Computational Medicine: What Electrophysiologists Should Know to Stay Ahead of the Curve.

PURPOSE OF REVIEW: Technology drives the field of cardiac electrophysiology. Recent computational advances will bring exciting changes. To stay ahead of the curve, we recommend electrophysiologists develop a robust appreciation for novel computational techniques, including deterministic, statistical, and hybrid models. RECENT FINDINGS: In clinical applications, deterministic models use biophysically detailed simulations to offer patient-specific insights. Statistical techniques like machine learning and artificial intelligence recognize patterns in data. Emerging clinical tools are exploring avenues to combine all the above methodologies. We review three ways that computational medicine will aid electrophysiologists by: (1) improving personalized risk assessments, (2) weighing treatment options, and (3) guiding ablation procedures. Leveraging clinical data that are often readily available, computational models will offer valuable insights to improve arrhythmia patient care. As emerging tools promote personalized medicine, physicians must continue to critically evaluate technology-driven tools they consider using to ensure their appropriate implementation.

Lesion delivery and scar formation in catheter ablation for atrial fibrillation: The DECAAF II trial.

BACKGROUND: The Efficacy of Delayed Enhancement MRI-Guided Fibrosis Ablation vs Conventional Catheter Ablation of Atrial Fibrillation randomized trial showed no difference in atrial fibrillation (AF) recurrence with additional delayed enhancement magnetic resonance imaging (DE-MRI) fibrosis-targeted ablation to pulmonary vein isolation (PVI) in persistent AF. OBJECTIVE: We evaluated the effect of lesion delivery on ablation-induced scarring and AF recurrence. METHODS: Lesions delivered, targeting fibrotic and nonfibrotic areas identified from preablation DE-MRI, were studied in relation to ablation-induced scarring on 3-month DE-MRI, including their association with arrhythmia recurrence. RESULTS: A total of 593 patients treated with radiofrequency were analyzed: 293 (49.4%) underwent PVI and 300 (50.6%) underwent additional fibrosis-guided ablation. Lesion analysis showed that 80.9% in the MRI fibrosis-guided group vs 16.5% in the PVI group (P < .001) had ≥40% of baseline fibrosis targeted. MRI assessment of ablation-induced scar showed that 44.8% of fibrosis-guided ablation and 15.5% of PVI had ≥40% of their fibrosis covered by scar (P < .001), demonstrating significant attenuation from lesions delivered to scar formed. In the overall population, fibrosis coverage with scar was not associated with recurrence (hazard ratio [HR] 0.90; 95% confidence interval [CI] 0.80-1.01; P = .08 per 20% increase). In patients with baseline fibrosis < 20%, fibrosis coverage with scar was associated with lower recurrence than PVI (HR 0.85; 95% CI 0.73-0.97; P = .03), whereas the association was not significant when baseline fibrosis ≥ 20% (HR 0.97; 95% CI 0.80-1.17; P = .77). Significant center variation was observed in fibrosis targeting and coverage with scarring. CONCLUSION: Radiofrequency ablation lesions do not uniformly result in scar formation. A post hoc analysis suggests reduced arrhythmia recurrence when ablation-induced scarring covers fibrotic regions in patients with low baseline fibrosis.

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.

Sex-specific outcomes and left atrial remodeling following catheter ablation of persistent atrial fibrillation: results from the DECAAF II trial.

