Relation between left atrial wall composition by late gadolinium enhancement and complex fractionated atrial electrograms in patients with persistent atrial fibrillation: influence of non-fibrotic substrate in the left atrium

Early Detection of Atrial Fibrillation in Chronic Obstructive Pulmonary Disease Patients

Atrial fibrillation (AF) is an important medical problem, as it significantly affects patients' quality of life and prognosis. AF often complicates the course of chronic obstructive pulmonary disease (COPD), a widespread disease with heavy economic and social burdens. A growing body of evidence suggests multiple links between COPD and AF. This review considers the common pathogenetic mechanisms (chronic hypoxia, persistent inflammation, endothelial dysfunction, and myocardial remodeling) of these diseases and describes the main risk factors for the development of AF in patients with COPD. The most effective models based on clinical, laboratory, and functional indices are also described, which enable the identification of patients suffering from COPD with a high risk of AF development. Thus, AF in COPD patients is a frequent problem, and the search for new tools to identify patients at a high risk of AF among COPD patients remains an urgent medical problem.

Left Atrial Dysfunction, Fibrosis and the Risk of Thromboembolism in Patients With Paroxysmal and Persistent Atrial Fibrillation

Background and Objectives

Left atrial (LA) fibrosis is an important component of the arrhythmogenic substrate and is related to LA dysfunction in patients with atrial fibrillation (AF). However, its relationship with functional changes and the risk of thrombus in patients with paroxysmal AF (PAF) and persistent AF (PeAF) remains unclear.

Methods

We included 139 patients with preprocedural cardiac magnetic resonance imaging (CMR) and transesophageal echocardiography (TEE) for the first AF catheter ablation. Spontaneous echo contrast (SEC) and multiple parameters of LA were measured from TEE and CMR. LA fibrosis was evaluated by late gadolinium enhancement of LA (LA-LGE) of CMR.

Results

The presence of SEC was higher in patients with PeAF than in patients with PAF (26.4% vs. 11.9%, p=0.03). The patients with SEC had more enlarged LA size and impaired function of LA and LAA, regardless of AF type. However, the area of LA-LGE was more extensive in patients with SEC in PeAF (27.5±15.9 vs. 20.1±10.3, p=0.033), not in PAF. In PAF, maximal LA volume index was closely related to the presence of SEC with marginal trend toward significance (odd ratio [OR], 1.07; 95% confidence interval [CI], 0.99–1.16; p=0.072). Whereas, a larger area of LA-LGE and lower emptying flux of LA appendage were independently related with SEC (OR, 1.10; 95% CI, 1.0–1.20; p=0.049 and OR, 0.93; 95% CI, 0.86–0.99; p=0.022, respectively) after adjusting related cardiovascular risk factors of SEC

Conclusions

In this study, we suggest that the risk of thrombus is provoked by LA enlargement with dysfunction in early-stage AF and by stiffened LA with fibrosis rather than LA size when it becomes PeAF.

Prediction of Atrial Fibrillation Using Machine Learning: A Review

There has been recent immense interest in the use of machine learning techniques in the prediction and screening of atrial fibrillation, a common rhythm disorder present with significant clinical implications primarily related to the risk of ischemic cerebrovascular events and heart failure. Prior to the advent of the application of artificial intelligence in clinical medicine, previous studies have enumerated multiple clinical risk factors that can predict the development of atrial fibrillation. These clinical parameters include previous diagnoses, laboratory data (e.g., cardiac and inflammatory biomarkers, etc.), imaging data (e.g., cardiac computed tomography, cardiac magnetic resonance imaging, echocardiography, etc.), and electrophysiological data. These data are readily available in the electronic health record and can be automatically queried by artificial intelligence algorithms. With the modern computational capabilities afforded by technological advancements in computing and artificial intelligence, we present the current state of machine learning methodologies in the prediction and screening of atrial fibrillation as well as the implications and future direction of this rapidly evolving field.

