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The Value of Myocardial Fibrosis Parameters Derived from Cardiac Magnetic Resonance Imaging in Risk Stratification for Patients with Hypertrophic Cardiomyopathy

Published:January 03, 2023DOI:https://doi.org/10.1016/j.acra.2022.12.026

      Highlights

      • The global ECV is better than LGE, global native T1, and global postcontrast T1 in predicting the risk of SCD in HCM patients.
      • The global ECV is comparable to the HCM Risk-SCD scale in predicting SCD risk.
      • Cox regression analysis also showed that global ECV is an independent predictor of SCD adverse events in patients with HCM.

      Rationale and Objectives

      The aim of the study was to determine whether myocardial fibrosis parameters of cardiac magnetic resonance imaging (MRI) has added value in the risk stratification of hypertrophic cardiomyopathy (HCM) patients.

      Materials and Methods

      In this retrospective study, 108 patients with HCM (mean age ± standard deviation, 55.5 ± 13.4 years) were included from January 2019 to April 2022, and were followed up for 2 years to record sudden cardiac death (SCD) adverse events. All HCM patients underwent cardiac MRI and were divided into a training cohort (n = 81; mean age, 56.1 ± 13.0 years) and a validation cohort (n = 27; mean age, 57.8 ± 13.9 years). According to the presence of SCD risk factors defined by the 2020 AHA/ACC guidelines, HCM patients were classified into low-risk and high-risk groups. Cardiac MRI features, including late gadolinium enhancement (LGE), T1 mapping, and extracellular volume fraction (ECV), were assessed and compared between the two groups. Logistic regression analysis was used to select the optimal predictors of SCD from cardiac MRI features and HCM Risk-SCD score to construct prediction models. Receiver operating curve (ROC) analysis was used to assess the predictive performance of the constructed prediction model. Cox regression analysis was also used to determine the optimal predictors of SCD adverse events.

      Results

      Multivariate logistic analysis showed that the global ECV was the single myocardial fibrosis parameter predictive of the risk of SCD (p < 0.001). The areas under the ROC curves (AUC) of global ECV were higher than those of LGE, global native T1, global postcontrast T1, and HCM Risk-SCD (AUC = 0.85 vs. 0.74, 0.77, 0.63, 0.78). An integrative risk stratification model combining global ECV (odds ratio, 1.36 [95% CI: 1.16–1.60]; p < 0.001) and HCM Risk-SCD score (odds ratio, 1.63 [95% CI: 1.08–2.47]; p < 0.001) achieved an AUC of 0.89 (95% CI: 0.81-0.96) in the training cohort, which was significantly higher than that of HCM Risk-SCD score alone (p = 0.03). The AUC of the integrative model was 0.93 (95% CI: 0.84–1.00) in the validation cohort. Multivariate Cox regression analysis also showed that the global ECV was an independent predictor of SCD adverse events (hazard ratio, 1.27 [95% CI: 1.10–1.47]).

      Conclusion

      The ECV derived from cardiac MRI is comparable to the HCM Risk-SCD scale in predicting the SCD risk stratification in patients with HCM.

      Key words

      Abbreviations:

      HCM (Hypertrophic cardiomyopathy), SCD (Sudden cardiac death), ICD (Implantable cardioverter-defibrillator), LGE (Late gadolinium enhancement), ECV (Extracellular volume fraction), LVOT (Left ventricular outflow tract), VT (ventricular arrhythmia), NSVT (nonsustained ventricular tachycardia), EF (ejection fraction)
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      References

        • Marian AJ
        • Braunwald E
        Hypertrophic cardiomyopathy: genetics, pathogenesis, clinical manifestations, diagnosis, and therapy.
        Circ Res. 2017; 121: 749-770https://doi.org/10.1161/CIRCRESAHA.117.311059
        • Elliott P
        • Andersson B
        • Arbustini E
        • et al.
        Classification of the cardiomyopathies: a position statement from the European society of cardiology working group on myocardial and pericardial diseases.
        Eur Heart J. 2008; 29: 270-276https://doi.org/10.1093/eurheartj/ehm342
        • Norrish G
        • Ding T
        • Field E
        • et al.
        Development of a novel risk prediction model for sudden cardiac death in childhood hypertrophic cardiomyopathy (HCM Risk-Kids).
        JAMA Cardiol. 2019; 4: 918-927https://doi.org/10.1001/jamacardio.2019.2861
        • Weissler-Snir A
        • Allan K
        • Cunningham K
        • et al.
        Hypertrophic cardiomyopathy-related sudden cardiac death in young people in Ontario.
        Circulation. 2019; 140: 1706-1716https://doi.org/10.1161/CIRCULATIONAHA.119.040271
        • Gersh BJ
        • Maron BJ
        • Bonow RO
        • et al.
        2011 ACCF/AHA guideline for the diagnosis and treatment of hypertrophic cardiomyopathy: executive summary: a report of the American college of cardiology foundation/American heart association task force on practice guidelines.
        Circulation. 2011; 124: 2761-2796https://doi.org/10.1161/CIR.0b013e318223e230
        • Elliott PM
        • Poloniecki J
        • Dickie S
        • et al.
        Sudden death in hypertrophic cardiomyopathy: identification of high risk patients.
        J Am Coll Cardiol. 2000; 36: 2212-2218https://doi.org/10.1016/s0735-1097(00)01003-2
        • O'Mahony C
        • Tome-Esteban M
        • Lambiase PD
        • et al.
        A validation study of the 2003 American college of cardiology/European society of cardiology and 2011 American college of cardiology foundation/American heart association risk stratification and treatment algorithms for sudden cardiac death in patients with hypertrophic cardiomyopathy.
        Heart. 2013; 99: 534-541https://doi.org/10.1136/heartjnl-2012-303271
        • Elliott PM
        • Anastasakis A
        • Borger MA
        • et al.
        2014 ESC Guidelines on diagnosis and management of hypertrophic cardiomyopathy: the Task Force for the Diagnosis and Management of Hypertrophic Cardiomyopathy of the European Society of Cardiology (ESC).
        Eur Heart J. 2014; 35 (Epub 2014 Aug 29.): 2733-2779https://doi.org/10.1093/eurheartj/ehu284
        • O'Mahony C
        • Jichi F
        • Pavlou M
        • et al.
        A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy (HCM risk-SCD).
        Eur Heart J. 2014; 35: 2010-2020https://doi.org/10.1093/eurheartj/eht439
        • Ruiz-Salas A
        • Garcia-Pinilla JM
        • Cabrera-Bueno F
        • et al.
        Comparison of the new risk prediction model (HCM Risk-SCD) and classic risk factors for sudden death in patients with hypertrophic cardiomyopathy and defibrillator.
        Europace. 2016; 18: 773-777https://doi.org/10.1093/europace/euv079
        • Ommen SR
        • Mital S
        • Burke MA
        • et al.
        AHA/ACC guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy: a report of the American college of cardiology/american heart association joint committee on clinical practice guidelines.
        Circulation. 2020; 142: e558-e631https://doi.org/10.1161/CIR.0000000000000937
        • Freitas P
        • Ferreira AM
        • Arteaga-Fernandez E
        • et al.
        The amount of late gadolinium enhancement outperforms current guideline-recommended criteria in the identification of patients with hypertrophic cardiomyopathy at risk of sudden cardiac death.
        J Cardiovasc Magn Reson. 2019; 21: 50https://doi.org/10.1186/s12968-019-0561-4
        • Jellis CL
        • Desai MY.
        Sudden cardiac death prediction in hypertrophic cardiomyopathy using late gadolinium enhancement: trouble in paradise?.
        Heart. 2014; 100: 1821-1822https://doi.org/10.1136/heartjnl-2014-306295
        • Spiewak M
        • Klopotowski M
        • Kowalik E
        • et al.
        Sudden cardiac death risk in hypertrophic cardiomyopathy: comparison between echocardiography and magnetic resonance imaging.
        Sci Rep. 2021; 11: 7146https://doi.org/10.1038/s41598-021-86532-4
        • Wong TC
        • Piehler K
        • Meier CG
        • et al.
        Association between extracellular matrix expansion quantified by cardiovascular magnetic resonance and short-term mortality.
        Circulation. 2012; 126: 1206-1216https://doi.org/10.1161/CIRCULATIONAHA.111.089409
        • Weng Z
        • Yao J
        • Chan RH
        • et al.
        Prognostic value of LGE-CMR in HCM: a meta-analysis.
        JACC Cardiovasc Imaging. 2016; 9: 1392-1402https://doi.org/10.1016/j.jcmg.2016.02.031
        • Chan RH
        • Maron BJ
        • Olivotto I
        • et al.
        Prognostic value of quantitative contrast-enhanced cardiovascular magnetic resonance for the evaluation of sudden death risk in patients with hypertrophic cardiomyopathy.
        Circulation. 2014; 130: 484-495https://doi.org/10.1161/CIRCULATIONAHA.113.007094
        • Florian A
        • Ludwig A
        • Rosch S
        • et al.
        Myocardial fibrosis imaging based on T1-mapping and extracellular volume fraction (ECV) measurement in muscular dystrophy patients: diagnostic value compared with conventional late gadolinium enhancement (LGE) imaging.
        Eur Heart J Cardiovasc Imaging. 2014; 15: 1004-1012https://doi.org/10.1093/ehjci/jeu050
        • Miller CA
        • Naish JH
        • Bishop P
        • et al.
        Comprehensive validation of cardiovascular magnetic resonance techniques for the assessment of myocardial extracellular volume.
        Circ Cardiovasc Imaging. 2013; 6: 373-383https://doi.org/10.1161/CIRCIMAGING.112.000192
        • Li YC
        • Liu XM
        • Yang FY
        • et al.
        Prognostic value of myocardial extracellular volume fraction evaluation based on cardiac magnetic resonance T1 mapping with T1 long and short in hypertrophic cardiomyopathy.
        Eur Radiol. 2021; 7: 4557-4567https://doi.org/10.1007/s00330-020-07650-7
        • Avanesov M
        • Munch J
        • Weinrich J
        • et al.
        Prediction of the estimated 5-year risk of sudden cardiac death and syncope or non-sustained ventricular tachycardia in patients with hypertrophic cardiomyopathy using late gadolinium enhancement and extracellular volume CMR.
        Eur Radiol. 2017; 27: 5136-5145https://doi.org/10.1007/s00330-017-4869-x
        • Nagueh SF
        • Bierig SM
        • Budoff MJ
        • et al.
        American Society of Echocardiography clinical recommendations for multimodality cardiovascular imaging of patients with hypertrophic cardiomyopathy: endorsed by the American society of nuclear cardiology, society for cardiovascular magnetic resonance, and society of cardiovascular computed tomography.
        J Am Soc Echocardiogr. 2011; 24: 473-498https://doi.org/10.1016/j.echo.2011.03.006
        • Geske JB
        • Sorajja P
        • Nishimura RA
        • et al.
        Evaluation of left ventricular filling pressures by Doppler echocardiography in patients with hypertrophic cardiomyopathy: correlation with direct left atrial pressure measurement at cardiac catheterization.
        Circulation. 2007; 116: 2702-2708https://doi.org/10.1161/CIRCULATIONAHA.107.698985
        • Messroghli DR
        • Radjenovic A
        • Kozerke S
        • et al.
        Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart.
        Magn Reson Med. 2004; 52: 141-146https://doi.org/10.1002/mrm.20110
        • Zange L
        • Muehlberg F
        • Blaszczyk E
