Infarct tissue heterogeneity assessed with contrast-enhanced MRI predicts spontaneous ventricular arrhythmia in patients with ischemic cardiomyopathy and implantable cardioverter-defibrillator

Cardiac magnetic resonance reveals concealed structural heart disease in patients with frequent premature ventricular contractions and normal echocardiography: A systematic review

Premature ventricular contractions (PVCs) are a common form of arrhythmic events, often representing an idiopathic and benign condition without further therapeutic interventions. However, in certain circumstances PVCs may represent the epiphenomenon of a concealed structural heart disease (SHD). Surface 12‑leads EKG and 24-h dynamic EKG are necessary to assess their main characteristics such as site of origin, frequency and complexity. Echocardiography represents the first-line imaging tool recommended to evaluate cardiac structures and function. Cardiac Magnetic Resonance (CMR) is recognized as a superior modality for detecting structural cardiac alterations, that might evade detection by conventional echocardiography. Moreover, in specific populations such as athletes, CMR may have a crucial role to exclude a concealed SHD and the risk of serious arrhythmic events during sport activity. Some clinical characteristics such as male sex, older age or family history of sudden cardiac death (SCD) or cardiomyopathy, and some electrocardiographic features of PVCs, in particular a right branch bundle block (RBBB) with superior/intermediate axis morphology, the reproducibility of VAs during exercise test (ET) or the evidence of complex ventricular arrhythmias, may warrant a CMR evaluation, due to the high probability of SHD. In this systematic review our objective was to provide an exhaustive overview on the role of CMR in detecting a concealed SHD in patients with high daily burden of PVCs and a normal echocardiographic evaluation, paving the way for a more extensive utilization of CMR in presence of certain high-risk clinical and/or EKG features identified during the diagnostic workup.

Evolution of Substrate for Ventricular Arrhythmias Early Postinfarction: Insights From a Porcine Ischemia-Reperfusion Model

BACKGROUND

The evolution of myocardial scar and its arrhythmogenic potential postinfarct is incompletely understood.

OBJECTIVES

This study sought to investigate scar and border zone (BZ) channels evolution in an animal ischemia-reperfusion injury model using late gadolinium enhancement cardiac magnetic resonance (LGE-CMR).

METHODS

Five swine underwent 90-minute balloon occlusion of the mid-left anterior descending artery, followed by LGE-CMR at day (d) 3, d30, and d58 postinfarct. Invasive electroanatomic mapping (EAM) was performed at 2 months. Topographical reconstructions of LGE-CMR were analyzed for left ventricular core and BZ scar, BZ channel geometry, and complexity, including transmurality, orientation, and number of entrances/exits.

RESULTS

LVEF reduced from 48.0% ± 1.8% to 41.3% ± 2.3% postinfarct. Total scar mass reduced over time (P = 0.008), including BZ (P = 0.002) and core scar (P = 0.05). A total of 72 BZ channels were analyzed across all animals and timepoints. Channel length (P = 0.05) and complexity (P = 0.02) reduced progressively from d3 to d58. However, at d58, 64% of channels were newly formed and 36% were midmyocardial. Conserved channels were initially longer and more complex. All LGE-CMR channels colocalized to regions of maximal decrement on EAM, with significantly greater decrement (115 ± 31 ms vs 83 ± 29 ms; P < 0.001) and uncovering of split potentials (24.8% vs 2.6%; P < 0.001) within channels. In total, 3 of 5 animals had inducible VT and tended to have more channels with greater midmyocardial involvement and functional decrement than those without VT.

CONCLUSIONS

BZ channels form early postinfarct and demonstrate evolutionary complexity and functional conduction slowing on EAM, highlighting their arrhythmogenic potential. Some channels regress in complexity and length, but new channels form at 2 months' postinfarct, which may be midmyocardial, reflecting an evolving, 3-dimensional substrate for VT. LGE-CMR may help identify BZ channels that may support VT early postinfarct and lead to sudden death.

Variations in threshold values for border zone and dense scar produce significant changes in scar parameters obtained by ADAS-3D

BACKGROUND

ADAS-3D software elaborates cardiac magnetic resonance (CMR) images to obtain a quantitative evaluation of dense scar and border zone (BZ), including BZ channels, which can be useful for ventricular tachycardia ablation and risk stratification. However, most prior reports with ADAS-3D used flexible thresholds (60% ± 5% and 40% ± 5% of maximum pixel signal intensity) to define dense scar and BZ. The impact of such variations of the threshold values on the measurements obtained with ADAS-3D is unknown.

OBJECTIVE

This study aimed to quantify the degree of change in ADAS-3D measurements when different thresholds for dense scar and BZ are employed.

METHODS

A single-center retrospective observational cohort study including 87 consecutive patients with previous myocardial infarction who underwent CMR was conducted. ADAS-3D software semiautomatically processed CMR sequences. We compared the scar measurements obtained with the 9 possible combinations of thresholds (55%/60%/65% and 35%/40%/45% of maximum pixel signal intensity).

RESULTS

The overall comparison between thresholds showed highly significant differences (P < .001) in all scar parameters. Not a single patient maintained the same number of BZ channels with all the thresholds settings. A percentage difference of up to 200% in BZ channel numbers and channel mass was observed in all 36 comparisons. An absolute difference of up to 10 channels was also recorded. Of note, the highest median channel mass (obtained with the thresholds 35-65) was 59-fold higher compared with the lowest one (obtained with the 45-55 cutoffs).

CONCLUSION

Variations in threshold values result in statistically significant and high-magnitude changes in the quantification of scar parameters by ADAS-3D.

Antiarrhythmic and Anti-Inflammatory Effects of Sacubitril/Valsartan on Post-Myocardial Infarction Scar

BACKGROUND

Sacubitril/valsartan (Sac/Val) is superior to angiotensin-converting enzyme inhibitors in reducing the risk of heart failure hospitalization and cardiovascular death, but its mechanistic data on myocardial scar after myocardial infarction (MI) are lacking. The objective of this work was to assess the effects of Sac/Val on inflammation, fibrosis, electrophysiological properties, and ventricular tachycardia inducibility in post-MI scar remodeling in swine.

METHODS

After MI, 22 pigs were randomized to receive β-blocker (BB; control, n=8) or BB+Sac/Val (Sac/Val, n=9). The systemic immune response was monitored. Cardiac magnetic resonance data were acquired at 2-day and 29-day post MI to assess ventricular remodeling. Programmed electrical stimulation and high-density mapping were performed at 30-day post MI to assess ventricular tachycardia inducibility. Myocardial samples were collected for histological analysis.

RESULTS

Compared with BB, BB+Sac/Val reduced acute circulating leukocytes (P=0.009) and interleukin-12 levels (P=0.024) at 2-day post MI, decreased C-C chemokine receptor type 2 expression in monocytes (P=0.047) at 15-day post MI, and reduced scar mass (P=0.046) and border zone mass (P=0.043). It also lowered the number and mass of border zone corridors (P=0.009 and P=0.026, respectively), scar collagen I content (P=0.049), and collagen I/III ratio (P=0.040). Sac/Val reduced ventricular tachycardia inducibility (P=0.034) and the number of deceleration zones (P=0.016).

CONCLUSIONS

After MI, compared with BB, BB+Sac/Val was associated with reduced acute systemic inflammatory markers, reduced total scar and border zone mass on late gadolinium-enhanced magnetic resonance imaging, and lower ventricular tachycardia inducibility.

Multisize Electrode Field-of-View: Validation by High Resolution Gadolinium-Enhanced Cardiac Magnetic Resonance

BACKGROUND

Voltage mapping to detect ventricular scar is important for guiding catheter ablation, but the field-of-view of unipolar, bipolar, conventional, and microelectrodes as it relates to the extent of viable myocardium (VM) is not well defined.

OBJECTIVES

The purpose of this study was to evaluate electroanatomic voltage-mapping (EAVM) with different-size electrodes for identifying VM, validated against high-resolution ex-vivo cardiac magnetic resonance (HR-LGE-CMR).

METHODS

A total of 9 swine with early-reperfusion myocardial infarction were mapped with the QDOT microcatheter. HR-LGE-CMR (0.3-mm slices) were merged with EAVM. At each EAVM point, the underlying VM in multisize transmural cylinders and spheres was quantified from ex vivo CMR and related to unipolar and bipolar voltages recorded from conventional and microelectrodes.

RESULTS

In each swine, 220 mapping points (Q1, Q3: 216, 260 mapping points) were collected. Infarcts were heterogeneous and nontransmural. Unipolar and bipolar voltage increased with VM volumes from >175 mm3 up to >525 mm3 (equivalent to a 5-mm radius cylinder with height >6.69 mm). VM volumes in subendocardial cylinders with 1- or 3-mm depth correlated poorly with all voltages. Unipolar voltages recorded with conventional and microelectrodes were similar (difference 0.17 ± 2.66 mV) and correlated best to VM within a sphere of radius 10 and 8 mm, respectively. Distance-weighting did not improve the correlation.

CONCLUSIONS

Voltage increases with transmural volume of VM but correlates poorly with small amounts of VM, which limits EAVM in defining heterogeneous scar. Microelectrodes cannot distinguish thin from thick areas of subendocardial VM. The field-of-view for unipolar recordings for microelectrodes and conventional electrodes appears to be 8 to 10 mm, respectively, and unexpectedly similar.

