Correlation between Cardiac MRI and Voltage Mapping in Evaluating Atrial Fibrosis: A Systematic Review

Unipolar voltage electroanatomic mapping detects structural atrial remodeling identified by LGE-MRI

BACKGROUND

In atrial fibrillation (AF) management, understanding left atrial (LA) substrate is crucial. While both electroanatomic mapping (EAM) and late gadolinium enhancement magnetic resonance imaging (LGE-MRI) are accepted methods for assessing the atrial substrate and are associated with ablation outcome, recent findings have highlighted discrepancies between low-voltage areas (LVAs) in EAM and LGE areas.

OBJECTIVE

The purpose of this study was to explore the relationship between LGE regions and unipolar and bipolar LVAs using multipolar high-density mapping.

METHODS

Twenty patients scheduled for AF ablation underwent preablation LGE-MRI. LA segmentation was conducted using a deep learning approach, which subsequently generated a 3-dimensional mesh integrating the LGE data. High-density EAM was performed in sinus rhythm for each patient. The electroanatomic map and LGE-MRI mesh were coregistered. LVAs were defined using cutoffs of 0.5 mV for bipolar voltage and 2.5 mV for unipolar voltage. The correspondence between LGE areas and LVAs in the LA was analyzed using confusion matrices and performance metrics.

RESULTS

A considerable 87.3% of LGE regions overlapped with unipolar LVAs, compared with only 16.2% overlap observed with bipolar LVAs. Across all performance metrics, unipolar LVAs outperformed bipolar LVAs in identifying LGE areas (precision: 78.6% vs 61.1%; sensitivity: 87.3% vs 16.2%; F1 score: 81.3% vs 26.0%; accuracy: 74.0% vs 35.3%).

CONCLUSION

Our findings demonstrate that unipolar LVAs strongly correlate with LGE regions. These findings support the integration of unipolar mapping alongside bipolar mapping into clinical practice. This would offer a nuanced approach to diagnose and manage AF by revealing critical insights into the complex architecture of the atrial substrate.

Optimal Threshold and Interpatient Variability in Left Atrial Ablation Scar Assessment by Dark-Blood LGE CMR

BACKGROUND

Dark-blood late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) has better correlation with bipolar voltage (BiV) to define ablation scar in the left atrium (LA) compared to conventional bright-blood LGE CMR.

OBJECTIVES

This study sought to determine the optimal signal intensity threshold of dark-blood LGE CMR to identify LA ablation scar.

METHODS

In 54 patients scheduled for atrial fibrillation ablation, image intensity ratios (IIRs) were derived from preprocedural dark-blood LGE CMR. In 26 patients without previous ablation, the upper limit of normal was derived from the 95th and 98th percentiles of pooled IIR values. In 28 patients with previous atrial fibrillation ablation, BiV was compared with the corresponding IIR. Receiver-operating characteristics analyses were employed to determine the optimal IIR threshold (ie, the point with the smallest distance to the upper left corner of the receiver-operating characteristics) for LA ablation scar (BiV ≤0.15 mV).

RESULTS

Upper limit of normal corresponded to IIR values 1.16 and 1.21, yielding low sensitivities of 0.32 and 0.09 to detect LA ablation scar. Receiver-operating characteristics analysis of IIR and BiV comparison achieved a median area under the curve of 0.77. Median optimal IIR threshold for LA ablation scar was 1.09, with an average sensitivity of 0.73, specificity of 0.75, and accuracy of 0.71. Median IIR thresholds of 1.00 and 1.10 corresponded to 80% sensitivity and 80% specificity, respectively. There was considerable interpatient variability: optimal IIR thresholds per patient ranged from 1.01 to 1.22.

CONCLUSIONS

The optimal IIR threshold to identify LA ablation scar by dark-blood LGE CMR is 1.09. Because of interpatient variability, the investigators recommend using a lower (1.00) and upper (1.10) threshold to prevent over- or underestimation of ablation scar.

Practical approach for atrial cardiomyopathy characterization in patients with atrial fibrillation

Atrial fibrillation (AF) causes progressive structural and electrical changes in the atria that can be summarized within the general concept of atrial remodeling. In parallel, other clinical characteristics and comorbidities may also affect atrial tissue properties and make the atria susceptible to AF initiation and its long-term persistence. Overall, pathological atrial changes lead to atrial cardiomyopathy with important implications for rhythm control. Although there is general agreement on the role of the atrial substrate for successful rhythm control in AF, the current classification oversimplifies clinical management. The classification uses temporal criteria and does not establish a well-defined strategy to characterize the individual-specific degree of atrial cardiomyopathy. Better characterization of atrial cardiomyopathy may improve the decision-making process on the most appropriate therapeutic option. We review current scientific evidence and propose a practical characterization of the atrial substrate based on 3 evaluation steps starting with a clinical evaluation (step 1), then assess outpatient complementary data (step 2), and finally include information from advanced diagnostic tools (step 3). The information from each of the steps or a combination thereof can be used to classify AF patients in 4 stages of atrial cardiomyopathy, which we also use to estimate the success on effective rhythm control.

