Quantifying late gadolinium enhancement improved sudden cardiac death risk prediction in non-ischemic dilated cardiomyopathy

Abstract Background While previous studies have proved the late gadolinium enhancement (LGE) was associated with poor prognosis in non-ischemic dilated cardiomyopathy (DCM), the optimal method for LGE quantification and the ability of LGE extent in identifying sudden cardiac death (SCD) remain less clarified. Purpose This study sought to compare the reproducibility of LGE quantification methods and explore the asssociation between LGE extent and SCD endpoint in DCM patients. Methods In this prospective study, LGE was quantified by the 2-6 standard deviations (SD) above the remote myocardium and full-wide half-maximum (FWHM) methods. The primary endpoint was SCD and arrythmia endpoint included SCD and aborted SCD. Reproducibility of LGE quantification was measured by Bland-Altman analysis and intra-class correlation coefficients (ICC). Competing risk regression analysis, C-index and area under the curve (AUC) were performed to identify the prognostic value. Results Among the 770 patients, 336 (44%) patients had LGE. FWHM demonstrated the best reproducibility compared with other quantification methods (intraobserver variability: ICC = 0.94, mean bias: -0.43 ± 4.89%; interobserver variability: ICC = 0.90, mean bias: -2.65 ± 6.40%). After a median follow-up of 49 months, SCD occurred in 61 (8%) patients and arrythmia endpoint occurred in 87 (11%) patients. Among all quantification method, LGE extent measured by FWHM showed the highest predictive value of SCD (C index: 0.72) and arrythmia events (C index: 0.71) than other methods. In the competing risk analysis, LGE extent was independently association with SCD (Hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.03 - 1.07, P < 0.001) and arrythmia endpoint (HR 1.05, 95% CI 1.03 - 1.06, P < 0.001). LGE extent >8% showed significantly higher risk of SCD and arrythmia endpoint than those with LGE extent ≤8% (P < 0.001). Incoporating LGE exent and 35% left ventricular ejection fraction (LVEF) significantly improved the SCD (C index: 0.74 vs 0.61, P < 0.001) and arrythmia endpoint (C index: 0.73 vs 0.59, P < 0.001) prediction compared with LVEF. Conclusions FWHM demonstrated best reproducibility and highest SCD prediction ability among LGE quantification methods. Adding LGE extent to LVEF significantly improved the predictive value of SCD and arrythmia endpoint.Figure 1

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Journal
European Heart Journal
Published
2024-10-01
DOI
https://doi.org/10.1093/eurheartj/ehae666.225
Primary Topic
Cardiac Imaging and Diagnostics
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article
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article

Quantifying late gadolinium enhancement improved sudden cardiac death risk prediction in non-ischemic dilated cardiomyopathy

Yanming Xu, Jian Guo, Yu Chen, Yuan Li et al.
European Heart Journal
Cardiac Imaging and Diagnostics
article

Quantifying late gadolinium enhancement improved sudden cardiac death risk prediction in non-ischemic dilated cardiomyopathy

Yanming Xu, Jian Guo, Yu Chen, Yuan Li, Yang Han
article en

Abstract

Abstract Background While previous studies have proved the late gadolinium enhancement (LGE) was associated with poor prognosis in non-ischemic dilated cardiomyopathy (DCM), the optimal method for LGE quantification and the ability of LGE extent in identifying sudden cardiac death (SCD) remain less clarified. Purpose This study sought to compare the reproducibility of LGE quantification methods and explore the asssociation between LGE extent and SCD endpoint in DCM patients. Methods In this prospective study, LGE was quantified by the 2-6 standard deviations (SD) above the remote myocardium and full-wide half-maximum (FWHM) methods. The primary endpoint was SCD and arrythmia endpoint included SCD and aborted SCD. Reproducibility of LGE quantification was measured by Bland-Altman analysis and intra-class correlation coefficients (ICC). Competing risk regression analysis, C-index and area under the curve (AUC) were performed to identify the prognostic value. Results Among the 770 patients, 336 (44%) patients had LGE. FWHM demonstrated the best reproducibility compared with other quantification methods (intraobserver variability: ICC = 0.94, mean bias: -0.43 ± 4.89%; interobserver variability: ICC = 0.90, mean bias: -2.65 ± 6.40%). After a median follow-up of 49 months, SCD occurred in 61 (8%) patients and arrythmia endpoint occurred in 87 (11%) patients. Among all quantification method, LGE extent measured by FWHM showed the highest predictive value of SCD (C index: 0.72) and arrythmia events (C index: 0.71) than other methods. In the competing risk analysis, LGE extent was independently association with SCD (Hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.03 - 1.07, P < 0.001) and arrythmia endpoint (HR 1.05, 95% CI 1.03 - 1.06, P < 0.001). LGE extent >8% showed significantly higher risk of SCD and arrythmia endpoint than those with LGE extent ≤8% (P < 0.001). Incoporating LGE exent and 35% left ventricular ejection fraction (LVEF) significantly improved the SCD (C index: 0.74 vs 0.61, P < 0.001) and arrythmia endpoint (C index: 0.73 vs 0.59, P < 0.001) prediction compared with LVEF. Conclusions FWHM demonstrated best reproducibility and highest SCD prediction ability among LGE quantification methods. Adding LGE extent to LVEF significantly improved the predictive value of SCD and arrythmia endpoint.Figure 1

European Heart JournalVol. 45(Supplement_1)
Sichuan University (CN), The Ohio State University Wexner Medical Center (US), West China Hospital of Sichuan University (CN), Ohio State University Hospital (US)
Good health and well-being
Openalex Percentile: Top 68%
Cardiac Imaging and Diagnostics
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