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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.

Background Cardiovascular magnetic resonance (CMR) derived ventricular volumes and function guide clinical decision-making for various cardiac pathologies. We aimed to evaluate the efficiency and clinical applicability of a commercially available artificial intelligence (AI) method for performing biventricular volumetric analysis. Methods Three-hundred CMR studies (100 with normal CMR findings, 50 dilated cardiomyopathy, 50 hypertrophic cardiomyopathy, 50 ischaemic heart disease and 50 congenital or valvular heart disease) were randomly selected from database. Manual biventricular volumetric analysis (CMRtools) results were derived from clinical reports and automated volumetric analyses were performed using short axis volumetry AI function of CircleCVI42v5.12 software. For 20 studies, a combined method of manually adjusted AI contours was tested and all three methods were timed. Clinicians` confidence in AI method was assessed using an online survey. Results Although agreement was better for left ventricle than right ventricle, AI analysis results were comparable to manual method. Manual adjustment of AI contours further improved agreement: within subject coefficient of variation decreased from 5.0–4.5% for left ventricular ejection fraction (EF) and from 9.9–7.1% for right ventricular EF. Twenty manual analyses were performed in 250min12s whereas same task took 5min48s using AI method. Clinicians were open to adopt AI but concerns about accuracy and validity were raised. Conclusions The AI method provides clinically valid outcomes and saves significant time. To address concerns raised by survey participants and overcome shortcomings of the automated myocardial segmentation, visual assessment of contours and performing manual corrections where necessary appears to be a practical approach.

BACKGROUND: Dilated cardiomyopathy (DCM) is a final common manifestation of heterogenous etiologies. Adverse outcomes highlight the need for disease stratification beyond ejection fraction. OBJECTIVES: The purpose of this study was to identify novel, reproducible subphenotypes of DCM using multiparametric data for improved patient stratification. METHODS: Longitudinal, observational UK-derivation (n = 426; median age 54 years; 67% men) and Dutch-validation (n = 239; median age 56 years; 64% men) cohorts of DCM patients (enrolled 2009-2016) with clinical, genetic, cardiovascular magnetic resonance, and proteomic assessments. Machine learning with profile regression identified novel disease subtypes. Penalized multinomial logistic regression was used for validation. Nested Cox models compared novel groupings to conventional risk measures. Primary composite outcome was cardiovascular death, heart failure, or arrhythmia events (median follow-up 4 years). RESULTS: In total, 3 novel DCM subtypes were identified: profibrotic metabolic, mild nonfibrotic, and biventricular impairment. Prognosis differed between subtypes in both the derivation (P < 0.0001) and validation cohorts. The novel profibrotic metabolic subtype had more diabetes, universal myocardial fibrosis, preserved right ventricular function, and elevated creatinine. For clinical application, 5 variables were sufficient for classification (left and right ventricular end-systolic volumes, left atrial volume, myocardial fibrosis, and creatinine). Adding the novel DCM subtype improved the C-statistic from 0.60 to 0.76. Interleukin-4 receptor-alpha was identified as a novel prognostic biomarker in derivation (HR: 3.6; 95% CI: 1.9-6.5; P = 0.00002) and validation cohorts (HR: 1.94; 95% CI: 1.3-2.8; P = 0.00005). CONCLUSIONS: Three reproducible, mechanistically distinct DCM subtypes were identified using widely available clinical and biological data, adding prognostic value to traditional risk models. They may improve patient selection for novel interventions, thereby enabling precision medicine. ispartof: JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY vol:79 issue:22 pages:2219-2232 ispartof: location:United States status: published

