Arrhythmic Risk Stratification Research Articles

Current uses and understanding of PET imaging in cardiac sarcoidosis.

Sarcoidosis is a systemic disease with unclear etiology characterized by the accumulation of noncaseating, immune granulomas in affected tissues. In cardiac sarcoidosis (CS), white blood cells build up within the heart muscles, causing cardiac abnormalities. Accurate and early diagnosis of CS proves challenging. However, usage of positron emission tomography (PET) imaging, namely 18F-FDG-PET, has proven successful in diagnosing inflammatory cardiomyopathy. This review seeks to examine the role of PET in managing ventricular tachycardia in cardiac sarcoidosis. PET, in conjunction with cardiac magnetic resonance imaging (CMR) is also endorsed as the premier method for diagnosis and management of arrhythmias associated with CS by The Heart Rhythm Society. After a CS diagnosis, risk stratification of ventricular arrhythmias is a necessity given the potential for sudden cardiac death. 18F-FDG-PET has been successful in monitoring disease advancement and treatment responses in CS patients. Early stages of CS are often treated with immunosuppression drugs if there are additional signs of VT. Currently, corticosteroid and anti-arrhythmia compounds: methotrexate, cyclophosphamide, infliximab, amiodarone, and azathioprine are used to suppress inflammation. 18F-FDG-PET has certainly proven to be an incredibly useful and accurate diagnostic tool of CS. While late gadolinium enhancement by CMR is efficient in detecting myocardial necrosis and/or advanced fibrosis scarring, 18F-FDG portrays the increased uptake level of glucose metabolism. In combination PET/MRI has proven to be more successful in improving the efficacy of both scans, addressing their drawbacks, and highlighting their advantages. Managing CS patients is highly involved in detecting inflammatory regions of the heart. Early recognition prevents cardiac abnormality, mainly VT and VF in CS patients, and extends lifespan.

Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator

Risk stratification for ventricular arrhythmias currently relies on static measurements that fail to adequately capture dynamic interactions between arrhythmic substrate and triggers over time. We trained and internally validated a dynamic machine learning (ML) model and neural network that extracted features from longitudinally collected electrocardiograms (ECG), and used these to predict the risk of malignant ventricular arrhythmias. A multicentre study in patients implanted with an implantable cardioverter-defibrillator (ICD) between 2007 and 2021 in two academic hospitals was performed. Variational autoencoders (VAEs), which combine neural networks with variational inference principles, and can learn patterns and structure in data without explicit labelling, were trained to encode the mean ECG waveforms from the limb leads into 16 variables. Supervised dynamic ML models using these latent ECG representations and clinical baseline information were trained to predict malignant ventricular arrhythmias treated by the ICD. Model performance was evaluated on a hold-out set, using time-dependent receiver operating characteristic (ROC) and calibration curves. 2942 patients (61.7±13.9 years, 25.5% female) were included, with a total of 32,129 ECG recordings during a mean follow-up of 43.9±35.9 months. The mean time-varying area under the ROC curve for the dynamic model was 0.738±0.07, compared to 0.639±0.03 for a static (i.e. baseline-only model). Feature analyses indicated dynamic changes in latent ECG representations, particularly those affecting the T-wave morphology, were of highest importance for model predictions. Dynamic ML models and neural networks effectively leverage routinely collected longitudinal ECG recordings for personalised and updated predictions of malignant ventricular arrhythmias, outperforming static models. This publication is part of the project DEEP RISK ICD (with project number 452019308) of the research programme Rubicon which is (partly) financed by the Dutch Research Council (NWO). This research is partly funded by the Amsterdam Cardiovascular Sciences (personal grant F.V.Y.T).

Evaluation and Management of Sudden Death Risk in Repaired Tetralogy of Fallot.

Although substantial progress has been made to prevent sudden cardiac death in repaired tetralogy of Fallot patients, ventricular arrhythmia and sudden death continue to be major causes of morbidity and mortality in these patients. Greater survival in contemporary cohorts has been attributed to enhanced surgical techniques, more effective management of heart failure, and increased efforts in risk stratification and management of ventricular arrhythmias. More recently, our understanding of predictive risk factors has evolved into personalized risk prediction tools that rely on comprehensive demographic, imaging, functional, and electrophysiological data. However, the universal applicability of these different scoring systems is limited due to differences between study cohorts, types of anatomic repair, imaging modalities, and disease complexity. Noninvasive risk stratification is critical to identify those who may derive benefit from catheter ablation or cardioverter defibrillator implantation for primary prevention. Ultimately, assessment and risk stratification by a multidisciplinary team is crucial to analyze the various complex factors for every individual patient and discuss further options with patients and their families.

Imaging for the assessment of the arrhythmogenic potential of mitral valve prolapse.

