Arrhythmogenic right ventricular cardiomyopathy (ARVC) mimics: the knot unravelled by cardiovascular MRI

The Many Faces of Arrhythmogenic Cardiomyopathy: An Overview

Arrhythmogenic cardiomyopathy (AC) is a disease that involves electromechanical uncoupling of cardiomyocytes. This leads to characteristic histologic changes that ultimately lead to the arrhythmogenic clinical features of the disease. Initially thought to affect the right ventricle predominantly, more recent data show that it can affect both the ventricles or the left ventricle alone. Throughout the recent era, diagnostic modalities and criteria for AC have continued to evolve and our understanding of its clinical features in different age groups as well as the genotype to the phenotype correlations have improved. In this review, we set out to detail the epidemiology, etiologies, presentations, evaluation, and management of AC across the age continuum.

Arrhythmogenic cardiomyopathy is under-recognized in end-stage pediatric heart failure: A 36-year single-center experience

BACKGROUND

Although ventricular failure is a late finding in adults with AC, we hypothesize that this is a presenting symptom in pediatric heart failure patients who undergo HT and that their ventricular arrhythmia burden could differentiate AC from other cardiomyopathies.

METHODS

We performed a single-center retrospective cohort study reviewing 457 consecutive pediatric (≤18 years) HT recipients at our institution. Explanted hearts were examined to establish the primary diagnosis, based on pathologic findings. Demographic and clinical variables were compared between AC versus non-HCM cardiomyopathy cases.

RESULTS

Forty-five percent (n = 205/457) had non-HCM cardiomyopathies as the underlying primary diagnosis. Ten cases (10/205 = 4.9%) were diagnosed with AC. All 10 had biventricular disease. In 8/10 patients (80%), AC diagnosis was unrecognized pre-HT. Compared with non-AC cardiomyopathies, the AC group was older at diagnosis (9.3 years vs. 4.3 years, p = .012) and transplant (11.1 years vs. 6.5 years, p = .010), had more ventricular arrhythmias (80.0% vs 32.8%, p = .003), and required more anti-arrhythmic use (80.0% vs 32.3%, p = .001). Genetic testing yielded causative pathogenic variants in all tested individuals (n = 5/5, 100%).

CONCLUSION

AC is often an unrecognized cardiomyopathy pretransplant in children who undergo HT. Pediatric non-HCM phenotypes with heart failure who have a significant ventricular arrhythmia burden should be investigated for AC.

Anatomical-MRI Correlations in Adults and Children with Arrhythmogenic Right Ventricular Cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a rare disease in which the right ventricular myocardium is replaced by islands of fibro-adipose tissue. Therefore, ventricular re-entry circuits can occur, predisposing the patient to ventricular tachyarrhythmias, as well as dilation of the right ventricle that eventually leads to heart failure. Although it is a rare disease with low prevalence in Europe and the United States, many patients are addressed disproportionately for cardiac magnetic resonance imaging (MRI). The most severe consequence of this condition is sudden cardiac death at a young age due to untreated cardiac arrhythmias. The purpose of this paper is to revise the magnetic resonance characteristics of ARVC, including the segmental contraction abnormalities, fatty tissue replacement, decrease of the ejection fraction, and the global RV dilation. Herein, we also present several recent improvements of the 2010 Task Force criteria that are not included within the ARVC diagnosis guidelines. In our opinion, these features will be considered in a future Task Force Consensus.

Cardiovascular Magnetic Resonance in Heritable Cardiomyopathies

Cardiovascular magnetic resonance represents the imaging modality of choice for the investigation of patients with heritable cardiomyopathies. The combination of gold-standard volumetric analysis with tissue characterization can deliver precise phenotypic evaluation of both cardiac morphology and the underlying myocardial substrate. Cardiovascular magnetic resonance additionally has an established role in risk-stratifying patients with heritable cardiomyopathy and an emerging role in guiding therapies. This article explores the application and utility of cardiovascular magnetic resonance techniques with specific focus on the major heritable cardiomyopathies.