BACKGROUND: Catheter ablation is recognized as an effective treatment for atrial fibrillation (AF). Despite its effectiveness, significant sex-specific differences have been observed, which influence the outcomes of the procedure. This study explores these differences in a cohort of patients with persistent AF. We aim to assess sex differences in baseline characteristics, symptoms, quality of life, imaging findings, and response to catheter ablation in patients with persistent AF. METHODS: This post hoc analysis of the DECAAF II trial evaluated 815 patients (161 females, 646 males). Between July 2016 and January 2020, participants were enrolled and randomly assigned to receive either personalized ablation targeting left atrial (LA) fibrosis using DE-MRI in conjunction with pulmonary vein isolation (PVI) or PVI alone. In this analysis, we aimed to compare female and male patients in the full cohort in terms of demographics, risk factors, medications, and outcomes such as AF recurrence, AF burden, LA volume reduction assessed by LGE-MRI before and 3 months after ablation, quality of life assessed by the SF-36 score, and safety outcomes. Statistical methods included t-tests, chi-square, and multivariable Cox regression. RESULTS: Females were generally older with more comorbidities and experienced higher rates of arrhythmia recurrence post-ablation (53.3% vs. 40.2%, p < 0.01). Females also showed a higher AF burden (21% vs. 16%, p < 0.01) and a smaller reduction in left atrial volume indexed to body surface area post-ablation compared to male patients (8.36 (9.94) vs 11.35 (13.12), p-value 0.019). Quality of life scores were significantly worse in females both pre- and post-ablation (54 vs. 66 pre-ablation; 69 vs. 81 post-ablation, both p < 0.01), despite similar improvements across sexes. Safety outcomes and procedural parameters were similar between male and female patients. CONCLUSION: The study highlights significant differences in the outcomes of catheter ablation of persistent AF between sexes, with female patients showing worse quality of life, higher recurrence of AF and AF burden after ablation, and worse LA remodeling.

Multi-physics simulations reveal hemodynamic impacts of patient-derived fibrosis-related changes in left atrial tissue mechanics.

Stroke is a leading cause of death and disability worldwide. Atrial myopathy, including fibrosis, is associated with an increased risk of ischemic stroke, but the mechanisms underlying this association are poorly understood. Fibrosis modifies myocardial structure, impairing electrical propagation and tissue biomechanics, and creating stagnant flow regions where clots could form. Fibrosis can be mapped non-invasively using late gadolinium enhancement magnetic resonance imaging (LGE-MRI). However, fibrosis maps are not currently incorporated into stroke risk calculations or computational electro-mechano-fluidic models. We present multi-physics simulations of left atrial (LA) myocardial motion and hemodynamics using patient-specific anatomies and fibrotic maps from LGE-MRI. We modify tissue stiffness and active tension generation in fibrotic regions and investigate how these changes affect LA flow for different fibrotic burdens. We find that fibrotic regions and, to a lesser extent, non-fibrotic regions experience reduced myocardial strain, resulting in decreased LA emptying fraction consistent with clinical observations. Both fibrotic tissue stiffening and hypocontractility independently reduce LA function, but together, these two alterations cause more pronounced effects than either one alone. Fibrosis significantly alters flow patterns throughout the atrial chamber, and particularly, the filling and emptying jets of the left atrial appendage (LAA). The effects of fibrosis in LA flow are largely captured by the concomitant changes in LA emptying fraction except inside the LAA, where a multi-factorial behavior is observed. This work illustrates how high-fidelity, multi-physics models can be used to study thrombogenesis mechanisms in patient-specific anatomies, shedding light onto the links between atrial fibrosis and ischemic stroke. Key points: Left atrial (LA) fibrosis is associated with arrhythmogenesis and increased risk of ischemic stroke; its extent and pattern can be quantified on a patient-specific basis using late gadolinium enhancement magnetic resonance imaging.Current stroke risk prediction tools have limited personalization, and their accuracy could be improved by incorporating patient-specific information like fibrotic maps and hemodynamic patterns.We present the first electro-mechano-fluidic multi-physics computational simulations of LA flow, including fibrosis and anatomies from medical imaging. Mechanical changes in fibrotic tissue impair global LA motion, decreasing LA and left atrial appendage (LAA) emptying fractions, especially in subjects with higher fibrosis burdens. Fibrotic-mediated LA motion impairment alters LA and LAA flow near the endocardium and the whole cavity, ultimately leading to more stagnant blood regions in the LAA.

Atrial fibrillation increases thrombogenicity of LVAD therapy.