Mitral valve prolapse (MVP) is the most common valve disease in the western world and recently emerged as a possible substrate for sudden cardiac death (SCD). It is estimated an annual risk of sudden cardiac death of 0.2 to 1.9% mostly caused by complex ventricular arrhythmias (VA). Several mechanisms have been recognized as potentially responsible for arrhythmia onset in MVP, resulting from the combination of morpho-functional abnormality of the mitral valve, structural substrates (regional myocardial hypertrophy, fibrosis, Purkinje fibers activity, inflammation), and mechanical stretch. Echocardiography plays a central role in MVP diagnosis and assessment of severity of regurgitation. Several abnormalities detectable by echocardiography can be prognostic for the occurrence of VA, from morphological alteration including leaflet redundancy and thickness, mitral annular dilatation, and mitral annulus disjunction (MAD), to motion abnormalities detectable with "Pickelhaube" sign. Additionally, speckle-tracking echocardiography may identify MVP patients at higher risk for VA by detection of increased mechanical dispersion. On the other hand, cardiac magnetic resonance (CMR) has the capability to provide a comprehensive risk stratification combining the identification of morphological and motion alteration with the detection of myocardial replacement and interstitial fibrosis, making CMR an ideal method for arrhythmia risk stratification in patients with MVP. Finally, recent studies have suggested a potential role in risk stratification of new techniques such as hybrid PET-MR and late contrast enhancement CT. The purpose of this review is to provide an overview of the mitral valve prolapse syndrome with a focus on the role of imaging in arrhythmic risk stratification. CLINICAL RELEVANCE STATEMENT: Mitral valve prolapse is the most frequent valve condition potentially associated with arrhythmias. Imaging has a central role in the identification of anatomical, functional, mechanical, and structural alterations potentially associated with a higher risk of developing complex ventricular arrhythmia and sudden cardiac death. KEY POINTS: • Mitral valve prolapse is a common valve disease potentially associated with complex ventricular arrhythmia and sudden cardiac death. • The mechanism of arrhythmogenesis in mitral valve prolapse is complex and multifactorial, due to the interplay among multiple conditions including valve morphological alteration, mechanical stretch, myocardial structure remodeling with fibrosis, and inflammation. • Cardiac imaging, especially echocardiography and cardiac magnetic resonance, is crucial in the identification of several features associated with the potential risk of serious cardiac events. In particular, cardiac magnetic resonance has the advantage of being able to detect myocardial fibrosis which is currently the strongest prognosticator.

A high-risk late gadolinium enhancement pattern is associated with arrhythmic events in patients with dilated cardiomyopathy

Abstract Introduction Myocardial fibrosis constitutes a substrate for the development of ventricular arrhythmias in patients with non-ischaemic dilated cardiomyopathy (DCM). Late gadolinium enhancement (LGE)-cardiac magnetic resonance (CMR) imaging represents a powerful tool for arrhythmic risk stratification. Moreover, arrhythmic risk is determined by the extent and localization of LGE. A high-risk LGE pattern, defined as the presence of epicardial, transmural or septal plus free-wall LGE, has been recently associated with a higher incidence of arrhythmic events comparing with other LGE patterns. Purpose To evaluate the prevalence of a high-risk LGE pattern in patients with DCM and its association with arrhythmic events. Methods From 2014 to 2021, all patients (N = 229) with DCM were prospectively evaluated in our tertiary care hospital. 174 patients underwent a 1.5 Tesla scanner CMR as part of the diagnostic workup and were included in the present study. The primary endpoint was a composite of sudden cardiac death or sustained monomorphic ventricular tachycardia. Results Mean age of our cohort was 61 years (standard deviation 14.5), and 64.2% were male. Median follow-up was 41 (interquartile range 26-62) months. LGE was present in 96 (55.2%) patients of our cohort (LGE+), and a high risk LGE pattern was found in 41 (42.7% of all LGE+ patients). LGE was more frequently located in the basal segments (78.6%). Mid-wall septal LGE was found in 46.9% of LGE+ patients, and it was the most common pattern. 21.4% of LGE+ patients had combined septal and free-wall LGE, 23.5% had epicardial LGE and 13.3% had transmural LGE. Baseline characteristics of LGE+ patients with and without a high-risk LGE pattern are shown at the Table. The incidence of ventricular arrhythmic events during follow-up was 31.7% in patients with a high-risk LGE pattern, and 9.1% in LGE+ patients but without a high-risk pattern (p=0.005). In patients without a high-risk LGE, including LGE- patients and LGE+ patients with other LGE patterns, incidence of ventricular arrhythmic events was 8.3% (p<0.001). The survival free curves for the combined arrhythmic endpoint comparing LGE+ patients with and without a high-risk pattern are shown in the Figure. Conclusion The presence of a high-risk LGE pattern in patients with DCM its associated with a higher incidence of ventricular arrhythmic events, comparing with LGE+ patients without a high-risk pattern. We suggest that this high-risk pattern should be taken into account when performing arrhythmic risk stratification in patients with DCM.TableFigure

