Identification of Brugada syndrome based on P-wave features: an artificial intelligence-based approach.

AIMS: Brugada syndrome (BrS) is an inherited disease associated with an increased risk of ventricular arrhythmias. Recent studies have reported the presence of an altered atrial phenotype characterized by abnormal P-wave parameters. The aim of this study was to identify BrS based exclusively on P-wave features through an artificial intelligence (AI)-based model. METHODS AND RESULTS: Continuous 5 min 12-lead ECG recordings were obtained in sinus rhythm from (i) patients with spontaneous or ajmaline-induced BrS and no history of AF and (ii) subjects with suspected BrS and negative ajmaline challenge. The recorded ECG signals were processed and divided into epochs of 15 s each. Within these epochs, P-waves were first identified and then averaged. From the averaged P-waves, a total of 67 different features considered relevant to the classification task were extracted. These features were then used to train nine different AI-based supervised classifiers. A total of 2228 averaged P-wave observations, resulting from the analysis of 33 420 P-waves, were obtained from 123 patients (79 BrS+ and 44 BrS-). Averaged P-waves were divided using a patient-wise split, allocating 80% for training and 20% for testing, ensuring data integrity and reducing biases in AI-based model training. The BrS+ patients presented with longer P-wave duration (136 ms vs. 124 ms, P < 0.001) and higher terminal force in lead V1 (2.5 au vs. 1.7 au, P < 0.01) compared with BrS- subjects. Among classifiers, AdaBoost model had the highest values of performance for all the considered metrics, reaching an accuracy of over 81% (sensitivity 86%, specificity 73%). CONCLUSION: An AI machine-learning model is able to identify patients with BrS based only on P-wave characteristics. These findings confirm the presence of an atrial hallmark and open new horizons for AI-guided BrS diagnosis.

Coronary artery disease in atrial fibrillation ablation: impact on arrhythmic outcomes.

AIMS: Catheter ablation (CA) is an established treatment for atrial fibrillation (AF). A computed tomography (CT) may be performed before ablation to evaluate the anatomy of pulmonary veins. The aim of this study is to investigate the prevalence of patients with coronary artery disease (CAD) detected by cardiac CT scan pre-ablation and to evaluate the impact of CAD and revascularization on outcomes after AF ablation. METHODS AND RESULTS: All consecutive patients with AF diagnosis, hospitalized at Universitair Ziekenhuis Brussel, Belgium, between 2015 and 2019, were prospectively screened for enrolment in the study. Inclusion criteria were (i) AF diagnosis, (ii) first procedure of AF ablation with cryoballoon CA, and (iii) contrast CT scan performed pre-ablation. A total of 576 consecutive patients were prospectively included and analysed in this study. At CT scan, 122 patients (21.2%) were diagnosed with CAD, of whom 41 patients (7.1%) with critical CAD. At survival analysis, critical CAD at CT scan was a predictor of atrial tachyarrhythmia (AT) recurrence during the follow-up, only in Cox univariate analysis [hazard ratio (HR) = 1.79] but was not an independent predictor in Cox multivariate analysis. At Cox multivariate analysis, independent predictors of AT recurrence were as follows: persistent AF (HR = 2.93) and left atrium volume index (HR = 1.04). CONCLUSION: In patients undergoing CT scan before AF ablation, critical CAD was diagnosed in 7.1% of patients. Coronary artery disease and revascularization were not independent predictors of recurrence; thus, in this patient population, AF ablation should not be denied and can be performed together with CAD treatment.

Automatic reconstruction of the left atrium activation from sparse intracardiac contact recordings by inverse estimate of fibre structure and anisotropic conduction in a patient-specific model.

