantitativeanalysisofbrainamyloidpet