Pulmonary Veins Function as Echo Chambers in Persistent Atrial Fibrillation: Circuitous Re-Entry Generates Outgoing Wavefronts.

BACKGROUND: Although the substrate in persistent atrial fibrillation (PeAF) is not limited to the pulmonary veins (PVs), PV isolation (PVI) remains the cornerstone ablation strategy. OBJECTIVES: The aim of this study was to describe the mechanism of outgoing wavefronts (WFs) originating in the PV sleeves during PeAF. METHODS: Eleven patients presenting for first-time PeAF ablation were recruited (mean age 63.1 ± 10.9 years, 91% men). A 64-electrode catheter (Constellation; 38 mm) was positioned within the PV under fluoroscopic guidance. An inverse mapping technique was used to reconstruct unipolar atrial electrograms on the PV surface, and the resulting phase maps were used to identify incoming and outgoing WFs at the PV junction and to classify focal and re-entrant activity within the PV sleeves. RESULTS: During PeAF, the PVs gave rise to outgoing WFs with a frequency of 3.7 s-1 (Q1-Q3: 3.4-5.4 s-1) compared with 3.6 s-1 (Q1-Q3: 2.8-4.2 s-1) for incoming WFs. Circuitous macroscopic re-entry was the dominant mechanism driving outgoing WFs (frequency of re-entry 2.7 s-1 [Q1-Q3: 2.0-3.3 s-1] compared with focal activity 1.4 s-1 [Q1-Q3: 1.1-1.5 s-1]; P < 0.006). This was initiated by incoming WFs in 80% of cases. Consecutive focal activation from the same location was infrequent (10.0% ± 6.6%, n = 10). Rotors ≥360° were never observed. The median ratio (R) of outgoing to incoming WF frequency was 1.14 (Q1-Q3: 0.84-1.75), with R > 1 in 6 of 11 PVs. CONCLUSIONS: Electric activity generated by PV sleeves during PeAF is due mainly to circuitous re-entry initiated by incoming waves, frequently with R > 1. That is, the PVs act less as drivers of atrial fibrillation than as "echo chambers" that sustain and amplify fibrillatory activity.

Beatwise ECG Classification for the Detection of Atrial Fibrillation with Deep Learning.

Atrial fibrillation (AF) is the most common, sustained cardiac arrhythmia. Early intervention and treatment could have a much higher chance of reversing AF. An electrocardiogram (ECG) is widely used to check the heart's rhythm and electrical activity in clinics. The current manual processing of ECGs and clinical classification of AF types (paroxysmal, persistent and permanent AF) is ill-founded and does not truly reflect the seriousness of the disease. In this paper, we proposed a new machine learning method for beat-wise classification of ECGs to estimate AF burden, which was defined by the percentage of AF beats found in the total recording time. Both morphological and temporal features for categorizing AF were extracted via two combined classifiers: a 1D U-Net that evaluates fiducial points and segmentation to locate each heartbeat; and the other Recurrent Neural Network (RNN) to enhance the temporal classification of an individual heartbeat. The output of the classifiers had four target classes: Normal Sinus Rhythm (SN), AF, Noises (NO), and Others (OT). The approach was trained and validated on the Icentia11k dataset, with 1001 and 250 patients' ECGs, respectively. The testing accuracy for the four classes was found to be 0.86, 0.81, 0.79, and 0.75, respectively. Our study demonstrated the feasibility and superior performance of combing U-net and RNN to conduct a beat-wise classification of ECGs for AF burden. However, further investigation is warranted to validate this deep learning approach.Clinical relevance- This paper proposes a novel machine learning network for ECG beatwise classification, specifically for aiding AF burden determination.

Image-Based Tools and Analysis for Human RVOT/RV Structures.

The right-ventricular (RV) outflow tract (RVOT) and the transition to the RV free wall are recognized sources of arrhythmia in human hearts. However, we do not fully understand myocardial tissue structures in this region. Human heart tissue was processed for optical clarity, labelled with wheat-germ agglutin (WGA) and anti-Cx43, and imaged on a custom-built line scanning confocal microscope. The 3D images were analyzed for myocyte gross structures and cell morphology. There were regions of high organization as well as rapid changes to more heterogeneous regions. Preliminary cell segmentations were used to estimate cell morphology. Observed RVOT/RV structure is consistent with known arrhythmic substrates.Clinical Relevance- New views of human tissue structure enable clearer clinical understanding of arrhythmogenic activation pathways and targets for invasive treatment such as RF ablation.