AIMS: Electric conduction in the atria is direction-dependent, being faster in fibre direction, and possibly heterogeneous due to structural remodelling. Intracardiac recordings of atrial activation may convey such information, but only with high-quality data. The aim of this study was to apply a patient-specific approach to enable such assessment even when data are scarce, noisy, and incomplete. METHODS AND RESULTS: Contact intracardiac recordings in the left atrium from nine patients who underwent ablation therapy were collected before pulmonary veins isolation and retrospectively included in the study. The Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps (PIEMAP), previously developed, has been used to reconstruct the conductivity tensor from sparse recordings of the activation. Regional fibre direction and conduction velocity were estimated from the fitted conductivity tensor and extensively cross-validated by clustered and sparse data removal. Electrical conductivity was successfully reconstructed in all patients. Cross-validation with respect to the measurements was excellent in seven patients (Pearson correlation r > 0.93) and modest in two patients (r = 0.62 and r = 0.74). Bland-Altman analysis showed a neglectable bias with respect to the measurements and the limit-of-agreement at -22.2 and 23.0 ms. Conduction velocity in the fibre direction was 82 ± 25 cm/s, whereas cross-fibre velocity was 46 ± 7 cm/s. Anisotropic ratio was 1.91±0.16. No significant inter-patient variability was observed. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps correctly predicted activation times in late regions in all patients (r = 0.88) and was robust to a sparser dataset (r = 0.95). CONCLUSION: Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps offers a novel approach to extrapolate the activation in unmapped regions and to assess conduction properties of the atria. It could be seamlessly integrated into existing electro-anatomic mapping systems. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps also enables personalization of cardiac electrophysiology models.

Synergistic antiarrhythmic effect of inward rectifier current inhibition and pulmonary vein isolation in a 3D computer model for atrial fibrillation.

AIMS: Recent clinical studies showed that antiarrhythmic drug (AAD) treatment and pulmonary vein isolation (PVI) synergistically reduce atrial fibrillation (AF) recurrences after initially successful ablation. Among newly developed atrial-selective AADs, inhibitors of the G-protein-gated acetylcholine-activated inward rectifier current (IKACh) were shown to effectively suppress AF in an experimental model but have not yet been evaluated clinically. We tested in silico whether inhibition of inward rectifier current or its combination with PVI reduces AF inducibility. METHODS AND RESULTS: We simulated the effect of inward rectifier current blockade (IK blockade), PVI, and their combination on AF inducibility in a detailed three-dimensional model of the human atria with different degrees of fibrosis. IK blockade was simulated with a 30% reduction of its conductivity. Atrial fibrillation was initiated using incremental pacing applied at 20 different locations, in both atria. IK blockade effectively prevented AF induction in simulations without fibrosis as did PVI in simulations without fibrosis and with moderate fibrosis. Both interventions lost their efficacy in severe fibrosis. The combination of IK blockade and PVI prevented AF in simulations without fibrosis, with moderate fibrosis, and even with severe fibrosis. The combined therapy strongly decreased the number of fibrillation waves, due to a synergistic reduction of wavefront generation rate while the wavefront lifespan remained unchanged. CONCLUSION: Newly developed blockers of atrial-specific inward rectifier currents, such as IKAch, might prevent AF occurrences and when combined with PVI effectively supress AF recurrences in human.

Beat-to-beat P-wave morphological variability in patients with paroxysmal atrial fibrillation: an in silico study.

