Cardiac Magnetic Resonance Imaging Features in Hypertrophic Cardiomyopathy Diagnosed at <21 Years of Age

Prevalence and clinical significance of late gadolinium enhancement in children and adolescents with hypertrophic cardiomyopathy: a systematic review and meta-analysis

OBJECTIVES

Hypertrophic cardiomyopathy is the leading cause of sudden cardiac death among the paediatric population. The aim of this study is to investigate the prevalence and clinical significance of late gadolinium enhancement, as assessed by cardiac MRI, in paediatric hypertrophic cardiomyopathy.

METHODS

A systematic literature search was conducted in PubMed, SCOPUS, and Ovid SP to identify relevant studies. Pooled estimates with a 95% confidence interval were calculated using the random-effects generic inverse variance model. Statistical analysis was performed using Review Manager v5.4 and R programming.

RESULTS

Seventeen studies were included in this meta-analysis, encompassing a total of 778 patients. Late gadolinium enhancement was highly prevalent in paediatric hypertrophic cardiomyopathy, with a pooled prevalence of 51% (95% confidence interval, 40-62%). The estimated extent of focal fibrosis expressed as a percentage of left ventricular mass was 4.70% (95% confidence interval, 2.11-7.30%). The presence of late gadolinium enhancement was associated with an increased risk of adverse cardiac events (pooled odds ratio 3.49, 95% confidence interval 1.10-11.09). The left ventricular mass index of late gadolinium enhancement-positive group was higher than the negative group, with a standardised mean difference of 0.91 (95% confidence interval, 0.42-1.41).

CONCLUSION

This meta-analysis demonstrates that prevalence of late gadolinium enhancement in paediatric hypertrophic cardiomyopathy is similar to that in the adult population. The presence and extent of late gadolinium enhancement are independent predictors of adverse cardiac events, underscoring their prognostic significance among the paediatric population.

Cardiac MRI in diagnosis, prognosis, and follow-up of hypertrophic cardiomyopathy in children: current perspectives

Hypertrophic Cardiomyopathy (HCM) is an inherited myocardial disease characterised by left ventricular hypertrophy, which carries an increased risk of life-threatening arrhythmias and sudden cardiac death. The age of presentation and the underlying aetiology have a significant impact on the prognosis and quality of life of children with HCM, as childhood-onset HCM is associated with high mortality risk and poor long-term outcomes. Accurate cardiac assessment and identification of the HCM phenotype are therefore crucial to determine the diagnosis, prognostic stratification, and follow-up. Cardiac magnetic resonance (CMR) is a comprehensive evaluation tool capable of providing information on cardiac morphology and function, flow, perfusion, and tissue characterisation. CMR allows to detect subtle abnormalities in the myocardial composition and characterise the heterogeneous phenotypic expression of HCM. In particular, the detection of the degree and extent of myocardial fibrosis, using late-gadolinium enhanced sequences or parametric mapping, is unique for CMR and is of additional value in the clinical assessment and prognostic stratification of paediatric HCM patients. Additionally, childhood HCM can be progressive over time. The rate, timing, and degree of disease progression vary from one patient to the other, so close cardiac monitoring and serial follow-up throughout the life of the diagnosed patients is of paramount importance. In this review, an update of the use of CMR in childhood HCM is provided, focussing on its clinical role in diagnosis, prognosis, and serial follow-up.

Cardiomyopathies in children: An overview

Paediatric cardiomyopathies form a heterogeneous group of disorders characterized by structural and electrical abnormalities of the heart muscle, commonly due to a gene variant of the myocardial cell structure. Mostly inherited as a dominant or occasionally recessive trait, they might be part of a syndromic disorder of underlying metabolic or neuromuscular defects or combine early developing extracardiac abnormalities (i.e., Naxos disease). The annual incidence of 1 per 100,000 children appears higher during the first two years of life. Dilated and hypertrophic cardiomyopathy phenotypes share an incidence of 60% and 25%, respectively. Arrhythmogenic right ventricular cardiomyopathy (ARVC), restrictive cardiomyopathy, and left ventricular noncompaction are less commonly diagnosed. Adverse events such as severe heart failure, heart transplantation, or death usually appear early after the initial presentation. In ARVC patients, high-intensity aerobic exercise has been associated with worse clinical outcomes and increased penetrance in at-risk genotype-positive relatives. Acute myocarditis in children has an incidence of 1.4-2.1 cases/per 100,000 children per year, with a 6-14% mortality rate during the acute phase. A genetic defect is considered responsible for the progression to dilated cardiomyopathy phenotype. Similarly, a dilated or arrhythmogenic cardiomyopathy phenotype might emerge with an episode of acute myocarditis in childhood or adolescence. This review provides an overview of childhood cardiomyopathies focusing on clinical presentation, outcome, and pathology.

