Abstract:

INTRODUCTION: The "Experimental Data and Geometric Analysis Repository", or EDGAR is an Internet-based archive of curated data that are freely distributed to the international research community for the application and validation of electrocardiographic imaging (ECGI) techniques. The EDGAR project is a collaborative effort by the Consortium for ECG Imaging (CEI, ecg-imaging.org), and focused on two specific aims. One aim is to host an online repository that provides access to a wide spectrum of data, and the second aim is to provide a standard information format for the exchange of these diverse datasets. METHODS: The EDGAR system is composed of two interrelated components: 1) a metadata model, which includes a set of descriptive parameters and information, time signals from both the cardiac source and body-surface, and extensive geometric information, including images, geometric models, and measure locations used during the data acquisition/generation; and 2) a web interface. This web interface provides efficient, search, browsing, and retrieval of data from the repository. RESULTS: An aggregation of experimental, clinical and simulation data from various centers is being made available through the EDGAR project including experimental data from animal studies provided by the University of Utah (USA), clinical data from multiple human subjects provided by the Charles University Hospital (Czech Republic), and computer simulation data provided by the Karlsruhe Institute of Technology (Germany). CONCLUSIONS: It is our hope that EDGAR will serve as a communal forum for sharing and distribution of cardiac electrophysiology data and geometric models for use in ECGI research.

Abstract:

The interaction of spiral waves of excitation with atrial anatomy remains unclear. This simulation study isolates the role of atrial anatomical structures on spiral wave spontaneous drift in the human atrium. We implemented realistic and idealised 3D human atria models to investigate the functional impact of anatomical structures on the long-term ( approximately 40 s) behaviour of spiral waves. The drift of a spiral wave was quantified by tracing its tip trajectory, which was correlated to atrial anatomical features. The interaction of spiral waves with the following idealised geometries was investigated: (a) a wedge-like structure with a continuously varying atrial wall thickness; (b) a ridge-like structure with a sudden change in atrial wall thickness; (c) multiple bridge-like structures consisting of a bridge connected to the atrial wall. Spiral waves drifted from thicker to thinner regions and along ridge-like structures. Breakthrough patterns caused by pectinate muscles (PM) bridges were also observed, albeit infrequently. Apparent anchoring close to PM-atrial wall junctions was observed. These observations were similar in both the realistic and the idealised models. We conclude that spatially altering atrial wall thickness is a significant cause of drift of spiral waves. PM bridges cause breakthrough patterns and induce transient anchoring of spiral waves.

Abstract:

Models of cardiac mechanics are increasingly used to investigate cardiac physiology. These models are characterized by a high level of complexity, including the particular anisotropic material properties of biological tissue and the actively contracting material. A large number of independent simulation codes have been developed, but a consistent way of verifying the accuracy and replicability of simulations is lacking. To aid in the verification of current and future cardiac mechanics solvers, this study provides three benchmark problems for cardiac mechanics. These benchmark problems test the ability to accurately simulate pressure-type forces that depend on the deformed objects geometry, anisotropic and spatially varying material properties similar to those seen in the left ventricle and active contractile forces. The benchmark was solved by 11 different groups to generate consensus solutions, with typical differences in higher-resolution solutions at approximately 0.5%, and consistent results between linear, quadratic and cubic finite elements as well as different approaches to simulating incompressible materials. Online tools and solutions are made available to allow these tests to be effectively used in verification of future cardiac mechanics software.

Abstract:

Atrial fibrillation (AF) is the most common arrhythmia of the heart in industrialized countries. Its generation and the transitory behavior of paroxysmal AF are still not well understood. In this work we examine the interaction of two activation sources via an isthmus as possible cause for the initiation of fibrillation episodes. For this study, the electrophysiological model of Bueno-Orovio, Cherry and Fenton is adapted to atrial electrophysiology, both for physiological and electrophysiologically remodeled conditions due to AF. We show that the interaction of the pacemakers, combined with the geometrical constraints of the isthmus, can produce fibrillatory-type irregularities, which we quantify by the loss of spatial phase coherence in the transmembrane voltage. Transitions to irregular behavior occur when the frequencies of the pacemakers exceed certain thresholds, suggesting that AF episodes are initiated by frequency changes of the activating sources (sinus node, ectopic focus).