Atrial Substrate Underlies the Recurrence after Catheter Ablation in Patients with Atrial Fibrillation

Prediction of recurrences after catheter ablation of atrial fibrillation (AF) remains challenging. We sought to investigate the long-term outcomes after AF catheter ablation. A total of 2221 consecutive patients who underwent catheter ablation for symptomatic AF were included in this study (mean age 55 ± 11 years, 20.3% women, and 59.0% paroxysmal AF). Extensive ablation, in addition to circumferential pulmonary vein isolation, was more often accomplished in patients with non-paroxysmal AF than in those with paroxysmal AF (87.4% vs. 25.3%, p < 0.001). During a median follow-up of 54 months, sinus rhythm (SR) was maintained in 67.1% after index procedure. After redo procedures in 418 patients, 83.3% exhibited SR maintenance. Recurrence rates were similar for single and multiple procedures (17.4% vs. 16.7%, p = 0.765). Subanalysis showed that the extent of late gadolinium enhancement (LGE), as assessed by cardiac magnetic resonance, is greater in patients with recurrence than in those without recurrence (36.2 ± 23.9% vs. 21.8 ± 13.7%, p < 0.001). Cox-regression analysis revealed that non-paroxysmal AF (hazard ratio (HR) 2.238, 95% confidence interval (CI) 1.905-2.629, p < 0.001), overweight (HR 1.314, 95% CI 1.107-1.559, p = 0.020), left atrium dimension ≥ 45 mm (HR 1.284, 95% CI 1.085-1.518, p = 0.004), AF duration (HR 1.020 per year, 95% CI 1.006-1.034, p = 0.004), and LGE ≥ 25% (HR 1.726, 95% CI 1.330-2.239, p < 0.001) are significantly associated with AF recurrence after catheter ablation. This study showed that repeated catheter ablation improves the clinical outcomes of patients with non-paroxysmal AF, suggesting that AF substrate based on LGE may underpin the mechanism of recurrence after catheter ablation.

Association of Left Atrial High-Resolution Late Gadolinium Enhancement on Cardiac Magnetic Resonance With Electrogram Abnormalities Beyond Voltage in Patients With Atrial Fibrillation

BACKGROUND

Conflicting data have been reported on the association of left atrial (LA) late gadolinium enhancement (LGE) with atrial voltage in patients with atrial fibrillation. The association of LGE with electrogram fractionation and delay remains to be examined. We sought to examine the association between LA LGE on cardiac magnetic resonance and electrogram abnormalities in patients with atrial fibrillation.

METHODS

High-resolution LGE cardiac magnetic resonance was performed before electrogram mapping and ablation in atrial fibrillation patients. Cardiac magnetic resonance features were quantified using LA myocardial signal intensity Z score (SI-Z), a continuous normalized variable, as well as a dichotomous LGE variable based on previously validated methodology. Electrogram mapping was performed pre-ablation during sinus rhythm or LA pacing, and electrogram locations were coregistered with cardiac magnetic resonance images. Analyses were performed using multilevel patient-clustered mixed-effects regression models.

RESULTS

In the 40 patients with atrial fibrillation (age, 63.2±9.2 years; 1312.3±767.3 electrogram points per patient), lower bipolar voltage was associated with higher SI-Z in patients who had undergone previous ablation (coefficient, -0.049; P<0.001) but not in ablation-naive patients (coefficient, -0.004; P=0.7). LA electrogram activation delay was associated with SI-Z in patients with previous ablation (SI-Z: coefficient, 0.004; P<0.001 and LGE: coefficient, 0.04; P<0.001) but not in ablation-naive patients. In contrast, increased LA electrogram fractionation was associated with SI-Z (coefficient, 0.012; P=0.03) and LGE (coefficient, 0.035; P<0.001) only in ablation-naive patients.

CONCLUSIONS

The association of LA LGE with voltage is modified by ablation. Importantly, in ablation-naive patients, atrial LGE is associated with electrogram fractionation even in the absence of voltage abnormalities.

Left Atrial Fibrosis Assessed with Cardiac MRI in Patients with Paroxysmal and Those with Persistent Atrial Fibrillation