BACKGROUND: This study investigates the hypothesis that presence of atrial fibrillation (AF) in LVAD patients increases thrombogenicity in the left ventricle (LV) and exacerbates stroke risk. METHODS: Using an anatomical LV model implanted with an LVAD inflow cannula, we analyze thrombogenic risk and blood flow patterns in either AF or sinus rhythm (SR) using unsteady computational fluid dynamics (CFD). To analyze platelet activation and thrombogenesis in the LV, hundreds of thousands of platelets are individually tracked to quantify platelet residence time (RT) and shear stress accumulation history (SH). RESULTS: The irregular and chaotic mitral inflow associated with AF results in markedly different intraventricular flow patterns, with profoundly negative impact on blood flow-induced stimuli experienced by platelets as they traverse the LV. Twice as many platelets accumulated very high SH in the LVAD + AF case, resulting in a 36% increase in thrombogenic potential score, relative to the LVAD + SR case. CONCLUSIONS: This supports the hypothesis that AF results in unfavorable blood flow patterns in the LV adding to an increased stroke risk for LVAD + AF patients. Quantification of thrombogenic risk associated with AF for LVAD patients may help guide clinical decision-making on interventions to mitigate the increased risk of thromboembolic events.

Machine learning identifies esophageal luminal temperature patterns associated with thermal injury in catheter ablation for atrial fibrillation.

INTRODUCTION: Luminal esophageal temperature (LET) monitoring during atrial fibrillation (AF) ablation is widely used to reduce the incidence of endoscopically detected esophageal lesion (EDEL). We sought to assess whether specific patterns of LET variation are associated with EDEL. METHODS: A high-fidelity multisensor probe was used to record LET in AF patients undergoing radiofrequency ablation (RFA) or cryoballoon ablation (CBA). Explainable machine learning and SHapley Additive exPlanations (SHAP) analysis were used to predict EDEL and assess feature importance. RESULTS: A total of 94 patients (38.3% persistent AF, 71.3% male, 72 RFA, and 22 CBA) were included. EDEL was detected in 11 patients (10 RFA and one CBA). In the RFA group, the highest LET recorded was similar between patients with and without EDEL (40.6 [40.1-41]°C vs. 40.2 [39.1-40.9]°C; p = .313), however, the rate of LET rise for the highest recorded peak was higher (0.08 [0.03-0.12]°C/s vs. 0.02 [0.01-0.05]°C/s; p = .033), and the area under the curve (AUC) for the highest peak was smaller (412.5 [206.8-634.1] vs. 588.6 [380.4-861.1]; p = .047) in patients who had EDEL. In case of CBA, the patient with EDEL had a faster LET decline (0.12 vs. 0.07 [0.02-0.14]°C/s), and a smaller AUC for the lowest trough (2491.3 vs. 2629.3 [1712.6-5283.2]). SHAP analysis revealed that a rate of LET change higher than 0.05°C/s and an AUC less than 600 were more predictive of EDEL in RFA. CONCLUSION: The rate of LET change and AUC for the recorded temperature predicted EDEL, whereas absolute peak temperatures did not.

Personalized biomechanical insights in atrial fibrillation: opportunities & challenges.

INTRODUCTION: Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke. AREAS COVERED: In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care. EXPERT OPINION: Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.

People with atrial fibrillation (AF) experience a fast, chaotic heartbeat. AF greatly increases the risk of stroke. The hearts of AF patients often have an accumulation of fibrous tissue (fibrosis). Fibrosis patterns can be detected via medical imaging scans, like MRI. These images can be used to build patient-specific digital representations. These models can be used to explore how fibrosis might cause AF, stroke, and other health risks. Insights from imaging and modeling are becoming more and more useful as tools for personalizing AF treatment.

Comparing Inducibility of Re-Entrant Arrhythmia in Patient-Specific Computational Models to Clinical Atrial Fibrillation Phenotypes.