Abstract:

Background: Intracardiac electrograms are an indispensable part during diagnosis of supraventriculararrhythmias, but atrial activity (AA) can be obscured by ventricular far-fields (VFF). Concepts based onstatistical independence like principal component analysis (PCA) cannot be applied for VFF removalduring atrial tachycardia with stable conduction.Methods: A database of realistic electrograms containing AAand VFF was generated. Both PCA and thenew technique periodic component analysis (πCA) were implemented, benchmarked, and applied toclinical data.Results: The concept of πCA was successfully verified to retain compromised AA morphology,showing high correlation (cc = 0.98 ± 0.01) for stable atrial cycle length (ACL). Performance ofPCA failed during temporal coupling (cc = 0.03 ± 0.08) but improved for increasing conductionvariability (cc = 0.77 ± 0.14). Stability of ACL was identified as a critical parameter for πCAapplication. Analysis of clinical data confirmed these findings.Conclusion: πCA is introduced as a powerful new technique for artifact removal in periodic signals.Its concept and performance were benchmarked against PCA using simulated data and demonstratedon measured electrograms.

Abstract:

PURPOSE: To evaluate two commonly used respiratory motion correction techniques for coronary magnetic resonance angiography (MRA) regarding their dependency on motion estimation accuracy and final image quality and to compare both methods to the respiratory gating approach used in clinical practice. MATERIALS AND METHODS: Ten healthy volunteers were scanned using a non-Cartesian radial phase encoding acquisition. Respiratory motion was corrected for coronary MRA according to two motion correction techniques, image-based (IMC) and reconstruction-based (RMC) respiratory motion correction. Both motion correction approaches were compared quantitatively and qualitatively against a reference standard navigator-based respiratory gating (RG) approach. Quantitative comparisons were performed regarding visible vessel length, vessel sharpness, and total acquisition time. Two experts carried out a visual scoring of image quality. Additionally, numerical simulations were performed to evaluate the effect of motion estimation inaccuracy on RMC and IMC. RESULTS: RMC led to significantly better image quality than IMC (P's paired Student's t-test were smaller than 0.001 for vessel sharpness and visual scoring). RMC did not show a statistically significant difference compared to reference standard RG (vessel length [99% confidence interval]: 86.913 [83.097-95.015], P = 0.107; vessel sharpness: 0.640 [0.605-0.802], P = 0.012; visual scoring: 2.583 [2.410-3.424], P = 0.018) in terms of vessel visualization and image quality while reducing scan times by 56%. Simulations showed higher dependencies for RMC than for IMC on motion estimation inaccuracies. CONCLUSION: RMC provides a similar image quality as the clinically used RG approach but almost halves the scan time and is independent of subjects' breathing patterns. Clinical validation of RMC is now desirable. J. Magn. Reson. Imaging 2015.

Abstract:

Over the last decades, the information content derived from cardiac electric and magnetic field measurements has been debated. Our co-workers Wilhelms et al. inves- tigated electrically silent acute ischemia in human ven- tricles caused by occlusion of a coronary artery. In the present work, we extend the previous study by calculating associated magnetic fields produced by early stage acute ischemia with varying transmural extent. Multiscale com- putational simulations were performed for calculations of body surface potential maps (BSPM) and magnetocardio- grams (MCG) on a magnetometer sensor matrix situated above the anterior chest wall. Depending on the ischemia size, the ST-segments of the simulated electrocardiograms (ECG) experienced depression for subendocardial cases and elevation for transmural ischemia. One intermedi- ate extent resulted in a zero ST-segment which makes it diagnostically indistinguishable from the healthy case. Magnetic field calculations for this electrically silent is- chemia also revealed no difference compared to the control case. Otherwise, both ECG and MCG signals during ST- segments showed either depression or elevation from zero line. In this simulation study, MCG did not deliver addi- tional information to uncover electrically silent ischemia. For a general conclusion, further in-silico investigations with different ischemia shapes, sizes and positions should be performed and clinical studies with recordings of both ECG and MCG signals have to be conducted.

