Cargando…

Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization

PURPOSE: Methodologies for optimization of SPECT image acquisition can be challenging due to imaging throughput, physiological bias, and patient comfort constraints. We evaluated a vendor‐independent method for simulating lower count image acquisitions. METHODS: We developed an algorithm that recomb...

Descripción completa

Detalles Bibliográficos
Autores principales: Queiroz, Cleiton Cavalcante, Machado, Marcos Antonio Dorea, Ximenes, Antonio Augusto Brito, Pino, Andre Gustavo Silva, Netto, Eduardo Martins
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906212/
https://www.ncbi.nlm.nih.gov/pubmed/34918865
http://dx.doi.org/10.1002/acm2.13508
_version_ 1784665361255235584
author Queiroz, Cleiton Cavalcante
Machado, Marcos Antonio Dorea
Ximenes, Antonio Augusto Brito
Pino, Andre Gustavo Silva
Netto, Eduardo Martins
author_facet Queiroz, Cleiton Cavalcante
Machado, Marcos Antonio Dorea
Ximenes, Antonio Augusto Brito
Pino, Andre Gustavo Silva
Netto, Eduardo Martins
author_sort Queiroz, Cleiton Cavalcante
collection PubMed
description PURPOSE: Methodologies for optimization of SPECT image acquisition can be challenging due to imaging throughput, physiological bias, and patient comfort constraints. We evaluated a vendor‐independent method for simulating lower count image acquisitions. METHODS: We developed an algorithm that recombines the ECG‐gated raw data into reduced counting acquisitions. We then tested the algorithm to simulate reduction of counting statistics from phantom SPECT image acquisition, which was synchronized with an ECG simulator. The datasets were reconstructed with a resolution recovery algorithm and the summed stress score (SSS) was assessed by three readers (two experts and one automatic). RESULTS: The algorithm generated varying counting levels, simulating multiple examinations at the same time. The error between the expected and the simulated countings ranged from approximately 5% to 10% for the ungated simulations and 0% for the gated simulations. CONCLUSIONS: The vendor‐independent algorithm successfully generated lower counting statistics datasets from single‐gated SPECT raw data. This method can be readily implemented for optimal SPECT research aiming to lower the injected activity and/ or to shorten the acquisition time.
format Online
Article
Text
id pubmed-8906212
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-89062122022-03-10 Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization Queiroz, Cleiton Cavalcante Machado, Marcos Antonio Dorea Ximenes, Antonio Augusto Brito Pino, Andre Gustavo Silva Netto, Eduardo Martins J Appl Clin Med Phys Technical Notes PURPOSE: Methodologies for optimization of SPECT image acquisition can be challenging due to imaging throughput, physiological bias, and patient comfort constraints. We evaluated a vendor‐independent method for simulating lower count image acquisitions. METHODS: We developed an algorithm that recombines the ECG‐gated raw data into reduced counting acquisitions. We then tested the algorithm to simulate reduction of counting statistics from phantom SPECT image acquisition, which was synchronized with an ECG simulator. The datasets were reconstructed with a resolution recovery algorithm and the summed stress score (SSS) was assessed by three readers (two experts and one automatic). RESULTS: The algorithm generated varying counting levels, simulating multiple examinations at the same time. The error between the expected and the simulated countings ranged from approximately 5% to 10% for the ungated simulations and 0% for the gated simulations. CONCLUSIONS: The vendor‐independent algorithm successfully generated lower counting statistics datasets from single‐gated SPECT raw data. This method can be readily implemented for optimal SPECT research aiming to lower the injected activity and/ or to shorten the acquisition time. John Wiley and Sons Inc. 2021-12-17 /pmc/articles/PMC8906212/ /pubmed/34918865 http://dx.doi.org/10.1002/acm2.13508 Text en © 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine 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 Technical Notes
Queiroz, Cleiton Cavalcante
Machado, Marcos Antonio Dorea
Ximenes, Antonio Augusto Brito
Pino, Andre Gustavo Silva
Netto, Eduardo Martins
Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
title Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
title_full Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
title_fullStr Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
title_full_unstemmed Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
title_short Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
title_sort technical note: partitioning of gated single photon emission computed tomography raw data for protocols optimization
topic Technical Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906212/
https://www.ncbi.nlm.nih.gov/pubmed/34918865
http://dx.doi.org/10.1002/acm2.13508
work_keys_str_mv AT queirozcleitoncavalcante technicalnotepartitioningofgatedsinglephotonemissioncomputedtomographyrawdataforprotocolsoptimization
AT machadomarcosantoniodorea technicalnotepartitioningofgatedsinglephotonemissioncomputedtomographyrawdataforprotocolsoptimization
AT ximenesantonioaugustobrito technicalnotepartitioningofgatedsinglephotonemissioncomputedtomographyrawdataforprotocolsoptimization
AT pinoandregustavosilva technicalnotepartitioningofgatedsinglephotonemissioncomputedtomographyrawdataforprotocolsoptimization
AT nettoeduardomartins technicalnotepartitioningofgatedsinglephotonemissioncomputedtomographyrawdataforprotocolsoptimization