Imaging in patients with cardiovascular implantable electronic devices: part 1-imaging before and during device implantation. A clinical consensus statement of the European Association of Cardiovascular Imaging (EACVI) and the European Heart Rhythm Association (EHRA) of the ESC

More than 500 000 cardiovascular implantable electronic devices (CIEDs) are implanted in the European Society of Cardiology countries each year. The role of cardiovascular imaging in patients being considered for CIED is distinctly different from imaging in CIED recipients. In the former group, imaging can help identify specific or potentially reversible causes of heart block, the underlying tissue characteristics associated with malignant arrhythmias, and the mechanical consequences of conduction delays and can also aid challenging lead placements. On the other hand, cardiovascular imaging is required in CIED recipients for standard indications and to assess the response to device implantation, to diagnose immediate and delayed complications after implantation, and to guide device optimization. The present clinical consensus statement (Part 1) from the European Association of Cardiovascular Imaging, in collaboration with the European Heart Rhythm Association, provides comprehensive, up-to-date, and evidence-based guidance to cardiologists, cardiac imagers, and pacing specialists regarding the use of imaging in patients undergoing implantation of conventional pacemakers, cardioverter defibrillators, and resynchronization therapy devices. The document summarizes the existing evidence regarding the use of imaging in patient selection and during the implantation procedure and also underlines gaps in evidence in the field. The role of imaging after CIED implantation is discussed in the second document (Part 2).

Association of epicardial and intramyocardial fat with ventricular arrhythmias

BACKGROUND

Among patients with ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM), myocardial fibrosis is associated with an increased risk for ventricular arrhythmia (VA). Growing evidence suggests that myocardial fat contributes to ventricular arrhythmogenesis. However, little is known about the volume and distribution of epicardial adipose tissue and intramyocardial fat and their relationship with VAs.

OBJECTIVE

The purpose of this study was to assess the association of contrast-enhanced computed tomography (CE-CT)-derived left ventricular (LV) tissue heterogeneity, epicardial adipose tissue volume, and intramyocardial fat volume with the risk of VA in ICM and NICM patients.

METHODS

Patients enrolled in the PROSE-ICD registry who underwent CE-CT were included. Intramyocardial fat volume (voxels between -180 and -5 Hounsfield units [HU]), epicardial adipose tissue volume (between -200 and -50 HU), and LV tissue heterogeneity were calculated. The primary endpoint was appropriate ICD shocks or sudden arrhythmic death.

RESULTS

Among 98 patients (47 ICM, 51 NICM), LV tissue heterogeneity was associated with VA (odds ratio [OR] 1.10; P = .01), particularly in the ICM cohort. In the NICM subgroup, epicardial adipose tissue and intramyocardial fat volume were associated with VA (OR 1.11, P = .01; and OR = 1.21, P = .01, respectively) but not in the ICM patients (OR 0.92, P =.22; and OR = 0.96, P =.19, respectively).

CONCLUSION

In ICM patients, increased fat distribution heterogeneity is associated with VA. In NICM patients, an increased volume of intramyocardial fat and epicardial adipose tissue is associated with a higher risk for VA. Our findings suggest that fat's contribution to VAs depends on the underlying substrate.

Effect of myocardial scar size on the risk of ventricular arrhythmias in patients with chronic total coronary occlusion

BACKGROUND

The presence of an untreated chronic total coronary occlusion (CTO) is associated with a higher risk of ventricular arrhythmias (VAs). This increased risk may be modulated by the presence of an existing scar.

OBJECTIVES

To evaluate whether scar size is associated with VA in patients with an implantable cardioverter-defibrillator (ICD) and a CTO.

METHODS

In this retrospective study we included patients with a CTO that received an ICD between 2005 and 2015. Scar size was estimated using the Selvester QRS score on a baseline 12‑lead ECG. The primary endpoint was any appropriate ICD therapy.

RESULTS

Our study population comprised 148 CTO patients with a median scar size at baseline of 18% (IQR, 9-27%). Patients with a scar size ≥18% more often had a CTO located in the left anterior descending artery and a higher proportion of poor left ventricular function (<35%) and infarct-related CTO compared to patients with a smaller scar size (<18%). During a median follow-up of 35 months (interquartile range [IQR], 8-60 months), 42 patients (28%) received appropriate ICD therapy. The cumulative 5-year event rate was higher in the patients with a large scar in comparison to those with a smaller or no scar (36% versus 19%, P = 0.04). Multivariable Cox regression analysis demonstrated that large scar and diabetes mellitus were independent factors associated with appropriate ICD therapy.

CONCLUSION

In ICD recipients with an untreated CTO, a larger scar is an independent factor associated with an increased risk of VA.

Prognostic implications of left ventricular inward displacement assessed by cardiac magnetic resonance imaging in patients with myocardial infarction

Risk stratification of patients with ischemic heart disease (IHD) still depends mainly on the left ventricular ejection fraction (LVEF). LV inward displacement (InD) is a novel parameter of LV systolic function, derived from feature tracking cardiac magnetic resonance (CMR) imaging. We aimed to investigate the prognostic impact of InD in patients with IHD and prior myocardial infarction. A total of 111 patients (mean age 57 ± 10, 86% male) with a history of myocardial infarction who underwent CMR were included. LV InD was quantified by measuring the displacement of endocardially tracked points towards the centreline of the LV during systole with feature tracking CMR. The endpoint was a composite of all-cause mortality, heart failure hospitalization and arrhythmic events. During a median follow-up of 142 (IQR 107-159) months, 31 (27.9%) combined events occurred. Kaplan-Meier analysis demonstrated that patients with LV InD below the study population median value (23.0%) had a significantly lower event-free survival (P < 0.001). LV InD remained independently associated with outcomes (HR 0.90, 95% CI 0.84-0.98, P = 0.010) on multivariate Cox regression analysis. InD also provided incremental prognostic value to LVEF, LV global radial strain and CMR scar burden. LV InD, measured with feature tracking CMR, was independently associated with outcomes in patients with IHD and prior myocardial infarction. LV InD also provided incremental prognostic value, in addition to LVEF and LV global radial strain. LV InD holds promise as a pragmatic imaging biomarker for post-infarct risk stratification.

Prospects for Precision Medicine in Acute Myocardial Infarction: Patient-Level Insights into Myocardial Injury and Repair

The past decade has seen a marked expansion in the understanding of the pathobiology of acute myocardial infarction and the systemic inflammatory response that it elicits. At the same time, a portfolio of tools has emerged to characterise some of these processes in vivo. However, in clinical practice, key decision making still largely relies on assessment built around the timing of the onset of chest pain, features on electrocardiograms and measurements of plasma troponin. Better understanding the heterogeneity of myocardial injury and patient-level responses should provide new opportunities for diagnostic stratification to enable the delivery of more rational therapies. Characterisation of the myocardium using emerging imaging techniques such as the T1, T2 and T2* mapping techniques can provide enhanced assessments of myocardial statuses. Physiological measures, which include microcirculatory resistance and coronary flow reserve, have been shown to predict outcomes in AMI and can be used to inform treatment selection. Functionally informative blood biomarkers, including cellular transcriptomics; microRNAs; extracellular vesicle analyses and soluble markers, all give insights into the nature and timing of the innate immune response and its regulation in acute MI. The integration of these and other emerging tools will be key to developing a fuller understanding of the patient-level processes of myocardial injury and repair and should fuel new possibilities for rational therapeutic intervention.

Regional beat-to-beat variability of repolarization increases during ischemia and predicts imminent arrhythmias in a pig model of myocardial infarction

Ventricular arrhythmia (VT/VF) can complicate acute myocardial ischemia (AMI). Regional instability of repolarization during AMI contributes to the substrate for VT/VF. Beat-to-beat variability of repolarization (BVR), a measure of repolarization lability increases during AMI. We hypothesized that its surge precedes VT/VF. We studied the spatial and temporal changes in BVR in relation to VT/VF during AMI. In 24 pigs, BVR was quantified on 12-lead electrocardiogram recorded at a sampling rate of 1 kHz. AMI was induced in 16 pigs by percutaneous coronary artery occlusion (MI), whereas 8 underwent sham operation (sham). Changes in BVR were assessed at 5 min after occlusion, 5 and 1 min pre-VF in animals that developed VF, and matched time points in pigs without VF. Serum troponin and ST deviation were measured. After 1 mo, magnetic resonance imaging and VT induction by programmed electrical stimulation were performed. During AMI, BVR increased significantly in inferior-lateral leads correlating with ST deviation and troponin increase. BVR was maximal 1 min pre-VF (3.78 ± 1.36 vs. 5 min pre-VF, 1.67 ± 1.56, P < 0.0001). After 1 mo, BVR was higher in MI than in sham and correlated with the infarct size (1.43 ± 0.50 vs. 0.57 ± 0.30, P = 0.009). VT was inducible in all MI animals and the ease of induction correlated with BVR. BVR increased during AMI and temporal BVR changes predicted imminent VT/VF, supporting a possible role in monitoring and early warning systems. BVR correlated to arrhythmia vulnerability suggesting utility in risk stratification post-AMI.NEW & NOTEWORTHY The key finding of this study is that BVR increases during AMI and surges before ventricular arrhythmia onset. This suggests that monitoring BVR may be useful for monitoring the risk of VF during and after AMI in the coronary care unit settings. Beyond this, monitoring BVR may have value in cardiac implantable devices or wearables.