BackgroundHypertrophic cardiomyopathy (HCM) is an important cause of sudden cardiac death associated with heterogeneous phenotypes but there is no systematic framework for classifying morphology or assessing associated risks. Here we quantitatively survey genotype-phenotype associations in HCM to derive a data-driven taxonomy of disease expression.MethodsWe enrolled 436 HCM patients (median age 60 years; 28.8% women) with clinical, genetic and imaging data. An independent cohort of 60 HCM patients from Singapore (median age 59 years; 11% women) and a reference population from UK Biobank (n = 16,691, mean age 55 years; 52.5% women) were also recruited. We used machine learning to analyse the three-dimensional structure of the left ventricle from cardiac magnetic resonance imaging and build a tree-based classification of HCM phenotypes. Genotype and mortality risk distributions were projected on the tree.ResultsCarriers of pathogenic or likely pathogenic variants for HCM (P/LP) variants had lower left ventricular mass, but greater basal septal hypertrophy, with reduced lifespan (mean follow-up 9.9 years) compared to genotype negative individuals (hazard ratio: 2.66; 95% confidence interval [CI]: 1.42-4.96;P< 0.002). Four main phenotypic branches were identified using unsupervised learning of three-dimensional shape: 1) non-sarcomeric hypertrophy with co-existing hypertension; 2) diffuse and basal asymmetric hypertrophy associated with outflow tract obstruction; 3) isolated basal hypertrophy; 4) milder non-obstructive hypertrophy enriched for familial sarcomeric HCM (odds ratio for P/LP variants: 2.18 [95% CI: 1.93-2.28,P= 0.0001]). Polygenic risk for HCM was also associated with different patterns and degrees of disease expression. The model was generalisable to an independent cohort (trustworthinessM1: 0.86-0.88).ConclusionsWe report a data-driven taxonomy of HCM for identifying groups of patients with similar morphology while preserving a continuum of disease severity, genetic risk and outcomes. This approach will be of value in understanding the causes and consequences of disease diversity.

Background: Hypertrophic cardiomyopathy (HCM) is defined as left ventricular end-diastolic maximal wall thickness (WTMax) ≥15.0 mm, without accounting for ethnicity, sex, and body size. It is well-established that Asians have smaller hearts than do Caucasians. Objectives: This study aims to examine the implications of this single absolute WTMax threshold on the diagnosis of HCM in Asians. Methods: The study consisted of 360 healthy volunteers (male: n = 174; age: 50 ± 12 years) and 114 genetically characterized patients with HCM (male: n = 83; age: 52 ± 13 years; genotype-positive, n = 39). All participants underwent cardiovascular magnetic resonance. WTMax was measured semiautomatically at end-diastole according to the standard 16 myocardial segments. Results: Healthy male volunteers had increased WTMax compared with that of female volunteers (8.4 ± 1.2 mm vs 6.6 ± 1.1 mm, respectively; P < 0.001). Conversely, WTMax was similar between male and female patients with HCM (15.2 ± 3.4 mm vs 14.7 ± 3.0 mm, respectively; P = 0.484) and between those with and without a pathogenic gene variant (P = 0.828). Using the recommended diagnostic threshold of 15.0 mm, 56 patients with HCM had WTMax 15.0 mm (specificity of 100% and sensitivity of 51%). Lowering WTMax thresholds to 10.0 mm in female patients and 12.0 mm in male patients did not affect specificity (100%) but significantly improved sensitivity (84%). Despite lower left ventricular mass, female patients with HCM demonstrated more features of adverse cardiac remodeling than did male patients: increased myocardial fibrosis, higher asymmetric ratio, and disproportionately worse myocardial strain. Conclusions: The study highlights cautious application of guideline-recommended WTMax to diagnose HCM in Asians. Lowering WTMax to account for ethnicity and sex improves diagnostic sensitivity without compromising specificity.