Arrhythmic risk stratification in patients with left ventricular ring-like scar

Abstract Background Myocardial fibrosis assessment with late gadolinium enhancement (LGE) at cardiac magnetic resonance (CMR) has recently emerged as an independent predictor of major adverse events in patients with non-ischemic cardiomyopathy. Several studies have examined different locations and extension degrees of LGE, and the so called "ring-like pattern" has been related with an increased incidence of ventricular arrhythmias, in patients with dilated cardiomyopathy (DCM), but also in patients with preserved systolic function. Purpose To describe clinical, electrocardiographic, echocardiographic, CMR and genetic features of the left ventricular (LV) ring-like scar phenotype and to evaluate which characteristics may be associated with the risk of sudden cardiac death (SCD). Methods Patients diagnosed with LV ring-like scar were identified at 6 referral Centres. Diagnosis was based on: 1) ring-like LGE LV pattern, defined as at least 3 contiguous segments with subepicardial/midwall LGE in the same slice with or without fatty infiltration; or 2) pathology examination of explanted hearts/autoptic cases suffering from sudden cardiac death (SCD). Moreover, patients must have an additional inclusion criterion: a positive genetic test, or ≥1 patient in the same family with an ascertained cardiomyopathy. Major adverse arrhythmic cardiac events (MAACE), defined as a composite of SCD, aborted SCD, and sustained ventricular tachycardia (SVT), were the primary study endpoint. Results The final cohort comprised 129 patients (male 59.7%, median age at diagnosis 44 years). During a median follow-up of 3.4 years (IQR 1.2 – 64.), MAACE occurred in 31 patients (24%). Nearly 70% of the patients had a likely pathogenic/pathogenic mutation, mostly in desmoplakin (DSP) and filamin-C (FLNC) genes (65% and 19%, respectively). Sex, QRS width, and LGE in LV anterior wall and/or apex, were the only independent predictors of the outcome events (HR: 0.329, 95% CI: 0.119-0.916, P = 0.033; HR: 1.036, 95% CI 1.019-1.053, P < 0.001; HR 4.270, 95% CI 1.337-13.630, P = 0.014, respectively). A significant interaction between sex and LGE in anterior wall/apex was observed, being this regions associated with MAACE only in male patients (p for interaction = 0.033). Although related to the arrhythmic endpoint at the Kaplan-Meier survival curves, neither DCM echocardiographic phenotype, nor LV ejection fraction ≤35% remained statistically associated to MAACE at the multivariate analysis. Age, genetic mutations, right ventricular involvement, proband status, LV-LGE extension (number of segments) were not statistically related to the study endpoint. Conclusions In this selected cohort of patients with LV ring-like scar and either a genetic test or family history, malignant arrhythmic events were predicted by male sex, QRS width and LGE in anterior wall and/or apex.Graphical Abstract

Using the 3D architecture of scar to predict life-threatening ventricular arrhythmias, still a long way to go

Abstract Background Late gadolinium enhancement (LGE) has been proposed as an independent predictor of ventricular arrhythmias. Purpose The purpose of this study was to assess if myocardial scar characterization could enhance the risk stratification for life-threatening arrhythmias and sudden cardiac death (SCD). Methods We included patients with an indication for ICD or CRT-D implantation who underwent cardiac magnetic resonance for clinical proposes since February/2018 and in whom a 3D-LGE dataset was obtained. Patients with channelopathies (n=2) or inappropriate imaging quality (imaging artifacts; n=7) were excluded. Scar characterization using ADAS software was performed in 3D-LGE datasets in all but 16 patients, where 2D datasets were used. The primary endpoint was the composite of appropriate ICD therapy (classified as ATP or shock), sustained ventricular tachycardia or SCD. Results A total of 116 patients were analysed (mean age 66 ± 14 years; 81% male; mean LVEF 34 ± 14%; 74 patients with ischemic and 42 with non-ischemic cardiomyopathy; 40 patients received a device in the setting of secondary prevention). During a median follow-up of 2.3 years (IQR 1.3 – 3.3 years) there were 23 events (18 appropriate ICD therapies [9 shocks and 9 ATP], 3 episodes of VT under the threshold for ICD therapy and 2 SCD). No statistically significant differences were found between patients with or without events in terms of scar mass, border zone (BZ) mass, BZ channels (BZC), BZC mass, number of channels detected, and scar heterogeneity (BZ mass / scar mass ratio) - all p values > 0.2 – Figure. Restricting the analysis to only primary prevention cases yielded similar results. Overall, 26 patients did not show any channel. Four of these (all with non-ischemic LGE) experienced an arrhythmic event, yielding a negative predictive value of 83% (95% CI 64-93%) for the absence of channels. Conclusion In this cohort with still relatively limited follow-up duration, no single parameter reflecting scar tissue characterization was able to predict appropriate device therapies or sudden cardiac death.