Prognostic Value of Different Thresholds for Myocardial Scar Quantification on Cardiac MRI Late Gadolinium Enhancement Images in Patients Receiving Implantable Cardioverter Defibrillators

Purpose

To compare the predictive value of different myocardial scar quantification thresholds using cardiac MRI for appropriate implantable cardioverter defibrillator (ICD) shock and mortality.

Materials and Methods

In this retrospective, two-center observational cohort study, patients with ischemic or nonischemic cardiomyopathy underwent cardiac MRI prior to ICD implantation. Late gadolinium enhancement (LGE) was first determined visually and then quantified by blinded cardiac MRI readers using different SDs above the mean signal of normal myocardium, full-width half-maximum, and manual thresholding. The intermediate signal "gray zone" was calculated as the differences between different SDs.

Results

Among 374 consecutive eligible patients (mean age, 61 years ± 13 [SD]; mean left ventricular ejection fraction, 32% ± 14; secondary prevention, 62.7%), those with LGE had a higher rate of appropriate ICD shock or death than those without (37.5% vs 26.6%, log-rank P = .04) over a median follow-up of 61 months. In multivariable analysis, none of the thresholds for quantifying scar was a significant predictor of mortality or appropriate ICD shock, while the extent of gray zone was an independent predictor (adjusted hazard ratio per 1 g = 1.025; 95% CI: 1.008, 1.043; P = .005) regardless of the presence or absence of ischemic heart disease (P interaction = .57). Model discrimination was highest for the model incorporating the gray zone (between 2 SD and 4 SD).

Conclusion

Presence of LGE was associated with a higher rate of appropriate ICD shock or death. Although none of the scar quantification techniques predicted outcomes, the gray zone both in infarct and nonischemic scar was an independent predictor and may refine risk stratification.Keywords: MRI, Scar Quantification, Implantable Cardioverter Defibrillator, Sudden Cardiac Death Supplemental material is available for this article. © RSNA, 2023.

Implantable Cardioverter-Defibrillator for Primary Prevention in Asia

In a contemporary setting, where the risk of sudden cardiac death (SCD) is low, heart failure management is improved, and technology is advanced, identifying the patients who would benefit the most from an implantable cardioverter-defibrillator (ICD) treatment for primary prevention remains a challenge. The prevalence of SCD is lower in Asia when compared with the United States/Europe (35-45 per 100,000 person-years vs 55-100 per 100,000 person-years, respectively). Nevertheless, this should not explain the enormous gap in ICD's utilization among eligible candidates (∼12% in Asia vs ∼45% in the United States/Europe). The disparity between Asia and Western countries, together with significant variation among the Asian population and the previously mentioned challenges, requires an individualized approach and specific regional recommendation, especially in countries with limited resources where ICDs are being extremely underutilized This review focuses on the current knowledge of ICD therapy for SCD prevention and how to improve patient and device selection.

Strain Imaging and Ventricular Arrhythmia

Ventricular arrhythmia is one of the main causes of sudden cardiac death. Hence, identifying patients at risk of ventricular arrhythmias and sudden cardiac death is important but can be challenging. The indication for an implantable cardioverter defibrillator as a primary preventive strategy relies on the left ventricular ejection fraction as a measure of systolic function. However, ejection fraction is flawed by technical constraints and is an indirect measure of systolic function. There has, therefore, been an incentive to identify other markers to optimize the risk prediction of malignant arrhythmias to select proper candidates who could benefit from an implantable cardioverter defibrillator. Speckle-tracking echocardiography allows for a detailed assessment of cardiac mechanics, and strain imaging has repeatedly been shown to be a sensitive technique to identify systolic dysfunction unrecognized by ejection fraction. Several strain measures, including global longitudinal strain, regional strain, and mechanical dispersion, have consequently been proposed as potential markers of ventricular arrhythmias. In this review, we will provide an overview of the potential use of different strain measures in the context of ventricular arrhythmias.

Utility of cardiac imaging in patients with ventricular tachycardia

Ventricular tachycardia (VT) is a life-threatening arrhythmia that may be idiopathic or result from structural heart disease. Cardiac imaging is critical in the diagnostic workup and risk stratification of patients with VT. Data gained from cardiac imaging provides information on likely mechanisms and sites of origin, as well as risk of intervention. Pre-procedural imaging can be used to plan access route(s) and identify patients where post-procedural intensive care may be required. Integration of cardiac imaging into electroanatomical mapping systems during catheter ablation procedures can facilitate the optimal approach, reduce radiation dose, and may improve clinical outcomes. Intraprocedural imaging helps guide catheter position, target substrate, and identify complications early. This review summarises the contemporary imaging modalities used in patients with VT, and their uses both pre-procedurally and intra-procedurally.

Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease

BACKGROUND

Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).

OBJECTIVES

The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).

METHODS

Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.

RESULTS

Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.

CONCLUSIONS

Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

AI Cardiac MRI Scar Analysis Aids Prediction of Major Arrhythmic Events in the Multicenter DERIVATE Registry

Background Scar burden with late gadolinium enhancement (LGE) cardiac MRI (CMR) predicts arrhythmic events in patients with postinfarction in single-center studies. However, LGE analysis requires experienced human observers, is time consuming, and introduces variability. Purpose To test whether postinfarct scar with LGE CMR can be quantified fully automatically by machines and to compare the ability of LGE CMR scar analyzed by humans and machines to predict arrhythmic events. Materials and Methods This study is a retrospective analysis of the multicenter, multivendor CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry. Patients with chronic heart failure, echocardiographic left ventricular ejection fraction (LVEF) of less than 50%, and LGE CMR were recruited (from January 2015 through December 2020). In the current study, only patients with ischemic cardiomyopathy were included. Quantification of total, dense, and nondense scars was carried out by two experienced readers or a Ternaus network, trained and tested with LGE images of 515 and 246 patients, respectively. Univariable and multivariable Cox analyses were used to assess patient and cardiac characteristics associated with a major adverse cardiac event (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare model performances. Results In 761 patients (mean age, 65 years ± 11, 671 men), 83 MACEs occurred. With use of the testing group, univariable Cox-analysis found New York Heart Association class, left ventricle volume and/or function parameters (by echocardiography or CMR), guideline criterion (LVEF of ≤35% and New York Heart Association class II or III), and LGE scar analyzed by humans or the machine-learning algorithm as predictors of MACE. Machine-based dense or total scar conferred incremental value over the guideline criterion for the association with MACE (AUC: 0.68 vs 0.63, P = .02 and AUC: 0.67 vs 0.63, P = .01, respectively). Modeling with competing risks yielded for dense and total scar (AUC: 0.67 vs 0.61, P = .01 and AUC: 0.66 vs 0.61, P = .005, respectively). Conclusion In this analysis of the multicenter CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry, fully automatic machine learning-based late gadolinium enhancement analysis reliably quantifies myocardial scar mass and improves the current prediction model that uses guideline-based risk criteria for implantable cardioverter defibrillator implantation. ClinicalTrials.gov registration no.: NCT03352648 Published under a CC BY 4.0 license. Supplemental material is available for this article.

Machine learning analysis of complex late gadolinium enhancement patterns to improve risk prediction of major arrhythmic events

Background

Machine learning analysis of complex myocardial scar patterns affords the potential to enhance risk prediction of life-threatening arrhythmia in stable coronary artery disease (CAD).

Objective

To assess the utility of computational image analysis, alongside a machine learning (ML) approach, to identify scar microstructure features on late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) that predict major arrhythmic events in patients with CAD.

Methods

Patients with stable CAD were prospectively recruited into a CMR registry. Shape-based scar microstructure features characterizing heterogeneous ('peri-infarct') and homogeneous ('core') fibrosis were extracted. An ensemble of machine learning approaches were used for risk stratification, in addition to conventional analysis using Cox modeling.

Results

Of 397 patients (mean LVEF 45.4 ± 16.0) followed for a median of 6 years, 55 patients (14%) experienced a major arrhythmic event. When applied within an ML model for binary classification, peri-infarct zone (PIZ) entropy, peri-infarct components and core interface area outperformed a model representative of the current standard of care (LVEF<35% and NYHA>Class I): AUROC (95%CI) 0.81 (0.81-0.82) vs. 0.64 (0.63-0.65), p = 0.002. In multivariate cox regression analysis, these features again remained significant after adjusting for LVEF<35% and NYHA>Class I: PIZ entropy hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.38-2.56, p < 0.001; number of PIZ components HR 1.34, 95% CI 1.08-1.67, p = 0.009; core interface area HR 1.6, 95% CI 1.29-1.99, p = <0.001.

Conclusion

Machine learning models using LGE-CMR scar microstructure improved arrhythmic risk stratification as compared to guideline-based clinical parameters; highlighting a potential novel approach to identifying candidates for implantable cardioverter defibrillators in stable CAD.

Prognostic Value of Entropy Derived from Late Gadolinium Enhancement Images to Adverse Cardiac Events in Post-Myocardial Infarction Patients

RATIONALE AND OBJECTIVES

To explore the prognostic value of entropy derived from late gadolinium enhancement images on cardiac magnetic resonance (CMR) for major adverse cardiac events (MACE) in post-myocardial infarction (MI) patients.