AIMS: P-wave beat-to-beat morphological variability can identify patients prone to paroxysmal atrial fibrillation (AF). To date, no computational study has been carried out to mechanistically explain such finding. The aim of this study was to provide a pathophysiological explanation, by using a computer model of the human atria, of the correlation between P-wave beat-to-beat variability and the risk of AF. METHODS AND RESULTS: A physiological variability in the earliest activation site (EAS), on a beat-to-beat basis, was introduced into a computer model of the human atria by randomizing the EAS location. A methodology for generating multi-scale, spatially-correlated regions of heterogeneous conduction was developed. P-wave variability in the presence of such regions was compared with a control case. Simulations were performed with an eikonal model, for the activation map, and with the lead field approach, for P-wave computation. The methodology was eventually compared with a reference monodomain simulation. A total of 60 P-waves were simulated for each sinus node exit location (12 in total), and for each of the 15 patterns of heterogeneous conduction automatically generated by the model. A P-wave beat-to-beat variability was observed in all cases. Variability was significantly increased in presence of heterogeneous slow conducting regions, up to two-fold the variability in the control case. P-wave variability increased non-linearly with respect to the EAS variability and total area of slow conduction. Distribution of the heterogeneous conduction was more effective in increasing the variability when it surrounded the EAS locations and the fast conducting bundles. P-waves simulated by the eikonal approach compared excellently with the monodomain-based ones. CONCLUSION: P-wave variability in patients with paroxysmal AF could be explained by a variability in sinoatrial node exit location in combination with slow conducting regions.

Effect of Na+-channel blockade on the three-dimensional substrate of atrial fibrillation in a model of endo-epicardial dissociation and transmural conduction.

AIMS: Atrial fibrillation (AF) is a progressive arrhythmia characterized by structural alterations that increase its stability. Both clinical and experimental studies showed a concomitant loss of antiarrhythmic drug efficacy in later stages of AF. The mechanisms underlying this loss of efficacy are not well understood. We hypothesized that structural remodelling may explain this reduced efficacy by making the substrate more three-dimensional. To investigate this, we simulated the effect of sodium (Na+)-channel block on AF in a model of progressive transmural uncoupling. METHODS AND RESULTS: In a computer model consisting of two cross-connected atrial layers, with realistic atrial membrane behaviour, structural remodelling was simulated by reducing the number of connections between the layers. 100% of endo-epicardial connectivity represented a healthy atrium. At various degrees of structural remodelling, we assessed the effect of 60% sodium channel block on AF stability, endo-epicardial electrical activity dissociation (EED), and fibrillatory conduction pattern complexity quantified by number of waves, phase singularities (PSs), and transmural conduction ('breakthrough', BT). Sodium channel block terminated AF in non-remodelled but not in remodelled atria. The temporal excitable gap (EG) and AF cycle length increased at all degrees of remodelling when compared with control. Despite an increase of EED and EG, sodium channel block decreased the incidence of BT because of transmural conduction block. Sodium channel block decreased the number of waves and PSs in normal atrium but not in structurally remodelled atrium. CONCLUSION: This simple atrial model explains the loss of efficacy of sodium channel blockers in terminating AF in the presence of severe structural remodelling as has been observed experimentally and clinically. Atrial fibrillation termination in atria with moderate structural remodelling in the presence of sodium channel block is caused by reduction of AF complexity. With more severe structural remodelling, sodium channel block fails to promote synchronization of the two layers of the model.

How disruption of endo-epicardial electrical connections enhances endo-epicardial conduction during atrial fibrillation.

Aims: Loss of side-to-side electrical connections between atrial muscle bundles is thought to underlie conduction disturbances predisposing to atrial fibrillation (AF). Putatively, disruption of electrical connections occurs not only within the epicardial layer but also between the epicardial layer and the endocardial bundle network, thus impeding transmural conductions ('breakthroughs'). However, both clinical and experimental studies have shown an enhancement of breakthroughs during later stages of AF. We tested the hypothesis that endo-epicardial uncoupling enhances endo-epicardial electrical dyssynchrony, breakthrough rate (BTR), and AF stability. Methods and Results: In a novel dual-layer computer model of the human atria, 100% connectivity between the two layers served as healthy control. Atrial structural remodelling was simulated by reducing the number of connections between the layers from 96 to 6 randomly chosen locations. With progressive elimination of connections, AF stability increased. Reduction in the number of connections from 96 to 24 resulted in an increase in endo-epicardial dyssynchrony from 6.6 ± 1.9 to 24.6 ± 1.3%, with a concomitant increase in BTR. A further reduction to 12 and 6 resulted in more pronounced endo-epicardial dyssynchrony of 34.4 ± 1.15 and 40.2 ± 0.52% but with BTR reduction. This biphasic relationship between endo-epicardial coupling and BTR was found independently from whether AF was maintained by re-entry or by ectopic focal discharges. Conclusion: Loss of endo-epicardial coupling increases AF stability. There is a biphasic relation between endo-epicardial coupling and BTR. While at high degrees of endo-epicardial connectivity, the BTR is limited by the endo-epicardial synchronicity, at low degrees of connectivity, it is limited by the number of endo-epicardial connections.