Extended-volume image-derived models of coronary microcirculation.

OBJECTIVE: Recent advances in tissue clearing and high-throughput imaging have enabled the acquisition of extended-volume microvasculature images at a submicron resolution. The objective of this study was to extract information from this type of images by integrating a sequence of 3D image processing steps on Terabyte scale datasets. METHODS: We acquired coronary microvasculature images throughout an entire short-axis slice of a 3-month-old Wistar-Kyoto rat heart. This dataset covered 13 × 10 × 0.6 mm at a resolution of 0.933 × 0.933 × 1.866 µm and occupied 700 Gigabytes of disk space. We used chunk-based image segmentation, combined with an efficient graph generation technique, to quantify the microvasculature in the large-scale images. Specifically, we focused on the microvasculature with a vessel diameter up to 15 µm. RESULTS: Morphological data for the complete short-axis ring were extracted within 16 h using this pipeline. From the analyses, we identified that microvessel lengths in the rat coronary microvasculature varied from 6 to 300 µm. However, their distribution was heavily skewed toward shorter lengths, with a mode of 16.5 µm. In contrast, vessel diameters ranged from 3 to 15 µm and had an approximately normal distribution of 6.5 ± 2 µm. CONCLUSION: The tools and techniques from this study will serve other investigations into the microcirculation, and the wealth of data from this study will enable the analysis of biophysical mechanisms using computer models.

Multimodal imaging shows fibrosis architecture and action potential dispersion are predictors of arrhythmic risk in spontaneous hypertensive rats.

Hypertensive heart disease (HHD) increases risk of ventricular tachycardia (VT) and ventricular fibrillation (VF). The roles of structural vs. electrophysiological remodelling and age vs. disease progression are not fully understood. This cross-sectional study of cardiac alterations through HHD investigates mechanistic contributions to VT/VF risk. Risk was electrically assessed in Langendorff-perfused, spontaneously hypertensive rat hearts at 6, 12 and 18 months, and paced optical membrane voltage maps were acquired from the left ventricular (LV) free wall epicardium. Distributions of LV patchy fibrosis and 3D cellular architecture in representative anterior LV mid-wall regions were quantified from macroscopic and microscopic fluorescence images of optically cleared tissue. Imaging showed increased fibrosis from 6 months, particularly in the inner LV free wall. Myocyte cross-section increased at 12 months, while inter-myocyte connections reduced markedly with fibrosis. Conduction velocity decreased from 12 months, especially transverse to the myofibre direction, with rate-dependent anisotropy at 12 and 18 months, but not earlier. Action potential duration (APD) increased when clustered by age, as did APD dispersion at 12 and 18 months. Among 10 structural, functional and age variables, the most reliably linked were VT/VF risk, general LV fibrosis, a measure quantifying patchy fibrosis, and non-age clustered APD dispersion. VT/VF risk related to a quantified measure of patchy fibrosis, but age did not factor strongly. The findings are consistent with the notion that VT/VF risk is associated with rate-dependent repolarization heterogeneity caused by structural remodelling and reduced lateral electrical coupling between LV myocytes, providing a substrate for heterogeneous intramural activation as HHD progresses. KEY POINTS: There is heightened arrhythmic risk with progression of hypertensive heart disease. Risk is related to increasing left ventricular fibrosis, but the nature of this relationship has not been quantified. This study is a novel systematic characterization of changes in active electrical properties and fibrotic remodelling during progression of hypertensive heart disease in a well-established animal disease model. Arrhythmic risk is predicted by several left ventricular measures, in particular fibrosis quantity and structure, and epicardial action potential duration dispersion. Age alone is not a good predictor of risk. An improved understanding of links between arrhythmic risk and fibrotic architectures in progressive hypertensive heart disease aids better interpretation of late gadolinium-enhanced cardiac magnetic resonance imaging and electrical mapping signals.

Non-Contact Intracardiac Potential Mapping Using Mesh-Based and Meshless Inverse Solvers.