MATERIALS AND METHODS

Participants with MI underwent 3.0T CMR were retrospectively enrolled. CMR parameters, including the entropy of infarct core (IC), peri-infarct border zone (BZ), and infarct core and peri-infarct border zone (IBZ) were analyzed. Patients were divided into the No-MACE group and the MACE group according to the absence or presence of MACE during the follow-up period.

RESULTS

Eighty-four patients were included, among whom 51 patients without MACE and 33 patients with MACE. The MACE group showed higher IC mass, IBZ mass, IC entropy, BZ entropy, IBZ entropy, and LV entropy and lower LVEF than those of the NO-MACE group. LVEF, BZ entropy, and IBZ entropy were independent predictors of MACE (p < 0.05). Receiver operating characteristic curve revealed that the predictive values of BZ entropy with AUC of 0.860, IBZ entropy with AUC of 0.930, the combined model of LVEF and BZ entropy with AUC of 0.923, and the combined model of LVEF and IBZ entropy with AUC of 0.954 were higher than that of LVEF with AUC of 0.797. Delong test illustrated there was no significant difference in AUC among the three models with AUC > 0.900 (p > 0.05).

CONCLUSION

BZ entropy and IBZ entropy were noninvasive parameters for better risk stratification of post-MI patients. MI Patients with MACE showed higher BZ entropy and IBZ entropy than patients without MACE.

The scar: the wind in the perfect storm-insights into the mysterious living tissue originating ventricular arrhythmias

BACKGROUND

Arrhythmic death is very common among patients with structural heart disease, and it is estimated that in European countries, 1 per 1000 inhabitants yearly dies for sudden cardiac death (SCD), mainly as a result of ventricular arrhythmias (VA). The scar is the result of cardiac remodelling process that occurs in several cardiomyopathies, both ischemic and non-ischemic, and is considered the perfect substrate for re-entrant and non-re-entrant arrhythmias.

METHODS

Our aim was to review published evidence on the histological and electrophysiological properties of myocardial scar and to review the central role of cardiac magnetic resonance (CMR) in assessing ventricular arrhythmias substrate and its potential implication in risk stratification of SCD.

RESULTS

Scarring process affects both structural and electrical myocardial properties and paves the background for enhanced arrhythmogenicity. Non-uniform anisotropic conduction, gap junctions remodelling, source to sink mismatch and refractoriness dispersion are some of the underlining mechanisms contributing to arrhythmic potential of the scar. All these mechanisms lead to the initiation and maintenance of VA. CMR has a crucial role in the evaluation of patients suffering from VA, as it is considered the gold standard imaging test for scar characterization. Mounting evidences support the use of CMR not only for the definition of gross scar features, as size, localization and transmurality, but also for the identification of possible conducting channels suitable of discrete ablation. Moreover, several studies call out the CMR-based scar characterization as a stratification tool useful in selecting patients at risk of SCD and amenable to implantable cardioverter-defibrillator (ICD) implantation.

CONCLUSIONS

Scar represents the substrate of ventricular arrhythmias. CMR, defining scar presence and its features, may be a useful tool for guiding ablation procedures and for identifying patients at risk of SCD amenable to ICD therapy.

The role of multimodality imaging in the selection for implantable cardioverter-defibrillators in heart failure: A narrative review

Advanced pharmacologic and interventional therapies have improved survival in heart failure. Implantable cardioverter-defibrillators (ICD) have been shown to reduce mortality in patients with heart failure, but the benefit appears to be uneven in this population. We reviewed the evidence showing the benefit of ICD therapy in heart failure patients, the main issues arising from these studies, and the possible answers for a better risk stratification. In addition, we showed that multimodality imaging could improve patient selection for the implantation of ICDs, in both primary and secondary prevention, beyond the selection using only the left ventricular ejection fraction, by concentrating on arrhythmic substrate.

Multimodality Imaging of Sudden Cardiac Death and Acute Complications in Acute Coronary Syndrome

Sudden cardiac death (SCD) is a potentially fatal event usually caused by a cardiac arrhythmia, which is often the result of coronary artery disease (CAD). Up to 80% of patients suffering from SCD have concomitant CAD. Arrhythmic complications may occur in patients with acute coronary syndrome (ACS) before admission, during revascularization procedures, and in hospital intensive care monitoring. In addition, about 20% of patients who survive cardiac arrest develop a transmural myocardial infarction (MI). Prevention of ACS can be evaluated in selected patients using cardiac computed tomography angiography (CCTA), while diagnosis can be depicted using electrocardiography (ECG), and complications can be evaluated with cardiac magnetic resonance (CMR) and echocardiography. CCTA can evaluate plaque, burden of disease, stenosis, and adverse plaque characteristics, in patients with chest pain. ECG and echocardiography are the first-line tests for ACS and are affordable and useful for diagnosis. CMR can evaluate function and the presence of complications after ACS, such as development of ventricular thrombus and presence of myocardial tissue characterization abnormalities that can be the substrate of ventricular arrhythmias.

Imaging for risk stratification of sudden cardiac death

Sudden cardiac death (SCD) can be effectively prevented with the use of implantable cardioverter-defibrillator (ICD). Current guidelines advocate an ICD for primary prevention in the presence of an left ventricular ejection fraction (LVEF) ≤ 35%. The majority of individuals that experience SCD, however, have an LVEF > 35%. Multimodality cardiac imaging has the ability to visualize the three factors responsible for arrhythmia-mediated SCD, namely substrate, trigger and modulator. Advances in cardiac imaging techniques have allowed improved SCD risk stratification, especially in the group of patients with an LVEF > 35%. However, clinical integration of cardiac imaging for SCD risk stratification will require more comparative data between modalities and parameters, as well as evidence of an impact on outcomes. The current review represents an update on the use of multimodality imaging techniques for SCD risk stratification.

Advanced imaging for risk stratification for ventricular arrhythmias and sudden cardiac death

Sudden cardiac death (SCD) is a leading cause of mortality, comprising approximately half of all deaths from cardiovascular disease. In the US, the majority of SCD (85%) occurs in patients with ischemic cardiomyopathy (ICM) and a subset in patients with non-ischemic cardiomyopathy (NICM), who tend to be younger and whose risk of mortality is less clearly delineated than in ischemic cardiomyopathies. The conventional means of SCD risk stratification has been the determination of the ejection fraction (EF), typically via echocardiography, which is currently a means of determining candidacy for primary prevention in the form of implantable cardiac defibrillators (ICDs). Advanced cardiac imaging methods such as cardiac magnetic resonance imaging (CMR), single-photon emission computerized tomography (SPECT) and positron emission tomography (PET), and computed tomography (CT) have emerged as promising and non-invasive means of risk stratification for sudden death through their characterization of the underlying myocardial substrate that predisposes to SCD. Late gadolinium enhancement (LGE) on CMR detects myocardial scar, which can inform ICD decision-making. Overall scar burden, region-specific scar burden, and scar heterogeneity have all been studied in risk stratification. PET and SPECT are nuclear methods that determine myocardial viability and innervation, as well as inflammation. CT can be used for assessment of myocardial fat and its association with reentrant circuits. Emerging methodologies include the development of "virtual hearts" using complex electrophysiologic modeling derived from CMR to attempt to predict arrhythmic susceptibility. Recent developments have paired novel machine learning (ML) algorithms with established imaging techniques to improve predictive performance. The use of advanced imaging to augment risk stratification for sudden death is increasingly well-established and may soon have an expanded role in clinical decision-making. ML could help shift this paradigm further by advancing variable discovery and data analysis.

Role of cardiac magnetic resonance imaging in troponinemia syndromes

Cardiac magnetic resonance imaging (MRI) is an evolving technology, proving to be a highly accurate tool for quantitative assessment. Most recently, it has been increasingly used in the diagnostic and prognostic evaluation of conditions involving an elevation in troponin or troponinemia. Although an elevation in troponin is a nonspecific marker of myocardial tissue damage, it is a frequently ordered investigation leaving many patients without a specific diagnosis. Fortunately, the advent of newer cardiac MRI protocols can provide additional information. In this review, we discuss several conditions associated with an elevation in troponin such as myocardial infarction, myocarditis, Takotsubo cardiomyopathy, coronavirus disease 2019 related cardiac dysfunction and athlete’s heart syndrome.

Assessing Noninvasive Delineation of Low-Voltage Zones Using ECG Imaging in Patients With Structural Heart Disease

OBJECTIVES

This study sought to assess the association between electrocardiographic imaging (ECGI) parameters and voltage from simultaneous electroanatomic mapping (EAM).

BACKGROUND

ECGI offers noninvasive assessment of electrophysiologic features relevant for mapping ventricular arrhythmia and its substrate, but the accuracy of ECGI in the delineation of scar is unclear.

METHODS

Sixteen patients with structural heart disease underwent simultaneous ECGI (CardioInsight, Medtronic) and contact EAM (CARTO, Biosense-Webster) during ventricular tachycardia catheter ablation, with 7 mapped epicardially. ECGI and EAM geometries were coregistered using anatomic landmarks. ECGI points were paired to the closest site on the EAM within 10 mm. The association between EAM voltage and ECGI features from reconstructed epicardial unipolar electrograms was assessed by mixed-effects regression models. The classification of low-voltage regions was performed using receiver-operating characteristic analysis.