Practical Guide to Evaluating Myocardial Disease by Cardiac MRI

OBJECTIVE. A spectrum of pathophysiologic mechanisms can lead to the development of myocardial disorders including ischemia, genetic abnormalities, and systemic disorders. Cardiac MRI identifies different myocardial disorders, provides prognostic information, and directs therapy. In comparison with other imaging modalities, cardiac MRI has the advantage of allowing both functional assessment and tissues characterization in a single examination without the use of ionizing radiation. Newer cardiac MRI techniques including mapping can provide additional information about myocardial disease that may not be detected using conventional techniques. Emerging techniques including MR spectroscopy and finger printing will likely change the way we understand the pathophysiology mechanisms of the wide array of myocardial disorders. CONCLUSION. Imaging of myocardial disorders encompasses a large variety of conditions including both ischemic and nonischemic diseases. Cardiac MRI sequences, such as balanced steady-state free precession and late gadolinium enhancement, play a critical role in establishing diagnosis, determining prognosis, and guiding therapeutic management. Additional sequences-including perfusion imaging, T2*, real-time cine, and T2-weighted sequences-should be performed in specific clinical scenarios. There is emerging evidence for the use of mapping in imaging of myocardial disease. Multiple other new techniques are currently being studied. These novel techniques will likely change the way myocardial disorders are understood and diagnosed in the near future.

Left Ventricular Involvement in Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy Predicts Adverse Clinical Outcomes: A Cardiovascular Magnetic Resonance Feature Tracking Study

The aim of this study was to investigate left ventricular (LV) global myocardial strain and LV involvement characteristics in patients with arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) and to evaluate their predictive value of adverse cardiac events. Sixty consecutive ARVD/C patients with a definite diagnosis of ARVD/C who underwent CMR examination and thirty-four healthy controls were enrolled retrospectively. The CMR images were analyzed for LV myocardial strain and the presence of LV involvement. The endpoint was defined as a composite of sustained ventricular tachycardia or fibrillation, cardiac death, resuscitated cardiac arrest, heart transplantation, and appropriate implantable cardioverter-defibrillator shock. LV global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) were significantly impaired in ARVC/D patients compared to healthy controls (GLS: −13.89 ± 3.26% vs. −16.68 ± 2.74%, GCS: −15.65 ± 3.40% vs. −19.20 ± 2.23%, GRS: 34.57 ± 11.98% vs. 49.92 ± 12.59%; P < 0.001 for all). Even in ARVC/D patients with preserved LVEF, LV GLS, GCS and GRS were also significantly reduced than in controls. During a mean follow-up period of 4.10 ± 1.77 years, the endpoint was reached in 17 patients. LV GLS >−12.65% (HR, 3.58; 95%CI, 1.14 to 11.25; p = 0.029) and history of syncope (HR, 4.99; 95%CI, 1.88 to 13.24; p = 0.001) were the only independent predictors of cardiac outcomes. The LV myocardial deformation derived from FT CMR was significantly impaired in ARVD/C patients, and this alteration can occur before the impairment of LVEF. LV GLS >−12.65% and history of syncope were the only independent prognostic markers of adverse cardiac outcomes.

Decision Tree Predictive Learner-Based Approach for False Alarm Detection in ICU

In this work, a novel method has been proposed for false alarm detection in Intensive Care Unit (ICU) during arrhythmia. To detect false alarm, various inputs are used such as electrocardiogram (ECG) signals, atrial blood pressure (ABP), photoplethysmogram signals (PLETH) and respiration (RESP). The inputs are given to decision tree predictive learner (DTPL) based classifier for thedetection of false alarm. The proposed method has an accuracy of 97% for prediction of false alarm in ICU. Theresult of the proposed method is promising which suggest that it can be used effectively for false alarm detection in ICUs. To the best of our knowledge, there is no such assumption based classification approach.