Atrial fibrillation (AF) is the most common cardiac dysrhythmia and percutaneous catheter ablation is widely used to treat it. Panoramic mapping with multi-electrode catheters has been used to identify ablation targets in persistent AF but is limited by poor contact and inadequate coverage of the left atrial cavity. In this paper, we investigate the accuracy with which atrial endocardial surface potentials can be reconstructed from electrograms recorded with non-contact catheters. An in-silico approach was employed in which "ground-truth" surface potentials from experimental contact mapping studies and computer models were compared with inverse potential maps constructed by sampling the corresponding intracardiac field using virtual basket catheters. We demonstrate that it is possible to 1) specify the mixed boundary conditions required for mesh-based formulations of the potential inverse problem fully, and 2) reconstruct accurate inverse potential maps from recordings made with appropriately designed catheters. Accuracy improved when catheter dimensions were increased but was relatively stable when the catheter occupied >30% of atrial cavity volume. Independent of this, the capacity of non-contact catheters to resolve the complex atrial potential fields seen in reentrant atrial arrhythmia depended on the spatial distribution of electrodes on the surface bounding the catheter. Finally, we have shown that reliable inverse potential mapping is possible in near real-time with meshless methods that use the Method of Fundamental Solutions.

Intracardiac Inverse Potential Mapping Using the Method of Fundamental Solutions.

Introduction: Atrial fibrillation (AF) is the most prevalent cardiac dysrhythmia and percutaneous catheter ablation is widely used to treat it. Panoramic mapping with multi-electrode catheters can identify ablation targets in persistent AF, but is limited by poor contact and inadequate coverage. Objective: To investigate the accuracy of inverse mapping of endocardial surface potentials from electrograms sampled with noncontact basket catheters. Methods: Our group has developed a computationally efficient inverse 3D mapping technique using a meshless method that employs the Method of Fundamental Solutions (MFS). An in-silico test bed was used to compare ground-truth surface potentials with corresponding inverse maps reconstructed from noncontact potentials sampled with virtual catheters. Ground-truth surface potentials were derived from high-density clinical contact mapping data and computer models. Results: Solutions of the intracardiac potential inverse problem with the MFS are robust, fast and accurate. Endocardial surface potentials can be faithfully reconstructed from noncontact recordings in real-time if the geometry of cardiac surface and the location of electrodes relative to it are known. Larger catheters with appropriate electrode density are needed to resolve complex reentrant atrial rhythms. Conclusion: Real-time panoramic potential mapping is feasible with noncontact intracardiac catheters using the MFS. Significance: Accurate endocardial potential maps can be reconstructed in AF with appropriately designed noncontact multi-electrode catheters.

It's clearly the heart! Optical transparency, cardiac tissue imaging, and computer modelling.

Recent developments in clearing and microscopy enable 3D imaging with cellular resolution up to the whole organ level. These methods have been used extensively in neurobiology, but their uptake in other fields has been much more limited. Application of this approach to the human heart and effective use of the data acquired present challenges of scale and complexity. Four interlinked issues need to be addressed: 1) efficient clearing and labelling of heart tissue, 2) fast microscopic imaging of human-scale samples, 3) handling and processing of multi-terabyte 3D images, and 4) extraction of structural information in computationally tractable structure-based models of cardiac function. Preliminary studies show that each of these requirements can be achieved with the appropriate application and development of existing technologies.

A novel system for mapping regional electrical properties and characterizing arrhythmia in isolated intact rat atria.