Indications and management of implantable cardioverter-defibrillator therapy in childhood hypertrophic cardiomyopathy

Sudden cardiac death is the most common mode of death during childhood and adolescence in hypertrophic cardiomyopathy, and identifying those individuals at highest risk is a major aspect of clinical care. The mainstay of preventative therapy is the implantable cardioverter-defibrillator, which has been shown to be effective at terminating malignant ventricular arrhythmias in children with hypertrophic cardiomyopathy but can be associated with substantial morbidity. Accurate identification of those children at highest risk who would benefit most from implantable cardioverter-defibrillator implantation while minimising the risk of complications is, therefore, essential. This position statement, on behalf of the Association for European Paediatric and Congenital Cardiology (AEPC), reviews the currently available data on established and proposed risk factors for sudden cardiac death in childhood-onset hypertrophic cardiomyopathy and current approaches for risk stratification in this population. It also provides guidance on identification of individuals at risk of sudden cardiac death and optimal management of implantable cardioverter-defibrillators in children and adolescents with hypertrophic cardiomyopathy.

Artificial intelligence study on left ventricular function among normal individuals, hypertrophic cardiomyopathy and dilated cardiomyopathy patients using 1.5T cardiac cine MR images obtained by SSFP sequence

OBJECTIVES

To evaluate the performance of a deep learning-based method to automatically quantify left ventricular (LV) function from MR images in different cardiomyopathy.

METHODS

This retrospective study included MRI data sets from 2013 to 2020. Data on left ventricular function from patients with hypertrophic cardiomyopathy (HCM), patients with dilated cardiomyopathy (DCM), and healthy participants were analyzed. MRI data from a total of 388 patients were measured manually and automatically.The performance of Convolutional Neural Networks (CNNs) was evaluated based on the manual notes of two experienced observers: (a) LV segmentation accuracy, and (b) LV functional parameter accuracy. Bland-Altman analysis, Receiver operating Characteristic (ROC) curve analysis and Pearson correlation analysis were used to evaluate the consistency between fully automatic and manual diagnosis of HCM and DCM.

RESULTS

The deep-learning CNN performed best in HCM in evaluating LV function and worst in DCM. Compared with manual analysis, four parameters of LV function in the HCM group showed high correlation (r at least >0.901), and the correlation of DCM in all parameters was weaker than that of HCM, especially EF (r2 = 0.776) and SV (r2 = 0.645). ROC curve analysis indicated that at the optimal cut-off value, EF from automatic segmentation identified DCM and HCM patients with sensitivity of 92.31 and 78.05%, specificity of 82.96 and 54.07%, respectively.

CONCLUSION

Among different heart diseases, the analysis of cardiac function based on deep-learning CNN may have different performances, with DCM performing the worst and HCM the best and thus, special attention should be paid to DCM patients when assessing LV function through artificial intelligence method. LV function parameter obtained by artificial intelligence method may play an important role in the future AI diagnosis of HCM and DCM.

ADVANCES IN KNOWLEDGE

These data for the first time objectively evaluate the performance of a commercially available deep learning-based method in cardiac function evaluation of different cardiomyopathy and point out its advantages and disadvantages in different cardiomyopathy. This work did not attempt to design the algorithm itself, but rather applied an already existing method to a test dataset of clinical data and evaluated the results for a limited number of cardiomyopathy.

What Aspects of Phenotype Determine Risk for Sudden Cardiac Death in Pediatric Hypertrophic Cardiomyopathy?

Sudden cardiac death due to hypertrophic cardiomyopathy (HCM), is the most common autopsy-proven cause of unexpected medical death in children after infancy. This mode of death is preventable by implantation of an internal cardiac defibrillator (ICD), a procedure that has considerable morbidity in childhood patients, and even mortality. Since HCM is an inheritable disease (usually autosomal dominant, occasionally recessive), family screening may identify subjects at risk. This review summarizes published studies carried out to identify which phenotypic markers are important risk factors in childhood patients with HCM and reviews the performance of existing risk-stratification algorithms (HCM Risk-Kids, PRIMaCY) against those of single phenotypic markers. A significant proportion of HCM-patients diagnosed in childhood are associated with RASopathies such as Noonan syndrome, but a knowledge gap exists over risk stratification in this patient group. In conclusion, pediatric risk-stratification algorithms for sudden cardiac death perform better in children than adult HCM risk-stratification strategies. However, current multivariable algorithms overestimate risk substantially without having high sensitivity, and remain ‘a work in progress’. To include additional phenotypic parameters that can be reproducibly measured such as ECG-markers, e.g., ECG risk score (which has high sensitivity and negative predictive value), tissue Doppler diastolic function measurements, and quantification of myocardial scarring on cardiac magnetic resonance imaging, has the potential to improve risk-stratification algorithms. Until that work has been achieved, these are three factors that the clinician can combine with the current algorithm-calculated per cent risk, in order better to assess risk.