Left atrial wall thickness is associated with the low-voltage area in patients with paroxysmal atrial fibrillation

Utility of CT and MRI in Cardiac Electrophysiology

Cardiac electrophysiology involves the diagnosis and management of arrhythmias. CT and MRI play an increasingly important role in cardiac electrophysiology, primarily in preprocedural planning of ablation procedures but also in procedural guidance and postprocedural follow-up. The most common applications include ablation for atrial fibrillation (AF), ablation for ventricular tachycardia (VT), and for planning cardiac resynchronization therapy (CRT). For AF ablation, preprocedural evaluation includes anatomic evaluation and planning using CT or MRI as well as evaluation for left atrial fibrosis using MRI, a marker of poor outcomes following ablation. Procedural guidance during AF ablation is achieved by fusing anatomic data from CT or MRI with electroanatomic mapping to guide the procedure. Postprocedural imaging with CT following AF ablation is commonly used to evaluate for complications such as pulmonary vein stenosis and atrioesophageal fistula. For VT ablation, both MRI and CT are used to identify scar, representing the arrhythmogenic substrate targeted for ablation, and to plan the optimal approach for ablation. CT or MR images may be fused with electroanatomic maps for intraprocedural guidance during VT ablation and may also be used to assess for complications following ablation. Finally, functional information from MRI may be used to identify patients who may benefit from CRT, and cardiac vein mapping with CT or MRI may assist in planning access. ©RSNA, 2024 Supplemental material is available for this article.

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.

Tailored ablation index based on left atrial wall thickness assessed by computed tomography for pulmonary vein isolation in patients with atrial fibrillation

INTRODUCTION

Although left atrial wall thickness (LAWT) is known to be varied, a fixed target Ablation Index (AI) based pulmonary vein isolation (PVI) has been suggested in catheter ablation for atrial fibrillation (AF). We aimed to evaluate the efficacy and safety of PVI applying tailored AI based on LAWT assessed by cardiac computed tomography (CT).

METHODS

The thick segment was defined as the segment including ≥LAWT grade 3 (≥1.5 mm). The fixed AI strategy was defined as AI targets were 450 on the anterior/roof segments and 350 on the posterior/inferior/carina segments regardless of LAWT. The tailored AI strategy consisted of AI increasing the targets to 500 on the anterior/roof segments and to 400 on the posterior/inferior/carina segments when ablating the thick segment. After PVI, acute pulmonary vein (PV) reconnection, defined by the composite of residual potential and early reconnection, was evaluated.

RESULTS

A total of 156 patients (paroxysmal AF 72%) were consecutively included (86 for the fixed AI group and 70 for the tailored AI group). The tailored AI group showed a significantly lower rate of segments with acute PV reconnection than the fixed AI group (8% vs. 5%, p = .007). The tailored AI group showed a trend for shorter ablation time for PVI. One-year AF/atrial tachycardia free survival rate was similar in two groups (87.2% in the fixed AI group and 90.0% in the tailored AI group, p = .606).

CONCLUSION

Applying tailored AI based on the LAWT was a feasible and effective strategy to reduce acute PV reconnection after PVI.

Risk factors for new-onset atrial fibrillation during critical illness: A Delphi study

Background

New-onset atrial fibrillation (NOAF) is common during critical illness and is associated with poor outcomes. Many risk factors for NOAF during critical illness have been identified, overlapping with risk factors for atrial fibrillation in patients in community settings. To develop interventions to prevent NOAF during critical illness, modifiable risk factors must be identified. These have not been studied in detail and it is not clear which variables warrant further study.

Methods

We undertook an international three-round Delphi process using an expert panel to identify important predictors of NOAF risk during critical illness.

Results

Of 22 experts invited, 12 agreed to participate. Participants were located in Europe, North America and South America and shared 110 publications on the subject of atrial fibrillation. All 12 completed the three Delphi rounds. Potentially modifiable risk factors identified include 15 intervention-related variables.

Conclusions

We present the results of the first Delphi process to identify important predictors of NOAF risk during critical illness. These results support further research into modifiable risk factors including optimal plasma electrolyte concentrations, rates of change of these electrolytes, fluid balance, choice of vasoactive medications and the use of preventative medications in high-risk patients. We also hope our findings will aid the development of predictive models for NOAF.

Role of advanced imaging with cardiac computed tomography and MRI in atrial and ventricular ablation

PURPOSE OF REVIEW

Increasing evidence supports the use of advanced imaging with cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) in the work-up of patients with arrythmias being considered for ablation.

RECENT FINDINGS

Advances in imaging technology and postprocessing are facilitating the use of advanced imaging before, during and after ablation in patients with both atrial and ventricular arrhythmias.In atrial arrythmias, quantitative assessment of left atrial wall thickness on CCT and quantification of late gadolinium enhancement (LGE) on CMR identify patients more likely to develop recurrent atrial arrythmias following ablation. In addition, in patients with recurrent arrythmia post ablation, LGE CMR can potentially identify targets for repeat ablation.In ventricular arrythmias, qualitative assessment of LGE can aide in determining the optimal ablation approach and predicts likelihood of ventricular arrythmias inducibility. Quantitative assessment of LGE can identify conduction channels that can be targeted for ablation. On CCT, quantitative assessment of left ventricular wall thickness can demonstrate myocardial ridges associated with re-entrant circuits for ablation.