Detailed global maps of atrial electrical activity are needed to understand mechanisms of atrial rhythm disturbance in small animal models of heart disease. To date, optical mapping systems have not provided enough spatial resolution across sufficiently extensive regions of intact atrial preparations to achieve this goal. The aim of this study was to develop an integrated platform for quantifying regional electrical properties and analyzing reentrant arrhythmia in a biatrial preparation. Intact atria from 6/7-mo-old female spontaneously hypertensive rats (SHRs; n = 6) were isolated and secured in a constant flow superfusion chamber at 37°C. Optical mapping was performed with the membrane-voltage dye di-4-ANEPPS using LED excitation and a scientific complementary metal-oxide semiconductor (sCMOS) camera. Programmed stimulus trains were applied from right atrial (RA) and left atrial (LA) sites to assess rate-dependent electrical behavior and to induce atrial arrhythmia. Signal-to-noise ratio was improved by sequential processing steps that included spatial smoothing, temporal filtering, and, in stable rhythms, ensemble-averaging. Activation time, repolarization time, and action potential duration (APD) maps were constructed at high spatial resolution for a wide range of coupling intervals. These data were highly consistent within and between experiments. They confirmed preferential atrial conduction pathways and demonstrated distinct medial-to-lateral APD gradients. We also showed that reentrant arrhythmias induced in this preparation were explained by the spatial variation of these electrical properties. Our new methodology provides a robust means of 1) quantifying regional electrical properties in the intact rat atria at higher spatiotemporal resolution than previously reported, and 2) characterizing reentrant arrhythmia and analyzing mechanisms that give rise to it.NEW & NOTEWORTHY Despite wide-ranging optical mapping studies, detailed information on regional atrial electrical properties in small animal models of heart disease and how these contribute to reentrant arrhythmia remains limited. We have developed a novel experimental platform that enables both to be achieved in a geometrically intact isolated rat bi-atrial preparation.

Evidence of structural and functional plasticity occurring within the intracardiac nervous system of spontaneously hypertensive rats.

Plasticity is a fundamental property of neurons in both the central and peripheral nervous systems, enabling rapid changes in neural network function. The intracardiac nervous system (ICNS) is an extensive network of neurons clustered into ganglionated plexi (GP) on the surface of the heart. GP neurons are the final site of neuronal control of heart rhythm, and pathophysiological remodeling of the ICNS is proposed to feature in multiple cardiovascular diseases, including heart failure and atrial fibrillation. To examine the potential role of GP neuron plasticity in atrial arrhythmia and hypertension, we developed whole cell patch clamp recording techniques from GP neurons in isolated ICNS preparations from aged control (Wistar-Kyoto) and spontaneously hypertensive rats (SHRs). Anesthetized SHRs showed frequent premature ventricular contractions and episodes of atrial arrhythmia following carbachol injection, and isolated SHR atrial preparations were susceptible to pacing induced atrial arrhythmia. Whole cell recordings revealed elevated spontaneous postsynaptic current frequency in SHR GP neurons, as well as remodeled electrophysiology, with significant decreases in action potential amplitude and half-width. SHRs also showed a parallel increase in the number of cholinergic neurons and adrenergic glomus cells in cardiac ganglia, a higher proportion of synaptic α7-subunit but not ß2-containing nicotinic receptors, and an elevation in the number of synaptic terminals onto GP neurons. Our data show that significant structural and functional plasticity occurs in the intracardiac nervous system and suggest that enhanced excitability through synaptic plasticity, together with remodeling of cardiac neuron electrophysiology, contributes to the substrate for atrial arrhythmia in hypertensive heart disease.NEW & NOTEWORTHY We have developed intracardiac neuron whole cell recording techniques in atrial preparations from control and spontaneous hypertensive rats. This has enabled the identification of significant synaptic plasticity in the intracardiac nervous system, including enhanced postsynaptic current frequency, increased synaptic terminal density, and altered postsynaptic receptors. This increased synaptic drive together with altered cardiac neuron electrophysiology could increase intracardiac nervous system excitability and contribute to the substrate for atrial arrhythmia in hypertensive heart disease.

Cardiac intramural electrical mapping reveals focal delays but no conduction velocity slowing in the peri-infarct region.