Arrhythmic risk stratification of filamin C truncating variants carriers

Abstract Background Truncating variants in Filamin C (FLNCtv) are a rare cause of cardiomyopathy with heterogeneous phenotypic presentation and high incidence of life-threatening ventricular arrhythmias, including sudden cardiac death (SCD). Nevertheless, there is a residual gap in the definition of solid risk markers for the stratification of arrhythmic risk and the significance of conventional predictors (i.e. left ventricular ejection fraction [LVEF]) remains extremely controversial. Purpose The aim of this study was to analyze the risk profile and to identify the factors associated with increased risk of life-threatening arrhythmias in an international multicenter cohort of FLNCtv carriers. Methods Patients were retrospectively collected from 19 international tertiary care centers for genetic cardiomyopathies. Primary endpoint was SCD/major ventricular arrhythmias (MVA, i.e. sustained ventricular tachycardia and appropriate implantable cardioverter defibrillator [ICD] shocks). Multivariate Cox regression analysis was performed to identify the predictors of SCD/MVA, taking into account non-sudden cardiac death/heart transplant/destination left ventricle assist device as competing event and including family clusters in the model as clustering factor. Results Among the 326 included carriers (median age 45 years, IQR 33-57; 51% males), 120 (37%) were probands. 100 (31%) carriers had no clinical signs of overt disease; for the others, phenotypic presentation was heterogeneous (36% dilated cardiomyopathy, 17% arrhythmogenic left dominant cardiomyopathy, 4% arrhythmogenic right or biventricular cardiomyopathy, 11% minor phenotype). Median LVEF was 51% (IQR 35%-59%, 41% had LVEF<50%), 16% had right ventricle dysfunction. During a median follow-up of 32 months (IQR 8-63), 60 carriers (18%) experienced SCD/MVA (65% probands, 97% with overt disease, median age at event 48 years, IQR 38-64, min-max 18-78). Among variables associated with the risk of SCD/MVA at univariable analysis, male sex, previous syncope and non-sustained ventricular tachycardia maintained a significant association with the primary outcome at multivariable analysis (Table), whereas there was no significant association between LVEF and the risk of SCD/MVA neither as a continuous nor categorical (i.e. LVEF<50%) variable. In the subgroup of 175 patients with available cardiac magnetic resonance, 57% had late gadolinium enhancement with no significant association with the outcome. Conclusions In the largest worldwide cohort of FLNCtv carriers the high risk of SCD/MVA was confirmed. Three important factors emerged to be associated with higher arrhythmic risk and should be considered for decisions on ICD implantation. Remarkably, LVEF was not significantly associated with SCD/MVA risk. The higher risk observed in males compared with females advocates for prompt investigations on the influence of sex-related factors on the disease expression in genetic cardiomyopathies.

Abstract 16938: Epicardial Adipose Tissue on the Risk of Lethal Ventricular Arrhythmias in Patients With Nonischemic Cardiomyopathy Receiving Implantable Cardioverter-Defibrillator

Background: The arrhythmic risk stratification in patients with nonischemic cardiomyopathy (NICM) remains challenging. The implication of epicardial adipose tissue (EAT) on incident sudden cardiac death (SCD) is unclear. Objectives: To assess the relationship between EAT and SCD in NICM patients receiving implantable cardioverter-defibrillators (ICD) and compare this risk to patients with ischemic cardiomyopathy (ICM). Methods: A total of 421 patients scheduled for primary or secondary prevention ICD implantation underwent CMR at 1.5 or 3T, including cine and late gadolinium enhancement (LGE) imaging. EAT volume surrounding both ventricles was quantified with manual delineation on cine short-axis images and calculated by summation of EAT volume of each slice using the modified Simpson rule. LGE was semiautomatically quantified by adjusting a grayscale threshold. The primary endpoint was a composite of ICD therapy, including anti-tachycardia pacing and SCD. Results: We identified 265 NICM patients (mean age 54 years, 73% men), with LGE present in 152 patients (57%), including 85 patients (32%) with secondary prevention ICD. During the median follow-up of 2.9 years, 42 patients (16%) experienced the endpoint. Low EAT was associated with an increased risk of SCD in NICM patients (HR ad per 10ml decrease, 1.54; 95%CI, 1.19-1.96, p<0.001), even after adjustment for other relevant disease variables. A continuous relationship was evident between EAT and subsequent ICD therapies (p=0.001). Even when considering 85 patients with secondary prevention ICD as theoretically having an SCD event, the risk of EAT in predicting SCD remained essentially unchanged. In contrast, EAT was not associated with increased SCD risk in ICM patients. Conclusions: Low EAT was associated with increased SCD risk in NICM patients receiving ICD implantation, especially primary prevention ICD. These data suggest a potential role of EAT in identifying NICM patients at risk of SCD.