Comparison of voltages between atria: differences in sinus rhythm and atrial fibrillation

BACKGROUND

Ultra high-density mapping systems allow for comparison of atrial electroanatomical maps in unprecedented detail. Atrial scar determined by voltages and surface area between atria, rhythm and atrial fibrillation (AF) types was assessed.

METHODS

Left (LA) and right atrial (RA) maps were created using Rhythmia HDx in patients listed for ablation for paroxysmal (PAF, sinus rhythm (SR) maps only) or persistent AF (PeAF, AF and SR maps). Electrograms on corresponding SR/AF maps were paired for direct comparison. Percentage surface area of scar was assigned low- (LVM, ≤ 0.05 mV), intermediate- (IVM, 0.05-0.5 mV) or normal voltage myocardium, (NVM, > 0.5 mV).

RESULTS

Thirty-eight patients were recruited generating 96 maps using 913,480 electrograms. Paired SR-AF bipolar electrograms showed fair correlation in LA (Spearman's ρ = 0.32) and weak correlation in RA (ρ = 0.19) and were significantly higher in SR in both (LA: 0.61 mV (0.20-1.67) vs 0.31 mV (0.10-0.74), RA: 0.68 mV (0.19-1.88) vs 0.47 mV (0.14-1.07), p < 0.0005 both). Voltages were significantly higher in patients with PAF over PeAF, (LA: 1.13 mV (0.39-2.93) vs 0.52 mV (0.16-1.49); RA: 0.93 mV (0.24-2.46) vs 0.57 mV (0.17-1.69)). Minimal differences were seen in electrogram voltages between atria. Significantly more IVM/LVM surface areas were seen in AF over SR (LA only, p < 0005), and PeAF over PAF (LA: p = 0.01, RA: p = 0.04). There was minimal difference between atria within patients.

CONCLUSIONS

Ultra high-density mapping shows paired electrograms correlate poorly between SR and AF. SR electrograms are typically (but not always) larger than those in AF. Patients with PeAF have a lower global electrogram voltage than those with PAF. Electrogram voltages are similar between atria within individual patients.

Left Atrial Low-Voltage Areas Predict the Risk of Atrial Fibrillation Recurrence after Radiofrequency Ablation

Atrial fibrillation (AF), the most frequently encountered arrhythmia worldwide, is associated with increased cardiovascular morbidity and mortality. Left atrial (LA) and antral region of the pulmonary veins (PVs) remodeling are risk factors for AF perpetuation. Among the methods of LA fibrosis quantification, bipolar voltage mapping during three-dimensional electro-anatomical mapping is less studied. The main aim of this study was to analyze the relationship between the degree of LA fibrosis quantified in low-voltage areas and the efficacy of AF radiofrequency catheter ablation. All consecutive patients with AF ablation were included, and the degree of LA fibrosis was measured based on the low-voltage areas in the LA and the antral region of PVs (<0.5 mV for patients in sinus rhythm and <0.25 mV for patients in AF at the time of the ablation procedure). The efficacy of AF ablation was determined by the rate of recurrence after a blanking period of three months. A total of 106 patients were included; from these, 38 (35.8%) had AF recurrence after RF ablation, while 68 (64.2%) were free of events. The area and percentage of LA fibrosis were significantly higher in the patients with AF recurrence (p = 0.018 and p = 0.019, respectively). However, no significant differences were found between the patients with and without AF recurrence in terms of the area and percentage of PVs fibrosis (p = 0.896 and p = 0.888, respectively). Moreover, LA fibrosis parameters proved to be excellent predictors for AF recurrence (areas under the curve of 0.834 and 0.832, respectively, p < 0.001) even after adjustment for LA indexed volume and CHA2DS2-VASc score. In conclusion, LA fibrosis measured on bipolar voltage maps increases the risk of AF recurrence after the RF catheter ablation procedure.

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways

Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.

Research Progress of Low-Voltage Areas Associated with Atrial Fibrillation

Atrial fibrosis is an independent predictor of the recurrence of atrial fibrillation (AF) after catheter ablation. Low-voltage areas (LVA) measured during catheter ablation for AF are a commonly used surrogate for the presence of atrial fibrosis. LVA are associated with clinical outcomes and comorbidities and have links to triggering sites for AF. Several trials have shown promising data of targeting ablation in LVA, however the results have been mixed. This article will review the role of LVA in the prediction of adverse events in AF patients, including stroke, how to predict the presence of LVA, and the impact of LVA ablation on the recurrence of AF.