Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease

Richard E Jones; Hassan A Zaidi; Daniel J Hammersley; Suzan Hatipoglu; Ruth Owen; Gabriel Balaban; Antonio de Marvao; François Simard; Amrit S Lota; Ciara Mahon; Batool Almogheer; Lukas Mach; Francesca Musella; Xiuyu Chen; John Gregson; Laura Lazzari; Andrew Ravendren; Francisco Leyva; Shihua Zhao; Ali Vazir; Pablo Lamata; Brian P Halliday; Dudley J Pennell; Martin J Bishop; Sanjay K Prasad

doi:10.1016/j.jcmg.2022.10.020

Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease

Richard E Jones, Hassan A Zaidi, Daniel J Hammersley, Suzan Hatipoglu, Ruth Owen, Gabriel Balaban, Antonio de Marvao, François Simard, Amrit S Lota, Ciara Mahon, Batool Almogheer, Lukas Mach, Francesca Musella, Xiuyu Chen, John Gregson, Laura Lazzari, Andrew Ravendren, Francisco Leyva, Shihua Zhao, Ali VazirPablo Lamata, Brian P Halliday, Dudley J Pennell, Martin J Bishop, Sanjay K Prasad

Research output: Contribution to journal › Article › peer-review

Abstract

BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).

OBJECTIVES: The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).

METHODS: Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.

RESULTS: Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.

CONCLUSIONS: Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

Original language	English
Pages (from-to)	628-638
Number of pages	11
Journal	JACC. Cardiovascular imaging
Volume	16
Issue number	5
Early online date	11 Jan 2023
DOIs	https://doi.org/10.1016/j.jcmg.2022.10.020
Publication status	Published - May 2023

Bibliographical note

Copyright © 2022 by the American College of Cardiology Foundation. Published by Elsevier. This is an open access article distributed under the terms of the Creative Commons Attribution License CC BY [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Funding Support and Author Disclosures: This work was supported by a National Heart and Lung Institute Foundation grant awarded to Drs Prasad and Jones. This work was also supported by a British Heart Foundation grant (FS/ICRF/21/26019) awarded to Dr Halliday and an Engineering and Physical Sciences Research Council grant (2018/19 DTP - EP/R513064/1) awarded to Mr Zaidi. Dr Leyva is a consultant with and has received research funding from Medtronic Inc, Boston Scientific, Abbott, Microport, and Biotronik. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Keywords

computational analysis
sudden cardiac death
late gadolinium enhancement cardiac magnetic resonance
coronary artery disease

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10.1016/j.jcmg.2022.10.020Licence: CC BY 4.0

Joneseral_2023_VoR
Copyright © 2022 by the American College of Cardiology Foundation. Published by Elsevier. This is an open access article distributed under the terms of the Creative Commons Attribution License CC BY [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Final published version, 1.66 MBLicence: CC BY 4.0

Cite this

Jones, R. E., Zaidi, H. A., Hammersley, D. J., Hatipoglu, S., Owen, R., Balaban, G., de Marvao, A., Simard, F., Lota, A. S., Mahon, C., Almogheer, B., Mach, L., Musella, F., Chen, X., Gregson, J., Lazzari, L., Ravendren, A., Leyva, F., Zhao, S., ... Prasad, S. K. (2023). Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease. JACC. Cardiovascular imaging, 16(5), 628-638. https://doi.org/10.1016/j.jcmg.2022.10.020

@article{b8e3e131151441299c2b941f80f2db72,

title = "Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease",

abstract = "BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).OBJECTIVES: The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).METHODS: Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.RESULTS: Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.CONCLUSIONS: Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.",

keywords = "computational analysis, sudden cardiac death, late gadolinium enhancement cardiac magnetic resonance, coronary artery disease",

author = "Jones, {Richard E} and Zaidi, {Hassan A} and Hammersley, {Daniel J} and Suzan Hatipoglu and Ruth Owen and Gabriel Balaban and {de Marvao}, Antonio and Fran{\c c}ois Simard and Lota, {Amrit S} and Ciara Mahon and Batool Almogheer and Lukas Mach and Francesca Musella and Xiuyu Chen and John Gregson and Laura Lazzari and Andrew Ravendren and Francisco Leyva and Shihua Zhao and Ali Vazir and Pablo Lamata and Halliday, {Brian P} and Pennell, {Dudley J} and Bishop, {Martin J} and Prasad, {Sanjay K}",

