Myocardial Fibrosis as a Predictor of Sudden Death in Patients With Coronary Artery Disease

Cellular and molecular mechanisms driving cardiac tissue fibrosis: On the precipice of personalized and precision medicine

Cardiac fibrosis is a significant contributor to heart failure, a condition that continues to affect a growing number of patients worldwide. Various cardiovascular comorbidities can exacerbate cardiac fibrosis. While fibroblasts are believed to be the primary cell type underlying fibrosis, recent and emerging data suggest that other cell types can also potentiate or expedite fibrotic processes. Over the past few decades, clinicians have developed therapeutics that can blunt the development and progression of cardiac fibrosis. While these strategies have yielded positive results, overall clinical outcomes for patients suffering from heart failure continue to be dire. Herein, we overview the molecular and cellular mechanisms underlying cardiac tissue fibrosis. To do so, we establish the known mechanisms that drive fibrosis in the heart, outline the diagnostic tools available, and summarize the treatment options used in contemporary clinical practice. Finally, we underscore the critical role the immune microenvironment plays in the pathogenesis of cardiac fibrosis.

Small extracellular vesicles associated miRNA in myocardial fibrosis

Myocardial fibrosis involves the loss of cardiomyocytes, myocardial fibroblast proliferation, and a reduction in angiogenesis, ultimately leading to heart failure, Given its significant implications, it is crucial to explore novel therapies for myocardial fibrosis. Recently one emerging avenue has been the use of small extracellular vesicles (sEV)-carried miRNA. In this review, we summarize the regulatory role of sEV-carried miRNA in myocardial fibrosis. We explored not only the potential diagnostic value of circulating miRNA as biomarkers for heart disease but also the therapeutic implications of sEV-carried miRNA derived from various cellular sources and applications of modified sEV. This exploration is paramount for researchers striving to develop innovative, cell-free therapies as potential drug candidates for the management of myocardial fibrosis.

Imaging of Cardiac Fibrosis: An Update, From the AJR Special Series on Imaging of Fibrosis

Myocardial fibrosis (MF) is defined as excessive production and deposition of extra-cellular matrix proteins that result in pathologic myocardial remodeling. Three types of MF have been identified: replacement fibrosis from tissue necrosis, reactive fibrosis from myocardial stress, and infiltrative interstitial fibrosis from progressive deposition of nondegradable material such as amyloid. Although echocardiography, nuclear medicine, and CT play important roles in the assessment of MF, MRI is pivotal in the evaluation of MF, with the late gadolinium enhancement (LGE) technique used as a primary end point. The LGE technique focuses on the pattern and distribution of gadolinium accumulation in the myocardium and assists in the diagnosis and establishment of the cause of both ischemic and nonischemic cardiomyopathy. LGE MRI also aids prognostication and risk stratification. In addition, LGE MRI is used to guide the management of patients considered for ablation for arrhythmias. Parametric mapping techniques, including T1 mapping and extracellular volume measurement, allow detection and quantification of diffuse fibrosis, which may not be detected by LGE MRI. These techniques also allow monitoring of disease progression and therapy response. This review provides an update on the imaging of MF, including prognostication and risk stratification tools, electrophysiologic considerations, and disease monitoring.

The Role of Artificial Intelligence in Cardiac Imaging

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

Histologically Validated Myocardial Fibrosis in Relation to Left Ventricular Geometry and Its Function in Aortic Stenosis

Background and Objectives: The combination of aortic valve stenosis (AS) and ischemic heart disease (IHD) is quite common and is associated with myocardial fibrosis (MF). The purpose of this study was to evaluate the association between the histologically verified left ventricular (LV) MF and its geometry and function in isolated AS and AS within IHD groups. Materials and Methods: In a single-center, prospective trial, 116 patients underwent aortic valve replacement (AVR) with/without concomitant surgery. The study population was divided into groups of isolated AS with/without IHD. Echocardiography was used, and LV measurements and aortic valve parameters were obtained from all patients. Myocardial tissue was procured from all study patients undergoing elective surgery. Results: There were no statistical differences between isolated AS and AS+IHD groups in LV parameters or systolic and diastolic functions during the study periods. The collagen volume fraction was significantly different between the isolated AS and AS+IHD groups and was 7.3 ± 5.6 and 8.3 ± 6.4, respectively. Correlations between MF and left ventricular end-diastolic diameter (LVEDD) (r = 0.59, p = < 0.001), left ventricular mass (LVM) (r = 0.42, p = 0.011), left ventricular ejection fraction (LVEF) (r = -0.67, p < 0.001) and an efficient orifice area (EOA) (r = 0.371, p = 0.028) were detected in isolated AS during the preoperative period; the same was observed for LVEDD (r = 0.45, p = 0.002), LVM (r = 0.36, p = 0.026), LVEF (r = -0.35, p = 0.026) and aortic annulus (r = 0.43, p = 0.018) in the early postoperative period; and LVEDD (r = 0.35, p ≤ 0.05), LVM (r = 0.43, p = 0.007) and EOA (r = 0.496, p = 0.003) in the follow-up period. In the group of AS and IHD, correlations were found only with LV posterior wall thickness (r = 0.322, p = 0.022) in the follow-up period. Conclusions: Histological MF in AS was correlated with LVM and LVEDD in all study periods. No correlations between MF and LV parameters were found in aortic stenosis in the ischemic heart disease group across all study periods.

Current experimental and early investigational agents for cardiac fibrosis: where are we at?

INTRODUCTION

Myocardial fibrosis (MF) is induced by factors activating pro-fibrotic pathways such as acute and prolonged inflammation, myocardial ischemic events, hypertension, aging process, and genetically-linked cardiomyopathies. Dynamics and characteristics of myocardial fibrosis development are very different. The broad range of myocardial fibrosis presentations suggests the presence of multiple potential targets.

AREA COVERED

Heart failure treatment involves medications primarily aimed at counteracting neurohormonal activation. While these drugs have demonstrated efficacy against MF, not all specifically target inflammation or fibrosis progression with some exceptions such as RAAS inhibitors. Consequently, new therapies are being developed to address this issue. This article is aimed to describe anti-fibrotic drugs currently employed in clinical practice and emerging agents that target specific pathways, supported by evidence from both preclinical and clinical studies.