Abstract 17912: Late Potential and the Risk of Major Arrhythmic Events in Brugada Syndrome Patients: A Systematic Review and Meta-Analysis

Introduction: Brugada syndrome is an inherited arrhythmic disease associated with fatal ventricular arrhythmias. However, ventricular arrhythmia risk stratification remains challenging and controversial. Hypothesis: The late potential may be useful as a predictor of major arrhythmic events in Brugada syndrome patients. Aims: We aimed to assess the association between late potential and risk of major arrhythmic events by a systematic review and meta-analysis. Methods: We comprehensively searched the databases of MEDLINE and EMBASE from inception to January 2023. The included studies were cohort and case-control studies that reported the relationship between late potential and major arrhythmic events. The included studies were selected to yield a maximum total number of sample sizes without population duplications across the studies. Data from each study were combined using the random-effects model to calculate pooled odds ratio and 95% confidence intervals. The late potential was defined as RMS40 <20 μV and/or LAS40 >38 ms on signal-averaged ECG. Results: Five studies were included in this meta-analysis involving 743 Brugada syndrome patients (438 with late potential and 743 without late potential). The mean age was 47.3 ± 14.1 years. The patients were predominately men (61.6%). The late potential was not associated with major arrhythmic events (pooled odds ratio 1.17, 95% confidence intervals: 0.62-2.21, p=0.63, I 2 =21.3%). Conclusions: Our study demonstrated that late potential is not associated with a higher risk of major arrhythmic events in Brugada syndrome populations. To our knowledge, our study is the first meta-analysis of late potential in Brugada syndrome patients.

Artificial Intelligence ECG Analysis in Patients with Short QT Syndrome to Predict Life-Threatening Arrhythmic Events

Short QT syndrome (SQTS) is an inherited cardiac ion-channel disease related to an increased risk of sudden cardiac death (SCD) in young and otherwise healthy individuals. SCD is often the first clinical presentation in patients with SQTS. However, arrhythmia risk stratification is presently unsatisfactory in asymptomatic patients. In this context, artificial intelligence-based electrocardiogram (ECG) analysis has never been applied to refine risk stratification in patients with SQTS. The purpose of this study was to analyze ECGs from SQTS patients with the aid of different AI algorithms to evaluate their ability to discriminate between subjects with and without documented life-threatening arrhythmic events. The study group included 104 SQTS patients, 37 of whom had a documented major arrhythmic event at presentation and/or during follow-up. Thirteen ECG features were measured independently by three expert cardiologists; then, the dataset was randomly divided into three subsets (training, validation, and testing). Five shallow neural networks were trained, validated, and tested to predict subject-specific class (non-event/event) using different subsets of ECG features. Additionally, several deep learning and machine learning algorithms, such as Vision Transformer, Swin Transformer, MobileNetV3, EfficientNetV2, ConvNextTiny, Capsule Networks, and logistic regression were trained, validated, and tested directly on the scanned ECG images, without any manual feature extraction. Furthermore, a shallow neural network, a 1-D transformer classifier, and a 1-D CNN were trained, validated, and tested on ECG signals extracted from the aforementioned scanned images. Classification metrics were evaluated by means of sensitivity, specificity, positive and negative predictive values, accuracy, and area under the curve. Results prove that artificial intelligence can help clinicians in better stratifying risk of arrhythmia in patients with SQTS. In particular, shallow neural networks’ processing features showed the best performance in identifying patients that will not suffer from a potentially lethal event. This could pave the way for refined ECG-based risk stratification in this group of patients, potentially helping in saving the lives of young and otherwise healthy individuals.

The application of radiology for dilated cardiomyopathy diagnosis, treatment, and prognosis prediction: a bibliometric analysis.

Radiology plays a highly crucial role in the diagnosis, treatment, and prognosis prediction of dilated cardiomyopathy (DCM). Related research has increased rapidly over the past few years, but systematic analyses are lacking. This study thus aimed to provide a reference for further research by analyzing the knowledge field, development trends, and research hotspots of radiology in DCM using bibliometric methods. Articles on the radiology of DCM published between 2002 and 2021 in the Web of Science Core Collection database (WoSCCd) were searched and analyzed. Data were retrieved and analyzed using CiteSpace V, VOSviewer, and Scimago Graphic software, and included the name, research institution, and nationality of authors; journals of publication; and the number of citations. A total of 4,257 articles were identified on radiology of DCM from WoSCCd. The number of articles published in this field has grown steadily from 2002 to 2021 and is expected to reach 392 annually by 2024. According to subfields, the number of papers published in cardiac magnetic resonance field increased steadily. The authors from the United States published the most (1,364 articles, 32.04%) articles. The author with the most articles published was Bax JJ (54 articles, 1.27%) from Leiden University Medical Center. The most cited article was titled "2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure", with 138 citations. Citation-based clustering showed that arrhythmogenic cardiomyopathy, T1 mapping, and endomyocardial biopsy are the current hots pots for research in DCM radiology. The most frequently occurring keyword was "dilated cardiomyopathy". The keyword-based clusters mainly included "late gadolinium enhancement", "congestive heart failure", "cardiovascular magnetic resonance", "sudden cardiac death", "ventricular arrhythmia", and "cardiac resynchronization therapy". The United States and Northern Europe are the most influential countries in research on DCM radiology, with many leading distinguished research institutions. The current research hots pots are myocardial fibrosis, risk stratification of ventricular arrhythmia, the prognosis of cardiac resynchronization therapy (CRT) treatment, and subtype classification of DCM.