ObjectiveThe effect of moderate excess alcohol consumption is widely debated and has not been well defined in dilated cardiomyopathy (DCM). There is need for a greater evidence base to help advise patients. We sought to evaluate the effect of moderate excess alcohol consumption on cardiovascular structure, function and outcomes in DCM.MethodsProspective longitudinal observational cohort study. Patients with DCM (n=604) were evaluated for a history of moderate excess alcohol consumption (UK government guidelines; >14 units/week for women, >21 units/week for men) at cohort enrolment, had cardiovascular magnetic resonance and were followed up for the composite endpoint of cardiovascular death, heart failure and arrhythmic events. Patients meeting criteria for alcoholic cardiomyopathy were not recruited.ResultsDCM patients with a history of moderate excess alcohol consumption (n=98, 16%) had lower biventricular function and increased chamber dilatation of the left ventricle, right ventricle and left atrium, as well as increased left ventricular hypertrophy compared with patients without moderate alcohol consumption. They were more likely to be male (alcohol excess group: n=92, 94% vs n=306, 61%, p=ConclusionDCM patients with moderate excess alcohol consumption have adverse cardiac structure and function at presentation, but this is largely due to biological sex. Alcohol may contribute to sex-specific phenotypic differences in DCM. These findings help to inform lifestyle discussions for patients with DCM.

Acute myocarditis is an inflammatory condition that may herald the onset of dilated cardiomyopathy (DCM) or arrhythmogenic cardiomyopathy (ACM). We investigated the frequency and clinical consequences of DCM and ACM genetic variants in a population-based cohort of patients with acute myocarditis. This was a population-based cohort of 336 consecutive patients with acute myocarditis enrolled in London and Maastricht. All participants underwent targeted DNA sequencing for well-characterized cardiomyopathy-associated genes with comparison to healthy controls (n=1053) sequenced on the same platform. Case ascertainment in England was assessed against national hospital admission data. The primary outcome was all-cause mortality. Variants that would be considered pathogenic if found in a patient with DCM or ACM were identified in 8% of myocarditis cases compared with

BackgroundGuidelines recommend genetic testing and cardiovascular magnetic resonance (CMR) for the investigation of dilated cardiomyopathy (DCM). However, the incremental value is unclear. We assessed the impact of these investigations in determining etiology.MethodsSixty consecutive patients referred with DCM and recruited to our hospital biobank were selected. Six independent experts determined the etiology of each phenotype in a step-wise manner based on (1) routine clinical data, (2) clinical and genetic data and (3) clinical, genetic and CMR data. They indicated their confidence (1-3) in the classification and any changes to management at each step.ResultsSix physicians adjudicated 60 cases. The addition of genetics and CMR resulted in 57 (15.8%) and 26 (7.2%) changes in the classification of etiology, including an increased number of genetic diagnoses and a reduction in idiopathic diagnoses. Diagnostic confidence improved at each step (p < 0.0005). The number of diagnoses made with low confidence reduced from 105 (29.2%) with routine clinical data to 71 (19.7%) following the addition of genetics and 37 (10.3%) with the addition of CMR. The addition of genetics and CMR led to 101 (28.1%) and 112 (31.1%) proposed changes to management, respectively. Interobserver variability showed moderate agreement with clinical data (κ = 0.44) which improved following the addition of genetics (κ = 0.65) and CMR (κ = 0.68).ConclusionWe demonstrate that genetics and CMR, frequently changed the classification of etiology in DCM, improved confidence and interobserver variability in determining the diagnosis and had an impact on proposed management.

Purpose: To characterize the genetic architecture of left ventricular noncompaction (LVNC) and investigate the extent to which it may represent a distinct pathology or a secondary phenotype associated with other cardiac diseases. Methods: We performed rare variant association analysis with 840 LVNC cases and 125,748 gnomAD population controls, and compared results to similar analyses on dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). Results: We observed substantial genetic overlap indicating that LVNC often represents a phenotypic variation of DCM or HCM. In contrast, truncating variants in MYH7, ACTN2, and PRDM16 were uniquely associated with LVNC and may reflect a distinct LVNC etiology. In particular, MYH7 truncating variants (MYH7tv), generally considered nonpathogenic for cardiomyopathies, were 20-fold enriched in LVNC cases over controls. MYH7tv heterozygotes identified in the UK Biobank and healthy volunteer cohorts also displayed significantly greater noncompaction compared with matched controls. RYR2 exon deletions and HCN4 transmembrane variants were also enriched in LVNC, supporting prior reports of association with arrhythmogenic LVNC phenotypes. Conclusion: LVNC is characterized by substantial genetic overlap with DCM/HCM but is also associated with distinct noncompaction and arrhythmia etiologies. These results will enable enhanced application of LVNC genetic testing and help to distinguish pathological from physiological noncompaction.