RESULTS

A total of 9,541 ECGI points (median: 596; interquartile range: 377-737 across patients) were paired to an EAM site. Epicardial EAM voltage was associated with ECGI features of signal fractionation and local repolarization dispersion (N = 7; P < 0.05), but they poorly classified sites with bipolar voltage of <1.5 mV or <0.5 mV thresholds (median area under the curve across patients: 0.50-0.62). No association was found between bipolar EAM voltage and low-amplitude reconstructed epicardial unipolar electrograms or ECGI-derived bipolar electrograms. Similar results were found in the combined cohort (n = 16), including endocardial EAM voltage compared to epicardial ECGI features (n = 9).

CONCLUSIONS

Despite a statistically significant association between ECGI features and EAM voltage, the accuracy of the delineation of low-voltage zones was modest. This may limit ECGI use for pr-procedural substrate analysis in ventricular tachycardia ablation, but it could provide value in risk assessment for ventricular arrhythmias.

Association of Left Ventricular Tissue Heterogeneity and Intramyocardial Fat on Computed Tomography with Ventricular Arrhythmias in Ischemic Cardiomyopathy

Background

Gray zone, a measure of tissue heterogeneity on late gadolinium enhanced–cardiac magnetic resonance (LGE-CMR) imaging, has been shown to predict ventricular arrhythmias (VAs) in ischemic cardiomyopathy (ICM) patients. However, no studies have described whether left ventricular (LV) tissue heterogeneity and intramyocardial fat mass on contrast-enhanced computed tomography (CE-CT), which provides greater spatial resolution, is useful for assessing the risk of VAs in ICM patients with LV systolic dysfunction and no previous VAs.

Objective

The purpose of this proof-of-concept study was to determine the feasibility of measuring global LV tissue heterogeneity and intramyocardial fat mass by CE-CT for predicting the risk of VAs in ICM patients with LV systolic dysfunction and no previous history of VAs.

Methods

Patients with left ventricular ejection fraction ≤35% and no previous VAs were enrolled in a prospective, observational registry and underwent LGE-CMR. From this cohort, patients with ICM who additionally received CE-CT were included in the present analysis. Gray zone on LGE-CMR was defined as myocardium with signal intensity (SI) > peak SI of healthy myocardium but <50% maximal SI. Tissue heterogeneity on CE-CT was defined as the standard deviation of the Hounsfield unit image gradients (HU/mm) within the myocardium. Intramyocardial fat on CE-CT was identified as regions of image pixels between –180 and –5 HU. The primary outcome was VAs, defined as appropriate implantable cardioverter-defibrillator shock or sudden arrhythmic death.

Results

The study consisted of 47 ICM patients, 13 (27.7%) of whom experienced VA events during mean follow-up of 5.6 ± 3.4 years. Increasing tissue heterogeneity (per HU/mm) was significantly associated with VAs after multivariable adjustment, including for gray zone (odds ratio [OR] 1.22; P = .019). Consistently, patients with tissue heterogeneity values greater than or equal to the median (≥22.2 HU/mm) had >13-fold significantly increased risk of VA events, relative to patients with values lower than the median, after multivariable adjustment that included gray zone (OR 13.13; P = .028). The addition of tissue heterogeneity to gray zone improved prediction of VAs (area under receiver operating characteristic curve increased from 0.815 to 0.876). No association was found between intramyocardial fat mass on CE-CT and VAs (OR 1.00; P = .989).

Conclusion

In ICM patients, CE-CT–derived LV tissue heterogeneity was independently associated with VAs and may represent a novel marker useful for risk stratification.

Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart

Sudden cardiac death from arrhythmia is a major cause of mortality worldwide. Here, we develop a novel deep learning (DL) approach that blends neural networks and survival analysis to predict patient-specific survival curves from contrast-enhanced cardiac magnetic resonance images and clinical covariates for patients with ischemic heart disease. The DL-predicted survival curves offer accurate predictions at times up to 10 years and allow for estimation of uncertainty in predictions. The performance of this learning architecture was evaluated on multi-center internal validation data and tested on an independent test set, achieving concordance index of 0.83 and 0.74, and 10-year integrated Brier score of 0.12 and 0.14. We demonstrate that our DL approach with only raw cardiac images as input outperforms standard survival models constructed using clinical covariates. This technology has the potential to transform clinical decision-making by offering accurate and generalizable predictions of patient-specific survival probabilities of arrhythmic death over time.

Arrhythmic risk stratification in ischemic, non-ischemic and hypertrophic cardiomyopathy: A two-step multifactorial, electrophysiology study inclusive approach

Annual arrhythmic sudden cardiac death ranges from 0.6% to 4% in ischemic cardiomyopathy (ICM), 1% to 2% in non-ischemic cardiomyopathy (NICM), and 1% in hypertrophic cardiomyopathy (HCM). Towards a more effective arrhythmic risk stratification (ARS) we hereby present a two-step ARS with the usage of seven non-invasive risk factors: Late potentials presence (≥ 2/3 positive criteria), premature ventricular contractions (≥ 30/h), non-sustained ventricular tachycardia (≥ 1episode/24 h), abnormal heart rate turbulence (onset ≥ 0% and slope ≤ 2.5 ms) and reduced deceleration capacity (≤ 4.5 ms), abnormal T wave alternans (≥ 65μV), decreased heart rate variability (SDNN < 70ms), and prolonged QT_c interval (> 440 ms in males and > 450 ms in females) which reflect the arrhythmogenic mechanisms for the selection of the intermediate arrhythmic risk patients in the first step. In the second step, these intermediate-risk patients undergo a programmed ventricular stimulation (PVS) for the detection of inducible, truly high-risk ICM and NICM patients, who will benefit from an implantable cardioverter defibrillator. For HCM patients, we also suggest the incorporation of the PVS either for the low HCM Risk-score patients or for the patients with one traditional risk factor in order to improve the inadequate sensitivity of the former and the low specificity of the latter.

Quantification of myocardial fibrosis using noninvasive T2-mapping magnetic resonance imaging: Preclinical models of aging and pressure overload

Noninvasive imaging of cardiac fibrosis is important for early diagnosis and intervention in chronic heart diseases. Here, we investigated whether noninvasive, contrast agent-free MRI T₂ -mapping can quantify myocardial fibrosis in preclinical models of aging and pressure overload. Myocardial fibrosis and remodeling were analyzed in two animal models: (i) aging (15-month-old male CF-1 mice vs. young 6- to 8-week-old mice), and (ii) pressure overload (PO; by transverse aortic constriction in 4- to 5-month-old male C57BL/6 mice vs. sham-operated for 14 days). In vivo T₂ -mapping was performed by acquiring data during the isovolumic and early diastolic phases, with a modified respiratory and ECG-triggered multiecho TurboRARE sequence on a 7-T MRI. Cine MRI provided cardiac morphology and function. A quantitative segmentation method was developed to analyze the in vivo T₂ -maps of hearts at midventricle, apex, and basal regions. The cardiac fibrosis area was analyzed ex vivo by picro sirius red (PSR) staining. Both aged and pressure-overloaded hearts developed significant myocardial contractile dysfunction, cardiac hypertrophy, and interstitial fibrosis. The aged mice had two phenotypes, fibrotic and mild-fibrotic. Notably, the aged fibrotic subgroup and the PO mice showed a marked decrease in T₂ relaxation times (25.3 ± 0.6 in aged vs. 29.9 ± 0.7 ms in young mice, p = 0.002; and 24.3 ± 1.7 in PO vs. 28.7 ± 0.7 ms in shams, p = 0.05). However, no significant difference in T₂ was detected between the aged mild-fibrotic subgroup and the young mice. Accordingly, an inverse correlation between myocardial fibrosis percentage (FP) and T₂ relaxation time was derived (R²  = 0.98): T₂ (ms) = 30.45 - 1.05 × FP. Thus, these results demonstrate a statistical agreement between T₂ -map-quantified fibrosis and PSR staining in two different clinically relevant animal models. In conclusion, T₂ -mapping MRI is a promising noninvasive contrast agent-free quantitative technique to characterize myocardial fibrosis.

Myocardial Fibrosis Predicts Ventricular Arrhythmias and Sudden Death After Cardiac Electronic Device Implantation

BACKGROUND

Increasing evidence supports a link between myocardial fibrosis (MF) and ventricular arrhythmias.

OBJECTIVES

The purpose of this study was to determine whether presence of myocardial fibrosis on visual assessment (MFVA) and gray zone fibrosis (GZF) mass predicts sudden cardiac death (SCD) and ventricular fibrillation/sustained ventricular tachycardia after cardiac implantable electronic device (CIED) implantation.

METHODS

In this prospective study, total fibrosis and GZF mass, quantified using cardiovascular magnetic resonance, was assessed in relation to the primary endpoint of SCD and the secondary, arrhythmic endpoint of SCD or ventricular arrhythmias after CIED implantation.

