Comparative effectiveness of ventricular tachycardia ablation vs. escalated antiarrhythmic drug therapy by location of myocardial infarction: a sub-study of the VANISH trial

AIMS

Complexity of the ventricular tachycardia (VT) substrate and the size and thickness of infarction area border zones differ based on location of myocardial infarctions (MIs). These differences may translate into heterogeneity in the effectiveness of treatments. This study aims to examine the influence of infarct location on the effectiveness of VT ablation in comparison with escalated pharmacological therapy in patients with prior MI and antiarrhythmic drug (AAD)-refractory VT.

METHODS AND RESULTS

VANISH trial participants were categorized based on the presence or absence of an inferior MI scar. Inverse probability of treatment weighted Cox models were calculated for each subgroup. Of 259 randomized patients (median age 69.8 years, 7.0% women), 135 had an inferior MI and 124 had a non-inferior MI. Among patients with an inferior MI, no statistically significant difference in the composite primary outcome of all-cause mortality, appropriate implantable cardioverter-defibrillator (ICD) shock, and VT storm was detected between treatment arms [adjusted hazard ratio (aHR) 0.80, 95% confidence interval (CI) 0.51-1.20]. In contrast, patients with non-inferior MIs had a statistically significant reduction in the incidence of the primary outcome with ablation (aHR 0.48, 95% CI 0.27-0.86). In a sensitivity analysis of anterior MI patients (n = 83), a trend towards a reduction in the primary outcome with ablation was detected (aHR 0.50, 95% CI 0.23-1.09).

CONCLUSION

The effectiveness of VT ablation versus escalated AADs varies based on the location of the MI. Patients with MI scars located only in non-inferior regions of the ventricles derive greater benefit from VT ablation in comparison to escalation of AADs in reducing VT-related events.

Texture-based probability mapping for automatic scar assessment in late gadolinium-enhanced cardiovascular magnetic resonance images

Purpose

To evaluate a novel texture-based probability mapping (TPM) method for scar size estimation in LGE-CMRI.

Methods

This retrospective proof-of-concept study included chronic myocardial scars from 52 patients. The TPM was compared with three signal intensity-based methods: manual segmentation, full-width-half-maximum (FWHM), and 5-standard deviation (5-SD). TPM is generated using machine learning techniques, expressing the probability of scarring in pixels. The probability is derived by comparing the texture of the 3 × 3 pixel matrix surrounding each pixel with reference dictionaries from patients with established myocardial scars. The Sørensen-Dice coefficient was used to find the optimal TPM range. A non-parametric test was used to test the correlation between infarct size and remodeling parameters. Bland-Altman plots were performed to assess agreement among the methods.

Results

The study included 52 patients (76.9% male; median age 64.5 years (54, 72.5)). A TPM range of 0.328–1.0 was found to be the optimal probability interval to predict scar size compared to manual segmentation, median dice (25th and 75th percentiles)): 0.69(0.42–0.81). There was no significant difference in the scar size between TPM and 5-SD. However, both 5-SD and TPM yielded larger scar sizes compared with FWHM (p < 0.001 and p = 0.002). There were strong correlations between scar size measured by TPM, and left ventricular ejection fraction (LVEF, r = −0.76, p < 0.001), left ventricular end-diastolic volume index (r = 0.73, p < 0.001), and left ventricular end-systolic volume index (r = 0.75, p < 0.001).

Conclusion

The TPM method is comparable with current SI-based methods, both for the scar size assessment and the relationship with left ventricular remodeling when applied on LGE-CMRI.

•

Texture based probability mapping can be used to evaluate myocardial scar size.

•

The method can assess myocardial fibrosis independent of signal intensity.

•

The TPM method shows strong correlations between scar size and left ventricular ejection fraction.

Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy

Delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging requires novel and time-efficient approaches to characterize the myocardial substrate associated with ventricular arrhythmia in patients with ischemic cardiomyopathy. Using a translational approach in pigs and patients with established myocardial infarction, we tested and validated a novel 3D methodology to assess ventricular scar using custom transmural criteria and a semiautomatic approach to obtain transmural scar maps in ventricular models reconstructed from both 3D-acquired and 3D-upsampled-2D-acquired LGE-CMR images. The results showed that 3D-upsampled models from 2D LGE-CMR images provided a time-efficient alternative to 3D-acquired sequences to assess the myocardial substrate associated with ischemic cardiomyopathy. Scar assessment from 2D-LGE-CMR sequences using 3D-upsampled models was superior to conventional 2D assessment to identify scar sizes associated with the cycle length of spontaneous ventricular tachycardia episodes and long-term ventricular tachycardia recurrences after catheter ablation. This novel methodology may represent an efficient approach in clinical practice after manual or automatic segmentation of myocardial borders in a small number of conventional 2D LGE-CMR slices and automatic scar detection.