AimsHypertrophic cardiomyopathy (HCM) is characterised by left ventricular hypertrophy (LVH), myocardial fibrosis, enhanced oxidative stress and energy depletion. Unbound/loosely bound tissue copper II ions are powerful catalysts of oxidative stress and inhibitors of antioxidants. Trientine is a highly selective copper II chelator. In preclinical and clinical studies in diabetes, trientine is associated with reduced LVH and fibrosis, and improved mitochondrial function and energy metabolism. Trientine was associated with improvements in cardiac structure and function in an open-label study in patients with HCM.MethodsThe Efficacy and Mechanism of Trientine in Patients with Hypertrophic Cardiomyopathy (TEMPEST) trial is a multicentre, double-blind, parallel group, 1:1 randomised, placebo-controlled phase II trial designed to evaluate the efficacy and mechanism of action of trientine in patients with HCM. Patients with a diagnosis of HCM according to the European Society of Cardiology Guidelines and in New York Heart Association classes I–III are randomised to trientine or matching placebo for 52 weeks. Primary outcome is change in left ventricular (LV) mass indexed to body surface area, measured using cardiovascular magnetic resonance. Secondary efficacy objectives will determine whether trientine improves exercise capacity, reduces arrhythmia burden, reduces cardiomyocyte injury, improves LV and atrial function, and reduces LV outflow tract gradient. Mechanistic objectives will determine whether the effects are mediated by cellular or extracellular mass regression and improved myocardial energetics.ConclusionTEMPEST will determine the efficacy and mechanism of action of trientine in patients with HCM.Trial registration numbersNCT04706429andISRCTN57145331.

Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Unrestricted educational grants Background Increasing evidence supports a link between myocardial fibrosis (MF) and ventricular arrhythmias. We sought to determine whether presence of MF on visual assessment (MFVA) and gray zone fibrosis (GZF) mass predicts 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 sudden cardiac death (SCD) and the secondary, arrhythmic endpoint of SCD or ventricular arrhythmias after CIED implantation. Results Among 700 patients (age 68.0 ± 12.0yrs [mean ± SD]), 27 (3.85%) experienced a SCD and 121 (17.3%) met the arrhythmic endpoint over 6.93 yrs (median; interquartile range 5.82-9.32). MFVA predicted SCD (hazard ratio [HR]: HR:26.3 [95% confidence interval [CI] 3.70-3337]; negative predictive value: 100%). In competing risks analyses, MFVA also predicted the arrhythmic endpoint (subdistribution [sHR]: 19.9 [95% CI 6.40-61.9]; 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 6.12-5685) and the arrhythmic endpoint (sHR: 30.3 [95% CI 9.60-95.8]). 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.

Cardiovascular magnetic resonance (CMR) has an increasingly important role in the assessment of patients with heart failure. One major advantage of this modality is the ability to perform tissue characterization without exposure to ionizing radiation, enabling accurate diagnosis and improved prognostication. Given the high spatial resolution and the ability to image in any plane, it also provides reference-standard quantification of chamber size and function. Accurate assessment of left ventricular ejection fraction is fundamental to current decision-making in the contemporary management of heart failure. This chapter covers the basics of magnetic resonance imaging, including the components of a typical scan performed to evaluate a patient with heart failure, and discusses the major benefits CMR offers in the assessment of patients with heart failure and reduced ejection fraction and those with preserved ejection fraction.