        • et al.
        Quantification in cardiovascular magnetic resonance: agreement of software from three different vendors on assessment of left ventricular function, 2D flow and parametric mapping.
        J Cardiovasc Magn Reson. 2019; 21: 12https://doi.org/10.1186/s12968-019-0522-y
        • Tao Q
        • Lamb HJ
        • Zeppenfeld K
        • van der Geest RJ.
        Myocardial scar identification based on analysis of look-locker and 3D late gadolinium enhanced MRI.
        Int J Cardiovasc Imaging. 2014; 30: 925-934https://doi.org/10.1007/s10554-014-0402-3
        • Ugander M
        • Oki AJ
        • Hsu LY
        • et al.
        Extracellular volume imaging by magnetic resonance imaging provides insights into overt and sub-clinical myocardial pathology.
        Eur Heart J. 2012; 33: 1268-1278https://doi.org/10.1093/eurheartj/ehr481
        • Messroghli DR
        • Moon JC
        • Ferreira VM
        • et al.
        Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI).
        J Cardiovasc Magn Reson. 2017; 19: 75https://doi.org/10.1186/s12968-017-0389-8
        • Lafreniere-Roula M
        • Bolkier Y
        • Zahavich L
        • et al.
        Family screening for hypertrophic cardiomyopathy: Is it time to change practice guidelines?.
        Eur Heart J. 2019; 40: 3672-3681https://doi.org/10.1093/eurheartj/ehz396
        • Baron E
        • Karam N
        • Donal E
        • et al.
        Management and outcomes of hypertrophic cardiomyopathy in young adults.
        Arch Cardiovasc Dis. 2021; 114: 465-473https://doi.org/10.1016/j.acvd.2020.12.006
        • Maron MS.
        Contrast-enhanced CMR in HCM: what lies behind the bright light of LGE and why it now matters.
        JACC Cardiovasc Imaging. 2013; 6: 597-599https://doi.org/10.1016/j.jcmg.2012.10.028
        • Hennig A
        • Salel M
        • Sacher F
        • et al.
        High-resolution three-dimensional late gadolinium-enhanced cardiac magnetic resonance imaging to identify the underlying substrate of ventricular arrhythmia.
        Europace. 2018; 20: 179-191https://doi.org/10.1093/europace/eux278
        • Dass S
        • Suttie JJ
        • Piechnik SK
        • et al.
        Myocardial tissue characterization using magnetic resonance noncontrast t1 mapping in hypertrophic and dilated cardiomyopathy.
        Circ Cardiovasc Imaging. 2012; 5: 726-733https://doi.org/10.1161/CIRCIMAGING.112.976738
        • Xu J
        • Zhuang B
        • Sirajuddin A
        • et al.
        MRI T1 mapping in hypertrophic cardiomyopathy: evaluation in patients without late gadolinium enhancement and hemodynamic obstruction.
        Radiology. 2020; 294: 275-286https://doi.org/10.1148/radiol.2019190651
        • Kellman P
        • Wilson JR
        • Xue H
        • et al.
        Extracellular volume fraction mapping in the myocardium, part 2: initial clinical experience.
        J Cardiovasc Magn Reson. 2012; 14: 64https://doi.org/10.1186/1532-429X-14-64
        • Qin L
        • Min JH
        • Chen CH
        • et al.
        Incremental values of T1 mapping in the prediction of sudden cardiac death risk in hypertrophic cardiomyopathy: a comparison with two guidelines.
        Front Cardiovasc Med. 2021; 8661673https://doi.org/10.3389/fcvm.2021.661673
        • Knobelsdorff-Brenkenhoff F
        • Prothmann M
        • Dieringer MA
        • et al.
        Myocardial T1 and T2 mapping at 3 T: reference values, influencing factors and implications.
        J Cardiovasc Magn Reson. 2013; 15: 53https://doi.org/10.1186/1532-429X-15-53
        • Schelbert EB
        • Piehler KM
        • Zareba KM
        • et al.
        Myocardial fibrosis quantified by extracellular volume is associated with subsequent hospitalization for heart failure, death, or both across the spectrum of ejection fraction and heart failure stage.
        J Am Heart Assoc. 2015; 4e002613https://doi.org/10.1161/JAHA.115.002613