EXPERT OPINION

Despite various preclinical findings suggesting the potential utility of new drugs and molecules for treating cardiac fibrosis in animal models, there is a notable scarcity of clinical trials investigating these effects. However, the pathology of damage and repair in the heart muscle involves a complex network of interconnected inflammatory pathways and various types of immune cells. Our comprehension of the positive and negative roles played by specific immune cells and cytokines is an emerging area of research.

SCMR expert consensus statement for cardiovascular magnetic resonance of patients with a cardiac implantable electronic device

Cardiovascular magnetic resonance (CMR) is a proven imaging modality for informing diagnosis and prognosis, guiding therapeutic decisions, and risk stratifying surgical intervention. Patients with a cardiac implantable electronic device (CIED) would be expected to derive particular benefit from CMR given high prevalence of cardiomyopathy and arrhythmia. While several guidelines have been published over the last 16 years, it is important to recognize that both the CIED and CMR technologies, as well as our knowledge in MR safety, have evolved rapidly during that period. Given increasing utilization of CIED over the past decades, there is an unmet need to establish a consensus statement that integrates latest evidence concerning MR safety and CIED and CMR technologies. While experienced centers currently perform CMR in CIED patients, broad availability of CMR in this population is lacking, partially due to limited availability of resources for programming devices and appropriate monitoring, but also related to knowledge gaps regarding the risk-benefit ratio of CMR in this growing population. To address the knowledge gaps, this SCMR Expert Consensus Statement integrates consensus guidelines, primary data, and opinions from experts across disparate fields towards the shared goal of informing evidenced-based decision-making regarding the risk-benefit ratio of CMR for patients with CIEDs.

Decellularized heart extracellular matrix alleviates activation of hiPSC-derived cardiac fibroblasts

Human induced pluripotent stem cell derived cardiac fibroblasts (hiPSC-CFs) play a critical role in modeling human cardiovascular diseases in vitro. However, current culture substrates used for hiPSC-CF differentiation and expansion, such as Matrigel and tissue culture plastic (TCPs), are tissue mismatched and may provide pathogenic cues. Here, we report that hiPSC-CFs differentiated on Matrigel and expanded on tissue culture plastic (M-TCP-iCFs) exhibit transcriptomic hallmarks of activated fibroblasts limiting their translational potential. To alleviate pathogenic activation of hiPSC-CFs, we utilized decellularized extracellular matrix derived from porcine heart extracellular matrix (HEM) to provide a biomimetic substrate for improving hiPSC-CF phenotypes. We show that hiPSC-CFs differentiated and expanded on HEM (HEM-iCFs) exhibited reduced expression of hallmark activated fibroblast markers versus M-TCP-iCFs while retaining their cardiac fibroblast phenotype. HEM-iCFs also maintained a reduction in expression of hallmark genes associated with pathogenic fibroblasts when seeded onto TCPs. Further, HEM-iCFs more homogenously integrated into an hiPSC-derived cardiac organoid model, resulting in improved cardiomyocyte sarcomere development. In conclusion, HEM provides an improved substrate for the differentiation and propagation of hiPSC-CFs for disease modeling.

Tools to differentiate between Filamin C and Titin truncating variant carriers: value of MRI

Whereas truncating variants of the giant protein Titin (TTNtv) are the main cause of familial dilated cardiomyopathy (DCM), recently Filamin C truncating variants (FLNCtv) were identified as a cause of arrhythmogenic cardiomyopathy (ACM). Our aim was to characterize and compare clinical and MRI features of TTNtv and FLNCtv in the Belgian population. In index patients referred for genetic testing of ACM/DCM, FLNCtv and TTNtv were found in 17 (3.6%) and 33 (12.3%) subjects, respectively. Further family cascade screening yielded 24 and 19 additional truncating variant carriers in FLNC and TTN, respectively. The main phenotype was ACM in FLNCtv carriers whereas TTNtv carriers showed either an ACM or DCM phenotype. Non-sustained Ventricular Tachycardia was frequent in both populations. MRI data, available in 28/40 FLNCtv and 32/52 TTNtv patients, showed lower Left Ventricular (LV) ejection fraction and lower LV strain in TTNtv patients (p < 0.01). Conversely, both the frequency (68% vs 22%) and extent of non-ischemic myocardial late gadolinium enhancement (LGE) was significantly higher in FLNCtv patients (p < 0.01). Hereby, ring-like LGE was found in 16/19 (84%) FLNCtv versus 1/7 (14%) of TTNtv patients (p < 0.01). In conclusion, a large number of FLNCtv and TTNtv patients present with an ACM phenotype but can be separated by cardiac MRI. Whereas FLNCtv patients often have extensive myocardial fibrosis, typically following a ring-like pattern, LV dysfunction without or limited replacement fibrosis is the common TTNtv phenotype.

Cardiac Fibrosis in heart failure: Focus on non-invasive diagnosis and emerging therapeutic strategies

Heart failure is a leading cause of mortality and hospitalization worldwide. Cardiac fibrosis, resulting from the excessive deposition of collagen fibers, is a common feature across the spectrum of conditions converging in heart failure. Eventually, either reparative or reactive in nature, in the long-term cardiac fibrosis contributes to heart failure development and progression and is associated with poor clinical outcomes. Despite this, specific cardiac antifibrotic therapies are lacking, making cardiac fibrosis an urgent unmet medical need. In this context, a better patient phenotyping is needed to characterize the heterogenous features of cardiac fibrosis to advance toward its personalized management. In this review, we will describe the different phenotypes associated with cardiac fibrosis in heart failure and we will focus on the potential usefulness of imaging techniques and circulating biomarkers for the non-invasive characterization and phenotyping of this condition and for tracking its clinical impact. We will also recapitulate the cardiac antifibrotic effects of existing heart failure and non-heart failure drugs and we will discuss potential strategies under preclinical development targeting the activation of cardiac fibroblasts at different levels, as well as targeting additional extracardiac processes.

Management of Ventricular Arrhythmias in Heart Failure

PURPOSE OF REVIEW

Despite substantial progress in medical and device-based heart failure (HF) therapy, ventricular arrhythmias (VA) and sudden cardiac death (SCD) remain a major challenge. Here we review contemporary management of VA in the context of HF with one particular focus on recent advances in imaging and catheter ablation.