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

Background Quantitative cardiovascular magnetic resonance T1-mapping is increasingly used for myocardial tissue characterization. However, the lack of standardization limits direct comparability between centers and wider roll-out for clinical use or trials. Purpose To develop a quality assurance (QA) program assuring standardized T1 measurements for clinical use. Methods MR phantoms manufactured in 2013 were distributed, including ShMOLLI T1-mapping and reference T1 and T2 protocols. We first studied the T1 and T2 dependency on temperature and phantom aging using phantom datasets from a single site over 4 years. Based on this, we developed a multiparametric QA model, which was then applied to 78 scans from 28 other multi-national sites. Results T1 temperature sensitivity followed a second-order polynomial to baseline T1 values (R2 > 0.996). Some phantoms showed aging effects, where T1 drifted up to 49% over 40 months. The correlation model based on reference T1 and T2, developed on 1004 dedicated phantom scans, predicted ShMOLLI-T1 with high consistency (coefficient of variation 1.54%), and was robust to temperature variations and phantom aging. Using the 95% confidence interval of the correlation model residuals as the tolerance range, we analyzed 390 ShMOLLI T1-maps and confirmed accurate sequence deployment in 90%(70/78) of QA scans across 28 multiple centers, and categorized the rest with specific remedial actions. Conclusions The proposed phantom QA for T1-mapping can assure correct method implementation and protocol adherence, and is robust to temperature variation and phantom aging. This QA program circumvents the need of frequent phantom replacements, and can be readily deployed in multicenter trials., Highlights • CMR T1 correlated with reference T1 and T2; this derives the QA model for T1-map. • The proposed QA model is robust to temperature variations and phantom aging. • This QA method requires no frequent phantom replacements. • The T1-map QA program can be readily deployed in multicenter trials.

Atrial fibrillation (AF) in hypertrophic cardiomyopathy (HC) is associated with significant symptomatic deterioration, heart failure, and thromboembolic disease. There is a need for better mechanistic insight and improved identification of at risk patients. We used cardiovascular magnetic resonance (CMR) to assess predictors of AF in HC, in particular the role of myocardial fibrosis. Consecutive patients with HC referred for CMR 2003 to 2013 were prospectively enrolled. CMR parameters including left ventricular volumes, presence and percentage of late gadolinium enhancement in the left ventricle (%LGE) and left atrial volume index (LAVi) were measured. Overall, 377 patients were recruited (age 62 ± 14 years, 73% men). Sixty-two patients (16%) developed new-onset AF during a median follow up of 4.5 (interquartile range 2.9 to 6.0) years. Multivariable analysis revealed %LGE (hazard ratio [HR] 1.3 per 10% (confidence interval: 1.0 to 1.5; p = 0.02), LAVi (HR 1.4 per 10 mL/m 2[1.2 to 1.5; p < 0.001]), age at HC diagnosis, nonsustained ventricular tachycardia and diabetes to be independent predictors of AF. We constructed a simple risk prediction score for future AF based on the multivariable model with a Harrell's C-statistic of 0.73. In conclusion, the extent of ventricular fibrosis and LA volume independently predicted AF in patients with HC. This finding suggests a mechanistic relation between fibrosis and future AF in HC. CMR with quantification of fibrosis has incremental value over LV and LA measurements in risk stratification for AF. A risk prediction score may be used to identify patients at high risk of future AF who may benefit from more intensive rhythm monitoring and a lower threshold for oral anticoagulation.

The introduction of transcatheter aortic valve implantation (TAVI) has revolutionised the management of aortic stenosis (AS), with procedure numbers rapidly increasing. Although there has been enth...