Altered electrical behavior alongside healed myocardial infarcts (MIs) is associated with increased risk of sudden cardiac death. However, the multidimensional mechanisms are poorly understood and described. This study characterizes, for the first time, the intramural spread of electrical activation in the peri-infarct region of chronic reperfusion MIs. Four sheep were studied 13 wk after antero-apical reperfusion infarction. Extracellular potentials (ECPs) were recorded in a ~20 × 20-mm2 region adjacent to the infarct boundary (25 plunge needles <0.5-mm diameter with 15 electrodes at 1-mm centers) during multisite stimulation. Infarct geometry and electrode locations were reconstructed from magnetic resonance images. Three-dimensional activation spread was characterized by local activation times and interpolated ECP fields (n = 191 records). Control data were acquired in 4 non-infarcted sheep (n = 96 records). Electrodes were distributed uniformly around 15 ± 5% of the intramural infarct boundary. There were marked changes in pacing success and ECP morphology across a functional border zone (BZ) ±2 mm from the boundary. Stimulation adjacent to the infarct boundary was associated with low-amplitude electrical activity within the BZ and delayed activation of surrounding myocardium. Bulk tissue depolarization occurred 3.5-14.6 mm from the pacing site for 39% of stimuli with delays of 4-37 ms, both significantly greater than control (P < 0.0001). Conduction velocity (CV) adjacent to the infarct was not reduced compared with control, consistent with structure-only computer model results. Insignificant CV slowing, irregular stimulus-site specific activation delays, and obvious indirect activation pathways strongly suggest that the substrate for conduction abnormalities in chronic MI is predominantly structural in nature.NEW & NOTEWORTHY Intramural in vivo measurements of peri-infarct electrical activity were not available before this study. We use pace-mapping in a three-dimensional electrode array to show that a subset of stimuli in the peri-infarct region initiates coordinated myocardial activation some distance from the stimulus site with substantial associated time delays. This is site dependent and heterogeneous and occurs for <50% of ectopic stimuli in the border zone. Furthermore, once coordinated activation is initiated, conduction velocity adjacent to the infarct boundary is not significantly different from control. These results give new insights to peri-infarct electrical activity and do not support the widespread view of uniform electrical remodeling in the border zone of chronic myocardial infarcts, with depressed conduction velocity throughout.

Shift of leading pacemaker site during reflex vagal stimulation and altered electrical source-to-sink balance.

KEY POINTS: Vagal reflexes slow heart rate and can change where the heartbeat originates within the sinoatrial node (SAN). The mechanisms responsible for this process - termed leading pacemaker (LP) shift - have not been investigated fully. We used optical mapping to measure the effects of baroreflex, chemoreflex and carbachol on pacemaker entrainment and electrical conduction across the SAN. All methods of stimulation triggered shifts in LP site from the central SAN to one or two caudal pacemaker regions. These shifts were associated with reduced current generation capacity centrally and increased electrical load caudally. Previous studies suggest LP shift is a rate-dependent phenomenon whereby acetylcholine slows central pacemaker rate disproportionately, enabling caudal cells that are less acetylcholine sensitive to assume control. However, our findings indicate the LP region is defined by both pacemaker rate and capacity to drive activation. Shifts in LP site provide an important homeostatic mechanism for rapid switches in heart rate. ABSTRACT: Reflex vagal activity causes abrupt heart rate slowing with concomitant caudal shifts of the leading pacemaker (LP) site within the sinoatrial node (SAN). However, neither the mechanisms responsible nor their dynamics have been investigated fully. Therefore, the objective of this study was to elucidate the mechanisms driving cholinergic LP shift. Optical maps of right atrial activation were acquired in a rat working heart-brainstem preparation during baroreflex and chemoreflex stimulation or with carbachol. All methods of stimulation triggered shifts in LP site from the central SAN to caudal pacemaker regions, which were positive for HCN4 and received uniform cholinergic innervation. During baroreflex onset, the capacity of the central region to drive activation declined with a decrease in amplitude and gradient of optical action potentials (OAPs) in the surrounding myocardium. Accompanying this decline, there was altered entrainment in the caudal SAN as shown by decreased conduction velocity, OAP amplitude, gradient and activation time. Atropine abolished these responses. Chemoreflex stimulation produced similar effects but central capacity to drive activation was preserved before the LP shift. In contrast, carbachol produced a prolonged period of reduced capacity to drive and altered entrainment. Previous studies suggest LP shift is a rate-dependent phenomenon whereby acetylcholine slows central pacemaker rate disproportionately, enabling caudal cells that are less acetylcholine sensitive to assume control. Our findings indicate that cholinergic LP shifts are also determined by altered electrical source-to-sink balance in the SAN. We conclude that the LP region is defined by both rate and capacity to drive atrial activation.

Reconstruction of coronary circulation networks: A review of methods.