RECENT FINDINGS

Besides limited efficacy of antiarrhythmic drugs (AADs), their potentially life-threatening side effects are increasingly acknowledged. On the other hand, with tremendous advances in catheter technology, electroanatomical mapping, imaging, and understanding of arrhythmia mechanisms, catheter ablation has evolved into a safe, efficacious therapy. In fact, recent randomized trials support early catheter ablation, demonstrating superiority over AAD. Importantly, CMR imaging with gadolinium contrast has emerged as a central tool for the management of VA complicating HF: CMR is not only essential for an accurate diagnosis of the underlying entity and subsequent treatment decisions, but also improves risk stratification for SCD prevention and patient selection for ICD therapy. Finally, 3-dimensional characterization of arrhythmogenic substrate by CMR and imaging-guided ablation approaches substantially enhance procedural safety and efficacy. VA management in HF patients is highly complex and should be addressed in a multidisciplinary approach, preferably at specialized centers. While recent evidence supports early catheter ablation of VA, an impact on mortality remains to be demonstrated. Moreover, risk stratification for ICD therapy may have to be reconsidered, taking into account imaging, genetic testing, and other parameters beyond left ventricular function.

Artificial Intelligence in Ventricular Arrhythmias and Sudden Death

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

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.

Valvular Cardiomyopathy in Aortic Valve Regurgitation Correlates with Myocardial Fibrosis

Objective: At the tissue level, disruption of the extracellular matrix network leads to irreversible cardiac fibrosis, which contributes to myocardial dysfunction. At the myocyte level, downregulation of beta-adrenoceptors (beta-AR) reduces adaptation to increased workload. The aim of our study was to analyse the correlation between myocardial fibrosis and beta-AR sensitivity in patients with aortic valve (AV) disease. Methods: A total of 92 consecutive patients who underwent elective AV surgery between 2017-2019 were included in our study (51 with aortic regurgitation (AR-group); 41 with aortic stenosis (AS-group) and left ventricular (LV) biopsies were obtained intraoperatively. In vitro force contractility testing was performed by measuring beta-AR sensitivity (-log EC₅₀[ISO]). In parallel, a quantitative analysis of myocardial fibrosis burden was performed. Results: Mean age at the time of AV surgery was not statistically different in both groups (AR: 53.3 ± 15.3 years vs. AS: 58.7 ± 17.0 years; p = 0.116). The LV end-diastolic diameter was significantly enlarged in the AR-group when compared to the AS-group (59.4 ± 15.6 vs. 39.7 ± 21.2; p < 0.001). Analysis of beta-AR sensitivity (AR: -6.769 vs. AS: -6.659; p = 0.316) and myocardial fibrosis (AR: 8.9% vs. AS: 11.3%; p = 0.284) showed no significant differences between patients with AS and AR. There was no correlation between myocardial fibrosis and beta-AR sensitivity in the whole study cohort (R = 0.1987; p = 0.100) or in the AS-subgroup (R = 0.009; p = 0.960). However, significant correlation of fibrosis and beta-AR sensitivity was seen in AR-patients (R = 0.363; p = 0.023). Conclusion: More severe myocardial fibrosis was associated with reduced beta-AR sensitivity in patients presenting with AR but not with AS. Therefore, our results suggest that in patients with AR, cellular myocardial dysfunction is present and correlates with the extent of myocardial fibrosis in the myocardium.

Sudden cardiac death in ischaemic heart disease: coronary thrombosis or myocardial fibrosis?

The mechanisms underlying sudden cardiac death (SCD) in patients with ischaemic heart disease (IHD) caused by coronary atherosclerosis are not yet clarified. For decades, acute coronary causes have been sought as the main triggers of SCD in these patients. In fact, angiographic and pathological studies in cardiac arrest survivors and SCD victims, respectively, consistently show that acute plaque events occur in ∼50% of SCD of patients with IHD. Among the acute events, plaque rupture and erosion triggering acute coronary thrombosis remain the main substrates; however, a significant percentage of plaque haemorrhage (20%) is identified by pathological studies. Its role in acute coronary thrombosis is unknown and deserves future intravascular imaging developments. In the remaining 50% of SCD, the atherosclerotic coronary disease shows the characteristics of structural stability. More recent studies have focused attention not only on the coronary tree and on the search for acute complications of atherosclerotic plaques but also on myocardial tissue, identifying replacement and patchy fibrosis as the most frequent findings in the post-mortem hearts of these patients, a feature followed by cardiac hypertrophy, as assessed by the heart weight, usually associated with fibrosis. The possibility of characterizing myocardial fibrosis in vivo, besides confirming the pathological data, now offers new risk stratification perspectives to prevent SCD in IHD, alongside the consolidated secondary prevention criteria based on left ventricular dysfunction.

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.

Endogenous assessment of late gadolinium enhancement grey zone in patients with non-ischaemic cardiomyopathy with T1ρ and native T1 mapping

AIMS

This study aims to validate and compare the feasibility of T1ρ and native longitudinal relaxation time (T1) mapping in detection of myocardial fibrosis in patients with non-ischaemic cardiomyopathy, focusing on the performance of both methods in identifying late gadolinium enhancement (LGE) grey zone.

METHODS AND RESULTS

Twenty-seven hypertrophic cardiomyopathy (HCM) patients, 16 idiopathic dilated cardiomyopathy (DCM) patients, and 18 healthy controls were prospectively enrolled for native T1 and T1ρ mapping imaging and then all the patients underwent enhancement scan for LGE extent and extracellular volume (ECV) values. In LGE positive patients, the LGE areas were divided into LGE core (6 SDs above remote myocardium) and grey zone (2-6 SDs above remote myocardium) according to the signal intensity of LGE. Both HCM and DCM patients showed significantly higher native T1 values and T1ρ values than controls no matter the presence of LGE (all P < 0.01). There were significant differences in native T1 and T1ρ values among four different types of myocardia (LGE core, grey zone, remote area and control, P < 0.0001). However, the T1ρ values of grey zone were significantly higher than control (P < 0.01), while the native T1 values were not (P = 0.089). T1ρ values were significantly associated with both native T1 values (r = 0.54, P < 0.001) and ECV values (r = 0.54, P < 0.001).