Cardiac arrhythmias in the emergency settings of acute coronary syndrome and revascularization: an European Heart Rhythm Association (EHRA) consensus document, endorsed by the European Association of Percutaneous Cardiovascular Interventions (EAPCI), and European Acute Cardiovascular Care Association (ACCA)

Despite major therapeutic advances over the last decades, complex supraventricular and ventricular arrhythmias (VAs), particularly in the emergency setting or during revascularization for acute myocardial infarction (AMI), remain an important clinical problem. Although the incidence of VAs has declined in the hospital phase of acute coronary syndromes (ACS), mainly due to prompt revascularization and optimal medical therapy, still up to 6% patients with ACS develop ventricular tachycardia and/or ventricular fibrillation within the first hours of ACS symptoms. Despite sustained VAs being perceived predictors of worse in-hospital outcomes, specific associations between the type of VAs, arrhythmia timing, applied treatment strategies and long-term prognosis in AMI are vague. Atrial fibrillation (AF) is the most common supraventricular tachyarrhythmia that may be asymptomatic and/or may be associated with rapid haemodynamic deterioration requiring immediate treatment. It is estimated that over 20% AMI patients may have a history of AF, whereas the new-onset arrhythmia may occur in 5% patients with ST elevation myocardial infarction. Importantly, patients who were treated with primary percutaneous coronary intervention for AMI and developed AF have higher rates of adverse events and mortality compared with subjects free of arrhythmia. The scope of this position document is to cover the clinical implications and pharmacological/non-pharmacological management of arrhythmias in emergency presentations and during revascularization. Current evidence for clinical relevance of specific types of VAs complicating AMI in relation to arrhythmia timing has been discussed.

Three-dimensional cardiac fibre disorganization as a novel parameter for ventricular arrhythmia stratification after myocardial infarction

Aims

Myocardial infarction (MI) alters cardiac fibre organization with unknown consequences on ventricular arrhythmia. We used diffusion tensor imaging (DTI) of three-dimensional (3D) cardiac fibres and scar reconstructions to identify the main parameters associated with ventricular arrhythmia inducibility and ventricular tachycardia (VT) features after MI.

Methods and results

Twelve pigs with established MI and three controls underwent invasive electrophysiological characterization of ventricular arrhythmia inducibility and VT features. Animal-specific 3D scar and myocardial fibre distribution were obtained from ex vivo high-resolution contrast-enhanced T1 mapping and DTI sequences. Diffusion tensor imaging-derived parameters significantly different between healthy and scarring myocardium, scar volumes, and left ventricular ejection fraction (LVEF) were included for arrhythmia risk stratification and correlation analyses with VT features. Ventricular fibrillation (VF) was the only inducible arrhythmia in 4 out of 12 infarcted pigs and all controls. Ventricular tachycardia was also inducible in the remaining eight pigs during programmed ventricular stimulation. A DTI-based 3D fibre disorganization index (FDI) showed higher disorganization within dense scar regions of VF-only inducible pigs compared with VT inducible animals (FDI: 0.36; 0.36–0.37 vs. 0.32; 0.26–0.33, respectively, P = 0.0485). Ventricular fibrillation induction required lower programmed stimulation aggressiveness in VF-only inducible pigs than VT inducible and control animals. Neither LVEF nor scar volumes differentiated between VF and VT inducible animals. Re-entrant VT circuits were localized within areas of highly disorganized fibres. Moreover, the FDI within heterogeneous scar regions was associated with the median VT cycle length per animal (R² = 0.5320).

Conclusion

The amount of scar-related cardiac fibre disorganization in DTI sequences is a promising approach for ventricular arrhythmia stratification after MI.

The relationship between transmurality of ischemic scars and the heart rate of ventricular tachycardia

AIMS

The relationship between the heart rate of ventricular tachycardia (VT) and the transmurality of ischemic scars was assessed by a new semiautomatic coordinate-based analysis of late gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) images.

METHODS AND RESULTS

Twenty patients assessed by LGE-CMR before implantation of implantable cardioverter defibrillator (ICD) with verified VT during the first year following ICD implantation were included. Scar was defined by pixels with a signal intensity ≥ 50% of maximum signal intensity. All pixels were assigned a coordinate position between endo- and epicardium (λ) and the angle of the heart axis (φ). Based upon the λ and φ values, multiple scar features were computed for all scarred areas. These features were correlated to VT heart rate across the complete range of transmurality. The strongest correlation with univariate regression was found between VT heart rate and the sum of transmurality when the maximum transmurality of these features was ≥ 90% (R-square = 0.47). In multiple regressions analysis, the strongest relationship with VT heart rate was found with a maximum transmurality ≥ 90% and by a combination of scar size, transmurality, and endocardial extent of infarction (R-square = 0.64).

CONCLUSION

Transmurality is the strongest predictor of VT heart rate both in univariate and multivariate models. The strongest relationships were found at a transmurality level > 90%.

