Deep learning of left atrial structure and function provides link to atrial fibrillation risk

Correlation between left ventricular hypertrophy, myocardial fibrosis, and left atrial function in non-obstructive hypertrophic cardiomyopathy: insights from CMR-FT imaging

Nonobstructive hypertrophic cardiomyopathy (NOHCM) is associated with left ventricular (LV) hypertrophy and myocardial fibrosis, which progressively impair left atrial (LA) function. This study evaluated the impact of LV hypertrophy and fibrosis on LA dysfunction using cardiac magnetic resonance (CMR) imaging and feature-tracking (FT) strain analysis in 99 NOHCM patients, who were stratified into four groups based on the extent of late gadolinium enhancement (LGE): no fibrosis (LGE < 7%), mild fibrosis (7% ≤ LGE < 15%), moderate fibrosis (15% ≤ LGE < 30%), and severe fibrosis (LGE ≥ 30%). LA functional parameters, including reservoir strain (εs), conduit strain (εe), and pump strain (εa), showed significant reductions with increasing LGE burden (P < 0.05), with functional decline detectable even in mild fibrosis cases despite preserved LV ejection fraction. LV morphological and functional indices, such as global peak wall thickness (GPWT), LV end-systolic volume (LVESV), and LGE percentage, negatively correlated with LA strain metrics (r = -0.2 to -0.7, P < 0.05). Strain analysis demonstrated high reproducibility (ICC > 0.75). These findings highlight the clinical significance of CMR-FT as a sensitive and reliable tool for early detection of LA dysfunction in NOHCM patients, even before significant LV structural changes occur. The ability of CMR-FT to identify subtle changes in LA mechanics could provide valuable insights for risk stratification and guide early intervention strategies, ultimately improving clinical outcomes in this patient population.

Hearts, Data, and Artificial Intelligence Wizardry: From Imitation to Innovation in Cardiovascular Care

Artificial intelligence (AI) is transforming cardiovascular medicine by enabling the analysis of high-dimensional biomedical data with unprecedented precision. Initially employed to automate human tasks such as electrocardiogram (ECG) interpretation and imaging segmentation, AI's true potential lies in uncovering hidden disease data patterns, predicting long-term cardiovascular risk, and personalizing treatments. Unlike human cognition, which excels in certain tasks but is limited by memory and processing constraints, AI integrates multimodal data sources-including ECG, echocardiography, cardiac magnetic resonance (CMR) imaging, genomics, and wearable sensor data-to generate novel clinical insights. AI models have demonstrated remarkable success in early dis-ease detection, such as predicting heart failure from standard ECGs before symptom on-set, distinguishing genetic cardiomyopathies, and forecasting arrhythmic events. However, several challenges persist, including AI's lack of contextual understanding in most of these tasks, its "black-box" nature, and biases in training datasets that may contribute to disparities in healthcare delivery. Ethical considerations and regulatory frameworks are evolving, with governing bodies establishing guidelines for AI-driven medical applications. To fully harness the potential of AI, interdisciplinary collaboration among clinicians, data scientists, and engineers is essential, alongside open science initiatives to promote data accessibility and reproducibility. Future AI models must go beyond task automation, focusing instead on augmenting human expertise to enable proactive, precision-driven cardiovascular care. By embracing AI's computational strengths while addressing its limitations, cardiology is poised to enter an era of transformative innovation beyond traditional diagnostic and therapeutic paradigms.

The potential role of cardiac CT in ischemic stroke: bridging cardiovascular and cerebrovascular health

Ischemic stroke, accounting for approximately 80% of all stroke cases, remains a leading cause of death and disability worldwide. Effective management of ischemic stroke is heavily influenced by its etiology, which can range from large-artery atherosclerosis and cardiac embolism to cerebral small-vessel occlusions and cryptogenic strokes. Cardioembolic stroke, which makes up about 30% of ischemic strokes, often leads to more severe symptoms and worse outcomes, necessitating anticoagulation therapy for prevention. Cryptogenic strokes, comprising over 25% of ischemic strokes, pose significant challenges for treatment and prevention due to their elusive nature. Thorough investigation of cardioembolic sources during the acute phase of stroke is crucial. While transthoracic and transesophageal echocardiography are traditional methods for detecting intracardiac thrombi and patent foramen ovale (PFO), cardiac CT has emerged as a non-invasive, efficient alternative. Cardiac CT can effectively visualize intracardiac thrombi, PFO, valvular abnormalities, tumors, and complex aortic plaques. This review discusses the potential applications of cardiac CT in ischemic stroke, emphasizing its role in identifying stroke etiology, predicting stroke risk, and assessing patient prognosis. The integration of advanced imaging technologies and artificial intelligence further enhances its diagnostic accuracy and clinical utility, promising to improve outcomes and reduce the healthcare burden associated with ischemic stroke.