Background Electrophysiology studies have demonstrated that left atrial late gadolinium enhancement (LGE) is associated with the chronicity of atrial fibrillation (AF). To date, cardiac MRI has been used to assess the extent of atrial LGE but not the distribution pattern of LGE in the left atrium. Purpose To determine whether the MRI pattern of left atrial fibrosis is associated with the chronicity of AF. Materials and Methods This retrospective study included patients with AF who underwent LGE MRI between June 2017 and May 2018. The presence of left atrial LGE was assessed at nine left atrial segments; the extent was determined by the number of segments involved. According to the chronicity of AF, patients were separated into paroxysmal AF (PAF) and persistent AF (PeAF) groups. The location and extent of left atrial LGE were compared between PAF and PeAF by using the χ² test and logistic regression analysis. Results Of the 195 patients (mean age, 55 years ± 10 [standard deviation], 161 men), 74 (38%) had PAF and 121 (62%) had PeAF. Of all patients, 114 (58.4%) had at least one left atrial LGE segment. The mean number of LGE segments was higher (1.4 ± 1.1 vs 0.6 ± 0.7, P = .002) in the PeAF group than in the PAF group. The incidence of LGE at the left inferior pulmonary vein (LIPV) antrum was higher in the PeAF group than in the PAF group (39.2% [29 of 74] vs 7.4% [nine of 121]; P < .001). In multivariable analysis, LGE at the LIPV antrum was independently associated with PeAF (odds ratio = 4.2; 95% confidence interval: 1.7, 10.5; P < .001). Conclusion The presence of fibrosis assessed with late gadolinium enhancement MRI of the left inferior pulmonary vein antrum was associated with persistent atrial fibrillation. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Almeida in this issue.

Anatomical hotspots of fractionated electrograms in the left and right atrium: do they exist?

Aims

Targeting of complex fractionated electrograms (CFEs) in the atria is not yet beneficial in treating drug-refractory atrial fibrillation (AF). In order to gain insight into potential anatomical hotspots of fractionated electrograms, a structured literature search was performed.

Methods and results

PubMed was searched for studies describing fractionation during human atrial electrophysiological measurements (n = 565), of which 36 articles described the pre-ablation distribution of fractionated electrograms for the left atrium and/or right atrium in at least four regions. Fractionation was commonly found in high proportions within all regions of both atria, without clear preference for specific regions. Furthermore, no differences in the fractionation distribution between paroxysmal AF and persistent AF patients were observed.

Conclusion

Whereas atrial inhomogeneous conduction is widely believed to play a key role in AF initiation and perpetuation, different electrophysiological causes for fractionation and the influence of measurement properties complicate identification of the arrhythmogenic substrate. Thereby, simply targeting all CFEs would be short-sighted. Further research is warranted on how to distinguish 'physiologic CFEs' from 'pathologic CFEs', with only the latter reflecting potential targets for ablative therapy of AF.

Validating Left Atrial Low Voltage Areas During Atrial Fibrillation and Atrial Flutter Using Multielectrode Automated Electroanatomic Mapping

OBJECTIVES

This study aimed: 1) to determine the voltage correlation between sinus rhythm (SR) and atrial fibrillation (AF)/atrial flutter (AFL) using multielectrode fast automated mapping; 2) to identify a bipolar voltage cutoff for scar and/or low voltage areas (LVAs); and 3) to examine the reproducibility of voltage mapping in AF.

BACKGROUND

It is unclear if bipolar voltage cutoffs should be adjusted depending on the rhythm and/or area being mapped.

METHODS

High-density mapping was performed first in SR and afterward in induced AF/AFL. In some patients, 2 maps were performed during AF. Maps were combined to create a new one. Points of <1 mm difference were analyzed. Correlation was explored with scatterplots and agreement analysis was assessed with Bland-Altman plots. The generalized additive model was also applied.

RESULTS

A total of 2,002 paired-points were obtained. A cutoff of 0.35 mV in AFL predicted a sinus voltage of 0.5 mV (95% confidence interval [CI]: 0.12 to 2.02) and of 0.24 mV in AF (95% CI: 0.11 to 2.18; specificity [SP]: 0.94 and 0.96; sensitivity [SE]: 0.85 and 0.75, respectively). When generalized additive models were used, a cutoff of 0.38 mV was used for AFL for predicting a minimum value of 0.5 mV in SR (95% CI: 0.5 to 1.6; SP: 0.94, SE: 0.88) and of 0.31 mV for AF (95% CI: 0.5 to 1.2; SP: 0.95, SE: 0.82). With regard to AF maps, there was no change in the classification of any left atrial region other than the roof.

CONCLUSIONS

It is possible to establish new cutoffs for AFL and/or AF with acceptable validity in predicting a sinus voltage of <0.5 mV. Multielectrode fast automated mapping in AFL and/or AF seems to be reliable and reproducible when classifying LVAs. These observations have clinical implications for left atrial voltage distribution and in procedures in which scar distribution is used to guide pulmonary vein isolation and/or re-isolation.