RESULTS

Among 700 patients (age 68.0 ± 12.0 years), 27 (3.85%) experienced a SCD and 121 (17.3%) met the arrhythmic endpoint over median 6.93 years (IQR: 5.82-9.32 years). MFVA predicted SCD (HR: 26.3; 95% CI: 3.7-3,337; negative predictive value: 100%). In competing risk analyses, MFVA also predicted the arrhythmic endpoint (subdistribution HR: 19.9; 95% CI: 6.4-61.9; negative predictive value: 98.6%). Compared with no MFVA, a GZF mass measured with the 5SD method (GZF5SD) >17 g was associated with highest risk of SCD (HR: 44.6; 95% CI: 6.12-5,685) and the arrhythmic endpoint (subdistribution HR: 30.3; 95% CI: 9.6-95.8). Adding GZF5SD mass to MFVA led to reclassification of 39% for SCD and 50.2% for the arrhythmic endpoint. In contrast, LVEF did not predict either endpoint.

CONCLUSIONS

In CIED recipients, MFVA excluded patients at risk of SCD and virtually excluded ventricular arrhythmias. Quantified GZF5SD mass added predictive value in relation to SCD and the arrhythmic endpoint.

Kidney function and the risk of sudden cardiac death in the general population

Background

Chronic kidney disease increases sudden cardiac death (SCD) risk, but the association between kidney function and SCD in a general population is largely unknown. Therefore, we investigated the association between kidney function and SCD in a general middle-aged and elderly population.

Methods

We included individuals aged ≥45 years from a prospective population-based cohort study. The association between kidney function assessments [estimated glomerular filtration rate based on serum creatinine (eGFRcreat), cystatin C (eGFRcys) or both (eGFRcreat-cys)] and SCD was investigated using Cox proportional-hazards and joint models. Absolute 10-year risks were computed using competing risk analyses. Mediation analyses were performed using a four-way decomposition method.

Results

We included 9687 participants (median follow-up 8.9 years; mean age 65.3 years; 56.7% women; 243 SCD cases). Lower eGFRcys and eGFRcreat-cys were associated with increased SCD risk [hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.12–1.34 and HR 1.17, 95% CI 1.06–1.29, per 10 mL/min/1.73 m² eGFR decrease]. A significant trend (P = 0.001) across eGFRcys categories was found, with an HR of 2.11 (95% CI 1.19–3.74) for eGFRcys <60 compared with eGFRcys >90 mL/min/1.73 m². Comparing eGFRcys of 90 to 60 mL/min/1.73 m², absolute 10-year risk increased from 1.0% to 2.5%. Identified subgroups at increased risk included older participants and participants with atrial fibrillation. The associations were not mediated by coronary heart disease, hypertension or diabetes.

Conclusions

Reduced kidney function is associated with increased SCD risk in the general population, especially with eGFRcys. eGFRcys could be added to prediction models and screening programmes for SCD prevention.

Effect of implantable cardioverter-defibrillators in patients with non-ischaemic systolic heart failure and concurrent coronary atherosclerosis

Aims

Prophylactic implantable cardioverter‐defibrillators (ICD) reduce mortality in patients with ischaemic heart failure (HF), whereas the effect of ICD in patients with non‐ischaemic HF is less clear. We aimed to investigate the association between concomitant coronary atherosclerosis and mortality in patients with non‐ischaemic HF and the effect of ICD implantation in these patients.

Methods and results

Patients were included from DANISH (Danish Study to Assess the Efficacy of Implantable Cardioverter Defibrillators in Patients with Non‐Ischaemic Systolic Heart Failure on Mortality), randomizing patients to ICD or control. Study inclusion criteria for HF were left ventricular ejection fraction ≤ 35% and increased levels (>200 pg/mL) of N‐terminal pro‐brain natriuretic peptide. Of the 1116 patients from DANISH, 838 (75%) patients had available data from coronary angiogram and were included in this subgroup analysis. We used Cox regression to assess the relationship between coronary atherosclerosis and mortality and the effect of ICD implantation. Of the included patients, 266 (32%) had coronary atherosclerosis. Of these, 216 (81%) had atherosclerosis without significant stenoses, and 50 (19%) had significant stenosis. Patients with atherosclerosis were significantly older {67 [interquartile range (IQR) 61–73] vs. 61 [IQR 54–68] years; P < 0.0001}, and more were men (77% vs. 70%; P = 0.03). During a median follow‐up of 64.3 months (IQR 47–82), 174 (21%) of the patients died. The effect of ICD on all‐cause mortality was not modified by coronary atherosclerosis [hazard ratio (HR) 0.94; 0.58–1.52; P = 0.79 vs. HR 0.82; 0.56–1.20; P = 0.30], P for interaction = 0.67. In univariable analysis, coronary atherosclerosis was a significant predictor of all‐cause mortality [HR, 1.41; 95% confidence interval (CI), 1.04–1.91; P = 0.03]. However, this association disappeared when adjusting for cardiovascular risk factors (age, gender, diabetes, hypertension, smoking, and estimated glomerular filtration rate) (HR 1.05, 0.76–1.45, P = 0.76).

Conclusions

In patients with non‐ischaemic systolic heart failure, ICD implantation did not reduce all‐cause mortality in patients either with or without concomitant coronary atherosclerosis. The concomitant presence of coronary atherosclerosis was associated with increased mortality. However, this association was explained by other risk factors.

Nonsustained Ventricular Tachycardia Is Independently Associated With Sustained Ventricular Arrhythmias in Nonischemic Dilated Cardiomyopathy

BACKGROUND

Spontaneous nonsustained ventricular tachycardia (NSVT) on Holter, VT inducibility during electrophysiology study, and late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) have been associated with sustained ventricular arrhythmias (SVAs) in nonischemic dilated cardiomyopathy (DCM). This study aimed to analyze whether these parameters carry independent prognostic value for spontaneous SVA in DCM.

METHODS

Between 2011 and 2018, patients with the DCM clinical spectrum and documented SVA, suspected SVA, or considered to be at intermediate or high risk for SVA were enrolled in the prospective Leiden Nonischemic Cardiomyopathy Study. Patients underwent a comprehensive evaluation including 24-hour Holter, LGE-CMR, and electrophysiology study. Holters were assessed for the presence of NSVT (≥3 beats; rate, ≥120 bpm; lasting <30 s) and NSVT characteristics (coupling interval, duration, cycle length, morphology, regularity). Patients were followed at 6 to 12 monthly intervals.

RESULTS

Of all 115 patients (age, 59±12 years; 77% men; left ventricular ejection fraction, 33±13%; history of SVA, 36%; LGE in 63%; median LGE mass, 13 g; interquartile range, 8-23 g), 62 (54%) had NSVT on Holter, and sustained monomorphic VT was inducible in 34 of 114 patients (30%). NSVT was not associated with LGE on CMR or VT inducibility during electrophysiology study nor were its features (all P>0.05). During 4.0±1.8 years of follow-up, SVA occurred in 39 patients (34%). NSVT (HR, 4.47 [95% CI, 1.87-10.72]; P=0.001) and VT inducibility (HR, 3.08 [95% CI, 1.08-8.81]; P=0.036) were independently associated with SVA during follow-up. A bivariable model including only noninvasively acquired parameters also allowed identification of a high-risk subgroup (ie, those with both NSVT and LGE on CMR). The findings remained similar when only patients without prior SVA were included.

CONCLUSIONS

In patients with DCM, NSVT on Holter and VT inducibility during electrophysiology study predict SVA during follow-up independent of LGE on CMR. NSVTs may serve as an initiator, and sustained VT inducibility indicates the presence of the substrate for SVA in DCM. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01940081.

Anatomically informed deep learning on contrast-enhanced cardiac magnetic resonance imaging for scar segmentation and clinical feature extraction

Background

Visualizing fibrosis on cardiac magnetic resonance (CMR) imaging with contrast enhancement (late gadolinium enhancement; LGE) is paramount in characterizing disease progression and identifying arrhythmia substrates. Segmentation and fibrosis quantification from LGE-CMR is intensive, manual, and prone to interobserver variability. There is an unmet need for automated LGE-CMR image segmentation that ensures anatomical accuracy and seamless extraction of clinical features.

Objective

This study aimed to develop a novel deep learning solution for analysis of contrast-enhanced CMR images that produces anatomically accurate myocardium and scar/fibrosis segmentations and uses these to calculate features of clinical interest.

Methods

Data sources were 155 2-dimensional LGE-CMR patient scans (1124 slices) and 246 synthetic "LGE-like" scans (1360 slices) obtained from cine CMR using a novel style-transfer algorithm. We trained and tested a 3-stage neural network that identified the left ventricle (LV) region of interest (ROI), segmented ROI into viable myocardium and regions of enhancement, and postprocessed the segmentation results to enforce conforming to anatomical constraints. The segmentations were used to directly compute clinical features, such as LV volume and scar burden.

Results

Predicted LV and scar segmentations achieved 96% and 75% balanced accuracy, respectively, and 0.93 and 0.57 Dice coefficient when compared to trained expert segmentations. The mean scar burden difference between manual and predicted segmentations was 2%.

Conclusion

We developed and validated a deep neural network for automatic, anatomically accurate expert-level LGE- CMR myocardium and scar/fibrosis segmentation, allowing direct calculation of clinical measures. Given the training set heterogeneity, our approach could be extended to multiple imaging modalities and patient pathologies.