Computational model of erratic arrhythmias in a cardiac cell network: the role of gap junctions

Cardiac morbidity and mortality increases with the population age. To investigate the underlying pathological mechanisms, and suggest new ways to reduce clinical risks, computational approaches complementing experimental and clinical investigations are becoming more and more important. Here we explore the possible processes leading to the occasional onset and termination of the (usually) non-fatal arrhythmias widely observed in the heart. Using a computational model of a two-dimensional network of cardiac cells, we tested the hypothesis that an ischemia alters the properties of the gap junctions inside the ischemic area. In particular, in agreement with experimental findings, we assumed that an ischemic episode can alter the gap junctions of the affected cells by reducing their average conductance. We extended these changes to include random fluctuations with time, and modifications in the gap junction rectifying conductive properties of cells along the edges of the ischemic area. The results demonstrate how these alterations can qualitatively give an account of all the main types of non-fatal arrhythmia observed experimentally, and suggest how premature beats can be eliminated in three different ways: a) with a relatively small surgical procedure, b) with a pharmacological reduction of the rectifying conductive properties of the gap-junctions, and c) by pharmacologically decreasing the gap junction conductance. In conclusion, our model strongly supports the hypothesis that non-fatal arrhythmias can develop from post-ischemic alteration of the electrical connectivity in a relatively small area of the cardiac cell network, and suggests experimentally testable predictions on their possible treatments.

Segmentation of Scarred Myocardium in Cardiac Magnetic Resonance Images

The segmentation of scarred and nonscarred myocardium in Cardiac Magnetic Resonance (CMR) is obtained using different features and feature combinations in a Bayes classifier. The used features are found as a local average of intensity values and the underlying texture information in scarred and nonscarred myocardium. The segmentation classifier was trained and tested with different experimental setups and parameter combinations and was cross validated due to limited data. The experimental results show that the intensity variations are indeed an important feature for good segmentation, and the average area under the Receiver Operating Characteristic (ROC) curve, that is, the AUC, is 91.58 ± 3.2%. The segmentation using texture features also gives good segmentation with average AUC values at 85.89 ± 5.8%, that is, lower than the direct current (DC) feature. However, the texture feature gives robust performance compared to a local mean (DC) feature in a test set simulated from the original CMR data. The segmentation of scarred myocardium is comparable to manual segmentation in all the cross validation cases.

Probability mapping of scarred myocardium using texture and intensity features in CMR images

Background

The myocardium exhibits heterogeneous nature due to scarring after Myocardial Infarction (MI). In Cardiac Magnetic Resonance (CMR) imaging, Late Gadolinium (LG) contrast agent enhances the intensity of scarred area in the myocardium.

Methods

In this paper, we propose a probability mapping technique using Texture and Intensity features to describe heterogeneous nature of the scarred myocardium in Cardiac Magnetic Resonance (CMR) images after Myocardial Infarction (MI). Scarred tissue and non-scarred tissue are represented with high and low probabilities, respectively. Intermediate values possibly indicate areas where the scarred and healthy tissues are interwoven. The probability map of scarred myocardium is calculated by using a probability function based on Bayes rule. Any set of features can be used in the probability function.

Results

In the present study, we demonstrate the use of two different types of features. One is based on the mean intensity of pixel and the other on underlying texture information of the scarred and non-scarred myocardium. Examples of probability maps computed using the mean intensity of pixel and the underlying texture information are presented. We hypothesize that the probability mapping of myocardium offers alternate visualization, possibly showing the details with physiological significance difficult to detect visually in the original CMR image.

Conclusion

The probability mapping obtained from the two features provides a way to define different cardiac segments which offer a way to identify areas in the myocardium of diagnostic importance (like core and border areas in scarred myocardium).

Prediction of ventricular arrhythmias using cardiovascular magnetic resonance

Ventricular tachycardia (VT) is the commonest cause of sudden cardiac death (SCD) in developed countries. Coronary artery disease (CAD) is the most frequent cause of VT in individuals over the age of 30, while hypertrophic cardiomyopathy (HCM), myocarditis and congenital heart disease in those below 30 years of age. Cardiac magnetic resonance (CMR), a non-invasive, non-radiating technique, can reliably detect the changes in ventricular volumes and the ejection fraction that can be predictive of VT/SCD. Furthermore, the capability of CMR to perform tissue characterization and detect oedema, fat and fibrotic substrate, using late gadolinium enhanced images (LGE), can predict VT/SCD in both ischaemic and non-ischaemic cardiomyopathy. The extent of LGE in HCM is correlated with risk factors of SCD and the likelihood of inducible VT. In idiopathic-dilated cardiomyopathy, the presence of midwall fibrosis, assessed by CMR, also predicts SCD/VT. Additionally, in arrhythmogenic right ventricle (RV) dysplasia/cardiomyopathy, CMR has an excellent correlation with histopathology and predicted inducible VT on programmed electrical stimulation, suggesting a possible role in evaluation and diagnosis of these patients. A direct correlation between LGE and VT prediction has been identified only in chronic Chagas' heart disease, but not in viral myocarditis. In CAD, infarct size is the strongest predictor of VT inducibility. The peri-infarct zone may also play a role; however, further studies are needed for definite conclusions. Left ventricle, RV, right ventricular outflow tract (RVOT) function, pulmonary regurgitation and LGE around the infundibular patch and RV anterior wall play an important role in the VT prediction in repaired Tetralogy of Fallot. Finally, in treated transposition of great arteries, the extent of LGE in the systemic RV correlates with age, ventricular dysfunction, electrophysiological parameters and adverse clinical events, suggesting prognostic importance.