Application of phase coherence in assessment of spatial alignment of electrodes during simultaneous endocardial-epicardial direct contact mapping of atrial fibrillation.

AIMS: Mapping and interpretation of wave conduction patterns recorded during simultaneous mapping of the electrical activity on both endocardial and epicardial surfaces are challenging because of the difficulty of reconstruction of reciprocal alignment of electrodes in space. Here, we suggest a method to overcome this difficulty using a concept of maximized endo-epicardial phase coherence. METHODS AND RESULTS: Endo-epicardial mapping was performed in six humans during induced atrial fibrillation (AF) in right atria using two sets of 8 × 8 electrode plaques. For each electrode, mean phase coherence (MPC) with all electrodes on the opposite side of the atrial wall was calculated. Localization error was defined as a distance between the directly opposing electrode and the electrode with the maximal MPC. Overall, there was a linear correlation between MPC and distance between electrodes with R(2) = 0.34. Localization error obtained for electrodes of the plaque in six patients resulted in a mean 2.3 ± 1.9 mm for 25 s electrogram segment length. Eighty-four per cent of the measurements resulted in error smaller than 3.4 mm. The duration of the recording used to compute MPC was negatively correlated with localization error; however, the effect reached plateau for segment durations longer than 15 s. CONCLUSION: Application of the concept of maximized endo-epicardial phase coherence to electrograms during AF allows reconstruction of reciprocal alignment of the electrodes on the opposite side of the atrial wall. This approach may be especially useful in settings where the spatial position of endo- and epicardial electrodes for intracardiac mapping cannot otherwise be determined.

High-density and high-coverage composite atrial activation maps: an in-silico validation study.

OBJECTIVE: Repetitive atrial activation patterns (RAAPs) during complex atrial tachycardia could be associated with localized mechanisms that can be targeted. Clinically available electroanatomical mapping systems are limited by either the spatial coverage or electrode density of the mapping catheters, preventing the adequate visualization of transiently occurring RAAPs. This work proposes a technique to overcome this shortcoming by stitching spatially overlapping conduction patterns together to a larger image- called a composite map. METHODS: Simulated stable mechanisms and meandering reentries are sequentially mapped (4x4 grid, 3mm spacing) and then reconstructed back to the original sizes with the proposed recurrence plot-based algorithm. RESULTS: The reconstruction of single linear waves presents minimal errors (local activation time (LAT) difference: 3.2 [1.6-4.9] ms, conduction direction difference: 5.2 [2.3-8.0] degrees). Errors significantly increase (p<0.05) for more complex patterns, being the highest with unstable reentries (LAT difference: 10.3 [3.5-16.2] ms, conduction direction difference: 18.2 [6.7-29.7] deg). In a second part of the analysis, 111 meandering reentries are reconstructed. Mapping 30 locations overlappingly around each reentry core was found to be the optimal mapping strategy. For this optimal setting, LAT, conduction direction, and core localization errors are low (6.1 [4.2-8.6] ms, 11.2 [8.6-15.5] deg and 4.1 [2.9-4.9] mm, respectively) and are weakly correlated with the degree of the meander ( ρ=0.41, ρ=0.40 and ρ=0.20, respectively). CONCLUSION: Our findings underline the feasibility of generating composite maps by stitching spatially overlapping recordings. SIGNIFICANCE: Composite maps can be instrumental in personalized ablation strategies.