CONCLUSION

T1ρ mapping is a feasible method to detect myocardial fibrosis in patients with non-ischaemic cardiomyopathy no matter the presence of LGE. Compared with native T1, T1ρ may serve as a better discriminator in the identification of LGE grey zone.

Levocarnitine regulates the growth of angiotensin II-induced myocardial fibrosis cells via TIMP-1

This study aimed to explore the effects of tissue inhibitor of metalloproteinases-1 (TIMP-1) on levocarnitine (LC)-mediated regulation of angiotensin II (AngII)-induced myocardial fibrosis (MF) and its underlying mechanisms. H9C2 cells were treated with AngII for 24 h to induce fibrosis. The cells were then treated with LC or transfected with TIMP-1-OE plasmid/si‑TIMP-1. Cell apoptosis, viability, migration, and related gene expression were analyzed. AngII treatment significantly upregulated Axl, α-SMA, and MMP3 expression (P < 0.05) and downregulated STAT4 and TIMP1 expression (P < 0.05) relative to the control levels. After transfection, cells with TIMP-1 overexpression/knockdown were successfully established. Compared with that of the control, AngII significantly inhibited cell viability and cell migration while promoting cell apoptosis (P < 0.05). LC and TIMP-1-OE transfection further suppressed cell viability and migration induced by Ang II and upregulated apoptosis, whereas si-TIMP-1 had the opposite effect. Furthermore, LC and TIMP-1-OE transfection downregulated Axl, AT1R, α-SMA, collagen III, Bcl-2, and MMP3 expression caused by AngII and upregulated caspase 3, p53, and STAT4 expression, whereas si-TIMP-1 had the opposite effect. TIMP-1 is therefore a potential therapeutic target for delaying MF progression.

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.

Time Trend in Incidence of Sudden Cardiac Death After Percutaneous Coronary Intervention from 2009 to 2017 (from the Japanese Multicenter Registry)

The advances in the integrated management of patients with coronary artery disease undergoing percutaneous coronary intervention (PCI) have reduced subsequent cardiovascular events. Nonetheless, sudden cardiac death (SCD) remains a major concern. Therefore, we aimed to investigate the time trend in SCD incidence after PCI and to identify the clinical factors contributing to SCD. From a prospective, multicenter cohort registry in Japan, 8,723 consecutive patients with coronary artery disease undergoing PCI between 2009 and 2017 were included. We evaluated the SCD incidence 2 years after PCI; all death events were adjudicated, and SCD was defined as unexpected death without a noncardiovascular cause in a previously stable patient within 24 hours from the onset. The Fine and Gray method was used to identify the factors associated with SCD. Overall, the mean age of the patients was 68.3 ± 11.3 years, and 1,173 patients (13.4%) had heart failure (HF). During the study period, the use of second-generation drug-eluting stents increased. The 2-year cumulative incidence of all-cause mortality and SCD was 4.29% and 0.45%, respectively. All-cause mortality remained stable during the study period (p for trend = 0.98), whereas the crude incidence of SCD tended to decrease over the study period (p for trend = 0.052). HF was the strongest predictor associated with the risk of SCD (crude incidence [vs non-HF] 2.13% vs 0.19%; p <0.001). In conclusion, the incidence of SCD after PCI decreased over the last decade, albeit the high incidence of SCD among patients with HF remains concerning.

S-Doped carbonized polymer dots inhibit early myocardial fibrosis by regulating mitochondrial function

Myocardial fibrosis (MF) is a critical pathological lesion in the progression of various acute and chronic cardiovascular diseases. However, there is still a lack of clinically effective drugs and treatments for MF therapies. Herein, for the first time, we developed fluorescent sulfur-doped carbonized polymer dots (S-CPDs) as new nano-antioxidants to reduce the cardiomyocyte damage caused by reactive oxygen species (ROS) in the early stage of fibrotic lesions. In vitro results suggested that the pre-protection of S-CPDs significantly increased the survival rate of H9c2 cells under severe oxidative stress, inhibited the isoproterenol (ISO)-induced hypertrophy of myocardial cells through improving the content of mitochondria related proteins and adenosine triphosphate (ATP) in cells. Moreover, S-CPD administration could effectively decrease cardiac hypertrophy and promote heart function in MF rat models. The rapid internalization, high biocompatibility and fluorescence imaging potential of S-CPDs revealed their promising application prospects in the diagnoses and treatments of cardiovascular diseases.

Treatment of cardiac fibrosis: from neuro-hormonal inhibitors to CAR-T cell therapy

Cardiac fibrosis is characterized by the deposition of extracellular matrix proteins in the spaces between cardiomyocytes following both acute and chronic tissue damage events, resulting in the remodeling and stiffening of heart tissue. Fibrosis plays an important role in the pathogenesis of many cardiovascular disorders, including heart failure and myocardial infarction. Several studies have identified fibroblasts, which are induced to differentiate into myofibroblasts in response to various types of damage, as the most important cell types involved in the fibrotic process. Some drugs, such as inhibitors of the renin-angiotensin-aldosterone system, have been shown to be effective in reducing cardiac fibrosis. There are currently no drugs with primarily anti-fibrotic action approved for clinical use, as well as the evidence of a clinical efficacy of these drugs is extremely limited, despite the numerous encouraging results from experimental studies. A new approach is represented by the use of CAR-T cells engineered in vivo using lipid nanoparticles containing mRNA coding for a receptor directed against the FAP protein, expressed by cardiac myofibroblasts. This strategy has proved to be safe and effective in reducing myocardial fibrosis and improving cardiac function in mouse models of cardiac fibrosis. Clinical studies are required to test this novel approach in humans.

Scar border zone mass and presence of border zone channels assessed with cardiac magnetic resonance imaging are associated with ventricular arrhythmia in patients with ST-segment elevation myocardial infarction

AIMS

Late gadolinium enhancement cardiac magnetic resonance (CMR) permits characterization of left ventricular ischaemic scars. We aimed to evaluate if scar core mass, border zone (BZ) mass, and BZ channels are risk markers for subsequent ventricular arrhythmia (VA) in ST-segment elevation myocardial infarction (STEMI).