Building anatomically accurate models of the coronary vascular system enables potentially deeper understandings of coronary circulation. To achieve this, (a) images at different levels of vascular network-arteries, arterioles, capillaries, venules, and veins-need to be obtained through suitable imaging modalities; and (b) from images, morphological and topological information needs to be extracted using image processing techniques. While there are several modalities that enable the imaging of large vessels, microcirculation imaging-capturing vessels having diameter lesser than 100 µm-has to date been typically confined to small regions of the heart. This spatially limited microcirculatory information has often been used within cardiac models, with the potentially erroneous assumption that it is representative of the whole organ. However, with the recent advancements in imaging and image processing, it is rapidly becoming feasible to acquire, process, and quantify microcirculation data at the scale of whole organ. In this review, we summarize the progress toward this goal followed through a presentation of the current state-of-the-art imaging and image processing techniques in the context of coronary microcirculation extraction, prominently but not exclusively, from small animals.

Quantitative descriptions of extended volume cardiac tissue architecture from multiple large hearts.

The arrangement of cardiac cells into strand and sheet-like structures within the heart wall, confers important electrical properties onto heart tissue. Unraveling cardiomyocyte architecture in both healthy and diseased hearts is fundamental to understanding the mechanisms generating normal rhythm and arrhythmia. We analyzed five extended volume serial image stacks of normal pig left ventricular tissue. Analysis included: (1) reconstruction of original tissue volume and shape with non-linear correction maps; (2) segmentation and higher-order descriptions, areas and orientations of laminar structures through the heart wall; (3)computation of fiber directions; (4) computation of tissue connectivity using a shell filter. These measures contributed to a deeper and more objective understanding of cardiac tissue structures and their spatial variation than previously possible.

A Machine Learning Aided Systematic Review and Meta-Analysis of the Relative Risk of Atrial Fibrillation in Patients With Diabetes Mellitus.

Background: Meta-analysis is a widely used tool in which weighted information from multiple similar studies is aggregated to increase statistical power. However, the exponential growth of publications in key areas of medical science has rendered manual identification of relevant studies increasingly time-consuming. The aim of this work was to develop a machine learning technique capable of robust automatic study selection for meta-analysis. We have validated this approach with an up-to-date meta-analysis to investigate the association between diabetes mellitus (DM) and new-onset atrial fibrillation (AF). Methods: The PubMed online database was searched from 1960 to September 2017 where 4,177 publications that mentioned both DM and AF were identified. Relevant studies were selected as follows. First, publications were clustered based on common text features using an unsupervised K-means algorithm. Clusters that best matched the selected set of potentially relevant studies (a "training" set of 139 articles) were then identified by using maximum entropy classification. The 139 articles selected automatically on this basis were screened manually to identify potentially relevant studies. To determine the validity of the automated process, a parallel set of studies was also assembled by manually screening all initially searched publications. Finally, detailed manual selection was performed on the full texts of the studies in both sets using standard criteria. Quality assessment, meta-regression random-effects models, sensitivity analysis and publication bias assessment were then conducted. Results: Machine learning-assisted screening identified the same 29 studies for meta-analysis as those identified by using manual screening alone. Machine learning enabled more robust and efficient study selection, reducing the number of studies needed for manual screening from 4,177 to 556 articles. A pooled analysis using the most conservative estimates indicated that patients with DM had ~49% greater risk of developing AF compared with individuals without DM. After adjusting for three additional risk factors i.e., hypertension, obesity and heart disease, the relative risk was 23%. Using multivariate adjusted models, the risk for developing AF in patients with DM was similar for all DM subtypes. Women with DM were 24% more likely to develop AF than men with DM. The risk for new-onset AF in patients with DM has also increased over the years. Conclusions: We have developed a novel machine learning method to identify publications suitable for inclusion in meta-analysis.This approach has the capacity to provide for a more efficient and more objective study selection process for future such studies. We have used it to demonstrate that DM is a strong, independent risk factor for AF, particularly for women.

Segmentation of histological images and fibrosis identification with a convolutional neural network.

