Association of low-voltage areas with the regional wall deformation and the left atrial shape in patients with atrial fibrillation: A proof of concept study

Atrial cardiomyopathy revisited-evolution of a concept: a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS)

AIMS

The concept of "atrial cardiomyopathy" (AtCM) had been percolating through the literature since its first mention in 1972. Since then, publications using the term were sporadic until the decision was made to convene an expert working group with representation from four multinational arrhythmia organizations to prepare a consensus document on atrial cardiomyopathy in 2016 (EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: definition, characterization, and clinical implication). Subsequently, publications on AtCM have increased progressively.

METHODS AND RESULTS

The present consensus document elaborates the 2016 AtCM document further to implement a simple AtCM staging system (AtCM stages 1-3) by integrating biomarkers, atrial geometry, and electrophysiological changes. However, the proposed AtCM staging needs clinical validation. Importantly, it is clearly stated that the presence of AtCM might serve as a substrate for the development of atrial fibrillation (AF) and AF may accelerates AtCM substantially, but AtCM per se needs to be viewed as a separate entity.

CONCLUSION

Thus, the present document serves as a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS) to contribute to the evolution of the AtCM concept.

The Atrium in Atrial Fibrillation - A Clinical Review on How to Manage Atrial Fibrotic Substrates

Atrial fibrillation (AF) is the most common sustained arrhythmia in the population and is associated with a significant clinical and economic burden. Rigorous assessment of the presence and degree of an atrial arrhythmic substrate is essential for determining treatment options, predicting long-term success after catheter ablation, and as a substrate critical in the pathophysiology of atrial thrombogenesis. Catheter ablation of AF has developed into an essential rhythm-control strategy. Nowadays is one of the most common cardiac ablation procedures performed worldwide, with its success inversely related to the extent of atrial structural disease. Although atrial substrate evaluation remains complex, several diagnostic resources allow for a more comprehensive assessment and quantification of the extent of left atrial structural remodeling and the presence of atrial fibrosis. In this review, we summarize the current knowledge on the pathophysiology, etiology, and electrophysiological aspects of atrial substrates promoting the development of AF. We also describe the risk factors for its development and how to diagnose its presence using imaging, electrocardiograms, and electroanatomic voltage mapping. Finally, we discuss recent data regarding fibrosis biomarkers that could help diagnose atrial fibrotic substrates.

Big Data in electrophysiology

The quantity of data produced and captured in medicine today is unprecedented. Technological improvements and automation have expanded the traditional statistical methods and enabled the analysis of Big Data. This has permitted the discovery of new associations with a granularity that was previously hidden to human eyes. In the first part of this review, the authors would like to provide an overview of basic Machine Learning (ML) principles and techniques in order to better understand their application in recent publications about cardiac arrhythmias. In the second part, ML-enabled advances in disease detection and diagnosis, outcome prediction, and novel disease characterization in topics like electrocardiography, atrial fibrillation, ventricular arrhythmias, and cardiac devices are presented. Finally, the limitations and challenges of applying ML in clinical practice, such as validation, replication, generalizability, and regulatory issues, are discussed. More carefully designed studies and collaborations are needed for ML to become feasible, trustworthy, accurate, and reproducible and to reach its full potential for patient-oriented precision medicine.

Revisiting left atrial volumetry by magnetic resonance imaging: the role of atrial shape and 3D angle between left ventricular and left atrial axis

Background

Accurate measurement of left atrial (LA) volumes is needed in cardiac diagnostics and the follow up of heart and valvular diseases. Geometrical assumptions with 2D methods for LA volume estimation contribute to volume misestimation. In this study, we test agreement of 3D and 2D methods of LA volume detection and explore contribution of 3D LA axis orientation and LA shape in introducing error in 2D methods by cardiovascular magnetic resonance imaging.