METHODS AND RESULTS

A sub-study of the DANish Acute Myocardial Infarction-3 multi-centre trial and Danegaptide phase II proof-of-concept clinical trial in which a total of 843 STEMI patients had a 3-month follow-up CMR. Of these, 21 patients subsequently experienced VA during 100 months of follow-up and were randomly matched 1:5 with 105 controls. A VA event was defined as: ventricular tachycardia, ventricular fibrillation, or sudden cardiac death. Ischaemic scar characteristics were automatically detected by specialized software. We included 126 patients with a median left ventricular ejection fraction of 51.0 ± 11.6% in cases with VA vs. 55.5 ± 8.5% in controls (P = 0.10). Cases had a larger mean BZ mass and more often BZ channels compared to controls [BZ mass: 17.2 ± 10.3 g vs. 10.3 ± 6.0 g; P = 0.0002; BZ channels: 17 (80%) vs. 44 (42%); P = 0.001]. A combination of ≥17.2 g BZ mass and the presence of BZ channels was five times more prevalent in cases vs. controls (P ≤ 0.00001) with an odds ratio of 9.40 (95% confidence interval 3.26-27.13; P ≤ 0.0001) for VA. This identified cases with 52% sensitivity and 90% specificity.

CONCLUSION(S)

Scar characterization with CMR indicates that a combination of ≥17.2 g BZ mass and the presence of BZ channels had the strongest association with subsequent VA in STEMI patients.

CLINICALTRIALS.GOV

Unique identifier: NCT01435408 (DANAMI 3-iPOST and DANAMI 3-DEFER), NCT01960933 (DANAMI 3-PRIMULTI), and NCT01977755 (Danegaptide).

Transcriptome and proteome profiling of activated cardiac fibroblasts supports target prioritization in cardiac fibrosis

BACKGROUND

Activated cardiac fibroblasts (CF) play a central role in cardiac fibrosis, a condition associated with most cardiovascular diseases. Conversion of quiescent into activated CF sustains heart integrity upon injury. However, permanence of CF in active state inflicts deleterious heart function effects. Mechanisms underlying this cell state conversion are still not fully disclosed, contributing to a limited target space and lack of effective anti-fibrotic therapies.

MATERIALS AND METHODS

To prioritize targets for drug development, we studied CF remodeling upon activation at transcriptomic and proteomic levels, using three different cell sources: primary adult CF (aHCF), primary fetal CF (fHCF), and induced pluripotent stem cells derived CF (hiPSC-CF).

RESULTS

All cell sources showed a convergent response upon activation, with clear morphological and molecular remodeling associated with cell-cell and cell-matrix interactions. Quantitative proteomic analysis identified known cardiac fibrosis markers, such as FN1, CCN2, and Serpine1, but also revealed targets not previously associated with this condition, including MRC2, IGFBP7, and NT5DC2.

CONCLUSION

Exploring such targets to modulate CF phenotype represents a valuable opportunity for development of anti-fibrotic therapies. Also, we demonstrate that hiPSC-CF is a suitable cell source for preclinical research, displaying significantly lower basal activation level relative to primary cells, while being able to elicit a convergent response upon stimuli.

Storax Attenuates Cardiac Fibrosis following Acute Myocardial Infarction in Rats via Suppression of AT1R-Ankrd1-P53 Signaling Pathway

Myocardial fibrosis following acute myocardial infarction (AMI) seriously affects the prognosis and survival rate of patients. This study explores the role and regulation mechanism of storax, a commonly used traditional Chinese medicine for treatment of cardiovascular diseases, on myocardial fibrosis and cardiac function. The AMI rat model was established by subcutaneous injection of Isoproterenol hydrochloride (ISO). Storax (0.1, 0.2, 0.4 g/kg) was administered by gavage once/d for 7 days. Electrocardiogram, echocardiography, hemodynamic and cardiac enzyme in AMI rats were measured. HE, Masson, immunofluorescence and TUNEL staining were used to observe the degree of pathological damage, fibrosis and cardiomyocyte apoptosis in myocardial tissue, respectively. Expression of AT1R, CARP and their downstream related apoptotic proteins were detected by WB. The results demonstrated that storax could significantly improve cardiac electrophysiology and function, decrease serum cardiac enzyme activity, reduce type I and III collagen contents to improve fibrosis and alleviate myocardial pathological damage and cardiomyocyte apoptosis. It also found that storax can significantly down-regulate expression of AT1R, Ankrd1, P53, P-p53 (ser 15), Bax and cleaved Caspase-3 and up-regulate expression of Mdm2 and Bcl-2. Taken together, these findings indicated that storax effectively protected cardiomyocytes against myocardial fibrosis and cardiac dysfunction by inhibiting the AT1R-Ankrd1-P53 signaling pathway.

Exosomes and Exosomal Cargos: A Promising World for Ventricular Remodeling Following Myocardial Infarction

Exosomes are a pluripotent group of extracellular nanovesicles secreted by all cells that mediate intercellular communications. The effective information within exosomes is primarily reflected in exosomal cargos, including proteins, lipids, DNAs, and non-coding RNAs (ncRNAs), the most intensively studied molecules. Cardiac resident cells (cardiomyocytes, fibroblasts, and endothelial cells) and foreign cells (infiltrated immune cells, cardiac progenitor cells, cardiosphere-derived cells, and mesenchymal stem cells) are involved in the progress of ventricular remodeling (VR) following myocardial infarction (MI) via transferring exosomes into target cells. Here, we summarize the pathological mechanisms of VR following MI, including cardiac myocyte hypertrophy, cardiac fibrosis, inflammation, pyroptosis, apoptosis, autophagy, angiogenesis, and metabolic disorders, and the roles of exosomal cargos in these processes, with a focus on proteins and ncRNAs. Continued research in this field reveals a novel diagnostic and therapeutic strategy for VR.

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.

Detection of myocardial fibrosis: Where we stand

Myocardial fibrosis, resulting from the disturbance of extracellular matrix homeostasis in response to different insults, is a common and important pathological remodeling process that is associated with adverse clinical outcomes, including arrhythmia, heart failure, or even sudden cardiac death. Over the past decades, multiple non-invasive detection methods have been developed. Laboratory biomarkers can aid in both detection and risk stratification by reflecting cellular and even molecular changes in fibrotic processes, yet more evidence that validates their detection accuracy is still warranted. Different non-invasive imaging techniques have been demonstrated to not only detect myocardial fibrosis but also provide information on prognosis and management. Cardiovascular magnetic resonance (CMR) is considered as the gold standard imaging technique to non-invasively identify and quantify myocardial fibrosis with its natural ability for tissue characterization. This review summarizes the current understanding of the non-invasive detection methods of myocardial fibrosis, with the focus on different techniques and clinical applications of CMR.