Cardiovascular (CV) imaging is an important tool in baseline risk assessment and detection of CV disease in oncology patients receiving cardiotoxic cancer therapies. This position statement examines the role of echocardiography, cardiac magnetic resonance, nuclear cardiac imaging and computed tomography in the management of cancer patients. The Imaging and Cardio-Oncology Study Groups of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) in collaboration with the European Association of Cardiovascular Imaging (EACVI) and the Cardio-Oncology Council of the ESC have evaluated the current evidence for the value of modern CV imaging in the cardio-oncology field. The most relevant echocardiographic parameters, including global longitudinal strain and three-dimensional ejection fraction, are proposed. The protocol for baseline pre-treatment evaluation and specific surveillance algorithms or pathways for anthracycline chemotherapy, HER2-targeted therapies such as trastuzumab, vascular endothelial growth factor tyrosine kinase inhibitors, BCr-Abl tyrosine kinase inhibitors, proteasome inhibitors and immune checkpoint inhibitors are presented. The indications for CV imaging after completion of oncology treatment are considered. The typical consequences of radiation therapy and the possibility of their identification in the long term are also summarized. Special populations are discussed including female survivors planning pregnancy, patients with carcinoid disease, patients with cardiac tumours and patients with right heart failure. Future directions and ongoing CV imaging research in cardio-oncology are discussed.

Objective: Interstitial fibrosis is a pathological expansion of the heart's inter-cellular collagen matrix. It is a potential complication of nonischemic cardiomyopathy (NICM), a class of diseases involving electrical and or mechanical dysfunction of cardiac tissue not caused by atherosclerosis. Patients with NICM and interstitial fibrosis often suffer from life threatening arrhythmias, which we aim to simulate in this study. Methods: Our methodology builds on an efficient discrete finite element (DFE) method which allows for the representation of fibrosis as infinitesimal splits in a mesh. We update the DFE method with a local connectivity analysis which creates a consistent topology in the fibrosis network. This is particularly important in nonischemic disease due to the potential presence of large and contiguous fibrotic regions and therefore potentially complex fibrosis networks. Results: In experiments with an image-based model, we demonstrate that our methodology is able to simulate reentrant electrical events associated with cardiac arrhythmias. These reentries depended crucially upon sufficient fibrosis density, which was marked by conduction slowing at high pacing rates. We also created a 2D test-case which demonstrated that fibrosis topologies can modulate transient conduction block, and thereby reentrant activations. Conclusion: Ventricular arrhythmias due to interstitial fibrosis in NICM can be efficiently simulated using our methods in medical image based geometries. Furthermore, fibrosis topology modulates transient conduction block, and should be accounted for in electrophysiological simulations with interstitial fibrosis. Significance: Our study provides methodology which has the potential to predict arrhythmias and to optimize treatments non-invasively for nonischemic cardiomyopathies.

Dilated cardiomyopathy (DCM) is a common condition, which carries significant mortality from sudden cardiac death and pump failure. Left ventricular ejection fraction has conventionally been used as a risk marker for sudden cardiac death, but has performed poorly in trials. There have been significant advances in the areas of cardiac magnetic resonance imaging and genetics, which are able to provide useful rick prediction in DCM. Biomarkers and cardiopulmonary exercise testing are well validated in the prediction of risk in heart failure; however, they have been tested less specifically in the DCM setting. This review will discuss these methods with a view toward multiparametric risk assessment in DCM with the hope of creating parametric risk models to predict sudden cardiac death and pump failure in the DCM population.

Aims:\ud There is an important need for better biomarkers to predict left ventricular (LV) remodelling in dilated cardiomyopathy (DCM). We undertook a comprehensive assessment of cardiac structure and myocardial composition to determine predictors of remodelling.\ud \ud Methods and results:\ud Prospective study of patients with recent‐onset DCM with cardiovascular magnetic resonance (CMR) assessment of ventricular structure and function, extracellular volume (T1 mapping), myocardial strain, myocardial scar (late gadolinium enhancement) and contractile reserve (dobutamine stress). Regression analyses were used to evaluate predictors of change in LV ejection fraction (LVEF) over 12 months. We evaluated 56 participants (34 DCM patients, median LVEF 43%; 22 controls). Absolute LV contractile reserve predicted change in LVEF (1% increase associated with 0.4% increase in LVEF at 12 months, P = 0.02). Baseline myocardial strain (P = 0.39 global longitudinal strain), interstitial myocardial fibrosis (P = 0.41), replacement myocardial fibrosis (P = 0.25), and right ventricular contractile reserve (P = 0.17) were not associated with LV reverse remodelling. There was a poor correlation between contractile reserve and either LV extracellular volume fraction (r = −0.22, P = 0.23) or baseline LVEF (r = 0.07, P = 0.62). Men were more likely to experience adverse LV remodelling (P = 0.01) but age (P = 0.88) and disease‐modifying heart failure medication (beta‐blocker, P = 0.28; angiotensin‐converting enzyme inhibitor, P = 0.92) did not predict follow‐up LVEF.\ud \ud Conclusions:\ud Substantial recovery of LV function occurs within 12 months in most patients with recent‐onset DCM. Women had the greatest improvement in LVEF. A low LV contractile reserve measured by dobutamine stress CMR appears to identify patients whose LVEF is less likely to recover.