Melatonin lessens the susceptibility to atrial fibrillation in sleep deprivation by ameliorating Ca2+ mishandling in response to mitochondrial oxidative stress

BACKGROUND

The antiarrhythmic effect of melatonin(MLT) has been demonstrated in several studies; however, this hypothesis has recently been contested. Our research seeks to determine if exogenous MLT supplementation can reduce atrial fibrillation (AF) susceptibility due to sleep deprivation (SD) by addressing Ca2+ mishandling and atrial mitochondrial oxidative stress.

METHODS

Adult rats received daily MLT or vehicle injections and were exposed to a modified water tank. We evaluated MLT's impact on AF susceptibility by analyzing atrial electrical and structural changes, calcium handling, and oxidative stress markers. Techniques used included electrophysiological recording, echocardiography, optical mapping, histopathology, and molecular assays to understand MLT's protective effects against sleep deprivation-induced AF.

RESULTS

Our findings indicate that MLT treatment effectively mitigates SD-induced AF, safeguards against atrial structural alterations, diminishes mitochondrial oxidative stress and normalizes calcium dynamics. Notably, MLT corrected calcium transient duration (CaD), action potential duration (APD), and conduction heterogeneity, shortened calcium transient refractoriness, and improved arrhythmogenic atrial alternans and spatially discordant alternans, thereby lowering the arrhythmogenic potential of the atria during sleep deprivation. In terms of mechanisms, MLT prevents SD-induced activation of ROS/CaMKII in atrial cardiomyocytes, reversing calcium transient refractoriness and inhibiting arrhythmogenic alternans.

CONCLUSIONS

MLT significantly decreases the susceptibility to SD-induced AF by ameliorating mitochondrial oxidative stress and Ca2+ mishandling. These findings suggest a potential therapeutic application of MLT as an antiarrhythmic intervention for SD-related AF and underscore the need for further investigation, including clinical studies, to validate these mechanisms.

A comprehensive evaluation of the left atrium using cardiovascular magnetic resonance

Atrial disease or myopathy is a growing concept in cardiovascular medicine, particularly in the context of atrial fibrillation, as well as amyloidosis and heart failure. Among cardiac imaging modalities, cardiovascular magnetic resonance (CMR) is particularly well suited for a comprehensive assessment of atrial myopathy, including tissue characterization and hemodynamics. The goal of this review article is to describe clinical applications and make recommendations on pulse sequences as well as imaging parameters to assess the left atrium and left atrial appendage. Furthermore, we aimed to create an overview of current and promising future emerging applications of left atrium-specific CMR pulse sequences focusing on both electrophysiologic (EP) and non-EP applications.

Molecular convergence of risk variants for congenital heart defects leveraging a regulatory map of the human fetal heart

Congenital heart defects (CHD) arise in part due to inherited genetic variants that alter genes and noncoding regulatory elements in the human genome. These variants are thought to act during fetal development to influence the formation of different heart structures. However, identifying the genes, pathways, and cell types that mediate these effects has been challenging due to the immense diversity of cell types involved in heart development as well as the superimposed complexities of interpreting noncoding sequences. As such, understanding the molecular functions of both noncoding and coding variants remains paramount to our fundamental understanding of cardiac development and CHD. Here, we created a gene regulation map of the healthy human fetal heart across developmental time, and applied it to interpret the functions of variants associated with CHD and quantitative cardiac traits. We collected single-cell multiomic data from 734,000 single cells sampled from 41 fetal hearts spanning post-conception weeks 6 to 22, enabling the construction of gene regulation maps in 90 cardiac cell types and states, including rare populations of cardiac conduction cells. Through an unbiased analysis of all 90 cell types, we find that both rare coding variants associated with CHD and common noncoding variants associated with valve traits converge to affect valvular interstitial cells (VICs). VICs are enriched for high expression of known CHD genes previously identified through mapping of rare coding variants. Eight CHD genes, as well as other genes in similar molecular pathways, are linked to common noncoding variants associated with other valve diseases or traits via enhancers in VICs. In addition, certain common noncoding variants impact enhancers with activities highly specific to particular subanatomic structures in the heart, illuminating how such variants can impact specific aspects of heart structure and function. Together, these results implicate new enhancers, genes, and cell types in the genetic etiology of CHD, identify molecular convergence of common noncoding and rare coding variants on VICs, and suggest a more expansive view of the cell types instrumental in genetic risk for CHD, beyond the working cardiomyocyte. This regulatory map of the human fetal heart will provide a foundational resource for understanding cardiac development, interpreting genetic variants associated with heart disease, and discovering targets for cell-type specific therapies.