Advancing Surgical Arrhythmia Ablation: Novel Insights on 3D Printing Applications and Two Biocompatible Materials.

To date, studies assessing the safety profile of 3D printing materials for application in cardiac ablation are sparse. Our aim is to evaluate the safety and feasibility of two biocompatible 3D printing materials, investigating their potential use for intra-procedural guides to navigate surgical cardiac arrhythmia ablation. Herein, we 3D printed various prototypes in varying thicknesses (0.8 mm-3 mm) using a resin (MED625FLX) and a thermoplastic polyurethane elastomer (TPU95A). Geometrical testing was performed to assess the material properties pre- and post-sterilization. Furthermore, we investigated the thermal propagation behavior beneath the 3D printing materials during cryo-energy and radiofrequency ablation using an in vitro wet-lab setup. Moreover, electron microscopy and Raman spectroscopy were performed on biological tissue that had been exposed to the 3D printing materials to assess microparticle release. Post-sterilization assessments revealed that MED625FLX at thicknesses of 1 mm, 2.5 mm, and 3 mm, along with TPU95A at 1 mm and 2.5 mm, maintained geometrical integrity. Thermal analysis revealed that material type, energy source, and their factorial combination with distance from the energy source significantly influenced the temperatures beneath the 3D-printed material. Electron microscopy revealed traces of nitrogen and sulfur underneath the MED625FLX prints (1 mm, 2.5 mm) after cryo-ablation exposure. The other samples were uncontaminated. While Raman spectroscopy did not detect material release, further research is warranted to better understand these findings for application in clinical settings.

High Prevalence of New Clinically Significant Findings in Patients With Embolic Stroke of Unknown Source Evaluated by Cardiac Magnetic Resonance Imaging.

BACKGROUND: Embolic stroke of unknown source (ESUS) accounts for 1 in 6 ischemic strokes. Current guidelines do not recommend routine cardiac magnetic resonance (CMR) imaging in ESUS, and beyond the identification of cardioembolic sources, there are no data assessing new clinical findings from CMR in ESUS. This study aimed to assess the prevalence of new cardiac and noncardiac findings and to determine their impact on clinical care in patients with ESUS. METHODS AND RESULTS: In this prospective, multicenter, observational study, CMR imaging was performed within 3 months of ESUS. All scans were reported according to standard clinical practice. A new clinical finding was defined as one not previously identified through prior clinical evaluation. A clinically significant finding was defined as one resulting in further investigation, follow-up, or treatment. A change in patient care was defined as initiation of medical, interventional, surgical, or palliative care. From 102 patients recruited, 96 underwent CMR imaging. One or more new clinical findings were observed in 59 patients (61%). New findings were clinically significant in 48 (81%) of these patients. Of 40 patients with a new clinically significant cardiac finding, 21 (53%) experienced a change in care (medical therapy, n=15; interventional/surgical procedure, n=6). In 12 patients with a new clinically significant extracardiac finding, 6 (50%) experienced a change in care (medical therapy, n=4; palliative care, n=2). CONCLUSIONS: CMR imaging identifies new clinically significant cardiac and noncardiac findings in half of patients with recent ESUS. Advanced cardiovascular screening should be considered in patients with ESUS. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04555538.

State of the art paper: Cardiac computed tomography of the left atrium in atrial fibrillation.

The clinical spectrum of atrial fibrillation means that a patient-individualized approach is required to ensure optimal treatment. Cardiac computed tomography can accurately delineate atrial structure and function and could contribute to a personalized care pathway for atrial fibrillation patients. The imaging modality offers excellent spatial resolution and has been utilised in pre-, peri- and post-procedural care for patients with atrial fibrillation. Advances in temporal resolution, acquisition times and analysis techniques suggest potential expanding roles for cardiac computed tomography in the future management of patients with atrial fibrillation. The aim of the current review is to discuss the use of cardiac computed tomography in atrial fibrillation in pre-, peri- and post-procedural settings. Potential future applications of cardiac computed tomography including atrial wall thickness assessment and epicardial fat volume quantification are discussed together with emerging analysis techniques including computational modelling and machine learning with attention paid to how these developments may contribute to a personalized approach to atrial fibrillation management.