IMPORTANCE: Low-flow severe aortic stenosis (AS) has higher mortality than severe AS with normal flow. The conventional definition of low-flow AS is an indexed stroke volume (SVi) by echocardiography less than 35 mL/m(2). Cardiovascular magnetic resonance (CMR) is the reference standard for quantifying left ventricular volumes and function from which SVi by CMR can be derived. OBJECTIVE: To determine the association of left ventricular SVi by CMR with myocardial remodeling and survival among patients with severe AS after valve replacement. DESIGN, SETTING, AND PARTICIPANTS: This multicenter longitudinal cohort study was conducted between January 2003 and May 2015 across 6 UK cardiothoracic centers. Patients with severe AS listed for either surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR) were included. Patients underwent preprocedural echocardiography and CMR. Patients were stratified by echocardiography-derived aortic valve mean and/or peak gradient and SVi by CMR into 4 AS endotypes: low-flow, low-gradient AS; low-flow, high-gradient AS; normal-flow, low-gradient AS; and normal-flow, high-gradient AS. Patients were observed for a median of 3.6 years. Data were analyzed from September to November 2021. EXPOSURES: SAVR or TAVR. MAIN OUTCOMES AND MEASURES: All-cause and cardiovascular (CV) mortality after aortic valve intervention. RESULTS: Of 674 included patients, 425 (63.1%) were male, and the median (IQR) age was 75 (66-80) years. The median (IQR) aortic valve area index was 0.4 (0.3-0.4) cm(2)/m(2). Patients with low-flow AS endotypes (low gradient and high gradient) had lower left ventricular ejection fraction, mass, and wall thickness and increased all-cause and CV mortality than patients with normal-flow AS (all-cause mortality: hazard ratio [HR], 2.08; 95% CI, 1.37-3.14; P

BACKGROUND: Empirical evidence suggests a strong link between exposure to air pollution and heart failure incidence, hospitalizations, and mortality, but the biological basis of this remains unclear. We sought to determine the relationship between differential air pollution levels and changes in cardiac structure and function in patients with dilated cardiomyopathy.METHODS AND RESULTS: We undertook a prospective longitudinal observational cohort study of patients in England with dilated cardiomyopathy (enrollment 2009-2015, n = 716, 66% male, 85% Caucasian) and conducted cross sectional analysis at the time of study enrollment. Annual average air pollution exposure estimates for nitrogen dioxide (NO 2) and particulate matter with diameter of 2.5 µm or less (PM 2.5) at enrolment were assigned to each residential postcode (on average 12 households). The relationship between air pollution and cardiac morphology was assessed using linear regression modelling. Greater ambient exposure to NO 2 was associated with higher indexed left ventricular (LV) mass (4.3 g/m 2 increase per interquartile range increase in NO 2, 95% confidence interval 1.9-7.0 g/m 2) and lower LV ejection fraction (-1.5% decrease per interquartile range increase in NO 2, 95% confidence interval -2.7% to -0.2%), independent of age, sex, socioeconomic status, and clinical covariates. The associations were robust to adjustment for smoking status and geographical clustering by postcode area. The effect of air pollution on LV mass was greatest in women. These effects were specific to NO 2 exposure. CONCLUSIONS: Exposure to air pollution is associated with raised LV mass and lower LV ejection fraction, with the strongest effect in women. Although epidemiological associations between air pollution and heart failure have been established and supported by preclinical studies, our findings provide novel empirical evidence of cardiac remodeling and exposure to air pollution with important clinical and public health implications.