Abstract:

BACKGROUND: Considering the rates of sudden cardiac death (SCD) and pump failure death (PFD) in chronic heart failure (CHF) patients and the cost-effectiveness of their preventing treatments, identification of CHF patients at risk is an important challenge. In this work, we studied the prognostic performance of the combination of an index potentially related to dispersion of repolarization restitution (Deltaalpha), an index quantifying T-wave alternans (IAA) and the slope of heart rate turbulence (TS) for classification of SCD and PFD. METHODS: Holter ECG recordings of 597 CHF patients with sinus rhythm enrolled in the MUSIC study were analyzed and Deltaalpha, IAA and TS were obtained. A strategy was implemented using support vector machines (SVM) to classify patients in three groups: SCD victims, PFD victims and other patients (the latter including survivors and victims of non-cardiac causes). Cross-validation was used to evaluate the performance of the implemented classifier. RESULTS: Deltaalpha and IAA, dichotomized at 0.035 (dimensionless) and 3.73 muV, respectively, were the ECG markers most strongly associated with SCD, while TS, dichotomized at 2.5 ms/RR, was the index most strongly related to PFD. When separating SCD victims from the rest of patients, the individual marker with best performance was Deltaalpha>/=0.035, which, for a fixed specificity (Sp) of 90%, showed a sensitivity (Se) value of 10%, while the combination of Deltaalpha and IAA increased Se to 18%. For separation of PFD victims from the rest of patients, the best individual marker was TS </= 2.5 ms/RR, which, for Sp=90%, showed a Se of 26%, this value being lower than Se=34%, produced by the combination of Deltaalpha and TS. Furthermore, when performing SVM classification into the three reported groups, the optimal combination of risk markers led to a maximum Sp of 79% (Se=18%) for SCD and Sp of 81% (Se=14%) for PFD. CONCLUSIONS: The results shown in this work suggest that it is possible to efficiently discriminate SCD and PFD in a population of CHF patients using ECG-derived risk markers like Deltaalpha, TS and IAA.

Abstract:

Catheter ablation has emerged as an effective treatment strategy for atrial fibrillation (AF) in recent years. During AF, complex fractionated atrial electrograms (CFAE) can be recorded and are known to be a potential target for ablation. Automatic algorithms have been developed to simplify CFAE detection, but they are often based on a single descriptor or a set of descriptors in combination with sharp decision classifiers. However, these methods do not reflect the progressive transition between CFAE classes. The aim of this study was to develop an automatic classification algorithm, which combines the information of a complete set of descriptors and allows for progressive and transparent decisions. We designed a method to automatically analyze CFAE based on a set of descriptors representing various aspects, such as shape, amplitude and temporal characteristics. A fuzzy decision tree (FDT) was trained and evaluated on 429 predefined electrograms. CFAE were classified into four subgroups with a correct rate of 81+/-3%. Electrograms with continuous activity were detected with a correct rate of 100%. In addition, a percentage of certainty is given for each electrogram to enable a comprehensive and transparent decision. The proposed FDT is able to classify CFAE with respect to their progressive transition and may allow objective and reproducible CFAE interpretation for clinical use.

Abstract:

The fiber orientation in the atria has a significant contribution to the electrophysiologic behavior of the heart and to the genesis of arrhythmia. Atrial fiber orientation has a direct effect on excitation propagation, activation patterns and the P-wave. We present a rule-based algorithm that works robustly on different volumetric meshes composed of either isotropic hexahedra or arbitrary tetrahedra as well as on 3-dimensional triangular surface meshes in patient-specific geometric models. This method fosters the understanding of general pro-arrhythmic mechanisms and enhances patient-specific modeling approaches.

Abstract:

Electroencephalography (EEG) is a method to measure the electrical activity of brain signals by electrodes attached to the scalp at multiple locations. In this study we used the EEG signals of Alcoholic and Control subjects were obtained from Machine Learning repository according to the 10-20 International System. There were 29 subjects from control group and 29 from alcoholic comprising of electrodes from different brain lobes such as Central Lobe (C3, C4), Frontal (F3, F4, F7, F8), Occipital Lobe (O1, O2), Parietal Lobe (P3, P4), Temporal Lobe (T7) and Front Polar (Fp1, Fp2). In the first phase, the nonlinear complexity based features are computed such as Approximate Entropy, Sample Entropy and Wavelet Entropy. These features for each electrode are passed as input to the Machine Learning classifiers such as Multilayer Perceptron (MPL), K-nearest Neighbor (KNN) and LIB Support Vector Machine (SVM) to classify for alcoholic and control group. The highest accuracy was obtained using MLP of 98.22 % at electrode C3. Moreover, above 90% accuracy was obtained using MPL at electrode C3, C4, F7; KNN at electrodes C3, C4, F7 and LIB SVM at electrodes C3, C4, F7 where KNN gives highest accuracy of 97.67% at electrode C4 and LIB SVM an accuracy of 94.67 % at electrode F7. Secondly, the ensemble methods are employed such as Minimum, Maximum, Sum, Average, Product, Majority Vote, Bayes, Decision Template and Dempster Shefer Fusion. Using ensemble methods most electrodes depicted higher accuracy than individual classifier such as Electrode F4, Fp2, O1, O2 and T7. While electrode C3 the ensemble methods Moving Average, DT, DFT gives highest accuracy of 98.22% and at electrodes C4 Moving Average, Sum, Average, DT, DFT provided an accuracy of 97.11%.