Impact of Cardiac Magnetic Resonance to Arrhythmic Risk Stratification in Nonischemic Cardiomyopathy.

Left ventricular ejection fraction-based arrhythmic risk stratification in nonischemic cardiomyopathy (NICM) is insufficient and has led to the failure of primary prevention implantable cardioverter defibrillator trials, mainly due to the inability of selecting patients at high risk for sudden cardiac death (SCD). Cardiac magnetic resonance offers unique opportunities for tissue characterization and has gained a central role in arrhythmic risk stratification in NICM. The presence of myocardial scar, denoted by late gadolinium enhancement, is a significant, independent, and strong predictor of ventricular arrhythmias and SCD with high negative predictive value. T1 maps and extracellular volume fraction, which are able to quantify diffuse fibrosis, hold promise as complementary tools but need confirmatory results from large studies.

"Function follows form": Role of cardiac magnetic resonance for ventricular arrhythmia risk stratification in patients with cardiac sarcoidosis.

Cardiac involvement is common and may become clinically relevant in approximately 5%-10% of patients with systemic sarcoidosis. Although reduced left ventricular ejection fraction is a recognized predictor of mortality, recent studies have suggested an increased risk of ventricular arrhythmia (VAs) and sudden cardiac death (SCD) in patients with cardiac sarcoidosis (CS) and evidence of late gadolinium enhancement-cardiac magnetic resonance (LGE-CMR), irrespective of the underlying left ventricular systolic function. We performed a meta-analysis to assess the correlation between VAs/SCD and presence of LGE-CMR in CS patients. We systematically searched Medline, Embase, and Cochrane electronic databases up to January 2, 2023, for studies enrolling patients with suspected or confirmed CS undergoing LGE-CMR. Clinical outcomes of interest included clinically relevant VAs, defined as sustained ventricular tachycardia, ventricular fibrillation, SCD, or aborted SCD during follow-up. The effect size was estimated using a random-effect model as risk ratio (RR) and relative 95% confidence interval (CI). A total of 14 studies fulfilled the selection criteria and were included in the final analysis. Among 1273 patients, LGE was detected in 465 (36.5%; Group LGE+). Males accounted for 45.2% (95% CI: 40.5%-55.7%) of the total population and the average age was 56.8 (95% CI: 52.7%-60.9) years. A total of 104 (22.3%) of 465 LGE+ patients experienced a clinically relevant VA, compared to 6 (0.7%) of 808 LGE- ones. LGE+ was associated with a ninefold increased risk in life-threatening VAs (22.3% vs. 0.7%; RR = 9.52; 95% CI [5.18-17.49]; p < .0001) compared to patients without LGE (heterogeneity I2 = 0%). In our meta-analysis, LGE+ in patients with CS was associated with a ninefold increased risk in life-threatening VAs compared to patients without LGE.

Predictors of Ventricular Arrhythmias in Patients With Mitral Valve Prolapse: A Meta-analysis.

Mitral valve prolapse (MVP) has an estimated prevalence of 2-3% in the general population. Patients with MVP have an increased risk of ventricular arrhythmic events. The aim of this meta-analysis was to identify easily obtained markers that can be used for the arrhythmic risk stratification of MVP patients. This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA Statement). The search strategy identified 23 studies that were finally included in the study. The quantitative synthesis showed that late gadolinium enhancement (LGE) [RR 6.40 (2.11-19.39), I2 77%, P = 0.001], longer QTc interval [mean difference: 14.2 (8.92-19.49) I2 0%, P < 0.001], T-wave inversion in inferior leads [RR 1.60 (1.39-1.86), I2 0%, P < 0.001], mitral annular disjunction (MAD) [RR 1.77 (1.29-2.44), I2 37%, P = 0.0005], lower left ventricular ejection fraction (LVEF) [mean difference: -0.77 (-1.48, -0.07) I2 0%, P = 0.03], bileaflet MVP [RR 1.32 (1.16-1.49), I2 0%, P < 0.001], increased anterior [mean difference: 0.45 (0.28, 0.61), I2 0%, P < 0.001] and posterior [mean difference: 0.39 (0.26, 0.52), I2 0%, P < 0.001] mitral leaflet thickness were significantly associated with ventricular arrhythmias in MVP patients. On the other hand, gender, QRS duration, anterior, and posterior mitral leaflet length were not associated with increased risk of arrhythmias. In conclusion, inferior T-wave inversions, QTc interval, LGE, LVEF, MAD, bileaflet MVP, anterior, and posterior mitral leaflet thickness are easily obtained markers that can be used for the risk stratification of patients with MVP. Prospective studies should be designed for the better stratification of this population.