Machine Learning to Identify Patients at Risk of Developing New-Onset Atrial Fibrillation after Coronary Artery Bypass.

BACKGROUND: This study aims to get an effective machine learning (ML) prediction model of new-onset postoperative atrial fibrillation (POAF) following coronary artery bypass grafting (CABG) and to highlight the most relevant clinical factors. METHODS: Four ML algorithms were employed to analyze 394 patients undergoing CABG, and their performances were compared: Multivariate Adaptive Regression Spline, Neural Network, Random Forest, and Support Vector Machine. Each algorithm was applied to the training data set to choose the most important features and to build a predictive model. The better performance for each model was obtained by a hyperparameters search, and the Receiver Operating Characteristic Area Under the Curve metric was selected to choose the best model. The best instances of each model were fed with the test data set, and some metrics were generated to assess the performance of the models on the unseen data set. A traditional logistic regression was also performed to be compared with the machine learning models. RESULTS: Random Forest model showed the best performance, and the top five predictive features included age, preoperative creatinine values, time of aortic cross-clamping, body surface area, and Logistic Euro-Score. CONCLUSIONS: The use of ML for clinical predictions requires an accurate evaluation of the models and their hyperparameters. Random Forest outperformed all other models in the clinical prediction of POAF following CABG.

The Impact of Atrial Fibrillation Treatment Strategies on Cognitive Function.

There is increasing evidence to suggest that atrial fibrillation is associated with a heightened risk of dementia. The mechanism of interaction is unclear. Atrial fibrillation-induced cerebral infarcts, hypoperfusion, systemic inflammation, and anticoagulant therapy-induced cerebral microbleeds, have been proposed to explain the link between these conditions. An understanding of the pathogenesis of atrial fibrillation-associated cognitive decline may enable the development of treatment strategies targeted towards the prevention of dementia in atrial fibrillation patients. The aim of this review is to explore the impact that existing atrial fibrillation treatment strategies may have on cognition and the putative mechanisms linking the two conditions. This review examines how components of the 'Atrial Fibrillation Better Care pathway' (stroke risk reduction, rhythm control, rate control, and risk factor management) may influence the trajectory of atrial fibrillation-associated cognitive decline. The requirements for further prospective studies to understand the mechanistic link between atrial fibrillation and dementia and to develop treatment strategies targeted towards the prevention of atrial fibrillation-associated cognitive decline, are highlighted.

3D-Printed Biomaterial Testing in Response to Cryoablation: Implications for Surgical Ventricular Tachycardia Ablation.

Background: The lack of thermally and mechanically performant biomaterials represents the major limit for 3D-printed surgical guides, aimed at facilitating complex surgery and ablations. Methods: Cryosurgery is a treatment for cardiac arrhythmias. It consists of obtaining cryolesions, by freezing the target tissue, resulting in selective and irreversible damage. MED625FLX and TPU95A are two biocompatible materials for surgical guides; however, there are no data on their response to cryoenergy delivery. The study purpose is to evaluate the biomaterials' thermal properties, examining the temperature changes on the porcine muscle samples (PMS) when the biomaterials are in place during the cryoablation. Two biomaterials were selected, MED625FLX and TPU95A, with two thicknesses (1.0 and 2.5 mm). To analyze the biomaterials' behavior, the PMS temperatures were measured during cryoablation, firstly without biomaterials (control) and after with the biomaterials in place. To verify the biomaterials' suitability, the temperatures under the biomaterial samples should not exceed a limit of -30.0 °C. Furthermore, the biomaterials' geometry after cryoablation was evaluated using the grid paper test. Results: TPU95A (1.0 and 2.5 mm) successfully passed all tests, making this material suitable for cryoablation treatment. MED625FLX of 1.0 mm did not retain its shape, losing its function according to the grid paper test. Further, MED625FLX of 2.5 mm is also suitable for use with a cryoenergy source. Conclusions: TPU95A (1.0 and 2.5 mm) and MED625FLX of 2.5 mm could be used in the design of surgical guides for cryoablation treatment, because of their mechanical, geometrical, and thermal properties. The positive results from the thermal tests on these materials and their thickness prompt further clinical investigation.

