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Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT

BACKGROUND: We investigated fully automatic coronary artery calcium (CAC) scoring and cardiovascular disease (CVD) risk categorization from CT attenuation correction (CTAC) acquired at rest and stress during cardiac PET/CT and compared it with manual annotations in CTAC and with dedicated calcium sc...

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Autores principales: Išgum, Ivana, de Vos, Bob D., Wolterink, Jelmer M., Dey, Damini, Berman, Daniel S., Rubeaux, Mathieu, Leiner, Tim, Slomka, Piotr J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5628109/
https://www.ncbi.nlm.nih.gov/pubmed/28378112
http://dx.doi.org/10.1007/s12350-017-0866-3
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author Išgum, Ivana
de Vos, Bob D.
Wolterink, Jelmer M.
Dey, Damini
Berman, Daniel S.
Rubeaux, Mathieu
Leiner, Tim
Slomka, Piotr J.
author_facet Išgum, Ivana
de Vos, Bob D.
Wolterink, Jelmer M.
Dey, Damini
Berman, Daniel S.
Rubeaux, Mathieu
Leiner, Tim
Slomka, Piotr J.
author_sort Išgum, Ivana
collection PubMed
description BACKGROUND: We investigated fully automatic coronary artery calcium (CAC) scoring and cardiovascular disease (CVD) risk categorization from CT attenuation correction (CTAC) acquired at rest and stress during cardiac PET/CT and compared it with manual annotations in CTAC and with dedicated calcium scoring CT (CSCT). METHODS AND RESULTS: We included 133 consecutive patients undergoing myocardial perfusion (82)Rb PET/CT with the acquisition of low-dose CTAC at rest and stress. Additionally, a dedicated CSCT was performed for all patients. Manual CAC annotations in CTAC and CSCT provided the reference standard. In CTAC, CAC was scored automatically using a previously developed machine learning algorithm. Patients were assigned to a CVD risk category based on their Agatston score (0, 1-10, 11-100, 101-400, >400). Agreement in CVD risk categorization between manual and automatic scoring in CTAC at rest and stress resulted in Cohen’s linearly weighted κ of 0.85 and 0.89, respectively. The agreement between CSCT and CTAC at rest resulted in κ of 0.82 and 0.74, using manual and automatic scoring, respectively. For CTAC at stress, these were 0.79 and 0.70, respectively. CONCLUSION: Automatic CAC scoring from CTAC PET/CT may allow routine CVD risk assessment from the CTAC component of PET/CT without any additional radiation dose or scan time. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12350-017-0866-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-56281092018-10-04 Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT Išgum, Ivana de Vos, Bob D. Wolterink, Jelmer M. Dey, Damini Berman, Daniel S. Rubeaux, Mathieu Leiner, Tim Slomka, Piotr J. J Nucl Cardiol Original Article BACKGROUND: We investigated fully automatic coronary artery calcium (CAC) scoring and cardiovascular disease (CVD) risk categorization from CT attenuation correction (CTAC) acquired at rest and stress during cardiac PET/CT and compared it with manual annotations in CTAC and with dedicated calcium scoring CT (CSCT). METHODS AND RESULTS: We included 133 consecutive patients undergoing myocardial perfusion (82)Rb PET/CT with the acquisition of low-dose CTAC at rest and stress. Additionally, a dedicated CSCT was performed for all patients. Manual CAC annotations in CTAC and CSCT provided the reference standard. In CTAC, CAC was scored automatically using a previously developed machine learning algorithm. Patients were assigned to a CVD risk category based on their Agatston score (0, 1-10, 11-100, 101-400, >400). Agreement in CVD risk categorization between manual and automatic scoring in CTAC at rest and stress resulted in Cohen’s linearly weighted κ of 0.85 and 0.89, respectively. The agreement between CSCT and CTAC at rest resulted in κ of 0.82 and 0.74, using manual and automatic scoring, respectively. For CTAC at stress, these were 0.79 and 0.70, respectively. CONCLUSION: Automatic CAC scoring from CTAC PET/CT may allow routine CVD risk assessment from the CTAC component of PET/CT without any additional radiation dose or scan time. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12350-017-0866-3) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-04-04 2018 /pmc/articles/PMC5628109/ /pubmed/28378112 http://dx.doi.org/10.1007/s12350-017-0866-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Išgum, Ivana
de Vos, Bob D.
Wolterink, Jelmer M.
Dey, Damini
Berman, Daniel S.
Rubeaux, Mathieu
Leiner, Tim
Slomka, Piotr J.
Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
title Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
title_full Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
title_fullStr Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
title_full_unstemmed Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
title_short Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
title_sort automatic determination of cardiovascular risk by ct attenuation correction maps in rb-82 pet/ct
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5628109/
https://www.ncbi.nlm.nih.gov/pubmed/28378112
http://dx.doi.org/10.1007/s12350-017-0866-3
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