Plaque histology and myocardial disease in sudden coronary death: the Fingesture study

AIMS

At least 50% of deaths due to coronary artery disease (CAD) are sudden cardiac deaths (SCDs), but the role of acute plaque complications on the incidence of sudden death in CAD is somewhat unclear. The present study aimed to investigate plaque histology and concomitant myocardial disease in sudden coronary death.

METHODS AND RESULTS

The study population is derived from the Fingesture study, which has collected data from 5869 consecutive autopsy-verified SCD victims in Northern Finland (population ≈600 000) between 1998 and 2017. In this substudy, histological examination of culprit lesions was performed in 600 SCD victims whose death was due to CAD. Determination of the cause of death was based on the combination of medical records, police reports, and autopsy data. Plaque histology was classified as either (i) plaque rupture or erosion, (ii) intraplaque haemorrhage, or (iii) stable plaque. The mean age of the study subjects was 64.9 ± 11.2 years, and 82% were male. Twenty-four per cent had plaque rupture or plaque erosion, 24% had an intraplaque haemorrhage, and 52% had a stable plaque. Myocardial hypertrophy was present in 78% and myocardial fibrosis in 93% of victims. The presence of myocardial hypertrophy or fibrosis was not associated with specific plaque histology.

CONCLUSION

Less than half of sudden deaths due to CAD had evidence of acute plaque complication, an observation which is contrary to historical perceptions. The prevalence of concomitant myocardial disease was high and independent of associated plaque morphology.

Toward Better Risk Stratification for Implantable Cardioverter-Defibrillator Recipients: Implications of Explainable Machine Learning Models

Background: Current guideline-based implantable cardioverter-defibrillator (ICD) implants fail to meet the demands for precision medicine. Machine learning (ML) designed for survival analysis might facilitate personalized risk stratification. We aimed to develop explainable ML models predicting mortality and the first appropriate shock and compare these to standard Cox proportional hazards (CPH) regression in ICD recipients. Methods and Results: Forty-five routine clinical variables were collected. Four fine-tuned ML approaches (elastic net Cox regression, random survival forests, survival support vector machine, and XGBoost) were applied and compared with the CPH model on the test set using Harrell’s C-index. Of 887 adult patients enrolled, 199 patients died (5.0 per 100 person-years) and 265 first appropriate shocks occurred (12.4 per 100 person-years) during the follow-up. Patients were randomly split into training (75%) and test (25%) sets. Among ML models predicting death, XGBoost achieved the highest accuracy and outperformed the CPH model (C-index: 0.794 vs. 0.760, p < 0.001). For appropriate shock, survival support vector machine showed the highest accuracy, although not statistically different from the CPH model (0.621 vs. 0.611, p = 0.243). The feature contribution of ML models assessed by SHAP values at individual and overall levels was in accordance with established knowledge. Accordingly, a bi-dimensional risk matrix integrating death and shock risk was built. This risk stratification framework further classified patients with different likelihoods of benefiting from ICD implant. Conclusions: Explainable ML models offer a promising tool to identify different risk scenarios in ICD-eligible patients and aid clinical decision making. Further evaluation is needed.

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.

Protective effects and mechanisms of lycorine against adriamycin-induced cardiotoxicity

BACKGROUND

Adriamycin (ADR), a high-efficiency, broad-spectrum anthraquinone chemotherapeutic agent, is currently used to treat various malignant tumors and can lead to cumulative, dose-dependent, and irreversible cardiotoxicity. Lycorine (LYC) is a benzyl phenethylamine alkaloid that exerts remarkable therapeutic effects on cancers and sepsis.

PURPOSE

However, researchers have not yet elucidated whether LYC exerts protective effects against cardiotoxicity induced by ADR and the possible molecular mechanisms.

DESIGN

This study established ADR injury models in vitro and in vivo to explore the effects of LYC against cardiotoxicity induced by ADR. The effects of LYC on blood biochemical parameters, cardiac parameters and structure, ADR-related pathophysiological processes, and the SIRT1/PPARγ signal pathway in ADR-injured models, were analyzed using a series of experimental methods.

RESULTS

LYC significantly improved survival rate, blood biochemical parameters (LDH, CK, and BUN), cardiac parameters (SV and CO), mitochondrial dysfunction, and ameliorated oxidative stress, apoptosis, and myocardial fibrosis in ADR-injured mice (p<0.05). Moreover, LYC obviously increased cell viability and reduced oxidative stress, apoptosis, and mitochondrial dysfunction in ADR-injured cells (p<0.05). Furthermore, this study confirmed that the protective effect of LYC on ADR-induced cardiotoxicitymight be mediated by the SIRT1/PPARγ signaling pathway. These results revealed that the beneficial role of LYC on cardiotoxicity induced by ADR were mediated via regulating SIRT1/PPARγ signaling for the first time.

CONCLUSION

These discoveries may provide a theoretical basis for the exploitation of LYC as a potential cardioprotective drug candidate due to its multiple biological functions to reduce ADR-induced cardiotoxicity, but further preclinical and clinical studies are still needed.

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.

Editor-in-Chief's Top Picks From 2021

Each week, I record audio summaries for every paper in JACC, as well as an issue summary. This process has become a true labor of love due to the time they require, but I am motivated by the sheer number of listeners (16M+), and it has allowed me to familiarize myself with every paper that we publish. Thus, I have selected the top 100 papers (both Original Investigations and Review Articles) from distinct specialties each year. In addition to my personal choices, I have included papers that have been the most accessed or downloaded on our websites, as well as those selected by the JACC Editorial Board members. In order to present the full breadth of this important research in a consumable fashion, we will present these abstracts in this issue of JACC, as well as their Central Illustrations and podcasts. The highlights comprise the following sections: Artificial Intelligence & Machine Learning (NEW section), Basic & Translational Research, Biomarkers (NEW section), Cardiac Failure & Myocarditis, Cardiomyopathies & Genetics, Cardio-Oncology, Cardiovascular Disease in Women, Coronary Disease & Interventions, Congenital Heart Disease, Coronavirus, Hypertension, Imaging, Metabolic & Lipid Disorders, Neurovascular Disease & Dementia, Promoting Health & Prevention, Rhythm Disorders & Thromboembolism, Vascular Medicine, and Valvular Heart Disease.^1-100.