Patients with non-ischemic systolic heart failure (HF) have increased risk of sudden cardiovascular death (SCD). The initiation and substrate for ventricular arrhythmias remains poorly understood. Our purpose was to describe the relationship between cardiac magnetic resonance (CMR) late gadolinium enhancement (LGE) and Holter recorded ventricular arrhythmic activity. Patients from the DANISH trial underwent a Holter-recording and a CMR-scan. The presence of non-sustained ventricular tachycardia (NSVT) and premature ventricular contractions (PVC) were examined in relation to presence and amount of LGE. Outcome measures were all-cause mortality and SCD. Overall, 180 patients were included. LGE was present in 86 (47%). NSVT occurred in 72 (40%), not different according to LGE status (p = 0.65). The amount of LGE was not correlated to the occurrence of NSVT (p = 0.40). The occurrence of couplet PVCs (p = 0.997), frequent PVCs (p = 0.12), PVCs in bigemini (p = 0.29), in trigemini (p = 0.26), or in quadrimini (p = 0.35) did not differ according to LGE status. LGE was significantly associated with risk of all-cause mortality (HR 2.14; 95% CI 1.05-4.37, p = 0.04). NSVT did not increase risk of all-cause mortality in either patients with LGE (HR 1.00; 95% CI 0.46-2.16, p = 0.996) or without LGE (HR 1.37; 95% CI 0.46-4.08, p = 0.57). There was no interaction between LGE and NSVT for the risk of all-cause mortality (p = 0.62). In patients with non-ischemic systolic HF there was no relationship between the presence of LGE and NSVT or any other Holter recorded ventricular tachyarrhythmia. LGE was associated with increased risk of mortality, independent of the presence of NSVT.

Objectives(1) To evaluate the prevalence and hospitalisation rate of COVID-19 infections among patients with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) in the Royal Brompton and Harefield Hospital Cardiovascular Research Centre (RBHH CRC) Biobank. (2) To evaluate the indirect impact of the pandemic on patients with cardiomyopathy through the Heart Hive COVID-19 study. (3) To assess the impact of the pandemic on national cardiomyopathy-related hospital admissions.Methods(1) 1236 patients (703 DCM, 533 HCM) in the RBHH CRC Biobank were assessed for COVID-19 infections and hospitalisations; (2) 207 subjects (131 cardiomyopathy, 76 without heart disease) in the Heart Hive COVID-19 study completed online surveys evaluating physical health, psychological well-being, and behavioural adaptations during the pandemic and (3) 11 447 cardiomyopathy-related hospital admissions across National Health Service (NHS) England were studied from NHS Digital Hospital Episode Statistics over 2019–2020.ResultsA comparable proportion of patients with cardiomyopathy in the RBHH CRC Biobank had tested positive for COVID-19 compared with the UK population (1.1% vs 1.6%, p=0.14), but a higher proportion of those infected were hospitalised (53.8% vs 16.5%, p=0.002). In the Heart Hive COVID-19 study, more patients with cardiomyopathy felt their physical health had deteriorated due to the pandemic than subjects without heart disease (32.3% vs 13.2%, p=0.004) despite only 4.6% of the cardiomyopathy cohort reporting COVID-19 symptoms. A 17.9% year-on-year reduction in national cardiomyopathy-related hospital admissions was observed in 2020.ConclusionPatients with cardiomyopathy had similar reported rates of testing positive for COVID-19 to the background population, but those with test-proven infection were hospitalised more frequently. Deterioration in physical health amongst patients could not be explained by COVID-19 symptoms, inferring a significant contribution of the indirect consequences of the pandemic.Trial registration numberNCT04468256