Optical mapping has become an increasingly important tool to study cardiac electrophysiology in the past 20 years. Multiple methods are used to process and analyze cardiac optical mapping data, and no consensus currently exists regarding the optimum methods. The specific methods chosen to process optical mapping data are important because inappropriate data processing can affect the content of the data and thus alter the conclusions of the studies. Details of the different steps in processing optical imaging data, including image segmentation, spatial filtering, temporal filtering, and baseline drift removal, are provided in this review. We also provide descriptions of the common analyses performed on data obtained from cardiac optical imaging, including activation mapping, action potential duration mapping, repolarization mapping, conduction velocity measurements, and optical action potential upstroke analysis. Optical mapping is often used to study complex arrhythmias, and we also discuss dominant frequency analysis and phase mapping techniques used for the analysis of cardiac fibrillation.

Measurements of cardiac conduction velocity provide valuable functional and structural insight into the initiation and perpetuation of cardiac arrhythmias, in both a clinical and laboratory context. The interpretation of activation wavefronts and their propagation can identify mechanistic properties of a broad range of electrophysiological pathologies. However, the sparsity, distribution and uncertainty of recorded data make accurate conduction velocity calculation difficult. A wide range of mathematical approaches have been proposed for addressing this challenge, often targeted towards specific data modalities, species or recording environments. Many of these algorithms require identification of activation times from electrogram recordings which themselves may have complex morphology or low signal-to-noise ratio. This paper surveys algorithms designed for identifying local activation times and computing conduction direction and speed. Their suitability for use in different recording contexts and applications is assessed.

Atrial fibrillation (AF) is the clinically most prevalent rhythm disorder with large impact on quality of life and increased risk for hospitalizations and mortality in both men and women. In recent years, knowledge regarding epidemiology, risk factors, and patho-physiological mechanisms of AF has greatly increased. Sex differences have been identified in the prevalence, clinical presentation, associated comorbidities, and therapy outcomes of AF. Although it is known that age-related prevalence of AF is lower in women than in men, women have worse and often atypical symptoms and worse quality of life as well as a higher risk for adverse events such as stroke and death associated with AF. In this review, we evaluate what is known about sex differences in AF mechanisms-covering structural, electrophysiological, and hormonal factors-and underscore areas of knowledge gaps for future studies. Increasing our understanding of mechanisms accounting for these sex differences in AF is important both for prognostic purposes and the optimization of (targeted, mechanism-based, and sex-specific) therapeutic approaches.

Background—Recent studies have demonstrated conflicting mechanisms underlying atrial fibrillation (AF), with the spatial resolution of data often cited as a potential reason for the disagreement. The purpose of this study was to investigate whether the variation in spatial resolution of mapping may lead to misinterpretation of the underlying mechanism in persistent AF. Methods and Results—Simulations of rotors and focal sources were performed to estimate the minimum number of recording points required to correctly identify the underlying AF mechanism. The effects of different data types (action potentials and unipolar or bipolar electrograms) and rotor stability on resolution requirements were investigated. We also determined the ability of clinically used endocardial catheters to identify AF mechanisms using clinically recorded and simulated data. The spatial resolution required for correct identification of rotors and focal sources is a linear function of spatial wavelength (the distance between wavefronts) of the arrhythmia. Rotor localization errors are larger for electrogram data than for action potential data. Stationary rotors are more reliably identified compared with meandering trajectories, for any given spatial resolution. All clinical high-resolution multipolar catheters are of sufficient resolution to accurately detect and track rotors when placed over the rotor core although the low-resolution basket catheter is prone to false detections and may incorrectly identify rotors that are not present. Conclusions—The spatial resolution of AF data can significantly affect the interpretation of the underlying AF mechanism. Therefore, the interpretation of human AF data must be taken in the context of the spatial resolution of the recordings.

Background: Ischemic heart disease is a leading cause of heart failure and despite advanced therapeutic options, morbidity and mortality rates remain high. Although acute inflammation in response to myocardial cell death has been extensively studied, subsequent adaptive immune activity and anti-heart autoimmunity may also contribute to the development of heart failure. After ischemic injury to the myocardium, dendritic cells (DC) respond to cardiomyocyte necrosis, present cardiac antigen to T cells, and potentially initiate a persistent autoimmune response against the heart. Cross-priming DC have the ability to activate both CD4 ⁺ helper and CD8 ⁺ cytotoxic T cells in response to necrotic cells and may thus be crucial players in exacerbating autoimmunity targeting the heart. This study investigates a role for cross-priming DC in post–myocardial infarction immunopathology through presentation of self-antigen from necrotic cardiac cells to cytotoxic CD8 ⁺ T cells. Methods: We induced type 2 myocardial infarction–like ischemic injury in the heart by treatment with a single high dose of the β-adrenergic agonist isoproterenol. We characterized the DC population in the heart and mediastinal lymph nodes and analyzed long-term cardiac immunopathology and functional decline in wild type and Clec9a -depleted mice lacking DC cross-priming function. Results: A diverse DC population, including cross-priming DC, is present in the heart and activated after ischemic injury. Clec9a ^−/− mice deficient in DC cross-priming are protected from persistent immune-mediated myocardial damage and decline of cardiac function, likely because of dampened activation of cytotoxic CD8 ⁺ T cells. Conclusion: Activation of cytotoxic CD8 ⁺ T cells by cross-priming DC contributes to exacerbation of postischemic inflammatory damage of the myocardium and corresponding decline in cardiac function. Importantly, this provides novel therapeutic targets to prevent postischemic immunopathology and heart failure.

There is an unmet need to develop low-cost, rapid and highly multiplexed diagnostic technology platforms for quantitatively detecting blood biomarkers to advance clinical diagnostics beyond the single biomarker model. Here we perform nanopore sequencing of DNA-barcoded molecular probes engineered to recognize a panel of analytes. This allows for highly multiplexed and simultaneous quantitative detection of at least 40 targets, such as microRNAs, proteins and neurotransmitters, on the basis of the translocation dynamics of each probe as it passes through a nanopore. Our workflow is built around a commercially available MinION sequencing device, offering a one-hour turnaround time from sample preparation to results. We also demonstrate that the strategy can directly detect cardiovascular disease-associated microRNA from human serum without extraction or amplification. Due to the modularity of barcoded probes, the number and type of targets detected can be significantly expanded.