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.

OUP accepted manuscript

More than 40 years after the first implantable cardioverter-defibrillator (ICD) implantation, sudden cardiac death (SCD) still accounts for more than five million deaths worldwide every year. Huge efforts in the field notwithstanding, it is now increasingly evident that the current strategy of long-term prevention based on left ventricular ejection fraction as the key selection criterion is actually of very limited impact, also because the largest absolute numbers of SCD are encountered in the general population not known to be at risk. It has been recently reemphasized that SCD is often not so sudden, with almost half of the victims experiencing typical warning symptoms preceding the event. Importantly, heeded and prompt medical attention can dramatically improve survival. Essentially, such timely action increases the chances of the SCD event being witnessed by emergency medical services and provides the opportunity for early intervention. In addition, newer technologies incorporating digital data acquisition, transfer between interconnected devices, and artificial intelligence, should allow dynamic, real-time monitoring of diverse parameters and therefore better identification of subjects at short-term SCD risk. Along with warning symptoms, these developments allow a new approach of near-term prevention based on the hours and minutes preceding SCD. In the present review, we challenge the current paradigm of mid- and long-term prevention using ICD in patients at the highest risk of SCD, and introduce a complementary concept applicable to the entire population that would aim to pre-empt SCD by timely detection and intervention within the minutes or hours prior to the event.

Clinical Impact of Circulating Galectin-3 on Ventricular Arrhythmias and Heart Failure Hospitalization Independent of Prior Ventricular Arrhythmic Events in Patients with Implantable Cardioverter-defibrillators

Objective For risk stratification of sudden cardiac death in patients with structural heart disease, more precise predictors in addition to left ventricular ejection fraction (LVEF) are clinically needed. The present study assessed the utility of galectin-3 as an independent indicator for the prognosis of heart failure patients with implantable cardioverter-defibrillators (ICD). Methods The study population consisted of 91 consecutive patients who underwent a routine ICD checkup in our ICD outpatient clinic. Circulating galectin-3 was assessed using a commercially available enzyme-linked immunosorbent assay kit. The enrolled patients were prospectively followed. The primary endpoint was defined as the occurrence of appropriate ICD therapy (AIT), and the secondary endpoint was defined as the occurrence of unplanned overnight hospitalization due to decompensated heart failure (dHF). Results During a mean follow-up of 472±107 days, AIT occurred in 18 patients (20%). Unplanned hospitalizations due to dHF were noted in 12 patients (13%). A receiver-operative characteristics analysis demonstrated a sensitivity of 83% and specificity of 68% for AIT occurrences with a galectin-3 cut-off value of 13.1 ng/mL (area under the curve =0.82). A Kaplan-Meier analysis demonstrated that patients with galectin-3 >13.1 ng/mL had significantly higher incidences of AIT as compared to those with lower galectin-3 (log-rank, p<0.001). This significance was also observed in both subgroup analyses with ischemic and non-ischemic etiology. Cox regression demonstrated that higher galectin-3 was an independent predictor of AIT and dHF, even after adjusting for previous arrhythmic events. Conclusion The circulating galectin-3 level can be used as a clinical indicator of subsequent occurrence of ventricular arrhythmic events and decompensated heart failure, regardless of a history of ventricular arrhythmias.

Targeting the extracellular matrix for immunomodulation: applications in drug delivery and cell therapies

Host immune cells interact bi-directionally with their extracellular matrix (ECM) to receive and deposit molecular signals, which orchestrate cellular activation, proliferation, differentiation, and function to maintain healthy tissue homeostasis. In response to pathogens or damage, immune cells infiltrate diseased sites and synthesize critical ECM molecules such as glycoproteins, proteoglycans, and glycosaminoglycans to promote healing. When the immune system misidentifies pathogens or fails to survey damaged cells effectively, maladies such as chronic inflammation, autoimmune diseases, and cancer can develop. In these conditions, it is essential to restore balance to the body through modulation of the immune system and the ECM. This review details the components of dysregulated ECM implicated in pathogenic environments and therapeutic approaches to restore tissue homeostasis. We evaluate emerging strategies to overcome inflamed, immune inhibitory, and otherwise diseased microenvironments, including mechanical stimulation, targeted proteases, adoptive cell therapy, mechanomedicine, and biomaterial-based cell therapeutics. We highlight various strategies that have produced efficacious responses in both pre-clinical and human trials and identify additional opportunities to develop next-generation interventions. Significantly, we identify a need for therapies to address dense or fibrotic tissue for the treatment of organ tissue damage and various cancer subtypes. Finally, we conclude that therapeutic techniques that disrupt, evade, or specifically target the pathogenic microenvironment have a high potential for improving therapeutic outcomes and should be considered a priority for immediate exploration. A schematic showing the various methods of extracellular matrix disruption/targeting in both fibrotic and cancerous environments. a Biomaterial-based cell therapy can be used to deliver anti-inflammatory cytokines, chemotherapeutics, or other factors for localized, slow release of therapeutics. b Mechanotherapeutics can be used to inhibit the deposition of molecules such as collagen that affect stiffness. c Ablation of the ECM and target tissue can be accomplished via mechanical degradation such as focused ultrasound. d Proteases can be used to improve the distribution of therapies such as oncolytic virus. e Localization of therapeutics such as checkpoint inhibitors can be improved with the targeting of specific ECM components, reducing off-target effects and toxicity.

Rationale and design of a multi-center, prospective randomized controlled trial on the effects of sacubitril-valsartan versus enalapril on left ventricular remodeling in ST-elevation myocardial infarction: The PERI-STEMI study

BACKGROUND

Angiotensin receptor neprilysin inhibitor (ARNI) sacubitril-valsartan has been recommended as one of the first-line therapies in heart failure with reduced ejection fraction. However, whether ARNI could benefit patients with ST-segment elevation myocardial infarction (STEMI) by improving left ventricular (LV) remodeling remains unknown. The primary objective of the PERI-STEMI trial is to assess whether sacubitril-valsartan is more effective in preventing adverse LV remodeling for patients with STEMI than enalapril.

