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Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables

PURPOSE: Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore...

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Autores principales: Kuronuma, Keiichiro, Miller, Robert J. H., Van Kriekinge, Serge D., Han, Donghee, Singh, Ananya, Gransar, Heidi, Dey, Damini, Berman, Daniel S., Slomka, Piotr J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547643/
https://www.ncbi.nlm.nih.gov/pubmed/37428217
http://dx.doi.org/10.1007/s00259-023-06323-z
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author Kuronuma, Keiichiro
Miller, Robert J. H.
Van Kriekinge, Serge D.
Han, Donghee
Singh, Ananya
Gransar, Heidi
Dey, Damini
Berman, Daniel S.
Slomka, Piotr J.
author_facet Kuronuma, Keiichiro
Miller, Robert J. H.
Van Kriekinge, Serge D.
Han, Donghee
Singh, Ananya
Gransar, Heidi
Dey, Damini
Berman, Daniel S.
Slomka, Piotr J.
author_sort Kuronuma, Keiichiro
collection PubMed
description PURPOSE: Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables. METHODS: Consecutive patients who underwent pharmacological stress-rest (82)Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM). RESULTS: In a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18–1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01–1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1). CONCLUSION: Stress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06323-z.
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spelling pubmed-105476432023-10-05 Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables Kuronuma, Keiichiro Miller, Robert J. H. Van Kriekinge, Serge D. Han, Donghee Singh, Ananya Gransar, Heidi Dey, Damini Berman, Daniel S. Slomka, Piotr J. Eur J Nucl Med Mol Imaging Original Article PURPOSE: Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables. METHODS: Consecutive patients who underwent pharmacological stress-rest (82)Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM). RESULTS: In a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18–1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01–1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1). CONCLUSION: Stress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06323-z. Springer Berlin Heidelberg 2023-07-10 2023 /pmc/articles/PMC10547643/ /pubmed/37428217 http://dx.doi.org/10.1007/s00259-023-06323-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Kuronuma, Keiichiro
Miller, Robert J. H.
Van Kriekinge, Serge D.
Han, Donghee
Singh, Ananya
Gransar, Heidi
Dey, Damini
Berman, Daniel S.
Slomka, Piotr J.
Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables
title Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables
title_full Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables
title_fullStr Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables
title_full_unstemmed Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables
title_short Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables
title_sort incremental prognostic value of stress phase entropy over standard pet myocardial perfusion imaging variables
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547643/
https://www.ncbi.nlm.nih.gov/pubmed/37428217
http://dx.doi.org/10.1007/s00259-023-06323-z
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