Methods

30 patients with prior first-ever ischemic stroke and no known heart disease, and 30 healthy controls were enrolled (age 18–49) in a substudy of a prospective case–control study. All study subjects underwent cardiac magnetic resonance imaging and were pooled for this methodological study. LA volumes were calculated by biplane area-length method from both conventional long axis (LAV_AL-LV) and LA long axis-oriented images (LAV_AL-LA) and were compared to 3D segmented LA volume (LAV_SAX) to assess accuracy of volume detection. 3D orientation of LA long axis to left ventricular (LV) long axis and to four-chamber plane were determined, and LA 3D sphericity indices were calculated to assess sources of error in LA volume calculation. Shapiro–Wilk test, Bland–Altman analysis, intraclass and Pearson correlation, and Spearman’s rho were used for statistical analysis.

Results

Biases were − 9.9 mL (− 12.5 to − 7.2) for LAV_AL-LV and 13.4 (10.0–16.9) for LAV_AL-LA [mean difference to LAV_SAX (95% confidence interval)]. End-diastolic LA long axis 3D deviation angle to LV long axis was 28.3 ± 6.2° [mean ± SD] and LA long axis 3D rotation angle to four-chamber plane 20.5 ± 18.0°. 3D orientation of LA axis or 3D sphericity were not correlated to error in LA volume calculation.

Conclusions

Calculated LA volume accuracy did not improve by using LA long axis-oriented images for volume calculation in comparison to conventional method. We present novel data on LA axis orientation and a novel metric of LA sphericity and conclude that these measures cannot be utilized to assess error in LA volume calculation.

Trial registration

Main study Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Etiology, Triggers, and Outcome (SECRETO; NCT01934725) has been registered previously.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-021-00701-5.

Biatrial volume ratio predicts low voltage areas in atrial fibrillation

BACKGROUND

Left atrial volume (LAV) and low voltage areas (LVAs) are acknowledged markers for worse rhythm outcome after ablation of atrial fibrillation (AF). Some studies reported the importance of increased right atrial volume (RAV) as a predictor for arrhythmia recurrences in AF patients.

OBJECTIVE

To investigate association between the LAV/RAV ratio and LVAs presence.

METHODS

Patients undergoing first AF ablation were included. LVAs were assessed peri-procedurally using high-density 3D maps and defined as <0.5 mV. All patients underwent pre-procedural cardiovascular magnetic resonance imaging. LAV (biplane) and RAV (monoplane 4-chamber) were assessed prior to ablation, and the LAV/RAV ratio was calculated.

RESULTS

The study population included 189 patients (age mean 63 ± 10 years, 33% women, 57% persistent AF, 22% LVAs). There were 149 (79%) patients with LAV > RAV. In univariable analysis LAV > RAV was associated with LVAs (OR 6.803, 95%CI 1.395-26.514, p = .016). The association remained robust in multivariable model after adjustment for persistent AF, CHA₂ DS₂ -VASc score, and heart rate (OR 5.981, 95%CI 1.256-28.484, p = .025). Using receiver operator curve analysis, LAV > RAV (AUC 0.668, 95%CI 0.585-0.751, p = .001) was significant predictor for LVAs. In multivariable analysis, after adjustment for age, persistent AF, and renal function, RAV≥LAV was threefold higher in males (OR 3.040, 95%CI 1.050-8.802, p = .04).

CONCLUSIONS

LAV > RAV is useful for the prediction of electro-anatomical substrate in AF. LAV > RAV was associated with LVAs presence, while male sex remained associated with RAV≥LAV and less LVAs.

Atrial remodeling and atrial fibrillation recurrence after catheter ablation : Past, present, and future developments

The term "atrial remodeling" is used to describe the electrical, mechanical, and structural changes associated with the presence of an arrhythmogenic substrate for atrial fibrillation. Rhythm control therapy may slow down or even reverse progressive atrial remodeling. Atrial remodeling has long been recognized as an important predictor of clinical outcomes and therapeutic success, but recent advances have highlighted its clinical relevance and revealed the implications of specific anatomical changes such as atrial asymmetry or shape. This has opened the path to computational precision medicine that captures these data in detail and combines them with other factors, to provide patient-specific solutions. The goal of precision medicine lies in improving clinical outcomes, reducing costs, and avoiding unnecessary procedures. In this article, we review the history of atrial remodeling and we summarize the insights from our research on anatomical atrial remodeling and its association with rhythm outcomes after catheter ablation. Finally, we present recent advances in the field, reflecting the beginning of a new technological era that will enable us to improve patient care by personalized patient-specific medicine.