Circulating ketone bodies, genetic susceptibility, with left atrial remodeling and atrial fibrillation: A prospective study from the UK Biobank

BACKGROUND

Ketone bodies (KBs) are an important cardiac metabolic energy source. Metabolic remodeling has recently been found to play an important role in the pathological process of atrial fibrillation (AF).

OBJECTIVE

The purpose of this study was to evaluate the associations of circulating KB levels with incident AF risk in the general population.

METHODS

We studied 237,163 participants [mean age, 56.5 years; 129,472 women (55%)] from the UK Biobank who were free of AF at baseline and had data on circulating β-hydroxybutyrate (β-OHB), acetoacetate, and acetone. The associations of KBs with new-onset AF were evaluated using Cox regression in the general population and across the 3 genetic risk groups: low, moderate, and high polygenic risk score of AF.

RESULTS

During a median follow-up of 14.8 (13.8, 15.5) years, 16,638 participants (7.0%) developed AF. There was a U-shaped association of total KBs and β-OHB with incident AF, with nadirs at 60.6 and 40.8 μmol/L, respectively (Pnonlinear < .05), whereas there was a positive association of acetoacetate and acetone with AF (Poverall < .001; Pnonlinear > .05). Consistently, there was a U-shaped association of total KBs and β-OHB with left atrial (LA) volume parameters, including LA maximum volume, LA minimum volume, and their body surface area-indexed counterparts, and there was an inverted U-shaped association of total KBs and β-OHB with LA ejection fraction (Pnonlinear < .05 for all). The associations of KBs with AF were stronger in individuals with low genetic risk (Pinteraction < .05), while the highest AF risk was in those with high genetic risk with high KB levels. Significant mediation effects of inflammatory markers on the associations between KBs and AF were identified.

CONCLUSION

There was a U-shaped association of circulating total KBs and β-OHB with incident AF as well as a positive association of acetoacetate and acetone levels with AF risk in the general population.

Heart Failure Risk Assessment Using Biomarkers in Patients With Atrial Fibrillation: Analysis From COMBINE-AF

BACKGROUND

Heart failure (HF) is common among patients with atrial fibrillation (AF), and accurate risk assessment is clinically important.

OBJECTIVES

The goal of this study was to investigate the incremental prognostic performance of N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and growth differentiation factor (GDF)-15 for HF risk stratification in patients with AF.

METHODS

Individual patient data from 3 large randomized trials comparing direct oral anticoagulants (DOACs) with warfarin (ARISTOTLE [Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation], ENGAGE AF-TIMI 48 [Effective Anticoagulation With Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis In Myocardial Infarction 48], and RE-LY [Randomized Evaluation of Long-Term Anticoagulation Therapy]) from the COMBINE-AF (A Collaboration Between Multiple Institutions to Better Investigate Non-Vitamin K Antagonist Oral Anticoagulant Use in Atrial Fibrillation) cohort were pooled; all patients with available biomarkers at baseline were included. The composite endpoint was hospitalization for HF (HHF) or cardiovascular death (CVD), and secondary endpoints were HHF and HF-related death. Cox regression was used, adjusting for clinical factors, and interbiomarker correlation was addressed using weighted quantile sum regression analysis.

RESULTS

In 32,041 patients, higher biomarker values were associated with a graded increase in absolute risk for CVD/HHF, HHF, and HF-related death. Adjusting for clinical variables and all biomarkers, NT-proBNP (HR per 1 SD: 1.68; 95% CI: 1.59-1.77), hs-cTnT (HR: 1.39; 95% CI: 1.33-1.44), and GDF-15 (HR: 1.20; 95% CI: 1.15-1.25) were significantly associated with CVD/HHF. The discrimination of the clinical model improved significantly upon addition of the biomarkers (c-index: 0.70 [95% CI: 0.69-0.71] to 0.77 [95% CI: 0.76-0.78]; likelihood ratio test, P < 0.001). Using weighted quantile sum regression analysis, the contribution to risk assessment was similar for NT-proBNP and hs-cTnT for CVD/HHF (38% and 41%, respectively); GDF-15 provided a statistically significant but lesser contribution to risk assessment. Results were similar for HHF and HF-related death, individually, and across key subgroups of patients based on a history of HF, AF pattern, and reduced or preserved left ventricular ejection fraction.

CONCLUSIONS

NT-proBNP, hs-cTnT, and GDF-15 contributed significantly and independently to the risk stratification for HF endpoints in patients with AF, with hs-cTnT being as important as NT-proBNP for HF risk stratification. Our findings support a possible future use of these biomarkers to distinguish patients with AF at low or high risk for HF.