Predictors of future onset of atrial fibrillation in hypertrophic cardiomyopathy

Predictive value of left atrial strain analysis in adverse clinical events in patients with hypertrophic cardiomyopathy: a CMR study

BACKGROUND

A subset of patients with hypertrophic cardiomyopathy (HCM) will experience adverse clinical events such as heart failure (HF), cardiovascular death, and new-onset atrial fibrillation (AF). Current risk stratification methods are imperfect and limit the identification of patients at high risk for HCM. This study aimed to evaluate the role of cardiac magnetic resonance (CMR)-derived left atrial strain parameters in the occurrence of adverse clinical events in patients with HCM.

METHODS

Left atrial (LA) structural, functional, and strain parameters were evaluated in 99 patients with HCM and compared with 89 age-, sex-, and BMI-matched control subjects. LA strain parameters were derived from CMR two- and four-chamber cine images by a semiautomatic method. LA strain parameters include global longitudinal strain (GLS) and global circumferential strain (GCS). The LA GLS includes reservoir strain (GLS reservoir), conduit strain (GLS conduit), and booster strain (GLS booster). Three LA GLS strain rate (SR) parameters were derived: SR reservoir, SR conduit, and SR booster. The primary endpoint was set as a composite of adverse clinical events, including SCD, new-onset or worsening to hospitalized HF, new-onset AF, thromboembolic events, and fatal ventricular arrhythmias.

RESULTS

LA GLS, GLS SR and GCS were impaired in HCM patients compared to control subjects (all p < 0.001). After a mean follow-up of 37.94 ± 23.69 months, 18 HCM patients reached the primary endpoint. LA GLS, GLS SR, and GCS were significantly lower in HCM patients with adverse clinical events than in those without adverse clinical events (all p < 0.05). In stepwise multiple Cox regression analysis, LV SV, LA diameter, pre-contraction LAV (LAV pre-ac), passive LA ejection fraction (EF), and LA GLS booster were all independent determinants of adverse clinical events. LA GLS booster ≤ 8.9% was the strongest determinant (HR = 8.9 [95%CI (1.951, 40.933)], p = 0.005). Finally, LA GLS booster provided predictive adverse clinical events value (AUC = 0.86 [95%CI 0.77-0.98]) that exceeded traditional outcome predictors.

CONCLUSION

LA strain assessment, a measure of LA function, provides additional predictive information for established predictors of HCM patients. LA GLS booster was independently associated with adverse clinical events in patients with HCM.

The predictive value of fast semi-automated left atrial long-axis strain analysis for atrial fibrillation in hypertrophic cardiomyopathy

OBJECTIVES

Hypertrophic cardiomyopathy (HCM) patients are closely related to LA functional impairment. Left atrial (LA) strain provides more insight into LA function. The study aimed to investigate the left atrial dysfunction of HCM patients by rapid semi-automatic method and determine the predictive value of left atrial long-axis strain (LAS) for atrial fibrillation (AF).

METHODS

We enrolled 372 HCM patients and 100 healthy participants to assess the LA functional parameters. LAS was obtained by semi-automated tracking of the distance between the mid-posterior point of LA wall which is defined as the intersection of the LA long axis and the posterior wall, and the origins of the mitral valve. The inferior and anterior mitral valve annular insertion points on the 2-chamber view and the lateral and septal insertion points on the 4-chamber view were chosen as the origins of the mitral valve. The clinical outcome was defined as detecting the onset of AF.

RESULTS

The LA strain values were analyzed as 20.8 ± 7.48% for ε_s, 9.81 ± 5.09% for ε_e, and 10.91 ± 4.24% for ε_a in HCM patients, which decreased significantly compared with normal controls. Significant correlations were detected between LV functional parameters and LA strain. During a median follow-up of 61 months, 44 (11.8%) patients developed AF. In the Cox regression analysis, LA strain was identified as a significant predictor of the onset of AF.

CONCLUSIONS

HCM patients had impairment of LA strain before LA enlargement and reduced EF. LA-LAS can be used as a predictive value for predicting the occurrence of AF in HCM patients.

KEY POINTS

• Fast semi-automated long-axis strain analysis by CMR is feasible and effective for evaluating the LA longitudinal function. • Hypertrophic cardiomyopathy patients show significant impairment of left atrial strain before LA enlargement. • The left atrial long-axis strain was an independent predictor of atrial fibrillation in hypertrophic cardiomyopathy.

Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model

Background

Hypertrophic cardiomyopathy (HCM) patients have a high incidence of atrial fibrillation (AF) and increased stroke risk, even with low CHA₂DS₂-VASc (congestive heart failure, hypertension, age diabetes, previous stroke/transient ischemic attack) scores. Hence, there is a need to understand the pathophysiology of AF/stroke in HCM. In this retrospective study, we develop and apply a data-driven, machine learning–based method to identify AF cases, and clinical/imaging features associated with AF, using electronic health record data.

Methods

HCM patients with documented paroxysmal/persistent/permanent AF (n = 191) were considered AF cases, and the remaining patients in sinus rhythm (n = 640) were tagged as No-AF. We evaluated 93 clinical variables; the most informative variables useful for distinguishing AF from No-AF cases were selected based on the 2-sample t test and the information gain criterion.

Results

We identified 18 highly informative variables that are positively (n = 11) and negatively (n = 7) correlated with AF in HCM. Next, patient records were represented via these 18 variables. Data imbalance resulting from the relatively low number of AF cases was addressed via a combination of oversampling and undersampling strategies. We trained and tested multiple classifiers under this sampling approach, showing effective classification. Specifically, an ensemble of logistic regression and naïve Bayes classifiers, trained based on the 18 variables and corrected for data imbalance, proved most effective for separating AF from No-AF cases (sensitivity = 0.74, specificity = 0.70, C-index = 0.80).

Conclusions

Our model (HCM-AF-Risk Model) is the first machine learning–based method for identification of AF cases in HCM. This model demonstrates good performance, addresses data imbalance, and suggests that AF is associated with a more severe cardiac HCM phenotype.

Hypertrophic Cardiomyopathy: Genetic Testing and Risk Stratification

PURPOSE OF REVIEW

Our knowledge of the genetic basis and molecular pathogenesis of hypertrophic cardiomyopathy (HCM) continues to evolve. We describe the genetic basis of HCM, recent advances in genetic testing and the role of genetics in guiding risk stratification and management, both now and in the future.

RECENT FINDINGS

While initially thought to be an exclusively Mendelian disease, we now know there are important HCM sub-groups. A proportion will have sarcomere variants as the cause of their disease, while others will have genetic variants in genes that can give rise to conditions that can mimic HCM. The role of genetics is primarily for cascade genetic testing, though there is emerging evidence of a role for prognosis and patient management. Genetic testing is a useful addition to management. Genotype may play a greater role in risk stratification, management, treatment and prognosis in future, offering improved outcomes for patients and their families with HCM.

Assessment of atrial function by myocardial deformation techniques in hypertrophic cardiomyopathy

BACKGROUND

Diastolic dysfunction in hypertrophic cardiomyopathy (HCM) is common, but its assessment is difficult using conventional echocardiography.

AIMS

To assess left atrial (LA) function in HCM by longitudinal strain and determine its role in understanding of symptoms.

METHODS

We studied 144 patients divided into 3 age- and sex-matched groups: 48 consecutive patients with HCM, 48 control subjects, and 48 athlete subjects. We assessed LA function by conventional echocardiographic parameters and by longitudinal atrial strain (early-diastolic left atrial strain during reservoir phase [LASr]; end-diastolic left atrial strain during conduit phase; end-systolic peak of the left atrial strain during contraction phase).

RESULTS

NYHA classification was as follows in HCM group: I in 46%, II in 31%, III in 19%, and IV in 4%. Conventional echocardiographic parameters of diastolic function were depressed in the HCM group as compared to the control and athlete groups, but not related to symptoms. All longitudinal atrial strain parameters were significantly reduced in HCM group as compared to two groups (P < .0001). LASr was significantly correlated to peak VO2 (r = 0.44, P = .01) and was the best parameter for detecting symptomatic patients presenting with HCM, with a cutoff value of 15%: Sensitivity was 71%, specificity was 79%, PPV was 77%, and NPV was 73%.

CONCLUSION

Assessment of LA function in HCM is feasible using longitudinal strain, and this technique is more reliable than conventional echocardiographic parameters for the understanding of determinants of symptoms.