BACKGROUND: Computational models of fibrosis-mediated, re-entrant left atrial (LA) arrhythmia can identify possible substrate for persistent atrial fibrillation (AF) ablation. Contemporary models use a 1-size-fits-all approach to represent electrophysiological properties, limiting agreement between simulations and patient outcomes. OBJECTIVES: The goal of this study was to test the hypothesis that conduction velocity (Ï´) modulation in persistent AF models can improve simulation agreement with clinical arrhythmias. METHODS: Patients with persistent AF (n = 37) underwent ablation and were followed up for ≥2 years to determine post-ablation outcomes: AF, atrial flutter (AFL), or no recurrence. Patient-specific LA models (n = 74) were constructed using pre-ablation and ≥90 days' post-ablation magnetic resonance imaging data. Simulated pacing gauged in silico arrhythmia inducibility due to AF-like rotors or AFL-like macro re-entrant tachycardias. A physiologically plausible range of Ï´ values (±10 or 20% vs. baseline) was tested, and model/clinical agreement was assessed. RESULTS: Fifteen (41%) patients had a recurrence with AF and 6 (16%) with AFL. Arrhythmia was induced in 1,078 of 5,550 simulations. Using baseline Ï´, model/clinical agreement was 46% (34 of 74 models), improving to 65% (48 of 74) when any possible Ï´ value was used (McNemar's test, P = 0.014). Ï´ modulation improved model/clinical agreement in both pre-ablation and post-ablation models. Pre-ablation model/clinical agreement was significantly greater for patients with extensive LA fibrosis (>17.2%) and an elevated body mass index (>32.0 kg/m2). CONCLUSIONS: Simulations in persistent AF models show a 41% relative improvement in model/clinical agreement when Ï´ is modulated. Patient-specific calibration of Ï´ values could improve model/clinical agreement and model usefulness, especially in patients with higher body mass index or LA fibrosis burden. This could ultimately facilitate better personalized modeling, with immediate clinical implications.

Explainable Machine Learning to Predict Anchored Reentry Substrate Created by Persistent Atrial Fibrillation Ablation in Computational Models.

Background Postablation arrhythmia recurrence occurs in ~40% of patients with persistent atrial fibrillation. Fibrotic remodeling exacerbates arrhythmic activity in persistent atrial fibrillation and can play a key role in reentrant arrhythmia, but emergent interaction between nonconductive ablation-induced scar and native fibrosis (ie, residual fibrosis) is poorly understood. Methods and Results We conducted computational simulations in pre- and postablation left atrial models reconstructed from late gadolinium enhanced magnetic resonance imaging scans to test the hypothesis that ablation in patients with persistent atrial fibrillation creates new substrate conducive to recurrent arrhythmia mediated by anchored reentry. We trained a random forest machine learning classifier to accurately pinpoint specific nonconductive tissue regions (ie, areas of ablation-delivered scar or vein/valve boundaries) with the capacity to serve as substrate for anchored reentry-driven recurrent arrhythmia (area under the curve: 0.91±0.03). Our analysis suggests there is a distinctive nonconductive tissue pattern prone to serving as arrhythmogenic substrate in postablation models, defined by a specific size and proximity to residual fibrosis. Conclusions Overall, this suggests persistent atrial fibrillation ablation transforms substrate that favors functional reentry (ie, rotors meandering in excitable tissue) into an arrhythmogenic milieu more conducive to anchored reentry. Our work also indicates that explainable machine learning and computational simulations can be combined to effectively probe mechanisms of recurrent arrhythmia.

Machine Learning and the Conundrum of Stroke Risk Prediction.

Stroke is a leading cause of death worldwide. With escalating healthcare costs, early non-invasive stroke risk stratification is vital. The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. Standard algorithms predict risk using regression-based statistical associations, which, while useful and easy to use, have moderate predictive accuracy. This review summarises recent efforts to deploy machine learning (ML) to predict stroke risk and enrich the understanding of the mechanisms underlying stroke. The surveyed body of literature includes studies comparing ML algorithms with conventional statistical models for predicting cardiovascular disease and, in particular, different stroke subtypes. Another avenue of research explored is ML as a means of enriching multiscale computational modelling, which holds great promise for revealing thrombogenesis mechanisms. Overall, ML offers a new approach to stroke risk stratification that accounts for subtle physiologic variants between patients, potentially leading to more reliable and personalised predictions than standard regression-based statistical associations.

Esophageal luminal temperature monitoring using a multi-sensor probe lowers the risk of esophageal injury in cryo and radiofrequency catheter ablation for atrial fibrillation.

