Nay Aung

Left atrial (LA) function and left ventricular (LV) myocardial fibrosis have complex bidirectional relationships via common pathways, including aberrant myocardial remodeling and LV diastolic dysfunction. 1 Although native T1 (which reflects myocardial diffuse fibrosis) and LA function have each been independently linked with cardiovascular events, no studies have investigated how these parameters in combination influence clinical outcomes. We evaluated the relationship between T1 and LA global and phasic function in the UK Biobank imaging study 2 and report the association of concurrent aberration of T1 and LA function with incident events. A total of 34,189 participants free from cardiovascular (CV) disease were included. The study is covered by the overall UK Biobank ethical approval (NHS National Research Ethics Service 21/NW/0157). T1 mapping was performed using the Shortened Modified Look …

Background: Myocardial strain using cardiac magnetic resonance (CMR) is a sensitive marker for predicting adverse outcomes in many cardiac disease states. The most promising and widely reported metric is left ventricular global longitudinal strain (LV GLS)(1, 2). Left ventricular global circumferential strain (LV GCS) and global radial strain (LV GRS) may also have prognostic value, but there are fewer studies demonstrating this (3–5). The prognostic value of myocardial strain in the general population has not been studied conclusively.Methods: Participants from the UK Biobank population imaging study were included (n~ 45,700, age 65±8 years)–see Table 1 for all baseline characteristics. CMR feature tracking (FT) derived LV GLS, GCS and GRS (see Figure 1) metrics were assessed for their prognostic value in predicting adverse outcomes (heart failure (HF), myocardial infarction (MI), stroke and death …

BackgroundThe absence of population-stratified cardiovascular magnetic resonance (CMR) reference ranges from large cohorts is a major shortcoming for clinical care.ObjectivesThis paper provides age-, sex-, and ethnicity-specific CMR reference ranges for atrial and ventricular metrics from the Healthy Hearts Consortium, an international collaborative comprising 9,088 CMR studies from verified healthy individuals, covering the complete adult age spectrum across both sexes, and with the highest ethnic diversity reported to date.MethodsCMR studies were analyzed using certified software with batch processing capability (cvi42, version 5.14 prototype, Circle Cardiovascular Imaging) by 2 expert readers. Three segmentation methods (smooth, papillary, anatomic) were used to contour the endocardial and epicardial borders of the ventricles and atria from long- and short-axis cine series. Clinically established …

Background Four hypertension-mediated left ventricular hypertrophy (LVH) phenotypes have been reported using cardiac magnetic resonance (CMR): normal LV, LV remodeling, eccentric and concentric LVH, with varying prognostic implications. The electrocardiogram (ECG) is routinely used to detect LVH, however its capacity to differentiate between LVH phenotypes is unknown. This study aimed to classify hypertension-mediated LVH from the ECG using machine learning (ML) and test for associations of ECG-predicted phenotypes with incident cardiovascular outcomes. Methods ECG biomarkers were extracted from the 12-lead ECG of 20,439 hypertensives in UK Biobank (UKB). Classification models integrating ECG and clinical variables were built using logistic regression, support vector machine (SVM) and random forest. The models were trained in 80% of participants, and the remaining 20% formed the test set. External validation was sought in 877 hypertensives from Study of Health in Pomerania (SHIP). In the UKB test set, we tested for associations between ECG-predicted LVH phenotypes and incident major adverse cardiovascular events (MACE) and heart failure. Results Among UKB participants 19,408 had normal LV, 758 LV remodeling, 181 eccentric and 92 concentric LVH. Classification performance of the three models was comparable, with SVM having a slightly superior performance (accuracy 0.79 ,sensitivity 0.59, specificity 0.87, AUC 0.69) and similar results observed in SHIP. There was superior prediction of eccentric LVH in both cohorts. In the UKB test set, ECG-predicted eccentric LVH was associated with heart failure …