Segmentation of histological images is one of the most crucial tasks for many biomedical analyses involving quantification of certain tissue types, such as fibrosis via Masson's trichrome staining. However, challenges are posed by the high variability and complexity of structural features in such images, in addition to imaging artifacts. Further, the conventional approach of manual thresholding is labor-intensive, and highly sensitive to inter- and intra-image intensity variations. An accurate and robust automated segmentation method is of high interest. We propose and evaluate an elegant convolutional neural network (CNN) designed for segmentation of histological images, particularly those with Masson's trichrome stain. The network comprises 11 successive convolutional - rectified linear unit - batch normalization layers. It outperformed state-of-the-art CNNs on a dataset of cardiac histological images (labeling fibrosis, myocytes, and background) with a Dice similarity coefficient of 0.947. With 100 times fewer (only 300,000) trainable parameters than the state-of-the-art, our CNN is less susceptible to overfitting, and is efficient. Additionally, it retains image resolution from input to output, captures fine-grained details, and can be trained end-to-end smoothly. To the best of our knowledge, this is the first deep CNN tailored to the problem of concern, and may potentially be extended to solve similar segmentation tasks to facilitate investigations into pathology and clinical treatment.

How Accurate Is Inverse Electrocardiographic Mapping? A Systematic In Vivo Evaluation.

BACKGROUND: Inverse electrocardiographic mapping reconstructs cardiac electrical activity from recorded body surface potentials. This noninvasive technique has been used to identify potential ablation targets. Despite this, there has been little systematic evaluation of its reliability. METHODS: Torso and ventricular epicardial potentials were recorded simultaneously in anesthetized, closed-chest pigs (n=5), during sinus rhythm, epicardial, and endocardial ventricular pacing (70 records in total). Body surface and cardiac electrode positions were determined and registered using magnetic resonance imaging. Epicardial potentials were reconstructed during ventricular activation using experiment-specific magnetic resonance imaging-based thorax models, with homogeneous or inhomogeneous (lungs, skeletal muscle, fat) electrical properties. Coupled finite/boundary element methods and a meshless approach based on the method of fundamental solutions were compared. Inverse mapping underestimated epicardial potentials >2-fold (P<0.0001). RESULTS: Mean correlation coefficients for reconstructed epicardial potential distributions ranged from 0.60±0.08 to 0.64±0.07 across all methods. Epicardial electrograms were recovered with reasonable fidelity at ≈50% of sites (median correlation coefficient, 0.69-0.72), but variation was substantial. General activation spread was reproduced (median correlation coefficient, 0.72-0.78 for activation time maps after spatio-temporal smoothing). Epicardial foci were identified with a median location error ≈16 mm (interquartile range, 9-29 mm). Inverse mapping with meshless method of fundamental solutions was better than with finite/boundary element methods, and the latter were not improved by inclusion of inhomogeneous torso electrical properties. CONCLUSIONS: Inverse potential mapping provides useful information on the origin and spread of epicardial activation. However the spatio-temporal variability of recovered electrograms limit resolution and must constrain the accuracy with which arrhythmia circuits can be identified independently using this approach.

Synaptic Plasticity in Cardiac Innervation and Its Potential Role in Atrial Fibrillation.

Synaptic plasticity is defined as the ability of synapses to change their strength of transmission. Plasticity of synaptic connections in the brain is a major focus of neuroscience research, as it is the primary mechanism underpinning learning and memory. Beyond the brain however, plasticity in peripheral neurons is less well understood, particularly in the neurons innervating the heart. The atria receive rich innervation from the autonomic branch of the peripheral nervous system. Sympathetic neurons are clustered in stellate and cervical ganglia alongside the spinal cord and extend fibers to the heart directly innervating the myocardium. These neurons are major drivers of hyperactive sympathetic activity observed in heart disease, ventricular arrhythmias, and sudden cardiac death. Both pre- and postsynaptic changes have been observed to occur at synapses formed by sympathetic ganglion neurons, suggesting that plasticity at sympathetic neuro-cardiac synapses is a major contributor to arrhythmias. Less is known about the plasticity in parasympathetic neurons located in clusters on the heart surface. These neuronal clusters, termed ganglionated plexi, or "little brains," can independently modulate neural control of the heart and stimulation that enhances their excitability can induce arrhythmia such as atrial fibrillation. The ability of these neurons to alter parasympathetic activity suggests that plasticity may indeed occur at the synapses formed on and by ganglionated plexi neurons. Such changes may not only fine-tune autonomic innervation of the heart, but could also be a source of maladaptive plasticity during atrial fibrillation.

Development of 3-D Intramural and Surface Potentials in the LV: Microstructural Basis of Preferential Transmural Conduction.