HYPOTHESIS

We hypothesize that sacubitril/valsartan is superior to enalapril in preventing adverse LV remodeling evaluated by cardiovascular magnetic resonance imaging at the 6-month follow-up.

METHODS

PERI-STEMI is an investigator-initiated, prospective, multi-center, randomized, open-label, superiority trial with blinded evaluation of outcomes. A total of 376 first-time STEMI patients with primary percutaneous coronary intervention (PPCI) within 12 h after symptom onset will be randomized to sacubitril-valsartan or enalapril treatment. All the patients will receive a baseline cardiovascular magnetic resonance (CMR) examination at 4-7 days post-PPCI. The primary endpoint is the change of indexed LV mass at the 6-month follow-up CMR.

RESULTS

Enrollment of the first patient is planned in November 2021. Recruitment is anticipated to last for 12-18 months and patients will be followed for 5 years after randomization. The study is expected to complete in June 2027.

CONCLUSIONS

The results of the PERI-STEMI trial are expected to provide CMR evidence on whether ARNI could benefit patients with STEMI, so as to facilitate the strategy of CMR-based risk stratification and therapy selection for these patients. PERI-STEMI is registered at ClinicalTrials.gov (NCT04912167).

Cardiovascular magnetic resonance determinants of ventricular arrhythmic events after myocardial infarction

AIMS

To non-invasively characterize, by means of late gadolinium enhancement cardiac magnetic resonance (LGE-CMR), scar differences, and potential variables associated with ventricular tachycardia (VT) occurrence in chronic post-myocardial infarction (MI) patients.

METHODS AND RESULTS

A case-control study was designed through retrospective LGE-CMR data analysis of chronic post-MI patients (i) consecutively referred for VT substrate ablation after a first VT episode (n = 66) and (ii) from a control group (n = 84) with no arrhythmia evidence. The myocardium was characterized differentiating core, border zone (BZ), and BZ channels (BZCs) using the ADAS 3D post-processing imaging platform. Clinical and scar characteristics, including a novel parameter, the BZC mass, were compared between both groups. One hundred and fifty post-MI patients were included. Four multivariable Cox proportional hazards regression models were created for total scar mass, BZ mass, core mass, and BZC mass, adjusting them by age, sex, and left ventricular ejection fraction (LVEF). A cut-off of 5.15 g of BZC mass identified the cases with 92.4% sensitivity and 86.9% specificity [area under the ROC curve (AUC) 0.93 (0.89-0.97); P < 0.001], with a significant increase in the AUC compared to other scar parameters (P < 0.001 for all pairwise comparisons). Adding BZC mass to LVEF allowed to reclassify 33.3% of the cases and 39.3% of the controls [net reclassification improvement = 0.73 (0.71-0.74)].

CONCLUSIONS

The mass of BZC is the strongest independent variable associated with the occurrence of sustained monomorphic ventricular tachycardia in post-MI patients after adjustment for age, sex, and LVEF. Border zone channel mass measurement could permit a more accurate VT risk stratification than LVEF in chronic post-MI patients.

Whole-heart ventricular arrhythmia modeling moving forward: Mechanistic insights and translational applications

Ventricular arrhythmias are the primary cause of sudden cardiac death and one of the leading causes of mortality worldwide. Whole-heart computational modeling offers a unique approach for studying ventricular arrhythmias, offering vast potential for developing both a mechanistic understanding of ventricular arrhythmias and clinical applications for treatment. In this review, the fundamentals of whole-heart ventricular modeling and current methods of personalizing models using clinical data are presented. From this foundation, the authors summarize recent advances in whole-heart ventricular arrhythmia modeling. Efforts in gaining mechanistic insights into ventricular arrhythmias are discussed, in addition to other applications of models such as the assessment of novel therapeutics. The review emphasizes the unique benefits of computational modeling that allow for insights that are not obtainable by contemporary experimental or clinical means. Additionally, the clinical impact of modeling is explored, demonstrating how patient care is influenced by the information gained from ventricular arrhythmia models. The authors conclude with future perspectives about the direction of whole-heart ventricular arrhythmia modeling, outlining how advances in neural network methodologies hold the potential to reduce computational expense and permit for efficient whole-heart modeling.

Risk of sudden coronary death based on genetic background in Chinese Han population

Associations between gene variations and sudden cardiac arrest or coronary artery disease have been reported by genome-wide association studies. However, the implication of the genetic status in cases of sudden coronary death (SCD) from the Chinese Han population has remained to be investigated. The present study established a mini-sequencing system to examine putative death-causing single nucleotide polymorphisms (SNPs) using multiplex PCR, single base extension reaction and capillary electrophoresis techniques. A total of 198 samples from the Chinese Han population (age range, 34-71 years; mean age, 53.86 years) were examined using this method. Samples were classified into three groups: Coronary heart disease (CHD, n=70), SCD (n=53) and control (n=75) group. Significant associations were identified for 10, 4 and 6 SNPs in CHD, SCD and sudden death from CHD, respectively, using the χ² test. The SNPs obtained by binary logistic regression may be used to assess and predict the risk of disease. The predictive accuracy of the SNPs in each prediction model and their area under the receiver operating characteristic curve (AUC) values were determined. The AUC of the four SNPs (rs12429889, rs10829156, rs16942421 and rs12155623) to predict CHD was 0.928, the AUC of the six SNPs (rs2389202, rs2982694, rs10183640, rs597503, rs16942421 and rs12155623) to predict SCD was 0.922 and the AUC of the four SNPs (rs16866933, rs4621553, rs10829156 and rs12155623) to predict sudden death from CHD was 0.912. The multifactor dimensionality reduction values were as follows: 0.8690 (prediction model of CHD), 0.7601 (prediction model of SCD) and 0.7628 (prediction model of sudden death from CHD). Taken together, the results of the present study suggested that these SNPs have considerable potential for application in genetic tests to predict CHD or SCD. However, further studies are required to investigate the putative functions of these SNPs.