BACKGROUND: Esophageal luminal temperature monitoring is a commonly used strategy to reduce esophageal thermal injury in catheter ablation for atrial fibrillation (AFib). OBJECTIVES: We sought to compare the incidence of endoscopically detected esophageal lesions (EDEL) between two commonly used esophageal luminal temperature probes. METHODS: Consecutive patients undergoing ablation with esophageal luminal temperature monitoring and upper endoscopy within 24 h after ablation were included. RESULTS: Four hundred forty-five patients (64 ± 10 years, 44% female) were included. Esophageal temperature monitoring was done with a single-sensor probe in 213 (48%) and multi-sensor probe in 232 (52%). Cryoballoon (CB) ablation was performed in 118 (27%) and radiofrequency (RF) ablation in 327 (73%) of patients. EDEL was present in 94 (22.9%) of which 85 were mild, 8 were moderate, and 1 was severe, and none progressed to atrial-esophageal fistula. The use of the multi-sensor probe during CB ablation was associated with a reduction in EDEL compared to single sensor (6.8% vs 24.3%; P = 0.016). Similarly, in the RF ablation group, EDEL was present in 19.5% of the multi-sensor group vs 32.8% in the single-sensor group (P = 0.001). Logistic regression showed that multi-sensor probe use was associated with reduction in EDEL with an odds ratio of 0.23 in CB ablation (P = 0.024) and 0.44 for RF ablation (P = 0.001). CONCLUSIONS: Esophageal luminal temperature monitoring during AFib ablation using a multi-sensor probe was associated with a significant reduction in EDEL compared to a single-sensor probe.

Network meta-analysis and systematic review comparing efficacy and safety between very high power short duration, high power short duration, and conventional radiofrequency ablation of atrial fibrillation.

BACKGROUND: High-power short-duration (HPSD) atrial fibrillation (AF) ablation with a power of 40-50 W was proved to be safe and effective. Very high-power short-duration (vHPSD) AF ablation is a novel method using >50 W to obtain more durable AF ablation. This study aimed to evaluate the efficacy and safety of vHPSD ablation compared with HPSD ablation and conventional power ablation. METHODS: A literature search for studies that reported AF ablation outcomes, including short-term freedom from atrial arrhythmia, first-pass isolation (FPI) rate, procedure time, and major complications, was conducted utilizing MEDLINE, EMBASE, and Cochrane databases. All relevant studies were included in this analysis. A random-effects model of network meta-analysis and surface under cumulative ranking curve (SUCRA) were used to rank the treatment for all outcomes. RESULTS: A total of 29 studies with 9721 patients were included in the analysis. According to the SUCRA analysis, HPSD ablation had the highest probability of maintaining sinus rhythm. Point estimation showed an odds ratio of 1.5 (95% confidence interval [CI]: 1.2-1.9) between HPSD ablation and conventional power ablation and an odds ratio of 1.3 (95% CI: 0.78-2.2) between vHPSD ablation and conventional power ablation. While the odds ratio of FPI between HPSD ablation and conventional power ablation was 3.6 (95% CI: 1.5-8.9), the odds ratio between vHPSD ablation and conventional power ablation was 2.2 (95% CI: 0.61-8.6). The procedure times of vHPSD and HPSD ablations were comparable and, therefore, shorter than that of conventional power ablation. Major complications were low in all techniques. CONCLUSION: vHPSD ablation did not yield higher efficacy than HPSD ablation and conventional power ablation. With the safety concern, vHPSD ablation outcomes were comparable with those of other techniques.

Elevated fibrosis burden as assessed by MRI predicts cryoballoon ablation failure.