SUMMARY

This review focuses on the utility of CCT and CMR in identifying key anatomical components and arrhythmogenic substrate contributing to both atrial and ventricular arrhythmias in patients being considered for ablation. Advanced imaging has the potential to improve procedural outcomes, decrease complications and shorten procedural time.

It Is Necessary to Re-understand the Low-Voltage Area in Atrial Fibrillation Patients

The presence of a low-voltage areas (LVAs) is a major feature of the progression of atrial fibrillation. Typically, the LVA is determined by invasive left atrial voltage mapping. In addition to pulmonary vein electrical isolation, Voltage-guided substrate modification by targeting LVAs in addition to PVI has been shown to be superior to conventional PVI “only” approaches regarding freedom from AF recurrences after ablation. Recent studies have found Atrial wall thickness correlates with low voltage areas, and the degree of atrial myocardial fibrosis can be better assessed by CT or MRI in combination with voltage mapping, which might help reduce the recurrence of AF after catheter ablation.

New Discovery of Left Atrial Macroreentry Tachycardia: Originating from the Spontaneous Scarring of Left Atrial Anterior Wall

AIMS

This study sought to describe left atrial macroreentry tachycardia (LAMRT) originating from the spontaneous scarring of left atrial anterior wall (LAAW) and its clinical and electrophysiological characteristics, mechanisms, and the formation of substrates.

METHODS AND RESULTS

9 of 123 patients (89% female, age 79.78 ± 5.59 years) had LAMRT originating from the LAAW with no cardiac surgery or prior left atrial (LA) ablation. The mean tachycardia cycle length (TCL) was 241.67 ± 38.00 milliseconds. Spontaneous scars areas and low voltage areas (LVAs) in the LAAW were found in all patients. Successful ablation of the critical isthmus caused termination of the LAMRT and was not inducible in all patients. Arrhythmogenic substrates of LAMRT were the spontaneous scars of LAAW, which matched with the aorta or/and pulmonary artery contact area. The area under the curve (AUC) of age and combination of gender and age for predicting the LAMRT originating from the LAAW were 0.918 and 0.951, respectively, with a cutoff value of ≥73.5 years of age and gender (female) predicting LAMRT with 88.9% sensitivity and 89% specificity.

CONCLUSION

Combination of gender and age provides a simple and useful criterion to distinguish LAMRT from cavotricuspid isthmus- (CTI-) dependent atrial tachycardia in macroreentry atrial tachycardia (MRAT) in patients without a history of surgery or ablation. Aorta or/and pulmonary artery contacting LA may be related to spontaneous scars. Ablation the isthmus eliminated LAMRT in all patients.

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.

Structural Cardiac Remodeling in Atrial Fibrillation

OBJECTIVES

This study sought to evaluate preablation computed tomography angiography (CTA) for atrial and epicardial features to predict atrial fibrillation (AF) recurrence after ablation.

BACKGROUND

Structural atrial remodeling is a process associated with occurrence or persistence of AF. Different anatomical imaging features have been proposed to influence atrial remodeling both negatively and positively as substrate for AF.

METHODS

Patients with nonvalvular AF underwent cardiac CTA before pulmonary vein isolation at 2 high-volume centers. Left atrial (LA) and right atrial volumes, LA wall thickness (LAWT), and epicardial adipose tissue volume and attenuation were evaluated. Additional subanalyses of electroanatomical maps were made. Follow-up was performed for at least 12 months, including subanalysis of repeated cardiac CTA studies. Interrater variability was assessed.

RESULTS

Of 732 patients, 270 (36.9%) had AF recurrence after a mean of 7 months. CT analysis revealed larger indexed LA volume (47.3 mL/m² vs 43.6 mL/m²; P = 0.0001) and higher mean anterior (1.91 mm vs 1.65 mm; P < 0.0001) and posterior (1.61 mm vs 1.39 mm; P = 0.001) LAWT in patients with AF recurrence. Epicardial adipose tissue volume in patients with AF recurrence was higher (144.5 mm³ vs 128.5 mm³; P < 0.0001) and further progressed significantly in a subset of 85 patients after 2 years (+11.8 mm² vs -3.5 mm²; P = 0.041). Attenuation levels were lower, indicating a higher lipid component associated with AF recurrence (-69.1 HU vs -67.5 HU; P = 0.001). A total of 103 atrial voltage maps were highly predictive of AF recurrence and showed good discriminatory power for patients with low voltage >50% and LAWT (1.55 ± 0.5 mm vs 1.81 ± 0.6 mm; P = 0.032). Net reclassification improvement (NRI) showed a significant incremental benefit (NRI = 0.279; P < 0.0001) when adding LAWT to established risk models.

CONCLUSIONS

Atrial wall thickness, epicardial fat volume, and attenuation are associated with AF recurrence in patients undergoing ablation therapy.