Evaluation of an open-source pipeline to create patient-specific left atrial models: A reproducibility study.

This work presents an open-source software pipeline to create patient-specific left atrial models with fibre orientations and a fibrDEFAULTosis map, suitable for electrophysiology simulations, and quantifies the intra and inter observer reproducibility of the model creation. The semi-automatic pipeline takes as input a contrast enhanced magnetic resonance angiogram, and a late gadolinium enhanced (LGE) contrast magnetic resonance (CMR). Five operators were allocated 20 cases each from a set of 50 CMR datasets to create a total of 100 models to evaluate inter and intra-operator variability. Each output model consisted of: (1) a labelled surface mesh open at the pulmonary veins and mitral valve, (2) fibre orientations mapped from a diffusion tensor MRI (DTMRI) human atlas, (3) fibrosis map extracted from the LGE-CMR scan, and (4) simulation of local activation time (LAT) and phase singularity (PS) mapping. Reproducibility in our pipeline was evaluated by comparing agreement in shape of the output meshes, fibrosis distribution in the left atrial body, and fibre orientations. Reproducibility in simulations outputs was evaluated in the LAT maps by comparing the total activation times, and the mean conduction velocity (CV). PS maps were compared with the structural similarity index measure (SSIM). The users processed in total 60 cases for inter and 40 cases for intra-operator variability. Our workflow allows a single model to be created in 16.72 ± 12.25 min. Similarity was measured with shape, percentage of fibres oriented in the same direction, and intra-class correlation coefficient (ICC) for the fibrosis calculation. Shape differed noticeably only with users' selection of the mitral valve and the length of the pulmonary veins from the ostia to the distal end; fibrosis agreement was high, with ICC of 0.909 (inter) and 0.999 (intra); fibre orientation agreement was high with 60.63% (inter) and 71.77% (intra). The LAT showed good agreement, where the median ± IQR of the absolute difference of the total activation times was 2.02 ± 2.45 ms for inter, and 1.37 ± 2.45 ms for intra. Also, the average ± sd of the mean CV difference was -0.00404 ± 0.0155 m/s for inter, and 0.0021 ± 0.0115 m/s for intra. Finally, the PS maps showed a moderately good agreement in SSIM for inter and intra, where the mean ± sd SSIM for inter and intra were 0.648 ± 0.21 and 0.608 ± 0.15, respectively. Although we found notable differences in the models, as a consequence of user input, our tests show that the uncertainty caused by both inter and intra-operator variability is comparable with uncertainty due to estimated fibres, and image resolution accuracy of segmentation tools.

Evaluation of photogrammetry for medical application in cardiology.

