Abstract:

BACKGROUND: Electrical impedance measurements have become an accepted tool for monitoring intracardiac radio frequency ablation. Recently, the long-established generator impedance was joined by novel local impedance measurement capabilities with all electrical circuit terminals being accommodated within the catheter. OBJECTIVE: This work aims at in silico quantification of distinct influencing factors that have remained challenges due to the lack of ground truth knowledge and the superposition of effects in clinical settings. METHODS: We introduced a highly detailed in silico model of two local impedance enabled catheters, namely IntellaNav MiFi™ OI and IntellaNav Stablepoint™, embedded in a series of clinically relevant environments. Assigning material and frequency specific conductivities and subsequently calculating the spread of the electrical field with the finite element method yielded in silico local impedances. The in silico model was validated by comparison to in vitro measurements of standardized sodium chloride solutions. We then investigated the effect of the withdrawal of the catheter into the transseptal sheath, catheter-tissue interaction, insertion of the catheter into pulmonary veins, and catheter irrigation. RESULTS: All simulated setups were in line with in vitro experiments and in human measurements and gave detailed insight into determinants of local impedance changes as well as the relation between values measured with two different devices. CONCLUSION: The in silico environment proved to be capable of resembling clinical scenarios and quantifying local impedance changes. SIGNIFICANCE: The tool can assists the interpretation of measurements in humans and has the potential to support future catheter development.

Abstract:

Regions with pathologically altered substrate have been identified as potentially proarrhythmic for atrial fibrillation. Mapping techniques, such as voltage mapping, are currently used to estimate the location of these fibrotic areas. Recently, local impedance (LI) has gained attention as another modality for atrial substrate assessment as it does not rely on the dynamically changing electrical activity of the heart. However, its limits for assessing non-transmural and complex fibrosis patterns have not yet been studied in detail. In this work, the ability of EGMs and LI to identify non-transmural fibrosis at different transmural levels using in silico experiments is explored. A pseudo-bidomain model was used to recover the extracellular potential on the surface of the tissue while LI reconstruction was calculated by a time-difference imaging approach with an homogeneous tissue background conductivity. Four fibrosis configurations were modeled to compare the two modalities using Pearson correlation coefficient. Only one transmural structure was detected by voltage whereas non-transmural structures, namely endo-, midmyo-, and epicardial, yielded zero. The correlation for LI maps ranged from -0.02 to 0.74. We conclude that LI, together with EGMs, can be expected to distinguish between healthy and fibrotic tissue, paving the way towards its use as a surrogate for non-transmural atrial substrate.

Abstract:

Atrial fibrillation is a heart condition that causes an irregular and abnormally fast heart rate, as well as a multifactorial and progressive cardiac disease with different manifestations in each patient. The treatment of such illness remains a challenge, especially on those patients showing severe remodelling of the cardiac substrate. Regions of scar and fibrotic tissue have been identified as a potential driving region of arrhythmic activity during AF, so the ablation of these areas represents a standard treatment. High density mapping techniques can provide important information about low voltage and slow conduction zones, both characteristics of arrhythmogenic areas. However, these modalities remain showing discordances in the location and extent of arrhythmogenic areas.Recently, local impedance (LI) measurements have gained attention as they are expected to distinguish between healthy and scar tissue independently from the atrial rhythm, which can improve the understanding of underlying substrate modifications. A new generation of ablation catheters incorporates the option of LI recordings as a novel technique to char- acterize the process of lesion formation. To extend this technology towards a mapping system implementation, a better understanding on how different factors are influencing LI measurements is needed. For that, two approaches were followed during this work: in silico investigations with different catheters and tissue settings, and in vitro experiments to support simulated studies.By performing in silico studies that can relate to commonly seen clinical scenarios, we were able to predict and understand how different factors contribute to measured LI values. A 3D model of the ablation catheters with the DirectSenseTM technology was employed in different scenarios reported in the clinics, such as the introduction of the catheter in a steerable sheath, or the variation of the catheter-tissue distance, angle, and force. LI data from recruited patients at the Städtisches Klinikum Karlsruhe allowed the validation of the simulation setting.Later, this in silico setting was extended to multielectrode catheters. Simulating the impact of several design parameters in LI, such as stimulation and measurement bipolar pairs, inter-electrode distance, or electrode shape and size, tissue conductivities were reconstructed to account for scarred tissue patterns.Lately, in vitro experiments with a mapping catheter were performed built on the previous simulated findings. Various contact impedance recordings in tissue phantom demonstrated statistical significance when comparing the measurements between electrodes in direct catheter-tissue contact and floating in saline. During this work, the potential capabilities of LI measurements were proven and paved the way towards its use as a surrogate for detection of fibrotic areas in cardiac mapping, complementing commonly used techniques based on electrogram (EGM) analysis.