Predictors and Mechanisms of Atrial Fibrillation in Patients With Hypertrophic Cardiomyopathy

Atrial fibrillation (AF) in hypertrophic cardiomyopathy (HC) is associated with significant symptomatic deterioration, heart failure, and thromboembolic disease. There is a need for better mechanistic insight and improved identification of at risk patients. We used cardiovascular magnetic resonance (CMR) to assess predictors of AF in HC, in particular the role of myocardial fibrosis. Consecutive patients with HC referred for CMR 2003 to 2013 were prospectively enrolled. CMR parameters including left ventricular volumes, presence and percentage of late gadolinium enhancement in the left ventricle (%LGE) and left atrial volume index (LAVi) were measured. Overall, 377 patients were recruited (age 62 ± 14 years, 73% men). Sixty-two patients (16%) developed new-onset AF during a median follow up of 4.5 (interquartile range 2.9 to 6.0) years. Multivariable analysis revealed %LGE (hazard ratio [HR] 1.3 per 10% (confidence interval: 1.0 to 1.5; p = 0.02), LAVi (HR 1.4 per 10 mL/m²[1.2 to 1.5; p < 0.001]), age at HC diagnosis, nonsustained ventricular tachycardia and diabetes to be independent predictors of AF. We constructed a simple risk prediction score for future AF based on the multivariable model with a Harrell's C-statistic of 0.73. In conclusion, the extent of ventricular fibrosis and LA volume independently predicted AF in patients with HC. This finding suggests a mechanistic relation between fibrosis and future AF in HC. CMR with quantification of fibrosis has incremental value over LV and LA measurements in risk stratification for AF. A risk prediction score may be used to identify patients at high risk of future AF who may benefit from more intensive rhythm monitoring and a lower threshold for oral anticoagulation.

Interleaved, undersampled radial multiple-acquisition steady-state free precession for improved left atrial cine imaging

PURPOSE

Balanced steady-state free precession (bSSFP) left atrial (LA) cine suffers from off-resonance artifacts, particularly in the pulmonary veins (PVs). Linear combination or multiple-acquisition SSFP (MA-SSFP) effectively removes banding but greatly increases scan time. We hypothesized that MA-SSFP with interleaved radial undersampling, where each phase-cycling is acquired with an interleaved set of radial projections, would improve image quality of LA cine with a small increase of scan time and streak artefacts.

METHODS

Undersampled radial MA-SSFP with and without interleaving was compared with fully sampled radial bSSFP by means of simulations, phantoms, and in vivo imaging. Ten healthy subjects were imaged on a 3T scanner, with bSSFP and MA-SSFP cine of the left atrium, and B0-mapping. Images were assessed (1 = worst, 5 = best) by 2 independent readers, with respect to 5 qualitative criteria and apparent signal-to-noise ratio.

RESULTS

In healthy subjects, off-resonance differed from the right inferior PVs to the LA cavity by 163 Hz ± 73 Hz at 3T. Compared with fully sampled radial bSSFP, interleaved radial MA-SSFP significantly improved image quality with respect to off-resonance artifacts (3.8 ± 0.6 versus 2.3 ± 1.0; P = 0.005), PV conspicuity (2.8 ± 1.0 versus 4.3 ± 0.5; P = 0.005), and the number of visualized PVs (1.7 ± 0.4 versus 0.9 ± 0.7; P = 0.008), although with greater streak artifacts (3.4 ± 0.4 versus 4.9 ± 0.2; P = 0.004) and lower measured apparent signal-to-noise ratio (24 ± 9 versus 69 ± 36; P = 0.002). Flow artifacts were similar. Interleaved radial MA-SSFP reduced streaking artifacts and increased apparent signal-to-noise ratio versus noninterleaved radial.

CONCLUSIONS

Interleaved radial MA-SSFP cine reduces banding artifacts with an acceptable increase of scan time and streak artifacts. The proposed technique improves the LA and PV visualization in bSSFP cine imaging.

Risk factors for atrial fibrillation in hypertrophic cardiomyopathy

Atrial fibrillation is the most common sustained arrhythmia in hypertrophic cardiomyopathy (HCM), occurring in approximately 25% of patients, which is four to six times more common than in similarly aged patients of the general population. Atrial fibrillation is poorly tolerated by HCM patients, largely due to their dependence on atrial systole for left ventricular filling. HCM patients who develop atrial fibrillation have an increased rate of heart failure related mortality and disabling or fatal thromboembolic events, as well as functional deterioration due to progressive heart failure when left untreated. Atrial fibrillation is both common in HCM and may lead to significant morbidity and mortality. Accurate risk stratification for atrial fibrillation in this population is crucial as contemporary treatments are highly successful. In this paper, we review the current understanding of known risk factors for atrial fibrillation, including different imaging-based parameters that assess left atrial structural and functional remodeling, electrocardiographic changes that reflect left atrial electrical remodeling, and a focus on comorbid obstructive sleep apnea, and in addition we review variables that have been reported to be predictive of atrial fibrillation. Last, we summarize the accumulating evidence for HCM patients having an intrinsic atrial myopathy.