Non-contact whole-chamber charge density mapping of the left ventricle: preclinical evaluation in a sheep model

BACKGROUND

Conventional contact-based electroanatomic mapping is poorly suited for rapid or dynamic ventricular arrhythmias. Whole-chamber charge density (CD) mapping could efficiently characterize complex ventricular tachyarrhythmias and yield insights into their underlying mechanisms.

OBJECTIVE

This study sought to evaluate the feasibility and accuracy of non-contact whole-chamber left ventricular (LV) CD mapping, and to characterize CD activation patterns during sinus rhythm, ventricular pacing, and ventricular fibrillation (VF).

METHODS

Ischemic scar as defined by CD amplitude thresholds was compared to late gadolinium enhancement criteria on magnetic resonance imaging using an iterative closest point algorithm. Electrograms recorded at sites of tissue contact were compared to the nearest non-contact CD-derived electrograms to calculate signal morphology cross-correlations and time differences. Regions of consistently slow conduction were examined relative to areas of scar and to localized irregular activation (LIA) during VF.

RESULTS

Areas under receiver operating characteristic curves (AUCs) of CD-defined dense and total LV scar were 0.92 ± 0.03 and 0.87 ± 0.06, with accuracies of 0.86±0.03 and 0.80±0.05, respectively. Morphology cross-correlation between 8,677 contact and corresponding non-contact electrograms was 0.93±0.10, with a mean time difference of 2.5±5.6 msec. Areas of consistently slow conduction tended to occur at scar borders and exhibited spatial agreement with LIA during VF (AUC 0.90±0.02).

CONCLUSION

Non-contact LV CD mapping can accurately delineate ischemic scar. CD-derived ventricular electrograms correlate strongly with conventional contact-based electrograms. Regions with consistently slow conduction are often at scar borders and tend to harbor LIA during VF.

Magnetic Resonance Texture Analysis in Myocardial Infarction

Texture analysis (TA) is a newly arisen field that can detect the invisible MRI signal changes among image pixels. Myocardial infarction (MI) is cardiomyocyte necrosis caused by myocardial ischemia and hypoxia, becoming the primary cause of death and disability worldwide. In recent years, various TA studies have been performed in patients with MI and show a good clinical application prospect. This review briefly presents the main pathogenesis and pathophysiology of MI, introduces the overview and workflow of TA, and summarizes multiple magnetic resonance TA (MRTA) clinical applications in MI. We also discuss the facing challenges currently for clinical utilization and propose the prospect.

Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm

BACKGROUND

Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium enhancement sequences (2D-SSLGE). The aim of the study is to assess the feasibility and comparison of 2D-MSLGE reconstructed with artificial intelligence reconstruction deep learning noise reduction (NR) algorithm compared to standard 2D-SSLGE in consecutive patients with ischemic cardiomyopathy (ICM).

METHODS

Fifty-seven patients with known ICM referred for a clinically indicated CMR were enrolled in this study. 2D-MSLGE were reconstructed using a growing level of NR (0%,25%,50%,75%and 100%). Subjective image quality, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were evaluated in each dataset and compared to standard 2D-SSLGE. Moreover, diagnostic accuracy, LGE mass and scan time were compared between 2D-MSLGE with NR and 2D-SSLGE.

RESULTS

The application of NR reconstruction ≥50% to 2D-MSLGE provided better subjective image quality, CNR and SNR compared to 2D-SSLGE (p < 0.01). The best compromise in terms of subjective and objective image quality was observed for values of 2D-MSLGE 75%, while no differences were found in terms of LGE quantification between 2D-MSLGE versus 2D-SSLGE, regardless the NR applied. The sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 2D-MSLGE NR 75% were 87.77%,96.27%,96.13%,88.16% and 94.22%, respectively. Time of acquisition of 2D-MSLGE was significantly shorter compared to 2D-SSLGE (p < 0.01).

CONCLUSION

When compared to standard 2D-SSLGE, the application of NR reconstruction to 2D-MSLGE provides superior image quality with similar diagnostic accuracy.

Spatial dispersion analysis of LGE-CMR for prediction of ventricular arrhythmias in patients with cardiac sarcoidosis

BACKGROUND

Patients with cardiac sarcoidosis (CS) are at increased risk of life-threatening ventricular arrhythmias (VA). Current approaches to risk stratification have limited predictive value.

OBJECTIVES

To assess the utility of spatial dispersion analysis of late gadolinium enhancement cardiac magnetic resonance (LGE-CMR), as a quantitative measure of myocardial tissue heterogeneity, in risk stratifying patients with CS for VA and death.

METHODS

Sixty two patients with CS underwent LGE-CMR. LGE images were segmented and dispersion maps of the left and right ventricles were generated as follows. Based on signal intensity (SI), each pixel was categorized as abnormal (SI ≥3SD above the mean), intermediate (SI 1-3 SD above the mean) or normal (SI <1SD above the mean); and each pixel was then assigned a value of 0 to 8 based on the number of adjacent pixels of a different category. Average dispersion score was calculated for each patient. The primary endpoint was VA during follow up. The composite of VA or death was assessed as a secondary endpoint.

RESULTS

During 4.7 ± 3.5 years of follow up, six patients had VA, and five without documented VA died. Average dispersion score was significantly higher in patients with VA versus those without (0.87 ± 0.08 vs. 0.71 ± 0.16; p = .002) and in patients with events versus those without (0.83 ± 0.08 vs. 0.70 ± 0.16; p = .003). Patients at higher tertiles of dispersion score had a higher incidence of VA (p = .03) and the composite of VA or death (p = .01).

CONCLUSIONS

Increased substrate heterogeneity, quantified by spatial dispersion analysis of LGE-CMR, may be helpful in risk-stratifying patients with CS for adverse events, including life-threatening arrhythmias.

Calcium dysregulation increases right ventricular outflow tract arrhythmogenesis in rabbit model of chronic kidney disease

Chronic kidney disease (CKD) increases the risk of arrhythmia. The right ventricular outflow tract (RVOT) is a crucial site of ventricular tachycardia (VT) origination. We hypothesize that CKD increases RVOT arrhythmogenesis through its effects on calcium dysregulation. We analysed measurements obtained using conventional microelectrodes, patch clamp, confocal microscopy, western blotting, immunohistochemical examination and lipid peroxidation for both control and CKD (induced by 150 mg/kg neomycin and 500 mg/kg cefazolin daily) rabbit RVOT tissues or cardiomyocytes. The RVOT of CKD rabbits exhibited a short action potential duration, high incidence of tachypacing (20 Hz)‐induced sustained VT, and long duration of isoproterenol and tachypacing‐induced sustained and non‐sustained VT. Tachypacing‐induced sustained and non‐sustained VT in isoproterenol‐treated CKD RVOT tissues were attenuated by KB‐R7943 and partially inhibited by KN93 and H89. The CKD RVOT myocytes had high levels of phosphorylated CaMKII and PKA, and an increased expression of tyrosine hydroxylase‐positive neural density. The CKD RVOT myocytes exhibited large levels of I_to, I_Kr, NCX and L‐type calcium currents, calcium leak and malondialdehyde but low sodium current, SERCA2a activity and SR calcium content. The RVOT in CKD with oxidative stress and autonomic neuron hyperactivity exhibited calcium handling abnormalities, which contributed to the induction of VT.

Cardiac Magnetic Resonance Tissue Characterization in Ischemic Cardiomyopathy

Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of myocardial abnormalities in acute and chronic settings. Myocardial edema, microvascular obstruction (MVO), intracardiac thrombus, intramyocardial hemorrhage, and late gadolinium enhancement of the myocardium are easily depicted using standard CMR sequences. In the acute setting, tissue characterization is mainly focused on assessment of ventricular thrombus and MVO, which are associated with poor prognosis. Conversely, in chronic ICM, it is important to depict late gadolinium enhancement and myocardial ischemia using stress perfusion sequences. Overall, with CMR's ability to accurately characterize myocardial tissue in acute and chronic ICM, it represents a valuable diagnostic and prognostic imaging method for treatment planning. In particular, tissue characterization abnormalities in the acute setting can provide information regarding the patients that may develop major adverse cardiac event and show the presence of ventricular thrombus; in the chronic setting, evaluation of viable myocardium can be fundamental for planning myocardial revascularization. In this review, the main findings on tissue characterization are illustrated in acute and chronic settings using qualitative and quantitative tissue characterization.

Myocardial Scar Characterization and Future Ventricular Arrhythmia in Patients With Ischemic Cardiomyopathy and an Implantable Cardioverter-Defibrillator

Background: Implantable cardioverter-defibrillator (ICD) therapy is associated with several deleterious effects, which can be reduced by antiarrhythmic drugs or catheter ablation. However, it is largely unknown which patients might benefit from these therapies. Therefore, this study aimed to investigate whether myocardial scar characterization improves risk stratification for ventricular arrhythmia (VA) occurrence in patients with ischemic cardiomyopathy and an ICD.

Methods: In this study, 82 patients with ischemic cardiomyopathy who received an ICD were enrolled retrospectively. Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) images were analyzed using an investigational software tool to obtain quantitative data regarding the total scar, core, and border zone (BZ). Data regarding the QRS complex was obtained from electrocardiography (ECG). The primary endpoint was appropriate ICD therapy.