INTRODUCTION: Extracellular potentials measured on the heart surfaces are used to infer events that originate deep within the heart wall. We have reconstructed intramural potentials in three dimensions for the first time, and compare these with epicardial and endocardial surface potentials and cardiac microstructure. METHODS AND RESULTS: Extracellular potentials from intramural point stimulation were measured from a high density 3-D electrode array in the in vivo pig LV. MR and extended volume imaging were used to register electrode locations and characterize fiber and laminar orientations throughout the recording volume. Measured potentials were compared with predictions of tissue-specific bidomain computer activation models. Positive potentials recorded in the LV wall preceded the depolarization wavefront as it spread in the fiber direction. Transverse to this, passive and active potentials spread preferentially in the laminar direction (anisotropy ratio ∼1.6:1). Epicardial surface potentials reflect initial intramural propagation at the stimulus location, but endocardial potentials do not, particularly adjacent to papillary muscles. Measured 3-D potentials were consistently better captured by computer models that incorporate three distinct conductivities aligned with local microstructural axes, but the preferential spread of potentials in the laminar direction was not fully predicted. CONCLUSIONS: This study provides evidence for preferential transmural conduction and raises questions about the extent to which intramural electrical events can be inferred from endocardial potentials.

Comparison of diffusion tensor imaging by cardiovascular magnetic resonance and gadolinium enhanced 3D image intensity approaches to investigation of structural anisotropy in explanted rat hearts.

BACKGROUND: Cardiovascular magnetic resonance (CMR) can through the two methods 3D FLASH and diffusion tensor imaging (DTI) give complementary information on the local orientations of cardiomyocytes and their laminar arrays. METHODS: Eight explanted rat hearts were perfused with Gd-DTPA contrast agent and fixative and imaged in a 9.4T magnet by two types of acquisition: 3D fast low angle shot (FLASH) imaging, voxels 50 × 50 × 50 µm, and 3D spin echo DTI with monopolar diffusion gradients of 3.6 ms duration at 11.5 ms separation, voxels 200 × 200 × 200 µm. The sensitivity of each approach to imaging parameters was explored. RESULTS: The FLASH data showed laminar alignments of voxels with high signal, in keeping with the presumed predominance of contrast in the interstices between sheetlets. It was analysed, using structure-tensor (ST) analysis, to determine the most (v1(ST)), intermediate (v2(ST)) and least (v3(ST)) extended orthogonal directions of signal continuity. The DTI data was analysed to determine the most (e1(DTI)), intermediate (e2(DTI)) and least (e3(DTI)) orthogonal eigenvectors of extent of diffusion. The correspondence between the FLASH and DTI methods was measured and appraised. The most extended direction of FLASH signal (v1(ST)) agreed well with that of diffusion (e1(DTI)) throughout the left ventricle (representative discrepancy in the septum of 13.3 ± 6.7°: median ± absolute deviation) and both were in keeping with the expected local orientations of the long-axis of cardiomyocytes. However, the orientation of the least directions of FLASH signal continuity (v3(ST)) and diffusion (e3(ST)) showed greater discrepancies of up to 27.9 ± 17.4°. Both FLASH (v3(ST)) and DTI (e3(DTI)) where compared to directly measured laminar arrays in the FLASH images. For FLASH the discrepancy between the structure-tensor calculated v3(ST) and the directly measured FLASH laminar array normal was of 9 ± 7° for the lateral wall and 7 ± 9° for the septum (median ± inter quartile range), and for DTI the discrepancy between the calculated v3(DTI) and the directly measured FLASH laminar array normal was 22 ± 14° and 61 ± 53.4°. DTI was relatively insensitive to the number of diffusion directions and to time up to 72 hours post fixation, but was moderately affected by b-value (which was scaled by modifying diffusion gradient pulse strength with fixed gradient pulse separation). Optimal DTI parameters were b = 1000 mm/s(2) and 12 diffusion directions. FLASH acquisitions were relatively insensitive to the image processing parameters explored. CONCLUSIONS: We show that ST analysis of FLASH is a useful and accurate tool in the measurement of cardiac microstructure. While both FLASH and the DTI approaches appear promising for mapping of the alignments of myocytes throughout myocardium, marked discrepancies between the cross myocyte anisotropies deduced from each method call for consideration of their respective limitations.