Background Automated algorithms are being used regularly to analyse cardiac magnetic resonance (CMR) images. Validating data output reliability from these methods is necessary to enable widespread adoption. We outline a visual quality control (QC) process for image analysis performed using automated batch processing methods. We aim to report the performance of automated methods and the reliability of replacing visual checks with a statistical outlier removal approach in UK Biobank CMR scans.Methods CMR scans included (n=1987) were from the UK Biobank COVID imaging study. Automated batch processing software developed by Circle Cardiovascular Imaging Inc (CVI 42) was used to extract chamber volumetric data, strain, native T1 and aortic flow data. The video outputs of the automated image analysis (~ 62,000 videos and 2000 images) were visually reviewed and rated by six experienced …

Background The extent of left ventricular (LV) trabeculation and its relationship with cardiovascular (CV) risk factors is unclear. Purpose To apply automated segmentation to UK Biobank cardiac MRI scans to (a) assess the association between individual characteristics and CV risk factors and trabeculated LV mass (LVM) and (b) establish normal reference ranges in a selected group of healthy UK Biobank participants. Materials and Methods In this cross-sectional secondary analysis, prospectively collected data from the UK Biobank (2006 to 2010) were retrospectively analyzed. Automated segmentation of trabeculations was performed using a deep …

We used expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) to conduct genome-wide Mendelian randomization (MR) using 27,799 cases of heart failure (HF) with reduced ejection fraction (HFrEF), 27,579 cases of HF with preserved ejection fraction (HFpEF), and 367,267 control individuals from the Million Veteran Program (MVP). We identified 70 HFrEF and 10 HFpEF gene-hits, of which 58 are novel. In 14 known loci for unclassified HF, we identified HFrEF as the subtype responsible for the signal. HFrEF hits ZBTB17, MTSS1, PDLIM5, and MLIP and novel HFpEF hits NFATC2IP, and PABPC4 showed robustness to MR assumptions, support from orthogonal sources, compelling evidence on mechanism of action needed for therapeutic efficacy, and no evidence of an unacceptable safety profile. We strengthen the value of pathways such as ubiquitin-proteasome system, small ubiquitin-related modifier pathway, inflammation, and mitochondrial metabolism as potential therapeutic targets for HF management. We identified IL6R, ADM, and EDNRA as suggestive hits for HFrEF and LPA for HFrEF and HFpEF, which enhances the odds of success for existing cardiovascular investigational drugs targeting. These findings confirm the unique value of human genetic studies in HFrEF and HFpEF for discovery of novel targets and generation of therapeutic target profiles needed to initiate new validation programs in HFrEF and HFpEF preclinical models.

Introduction There is growing interest in identifying cardiovascular magnetic resonance (CMR) signatures in ageing due to their relevance to cardiovascular health.1 It also remains uncertain whether patients with heart failure with preserved ejection fraction (HFpEF) have disruptions in their aortic flow. This study aimed to explore sophisticated indicators of aortic flow disturbances in ageing and in HFpEF.Materials and Methods This study used two-dimensional phase-contrast CMR data at an orthogonal plane just above the sino-tubular junction. We recruited 10 young healthy controls (HCs), 10 old HCs and 23 patients with HFpEF. We analysed average systolic aortic flow displacement (FDsavg), systolic flow reversal ratio (sFRR) and pulse wave velocity (PWV). In a sub-group analysis, we compared old HCs versus age-gender-matched HFpEF (N=10).Results Differences were significant in mean age (P<0.001 …

Cardiac disease affects the heart non-uniformly. Examples include focal septal or apical hypertrophy with reduced strain in hypertrophic cardiomyopathy, replacement fibrosis with akinesia in an infarct-related coronary artery territory, and a pattern of scarring in dilated cardiomyopathy. The detail and versatility of cardiovascular magnetic resonance (CMR) imaging mean it contains a wealth of information imperceptible to the naked eye and not captured by standard global measures. CMR-derived heterogeneity biomarkers could facilitate early diagnosis, better risk stratification, and a more comprehensive prediction of treatment response. Small cohort and case–control studies demonstrate the feasibility of proof-of-concept structural and functional heterogeneity measures. Detailed radiomic analyses of different CMR sequences using open-source software delineate unique voxel patterns as hallmarks of …