Background: In the field of medicine, photogrammetry has played for long time a marginal role due to the significant amount of work required that made it impractical for an extended medical use. Developments in digital photogrammetry occurred in the recent years, that have steadily increased the interest and application of this technique. The present study aims to compare photogrammetry reconstruction of heart with computed tomography (CT) as a reference. Methods: The photogrammetric reconstructions of digital images from ECG imaging derived images were performed. In particular, the ventricles of 15 patients with Brugada syndrome were reconstructed by using the free Zephyr Lite software. In order to evaluate the accuracy of the technique, measurements on the reconstructions were compared to patient-specific CT scan imported in ECG imaging software UZBCIT. Result: The results showed that digital photogrammetry in the context of ventricle reconstruction is feasible. The photogrammetric derived measurements of ventricles were not statistically different from CT scan measurements. Furthermore, the analysis showed high correlation of photogrammetry reconstructions with CT scan and a correlation coefficient close to 1. Conclusion: It is possible to reproduce digital objects by photogrammetry if the process described in this study is performed. The reconstruction of the ventricles from CT scan was very close to the values of the respective photogrammetric reconstruction.

A computer model of endo-epicardial electrical dissociation and transmural conduction during atrial fibrillation.

AIMS: Structural alterations during atrial fibrillation (AF) not only lead to electrical dissociation within the epicardial layer, but also between the epicardial layer and the endocardial bundle network. The aim of the study was to investigate the role of transmural conduction in the stability of AF episodes using a dual-layer computer model. METHODS AND RESULTS: A proof-of-principle dual-layer model was developed in which connections between the layers can be introduced or removed at any time during the simulation. Using an S1-S2 protocol, a spiral wave was initiated in one of the layers, which degenerated into a complex AF pattern after connection with the other layer at six randomly chosen sites. After 6 s, connections were either retained (dual-layer simulations) or removed (single-layer simulations). Dual-layer simulations were more complex, as indicated by the higher number of waves and phase singularities. Tracking waves through both layers revealed that the number of waves in dual-layer simulations was significantly higher than in the single-layer simulations, reflecting more opportunities for reentry and a concomitant increase in AF stability. In the dual-layer model, only 12% of the AF episodes died out within 6 s, while 59% died out in the single-layer model. CONCLUSION: Atrial fibrillation patterns are more complex and AF episodes are more stable in a dual-layer model. This study indicates an important role for endo-epicardial conduction for the stabilization of AF.

Fast Characterization of Inducible Regions of Atrial Fibrillation Models With Multi-Fidelity Gaussian Process Classification.

Computational models of atrial fibrillation have successfully been used to predict optimal ablation sites. A critical step to assess the effect of an ablation pattern is to pace the model from different, potentially random, locations to determine whether arrhythmias can be induced in the atria. In this work, we propose to use multi-fidelity Gaussian process classification on Riemannian manifolds to efficiently determine the regions in the atria where arrhythmias are inducible. We build a probabilistic classifier that operates directly on the atrial surface. We take advantage of lower resolution models to explore the atrial surface and combine seamlessly with high-resolution models to identify regions of inducibility. We test our methodology in 9 different cases, with different levels of fibrosis and ablation treatments, totalling 1,800 high resolution and 900 low resolution simulations of atrial fibrillation. When trained with 40 samples, our multi-fidelity classifier that combines low and high resolution models, shows a balanced accuracy that is, on average, 5.7% higher than a nearest neighbor classifier. We hope that this new technique will allow faster and more precise clinical applications of computational models for atrial fibrillation. All data and code accompanying this manuscript will be made publicly available at: https://github.com/fsahli/AtrialMFclass.

3D Printed Surgical Guide for Coronary Artery Bypass Graft: Workflow from Computed Tomography to Prototype.

Patient-specific three-dimensional (3D) printed models have been increasingly used in many medical fields, including cardiac surgery for which they are used as planning and communication tools. To locate and plan the correct region of interest for the bypass placement during coronary artery bypass graft (CABG) surgery, cardiac surgeons can pre-operatively rely on different medical images. This article aims to present a workflow for the production of a patient-specific 3D-printed surgical guide, from data acquisition and image segmentation to final prototyping. The aim of this surgical guide is to help visualize the region of interest for bypass placement during the operation, through the use of dedicated surgical holes. The results showed the feasibility of this surgical guide in terms of design and fitting to the phantom. Further studies are needed to assess material biocompatibility and technical properties.