Artificial Intelligence in Ventricular Arrhythmias and Sudden Death.

Sudden cardiac arrest due to lethal ventricular arrhythmias is a major cause of mortality worldwide and results in more years of potential life lost than any individual cancer. Most of these sudden cardiac arrest events occur unexpectedly in individuals who have not been identified as high-risk due to the inadequacy of current risk stratification tools. Artificial intelligence tools are increasingly being used to solve complex problems and are poised to help with this major unmet need in the field of clinical electrophysiology. By leveraging large and detailed datasets, artificial intelligence-based prediction models have the potential to enhance the risk stratification of lethal ventricular arrhythmias. This review presents a synthesis of the published literature and a discussion of future directions in this field.

Genetic spectrum of familial and sporadic dilated cardiomyopathy: arrhythmic phenotypes associated with mutations in the lamin A/C (LMNA) gene

Purpose. To study the diagnostic value of cascade family screening and the spectrum of genetic variants in patients with familial and sporadic DCM, assess clinical outcomes and comparative analysis of 5-year event-free survival.Materials and methods. The study included 156 unrelated patients with verified DCM. All patients (aged 46 [34; 57] years; 125 (80%) male; LVEF 31 [24; 38]%; LV EDD 68 [61; 74] mm; follow-up period - 77 [59; 108] months) a complex of clinical and instrumental studies (ECG, ECHO, HM, MRI), cascade family screening with genetic testing (NGS+Sanger) and segregation analysis were performed.Results. Criteria for familial DCM were identified in 73 (46.8%) probands. The genetic cause of DCM was identified in 47 (64,4%) familial cases, while for sporadic form DCM pathogenic variants were detected in 19 (22,9%) patients. The dominant mutations were truncating variants in the titin gene (10,9%) and variants in the lamin A/C (LMNA) gene - 8,33%. As a result of the evaluation of cumulative event-free survival (Kaplan-Meier curves), LMNA carriers showed the poor 5-year prognosis for ventricular tachyarrhythmic events (x2=39.9; p=0,0001) and composite adverse outcomes (x2=12.1; p=0.001). Probands who had a familial DCM (log rang x2=38.5; p=0,0001) showed the worst prognosis and low cumulative survival when compared with patients of the sporadic DCM.Conclusion. Cascade clinical family screening and genetic testing in the DCM cohort increased the level of diagnosis of familial DCM from 4.5% to 46.8%. Associations of LMNA mutations with life-threatening tachyarrhythmias are defined as prognostically significant, that confirms the important role of genetic stratification of arrhythmic risk.

Monitoring for arrhythmia in transthyretin cardiac amyloidosis with remote patch devices

Abstract Funding Acknowledgements Type of funding sources: None. Background/Introduction Transthyretin cardiac amyloidosis (ATTR-CA) is associated with an increased incidence of arrhythmias. We hypothesized that non-invasive, two-week outpatient cardiac rhythm monitoring of patients with ATTR-CA would detect high rates of ventricular tachycardia and atrial fibrillation/flutter (AF). Purpose To characterize arrhythmia in patients with ATTR-CA on two-week, non-invasive cardiac rhythm monitors. Methods 38 patients with ATTR-CA (mean age 76.9 SD 10.0 years, 89.5% male) who underwent two-week remote external patch monitoring were included in this single center retrospective study. An age-matched control group included 38 patients (mean age 73.9 SD 12.3, 76.3% male) who underwent the same cardiac rhythm monitoring as part of neurological workups. Results NSVT was detected on the remote monitor in 81.6% of ATTR-CA patients and AF was detected in 26.3% of patients. ATTR-CA was associated with higher rates of NSVT and AF compared to the control group (28.9% with NSVT and 5.3% with AF). As seen in Figure 1, there were only three ATTR-CA patients without either AF, NSVT, advanced atrioventricular block, or a significant pause detected on remote monitor. Among the ATTR-CA group, at median 45 weeks follow-up, there were 4 heart failure hospitalizations, 2 cardiovascular events (1 episode of sustained VT and 1 stroke), 6 permanent pacemakers placed, and 3 implantable cardioverter-defibrillators placed, including one for sustained VT. NSVT and AF were not associated with a composite of these adverse outcome. Conclusion ATTR-CA was associated with high rates of NSVT and AF on noninvasive remote monitors. While evidence regarding the management of arrhythmias, particularly NSVT/VT, in ATTR-CA remains limited, two-week noninvasive cardiac monitoring can be considered to aid in risk stratification for both atrial and ventricular arrhythmias in ATTR-CA.