Results: During a median follow-up duration of 3.98 years [interquartile range (IQR) 2.89–5.14 years], appropriate therapy occurred in 24 (29.3%) patients. Patients with appropriate ICD therapy had a significantly larger total scar mass [60.0 (IQR 41.2–73.4) vs. 43.3 (IQR 31.2–61.2) g; P = 0.009] and BZ mass [32.9 (IQR 26.9–42.4) vs. 24.5 (IQR 18.8–32.5) g; P = 0.001] than those without appropriate therapy. In multivariable Cox regression analyses, total scar mass [hazard ratio (HR) 1.02 [95% confidence interval (CI) 1.00–1.04]; P = 0.014] and BZ mass (HR 1.04 [95% CI 1.01–1.07]; P = 0.009) independently predicted appropriate ICD therapy. Core mass and the QRS complex, however, were not significantly associated with the primary endpoint.

Conclusion: LGE-CMR-based, but not ECG-based myocardial scar characterization improves risk stratification for VA occurrence in patients with ischemic cardiomyopathy who received an ICD.

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35

AIMS

To determine whether myocardial fibrosis and greyzone fibrosis (GZF) on cardiovascular magnetic resonance (CMR) is associated with ventricular arrhythmias in patients with coronary artery disease (CAD) and a left ventricular ejection fraction (LVEF) >35%.

METHODS AND RESULTS

In this retrospective study of CAD patients, GZF mass using the 3SD method (GZF3SD) and total fibrosis mass using the 2SD method (TF2SD) on CMR were assessed in relation to the primary, combined endpoint of sudden cardiac death, ventricular tachycardia, ventricular fibrillation, or resuscitated cardiac arrest. Among 701 patients [age: 65.8 ± 12.3 years (mean ± SD)], 28 (3.99%) patients met the primary endpoint over 5.91 years (median; interquartile range 4.42-7.64). In competing risks analysis, a GZF3SD mass ≥5.0 g was strongly associated with the primary endpoint [subdistribution hazard ratio (sHR): 17.4 (95% confidence interval, CI 6.64-45.5); area under receiver operator characteristic curve (AUC): 0.85, P < 0.001]. A weaker association was observed for TF2SD mass ≥23 g [sHR 10.4 (95% CI 4.22-25.8); AUC: 0.80, P < 0.001]. The range of sHRs for GZF3SD mass (1-527) was wider than for TF2SD mass (1-37.6).

CONCLUSIONS

In CAD patients with an LVEF >35%, GZF3SD mass was strongly associated with the arrhythmic endpoint. These findings hold promise for its use in identifying patients with CAD and an LVEF >35% at risk of arrhythmic events.

Myocardial Work, an Echocardiographic Measure of Post Myocardial Infarct Scar on Contrast-Enhanced Cardiac Magnetic Resonance

This study investigates the relation of non-invasive myocardial work and myocardial viability following ST-segment elevation myocardial infarction (STEMI) assessed on late gadolinium contrast enhanced cardiac magnetic resonance (LGE CMR) and characterizes the remote zone using non-invasive myocardial work parameters. STEMI patients who underwent primary percutaneous coronary intervention (PCI) were included. Several non-invasive myocardial work parameters were derived from speckle tracking strain echocardiography and sphygmomanometric blood pressure, e.g.: myocardial work index (MWI), constructive work (CW), wasted work (WW) and myocardial work efficiency (MWE). LGE was quantified to determine infarct transmurality and scar burden. The core zone was defined as the segment with the largest extent of transmural LGE and the remote zone as the diametrically opposed segment without LGE. A total of 53 patients (89% male, mean age 58 ± 9 years) and 689 segments were analyzed. The mean scar burden was 14 ± 7% of the total LV mass, and 76 segments (11%) demonstrated transmural hyperenhancement, 280 (41%) non-transmural hyperenhancement and 333 (48%) no LGE. An inverse relation was observed between segmental MWI, CW and MWE and infarct transmurality (p < 0.05). MWI, CW and MWE were significantly lower in the core zone compared to the remote zone (p<0.05). In conclusion, non-invasive myocardial work parameters may serve as potential markers of segmental myocardial viability in post-STEMI patients who underwent primary PCI. Non-invasive myocardial work can also be utilized to characterize the remote zone, which is an emerging prognostic marker as well as a therapeutic target.

Characterization of the Electrophysiologic Remodeling of Patients With Ischemic Cardiomyopathy by Clinical Measurements and Computer Simulations Coupled With Machine Learning

Rationale

Patients with ischemic cardiomyopathy (ICMP) are at high risk for malignant arrhythmias, largely due to electrophysiological remodeling of the non-infarcted myocardium. The electrophysiological properties of the non-infarcted myocardium of patients with ICMP remain largely unknown.

Objectives

To assess the pro-arrhythmic behavior of non-infarcted myocardium in ICMP patients and couple computational simulations with machine learning to establish a methodology for the development of disease-specific action potential models based on clinically measured action potential duration restitution (APDR) data.

Methods and Results

We enrolled 22 patients undergoing left-sided ablation (10 ICMP) and compared APDRs between ICMP and structurally normal left ventricles (SNLVs). APDRs were clinically assessed with a decremental pacing protocol. Using genetic algorithms (GAs), we constructed populations of action potential models that incorporate the cohort-specific APDRs. The variability in the populations of ICMP and SNLV models was captured by clustering models based on their similarity using unsupervised machine learning. The pro-arrhythmic potential of ICMP and SNLV models was assessed in cell- and tissue-level simulations. Clinical measurements established that ICMP patients have a steeper APDR slope compared to SNLV (by 38%, p < 0.01). In cell-level simulations, APD alternans were induced in ICMP models at a longer cycle length compared to SNLV models (385–400 vs 355 ms). In tissue-level simulations, ICMP models were more susceptible for sustained functional re-entry compared to SNLV models.

Conclusion

Myocardial remodeling in ICMP patients is manifested as a steeper APDR compared to SNLV, which underlies the greater arrhythmogenic propensity in these patients, as demonstrated by cell- and tissue-level simulations using action potential models developed by GAs from clinical measurements. The methodology presented here captures the uncertainty inherent to GAs model development and provides a blueprint for use in future studies aimed at evaluating electrophysiological remodeling resulting from other cardiac diseases.

Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy—both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.

CMR-Based Risk Stratification of Sudden Cardiac Death and Use of Implantable Cardioverter-Defibrillator in Non-Ischemic Cardiomyopathy

Non-ischemic cardiomyopathy (NICM) is one of the most important entities for arrhythmias and sudden cardiac death (SCD). Previous studies suggest a lower benefit of implantable cardioverter–defibrillator (ICD) therapy in patients with NICM as compared to ischemic cardiomyopathy (ICM). Nevertheless, current guidelines do not differentiate between the two subgroups in recommending ICD implantation. Hence, risk stratification is required to determine the subgroup of patients with NICM who will likely benefit from ICD therapy. Various predictors have been proposed, among others genetic mutations, left-ventricular ejection fraction (LVEF), left-ventricular end-diastolic volume (LVEDD), and T-wave alternans (TWA). In addition to these parameters, cardiovascular magnetic resonance imaging (CMR) has the potential to further improve risk stratification. CMR allows the comprehensive analysis of cardiac function and myocardial tissue composition. A range of CMR parameters have been associated with SCD. Applicable examples include late gadolinium enhancement (LGE), T1 relaxation times, and myocardial strain. This review evaluates the epidemiological aspects of SCD in NICM, the role of CMR for risk stratification, and resulting indications for ICD implantation.

Ventricular arrhythmia risk is associated with myocardial scar but not with response to cardiac resynchronization therapy

AIMS

Sudden cardiac death (SCD) risk estimation in patients referred for cardiac resynchronization therapy (CRT) remains a challenge. By CRT-mediated improvement of left ventricular ejection fraction (LVEF), many patients loose indication for primary prevention implantable cardioverter-defibrillator (ICD). Increasing evidence shows the importance of myocardial scar for risk prediction. The aim of this study was to investigate the prognostic impact of myocardial scar depending on the echocardiographic response in patients undergoing CRT.

METHODS AND RESULTS

Patients with indication for CRT were prospectively enrolled. Decision about ICD or pacemaker implantation was based on clinical criteria. All patients underwent delayed-enhancement cardiac magnetic resonance imaging. Median follow-up duration was 45 (24-75) months. Primary outcome was a composite of sustained ventricular arrhythmia, appropriate ICD therapy, or SCD. A total of 218 patients with LVEF 25.5 ± 6.6% were analysed [158 (73%) male, 64.9 ± 10.7 years]. Myocardial scar was observed in 73 patients with ischaemic cardiomyopathy (ICM) (95% of ICM patients); in 62 with non-ischaemic cardiomyopathy (45% of these patients); and in all but 1 of 36 (17%) patients who reached the primary outcome. Myocardial scar was the only significant predictor of primary outcome [odds ratio 27.7 (3.8-202.7)], independent of echocardiographic CRT response. A total of 55 (25%) patients died from any cause or received heart transplant. For overall survival, only a combination of the absence of myocardial scar with CRT response was associated with favourable outcome.

CONCLUSION

Malignant arrhythmic events and SCD depend on the presence of myocardial scar but not on CRT response. All-cause mortality improved only with the combined absence of myocardial scar and CRT response.