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Cardiac arrhythmias such as atrial fibrillation occur frequently in industrialized countries. Radiofrequency ablation (RFA) is a standard treatment if drug therapy fails. This minimally invasive surgery aims at stabilizing the heart rhythm on a permanent basis. However, the procedure commonly needs to be repeated because of the high recurrence rate of arrhythmias. Non-transmural lesions as well as gaps within linear lesions are among the main problems during the RFA. The assessment of lesion formation is not adequate in state of the art procedures. Therefore, the aim of this study is to investigate the short-term reversibility of lesions using human electrograms recorded by a high-density mapping system during an electrophysiological study (EPS). A predefined measurement protocol was executed during the EPS in order to create three ablation points in the left atrium. Subsequently, after preprocessing the recorded signals, electrogram (EGM) paths were formed along the endocardial surface of the atrium. By analyzing changes of peak to peak amplitudes of unipolar EGMs before and after ablation, it was possible to distinguish lesion area and healthy myocardium. The peak to peak amplitudes of the EGMs decreased by 40-61% after 30 seconds of ablation. Furthermore, we analyzed the morphological changes of EGMs surrounding the lesion. High-density mapping data showed that not only the tissue, which had direct contact with the catheter tip during the RFA, but also the surrounding tissue was affected. This was demonstrated by low peak to peak amplitudes in large areas with a width of 14 mm around the center of the ablation lesion. After right pulmonary vein isolation, high-density mapping was repeated on the previous lesions. The outer region of RFA-treated tissue appears to recover as opposed to the central core of the ablation point. This observation suggests that the meaningfulness of an immediate remap after ablation during an EPS may lead the physician to false conclusions

Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC) as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96).

Cardiac arrhythmias are a widely spread disease in industrialized countries. A common clinical treatment for this disease is radiofrequency ablation (RFA), in which high frequency alternating current creates a lesion on the myocardium. However, the formation of the lesion is not entirely understood. To obtain more information about ablation lesions (ALs) and their electrophysiological properties, we established an in-vitro setup to record electrical activity of rat myocardium. Electrical activity is measured by a circular shaped multielectrode array. This work was focused to gain more information by developing algorithms to process the measured electrical signals to collect different features, which may allow us to characterize an AL. First, pacing artefacts were detected and blanked. Subsequently, data were filtered. Afterwards, activations in atrial signals were detected using a non-linear energy operator (NLEO) and templates of these activations were generated. Finally, we determined different features on each activation in order to evaluate changes of unipolar as well as bipolar electrograms and considered these features before and after ablation. In conclusion, the majority of the signal features delivered significant differences between normal tissue and lesion. Among others, a reduction in peak to peak amplitude and a diminished spectral power in the band 0 to 100 Hz may be useful indicators for AL. These criteria should be verified in future studies with the aim of estimating indirectly the formation of a lesion.

Radiofrequency ablation is the gold standard for treating cardiac arrhythmias. However, the success rate of this procedure depends on numerous parameters. Wet lab experiments provide the opportunity to investigate cardiac electrophysiology under reproducible conditions. To evaluate the electrophysiological changes of ablated myocardium in these studies it is necessary to consider the three-dimensional (3D) geometry of the lesions. For this purpose, we investigated the usage of different magnetic resonance imaging (MRI) sequences as well as an image processing procedure to analyze in-vitro preparations. To differentiate signal intensities between nonablated and ablated tissue we evaluated FISP (fast imaging with steady-state precession; delivering dominantly T1-weighted images) and RARE (rapid acquisition with relaxation enhancement; delivering dominantly T2-weighted images). After image processing, the ablated tissue was segmented in each image slice forming a 3D volume. The geometry of the lesion was modeled by the boundary of this volume. It was generally feasible to distinguish between healthy myocardium and ablated tissue as well as to determine lesion transmurality. The analysis of the reconstructed lesion geometries from FISP and RARE MRI showed a high agreement, however T2-weighted sequences showed larger lesion volumes as well as higher variations in segmentation compared to T1- mapping. FISP with higher quality may be used to reconstruct the 3D geometry of the ablation lesions.

Recent studies about the development of endocardial radiofrequency (RF) ablation lesions (ALs) tried to identify reliable electrogram (EGM) markers for assessment of lesion transmurality. Additional clinically relevant information for physicians can be provided by examining endocardial EGM parameters like signal morphology, amplitude or time points in the signal. We investigated EGM features of the pulmonary vein ostia before and after RF ablation for three point-shaped lesions. Using high-density (HD) mapping, local activation time (LAT) and voltage maps were created, which provided information about the RF ALs regarding the lesion size and showed activation time delay as well as low-voltage areas with bipolar peak-to-peak voltages smaller than 2mV. The time delay of the depolarization front comparing the activation times anterior and posterior to the RF AL was up to 51.5 ms. In a circular area with 5mm radius around an RF AL the mean peak-to-peak voltage decreased by 62-94% to about 0.12-0.44mV and the mean maximal absolute EGM derivative was reduced by 65-96 %. Comparing the results of this study with EGMs of similar clinical settings confirmed our expectations regarding the low-voltage areas caused by the ablation procedure. An improved understanding of the electrophysiological changes is of fundamental importance to provide more information for enhanced RF ablation assessment.

Radiofrequency ablation (RFA) is a standard clinical procedure for treating many cardiac arrhythmias. In order to increase the success rate of this treatment, the evaluation of lesion development with the help of intracardiac electrogram (EGM) criteria has to be improved further. We are investigating in-vitro the electrophysiological characteristics of cardiac tissue by using fluorescence-optical and electrical techniques. In this project, it is intended to create ablation lesions under defined conditions in rat atria or ventricle and to determine the electrical activity in the myocardium surrounding these lesions less than 1 s after the ablation. Therefore, we developed a semi-automatic RFA procedure, which was integrated into an existing experimental setup. Firstly, a controllable protection circuit board was designed to galvanically isolate the sensitive amplifiers for measuring extracellular potentials during the ablation. Secondly, a real-time system was implemented to control and to autonomously monitor the RFA procedure. We verified each component as well as the different sequences of the RFA procedure. In conclusion, the expanded setup will be used in future in-vitro experiments to determine new EGM criteria to assess lesion formation during the RFA procedure.

Radiofrequency ablation (RFA) is a widely used clinical treatment for many types of cardiac arrhythmias. However, nontransmural lesions and gaps between linear lesions often lead to recurrence of the arrhythmia. Intracardiac electrograms (IEGMs) provide real-time information regarding the state of the cardiac tissue surrounding the catheter tip. Nevertheless, the formation and interpretation of IEGMs during the RFA procedure is complex and yet not fully understood. In this in-silico study, we propose a computational model for acute ablation lesions. Our model consists of a necrotic scar core and a border zone, describing irreversible and reversible temperature induced electrophysiological phenomena. These phenomena are modeled by varying the intra- and extracellular conductivity of the tissue as well as a regulating zone factor. The computational model is evaluated regarding its feasibility and validity. Therefore, this model was compared to an existing one and to clinical measurements of five patients undergoing RFA. The results show that the model can indeed be used to recreate IEGMs. We computed IEGMs arising from complex ablation scars, such as scars with gaps or two overlapping ellipsoid scars. For orthogonal catheter orientation, the presence of a second necrotic core in the near-field of a punctiform acute ablation lesion had minor impact on the resulting signal morphology. The presented model can serve as a base for further research on the formation and interpretation of IEGMs.