Using the 3D architecture of scar to predict life-threatening ventricular arrythmias - still a long way to go

Abstract Funding Acknowledgements Type of funding sources: None. Background Late gadolinium enhancement (LGE) has been proposed as an independent predictor of ventricular arrhythmias. Purpose The purpose of this study was to assess if myocardial scar characterization could enhance the risk stratification for life-threatening arrhythmias and sudden cardiac death (SCD). Methods We included patients with an indication for ICD or CRT-D implantation who underwent cardiac magnetic resonance for clinical proposes since February/2018 and in whom a 3D-LGE dataset was obtained. Patients with channelopathies (n=2) or inappropriate imaging quality (imaging artifacts; n=7) were excluded. Scar characterization using ADAS software was performed in 3D-LGE datasets in all but 5 patients, where 2D datasets were used. The primary endpoint was the composite of appropriate ICD therapy (classified as ATP or shock) or SCD. Results A total of 75 patients were analysed (mean age 63 ± 13 years; 83% male; mean LVEF 31 ± 13%; 50 patients with ischemic and 25 with non-ischemic cardiomyopathy; 14 patients received a device in the setting of secondary prevention). During a median follow-up of 1.4 years (IQR 0.7 – 2.4 years) there were 15 events (12 appropriate ICD therapies [8 shocks and 4 ATP] and 3 SCD). No statistically significant differences were found between patients with or without events in terms of scar mass, border zone (BZ) mass, BZ channels (BZC), BZC mass, number of channels detected, and scar heterogeneity (BZ mass / scar mass ratio) - all p values &amp;gt; 0.2 – Figure. Restricting the analysis to only primary prevention cases yielded similar results. Overall, 11 patients did not show any channel. Two of these experienced an arrhythmic event, yielding a negative predictive value of 80% (95% CI 75-83%) for the absence of channels. Conclusion In this cohort with still relatively limited follow-up duration, no single parameter reflecting scar tissue characterization was able to predict appropriate device therapies or sudden cardiac death.

Fibrosis entropy is associated with life-threatening arrhythmia in non-ischaemic cardiomyopathy

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by the National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Trust and King’s College, the Centre of Excellence in Medical Engineering funded by the Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC; WT088641/Z/09/Z). M.J.B. is supported by a Medical Research Council New Investigator Grant (MR/N011007/1) and British Heart Foundation (Project grant PG/18/74/34077). This work was supported by EPSRC 2018/19 DTP - EP/R513064/1 grant. This work was supported by a National Heart and Lung Institute Foundation grant awarded to Professor Sanjay Prasad and Dr Richard Jones. Background Enhanced risk stratification for implanted defibrillator requirement represents an important area of research in patients with non-ischemic cardiomyopathy (NICM). Myocardial fibrosis represents the major underlying arrhythmic substrate in this population, and its identification on late-gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) is associated with life-threatening arrhythmia (LTA). Fibrosis entropy, a measure of scar texture heterogeneity, may confer important information regarding the underlying pro-arrhythmic mechanisms of both core scar and areas of intermediate signal intensity (Gray Zone [GZ]). Purpose We sought to: 1) evaluate whether LGE-CMR assessment of left ventricular (LV) tissue entropy had incremental utility to fibrosis presence for arrhythmic risk stratification of patients with NICM; 2) quantify the added utility of GZ entropy in such analysis. Methods This study involved a prospective observational cohort of consecutive patients with NICM and myocardial fibrosis detected on LGE-CMR. Epicardial and endocardial contours obtained from LGE-CMR data were used with a FWHM method to delineate core fibrosis (≥50% maximum signal intensity) and GZ fibrosis (≥35%-&amp;lt;50% signal intensity). Fibrotic masks were subsequently used, along with native dicom LGE-CMR images to compute tissue entropy, defined by the standard Shannon Entropy for core fibrosis, GZ fibrosis, and combined core+GZ fibrosis. Patients underwent adjudicated long-term follow-up for LTA (composite of sudden cardiac death, aborted sudden cardiac death or sustained ventricular tachycardia). Results Of 291 patients with NICM and mid-wall/subepicardial fibrosis, 38 patients (13.1%) experienced LTA over median follow-up of 6.3 years (interquartile range 4.6-9.1 years). On Cox regression analysis, core fibrosis entropy (Hazard ratio [HR] 1.77, 95% CI 1.25-2.54, p=0.001), GZ fibrosis entropy (HR 1.74, 95% CI 1.20-2.54, p=0.004) and combined fibrosis entropy (HR 1.98, 95% CI 1.30-2.52, p=0.001) were associated LTA after adjustment for variables used to guide ICD implantation (LVEF &amp;lt;35% and NYHA class &amp;gt;1) and remained associated in multivariable models accounting separately for core and GZ fibrosis mass. The addition of core fibrosis entropy, GZ fibrosis entropy and combined fibrosis entropy to a baseline clinical model improved the C-statistic from 0.49 to 0.59, 0.62 and 0.62, respectively. LVEF &amp;lt;35% was not associated with LTA (HR 1.45, 95% CI 0.77-2.74, p=0.25) on multivariable analysis. Conclusions Fibrosis entropy on LGE-CMR offers incremental utility to LVEF and fibrosis presence for arrhythmic risk prediction in patients with NICM. The combination of core and GZ fibrosis entropy offers the highest association with risk.