INTRODUCTION: Late-gadolinium enhancement magnetic resonance (LGE-MRI) imaging is increasingly used in management of atrial fibrillation (AFib) patients. Here, we assess the usefulness of LGE-MRI-based fibrosis quantification to predict arrhythmia recurrence in patients undergoing cryoballoon ablation. Our secondary goal was to compare two widely used fibrosis quantification methods. METHODS: In 102 AF patients undergoing LGE-MRI and cryoballoon ablation (mean age 62 years; 64% male; 59% paroxysmal AFib), atrial fibrosis was quantified using the pixel intensity histogram (PIH) and image intensity ratio (IIR) methods. PIH segmentations were completed by a third-party provider as part of the standard of care at our hospital; Image intensity ratio (IIR) segmentations of the same scans were carried out in our lab using a commercially available software package. Fibrosis burdens and spatial distributions for the two methods were compared. Patients were followed prospectively for recurrent arrhythmia following ablation. RESULTS: Average PIH fibrosis was 15.6 ± 5.8% of the left atrial (LA) volume. Depending on threshold (IIRthr ), the average IIR fibrosis (% of LA wall surface area) ranged from 5.0 ± 7.2% (IIRthr = 1.2) to 37.4 ± 10.9% (IIRthr = 0.97). An IIRthr of 1.03 demonstrated the greatest agreement between the methods, but spatial overlap of fibrotic areas delineated by the two methods was modest (Sorenson Dice coefficient: 0.49). Fourty-two patients (41.2%) had recurrent arrhythmia. PIH fibrosis successfully predicted recurrence (HR 1.07; p = .02) over a follow-up period of 362 ± 149 days; regardless of IIRthr , IIR fibrosis did not predict recurrence. CONCLUSIONS: PIH-based volumetric assessment of atrial fibrosis was modestly predictive of arrhythmia recurrence following cryoballoon ablation in this cohort. IIR-based fibrosis was not predictive of recurrence for any of the IIRthr values tested, and the overlap in designated areas of fibrosis between the PIH and IIR methods was modest. Caution must therefore be exercised when interpreting LA fibrosis from LGE-MRI, since the values and spatial pattern are methodology-dependent.

Cryoballoon temperature parameters during cryoballoon ablation predict pulmonary vein reconnection and atrial fibrillation recurrence.

BACKGROUND: Cryoballoon ablation (CBA) is an established approach for rhythm management of atrial fibrillation (AF). We sought to assess balloon temperature (BT) parameters as predictors of pulmonary vein (PV) reconnection within the index procedure and AF recurrence following CBA. METHODS: BT was monitored in 119 AF patients undergoing CBA. PVs were assessed for reconnection during the procedure and patients were followed for arrhythmia recurrence. RESULTS: PV reconnection was identified in 39 (8.3%) of 471 PVs. BT was significantly colder in the absence of PV reconnection (30 s: - 33.5 °C [- 36; - 30] vs - 29.5 °C [- 35; - 25.5], p = 0.001; 60 s: - 41 °C [- 44; - 37] vs - 36.5 °C [- 42; - 33.5], p < 0.001; nadir: - 47 °C [- 52; - 43] vs - 41.5 °C [- 47; - 38], p < 0.001). PV reconnection was associated with significantly longer time to reach - 15 °C and - 40 °C (14.5 s [11.5-18.5] vs 12 s [10-15.5], p = 0.023; and 75 s [40-95.5] vs 46 s [37-66.75], p = 0.005) and shorter rewarming time (5.75 s [4.75-8.5] vs 7 s [6-9], p = 0.012). ROC analysis of these procedural parameters had an AUC = 0.71 in predicting PV reconnection. AF recurrence occurred in 51 (42.8%) patients. Kaplan-Meier analysis showed better arrhythmia-free survival for patients in whom BT decreased below - 40 °C in all PVs and patients who had no early PV reconnections, compared to patients in whom BT below - 40 °C was not achieved in at least one PV (log rank = 6.3, p = 0.012) and patients who had PV reconnections (log rank = 4.1, p = 0.043). CONCLUSIONS: Slower BT decline, warmer BT nadir, and faster rewarming time predict early PV reconnection. Absence of early PV reconnections and BT dropping below - 40 °C in all PVs during CBA are associated with lower rates of AF recurrence.

Positional obstructive sleep apnea in patients with atrial fibrillation.

PURPOSE: Obstructive sleep apnea (OSA) is a common, potentially modifiable condition implicated in the pathogenesis of atrial fibrillation (AF). The presence and severity of OSA is largely sleep position-dependent, yet there is high variability in positional dependence among patients with OSA. We investigated the prevalence of positional OSA (POSA) and examined associated factors in patients with AF. METHODS: We recruited an equal number of patients with and without AF who underwent diagnostic polysomnography. Patients included had ≥ 120 min of total sleep time with 30 min of sleep in both supine and lateral positions. POSA was defined as an overall apnea hypopnea index (AHI) ≥ 5/h, supine AHI (sAHI) ≥ 5/h, and sAHI greater than twice the non-supine AHI. POSA prevalence was compared in patients with and without AF adjusting for age, sex, OSA severity, and heart failure. RESULTS: A total of patients (male: 56%, mean age 62 years) were included. POSA prevalence was similar between the two groups (46% vs. 39%; p = 0.33). Obesity and severe OSA (AHI ≥ 30/h) were associated with low likelihood of POSA (OR [CI] of 0.17 [0.09-0.32] and 0.28 [0.12-0.62]). In patients with AF, male sex was associated with a higher likelihood of POSA (OR [CI] of 3.16 [1.06-10.4]). CONCLUSION: POSA is common, affecting more than half of patients with AF, but the prevalence was similar in those without AF. Obesity and more severe OSA are associated with lower odds of POSA. Positional therapy should be considered in patients with mild OSA and POSA.