Validation of 2D Flow MRI for Helical and Vortical Flows Toggle navigation Login Toggle navigation Validation of 2D Flow MRI for Helical and Vortical Flows QMRO Home William Harvey Research Institute Centre for Cardiovascular Medicine and Devices Validation of 2D Flow MRI for Helical and Vortical Flows QMRO Home William Harvey Research Institute Centre for Cardiovascular Medicine and Devices Validation of 2D Flow MRI for Helical and Vortical Flows All of QMROCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects Login Most Popular ItemsStatistics by CountryMost Popular Authors Validation of 2D Flow MRI for Helical and Vortical Flows View/Open Accepted version Embargoed until: 2099-01-01 Reason: Not yet published. Publisher BMJ Publishing Group Journal Open Heart ISSN 2053-3624 Metadata Show full item record Authors Petersen, …

The progress in deep learning solutions for disease diagnosis and prognosis based on cardiac magnetic resonance imaging is hindered by highly imbalanced and biased training data. To address this issue, we propose a method to alleviate imbalances inherent in datasets through the generation of synthetic data based on sensitive attributes such as sex, age, body mass index, and health condition. We adopt ControlNet based on a denoising diffusion probabilistic model to condition on text assembled from patient metadata and cardiac geometry derived from segmentation masks using a large-cohort study, specifically, the UK Biobank. We assess our method by evaluating the realism of the generated images using established quantitative metrics. Furthermore, we conduct a downstream classification task aimed at debiasing a classifier by rectifying imbalances within underrepresented groups through synthetically generated samples. Our experiments demonstrate the effectiveness of the proposed approach in mitigating dataset imbalances, such as the scarcity of younger patients or individuals with normal BMI level suffering from heart failure. This work represents a major step towards the adoption of synthetic data for the development of fair and generalizable models for medical classification tasks. Notably, we conduct all our experiments using a single, consumer-level GPU to highlight the feasibility of our approach within resource-constrained environments. Our code is available at https://github.com/faildeny/debiasing-cardiac-mri.

An open-source automated algorithm called DeepFlow enables large-scale derivation of aortic flow measurements, and genetic analysis of aortic flow, structural and functional traits demonstrates a causal relationship between aortic size and aortic valve regurgitation.

Background: Left ventricular (LV) mass is a known prognostic cardiovascular biomarker with established genetic underpinnings, and is a particularly important phenotype in the context of heart muscle diseases. Physical activity holds interest as a risk factor as in general, it is protective against cardiovascular disease, however, in certain circumstances it can lead to deleterious remodelling. This gene-lifestyle interaction study examines whether physical activity attenuates the effect of genetic variants known to be associated with LV mass.Methods: Genotype data (number of risk alleles) for 12 variants known to be associated with LV mass were retrieved for all participants in the UK Biobank. Of these, 42,309 had paired CMR and physical activity data. LV mass was indexed to body surface area. Physical activity levels in metabolic equivalent of task (MET)-minutes were determined from self-reported questionnaire data …

Excessive trabeculation, often referred to as “noncompacted” myocardium, has been described at all ages, from the fetus to the adult. Current evidence for myocardial development, however, does not support the formation of compact myocardium from noncompacted myocardium, nor the arrest of this process to result in so-called noncompaction. Excessive trabeculation is frequently observed by imaging studies in healthy individuals, as well as in association with pregnancy, athletic activity, and with cardiac diseases of inherited, acquired, developmental, or congenital origins. Adults with incidentally noted excessive trabeculation frequently require no further follow-up based on trabecular pattern alone. Patients with cardiomyopathy and excessive trabeculation are managed by cardiovascular symptoms rather than the trabecular pattern. To date, the prognostic role of excessive trabeculation in adults has not been …