note = "Copyright {\textcopyright} 2022 by the American College of Cardiology Foundation. Published by Elsevier. This is an open access article distributed under the terms of the Creative Commons Attribution License CC BY [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Funding Support and Author Disclosures: This work was supported by a National Heart and Lung Institute Foundation grant awarded to Drs Prasad and Jones. This work was also supported by a British Heart Foundation grant (FS/ICRF/21/26019) awarded to Dr Halliday and an Engineering and Physical Sciences Research Council grant (2018/19 DTP - EP/R513064/1) awarded to Mr Zaidi. Dr Leyva is a consultant with and has received research funding from Medtronic Inc, Boston Scientific, Abbott, Microport, and Biotronik. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. ",

year = "2023",

month = may,

doi = "10.1016/j.jcmg.2022.10.020",

language = "English",

volume = "16",

pages = "628--638",

number = "5",

}

Jones, RE, Zaidi, HA, Hammersley, DJ, Hatipoglu, S, Owen, R, Balaban, G, de Marvao, A, Simard, F, Lota, AS, Mahon, C, Almogheer, B, Mach, L, Musella, F, Chen, X, Gregson, J, Lazzari, L, Ravendren, A, Leyva, F, Zhao, S, Vazir, A, Lamata, P, Halliday, BP, Pennell, DJ, Bishop, MJ & Prasad, SK 2023, 'Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease', JACC. Cardiovascular imaging, vol. 16, no. 5, pp. 628-638. https://doi.org/10.1016/j.jcmg.2022.10.020

TY - JOUR

T1 - Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease

AU - Jones, Richard E

AU - Zaidi, Hassan A

AU - Hammersley, Daniel J

AU - Hatipoglu, Suzan

AU - Owen, Ruth

AU - Balaban, Gabriel

AU - de Marvao, Antonio

AU - Simard, François

AU - Lota, Amrit S

AU - Mahon, Ciara

AU - Almogheer, Batool

AU - Mach, Lukas

AU - Musella, Francesca

AU - Chen, Xiuyu

AU - Gregson, John

AU - Lazzari, Laura

AU - Ravendren, Andrew

AU - Leyva, Francisco

AU - Zhao, Shihua

AU - Vazir, Ali

AU - Lamata, Pablo

AU - Halliday, Brian P

AU - Pennell, Dudley J

AU - Bishop, Martin J

AU - Prasad, Sanjay K

N1 - Copyright © 2022 by the American College of Cardiology Foundation. Published by Elsevier. This is an open access article distributed under the terms of the Creative Commons Attribution License CC BY [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Funding Support and Author Disclosures: This work was supported by a National Heart and Lung Institute Foundation grant awarded to Drs Prasad and Jones. This work was also supported by a British Heart Foundation grant (FS/ICRF/21/26019) awarded to Dr Halliday and an Engineering and Physical Sciences Research Council grant (2018/19 DTP - EP/R513064/1) awarded to Mr Zaidi. Dr Leyva is a consultant with and has received research funding from Medtronic Inc, Boston Scientific, Abbott, Microport, and Biotronik. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

PY - 2023/5

Y1 - 2023/5

N2 - BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).OBJECTIVES: The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).METHODS: Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.RESULTS: Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.CONCLUSIONS: Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

AB - BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).OBJECTIVES: The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).METHODS: Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.RESULTS: Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.CONCLUSIONS: Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

KW - computational analysis

KW - sudden cardiac death

KW - late gadolinium enhancement cardiac magnetic resonance

KW - coronary artery disease

UR - https://www.sciencedirect.com/science/article/pii/S1936878X22006581?via%3Dihub

UR - http://www.scopus.com/inward/record.url?scp=85152733427&partnerID=8YFLogxK

U2 - 10.1016/j.jcmg.2022.10.020

DO - 10.1016/j.jcmg.2022.10.020

M3 - Article

C2 - 36752426

VL - 16

SP - 628

EP - 638

JO - JACC. Cardiovascular imaging

JF - JACC. Cardiovascular imaging

IS - 5

ER -

Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease

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