MRI-quantified left atrial epicardial adipose tissue predicts atrial fibrillation recurrence following catheter ablation.

Background: Epicardial adipose tissue (EAT) plays a significant role in promoting atrial fibrillation (AF) due to its proinflammatory properties and anatomic proximity to the myocardium. We sought to assess whether left atrial (LA) EAT volume is associated with AF recurrence following catheter ablation. Methods: EAT was assessed via the 3D MRI Dixon sequence in 101 patients undergoing AF ablation. Patients were followed for arrhythmia recurrence. Results: During an average follow-up period of 1 year, post-ablation AF recurrence occurred in 31 (30.7%) patients. LA EAT index was higher in those with compared to without recurrence (20.7 [16.9, 30.4] vs. 13.7 [10.5, 20.1] mL/m2, p < 0.001), and so was LA volume index (66 [52.6, 77.5] vs. 49.9 [37.7, 61.8] mL/m2, p = 0.001). Cox regression analysis showed LA EAT (HR = 1.089; 95% CI: [1.049-1.131], p < 0.001) to be an independent predictor of post-ablation AF recurrence. The ROC curve for LA EAT index in the prediction of AF recurrence had an AUC of 0.77 (95% CI 0.68-0.86, p < 0.001) and showed an optimal cutoff value of 14.29 mL/m2 to identify patients at risk of post-ablation AF recurrence. Integrating LA EAT with clinical risk factors improved prediction of AF recurrence (AUC increased from 0.65 to 0.79, DeLong test p = 0.044). Kaplan-Meier analysis for recurrence-free survival showed a significant difference between two groups of patients identified by the optimal LA EAT index cutoff of 14.29 mL/m2 (log rank = 14.79; p < 0.001). Conclusion: EAT quantified using cardiac MRI, a reproducible and widely accessible imaging parameter, is a strong and independent predictor of post-ablation AF recurrence.

Epicardial adipose tissue is associated with left atrial volume and fibrosis in patients with atrial fibrillation.

Background: Obesity is a risk factor for atrial fibrillation (AF) and strongly influences the response to treatment. Atrial fibrosis shows similar associations. Epicardial adipose tissue (EAT) may be a link between these associations. We sought to assess whether EAT is associated with body mass index (BMI), left atrial (LA) fibrosis and volume. Methods: LA fibrosis and EAT were assessed using late gadolinium enhancement, and Dixon MRI sequences, respectively. We derived 3D models incorporating fibrosis and EAT, then measured the distance of fibrotic and non-fibrotic areas to the nearest EAT to assess spatial colocalization. Results: One hundred and three AF patients (64% paroxysmal, 27% female) were analyzed. LA volume index was 54.9 (41.2, 69.7) mL/m2, LA EAT index was 17.4 (12.7, 22.9) mL/m2, and LA fibrosis was 17.1 (12.4, 23.1)%. LA EAT was significantly correlated with BMI (R = 0.557, p < 0.001); as well as with LA volume and LA fibrosis after BSA adjustment (R = 0.579 and R = 0.432, respectively, p < 0.001 for both). Multivariable analysis showed LA EAT to be independently associated with LA volume and fibrosis. 3D registration of fat and fibrosis around the LA showed no clear spatial overlap between EAT and fibrotic LA regions. Conclusion: LA EAT is associated with obesity (BMI) as well as LA volume and fibrosis. Regions of LA EAT did not colocalize with fibrotic areas, suggesting a systemic or paracrine mechanism rather than EAT infiltration of fibrotic areas.