Aims Left ventricular filling pressure (LVFP) can be estimated from cardiovascular magnetic resonance (CMR). We aimed to investigate whether CMR‐derived LVFP is associated with signs, symptoms, and prognosis in patients with recently diagnosed heart failure (HF). Methods and results This study recruited 454 patients diagnosed with HF who underwent same‐day CMR and clinical assessment between February 2018 and January 2020. CMR‐derived LVFP was calculated, as previously, from long‐ and short‐axis cines. CMR‐derived LVFP association with symptoms and signs of HF was investigated. Patients were followed for median 2.9 years (interquartile range 1.5–3.6 years) for major adverse cardiovascular events (MACE), defined as the composite of cardiovascular death, HF hospitalization, non‐fatal stroke, and non‐fatal myocardial infarction. The mean age was 62 ± 13 years, 36% were female (n …

BACKGROUND The consequences of exercise-induced premature ventricular contractions (PVCs) in asymptomatic individuals remain unclear. This study aimed to assess the association between PVC burdens during submaximal exercise and major adverse cardiovascular events (MI/HF/LTVA: myocardial infarction [MI], heart failure [HF], and life-threatening ventricular arrhythmia [LTVA]), and all-cause mortality. Additional end points were MI, LTVA, HF, and cardiovascular mortality. METHODS A neural network was developed to count PVCs from ECGs recorded during exercise (6 minutes) and recovery (1 minute) in 48 315 asymptomatic participants from UK Biobank. Associations were estimated using multivariable Cox proportional hazard models. Explorative studies were conducted in subgroups with cardiovascular magnetic resonance imaging data (n=6290) and NT-proBNP (N-terminal Pro-B-type …

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 …

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Institute for Health and Care Research British Cardiovascular Society. Background Cardiovascular magnetic resonance imaging (CMR) can estimate left ventricular filling pressure (LVFP). The relationship between LVFP, determined by CMR measurements, and established risk factors for cardiovascular disease is unknown. This study quantifies these associations and investigates the prognostic value of CMR-derived LVFP compared to known risk factors for cardiovascular disease. Methods Using data from the UK Biobank prospective observational cohort study, CMR-derived LVFP was calculated using a model incorporating left atrial volume and left ventricular mass. Logistic regression was used to explore the relationships …

Background Left ventricular maximum wall thickness (LVMWT) is an important biomarker of left ventricular hypertrophy and provides diagnostic and prognostic information in hypertrophic cardiomyopathy (HCM). Limited information is available on the genetic determinants of LVMWT. Methods We performed a genome-wide association study of LVMWT measured from the cardiovascular magnetic resonance examinations of 42 176 European individuals. We evaluated the genetic relationship between LVMWT and HCM by performing pairwise analysis using the data from the Hypertrophic Cardiomyopathy Registry in which the controls were randomly selected from UK Biobank individuals not included in the cardiovascular magnetic resonance sub-study. Results Twenty-one genetic loci were discovered at P<5×10−8. Several novel candidate genes were identified including PROX1, PXN, and PTK2, with known …

Background Chronic kidney disease (CKD) is an established predictor of left atrial (LA) and left ventricular (LV) morphological and functional changes, which translate into excessive cardiovascular morbidity and mortality. However, a focussed study exploring the impact of early stages of CKD defined as stage 1 (eGFR > 90 mL/min per 1.73 m2 + albuminuria) and stage 2 (eGFR 60–89 mL/min per 1.73 m2) with and without proteinuria on cardiac magnetic resonance (CMR) parameters is lacking. Purpose In this study, we analysed CMR structural and functional changes in participants with early stages of CKD in the UK Biobank population. Methods 41,095 participants from the UK Biobank imaging study were categorised into CKD stages. We calculated eGFR using the CKD-EPI 2021 equation and proteinuria was ascertained by the urinary protein creatinine …