Abstract:

Stroke is one of the main causes of death in western society. Regarding the two types, hemmorrhagic or ischemic stroke, fundamentally different treatment is necessary. In diagnosis of stroke, several imaging technologies like CT or MRT are already established but very expensive und not transportable. Microwave tomography is a promising technology to create a solution in order to improve diagnosis of hemorrhagic stroke. The developement of a measurement setup utilized for stroke detection is done using FDTD- Simulation to test the design and antennas. In this work, the approach was performed using a rectangular antenna-array with Vivaldi antennas for measurement. Therefor, a simple but realistic head-phantom with permittivity values comparable to human tissue was used. The simulation and measurement results are calculated by a software framework. It includes forward calculation using the MEEP-Framework and Gauss- Newton optimization for the update of values. The ill-posed inverse Problem is regularized by Tikhonov algorithm.

Abstract:

State of the art biomedical engineering allows for acquiring enormous amounts of intracardiac data to aid diagnosis and treatment of cardiac arrhythmias. Modern catheters, which are used to acquire electrical information from within the heart, are capable of recording up to 64 channels simultaneously. The software available for data analysis, however, does not provide adequate performance to neither analyze nor visualize the acquired information in an appropriate manner. We present a software package that fascilitates interdisciplinary collaborations between engineers and physicians to adress open questions about pathophysiological mechanisms using data from everyday electrophysiogical studies. Therefore, a package has been compiled that enables algorithm development using MATLAB and subsequent visualization using the VTK C++ class libraries. The resulting application KaPAVIE, which is presented in this paper, is designed to meet the requirements from the clinical side and has been successfully applied in the clinical environment.

Abstract:

By means of computer modeling general comprehension of electrophysiology (EP) of human atria can be improved and simulated patterns of ectopic foci, reentry and rotors can be created. On the other hand atrial electrograms are measured in the EP lab of many hospitals every day. In this contribution simulated and measured clinical signals are compared critically aiming at better understanding of atrial fibrillation and validation of computer modeling.

Abstract:

Heart Rate Variability studies are a known measure for the autonomous control of the heart rate. In special situations, its interpretation can be ambiguous, since the respiration has a major influence on the heart rate variability. For this reason it has often been proposed to measure Heart Rate Variability, while the subjects are breathing at a constant respiration rate. That way the spectral influence of the respiration is known. In this work we propose to remove this constant respiratory influence from the heart rate and the Heart Rate Variability parameters to gain respiration free autonomous controlled heart rate signal. The spectral respiratory component in the heart rate signal is detected and characterized. Subsequently the respiratory effect on Heart Rate Variability is removed using spectral filtering approaches, such as the Notch filter or the Raised Cosine filter. As a result new decoupled Heart Variability parameters are gained, which could lead to new additional interpretations of the autonomous control of the heart rate.

Abstract:

ECG derived respiration (EDR) is a technique applied to estimate the respiration signal using only the electrocardiogram (ECG). Different approaches have been proposed in the past on how respiration could be gained from the ECG. However, in many applications only one of them is used while the others are not considered at all. In this paper, we propose a new algorithm for the optimal linear combination of different EDR methods in order to create a more accurate estimation. Using two well known databases, it was statistically shown that an optimally chosen fixed set of coefficients for the linear combination delivers a better estimation than each of the methods used solely.

Abstract:

Automatic signal processing of intracardiac electrograms plays a decisive role in the diagnosis and treatment of supraventricular arrhythmias. During sustained atrial flutter, a repetitive signal is measured in the atrium. However, the ventricular far field may overlap with the atrial activity and compromises the automatic signal processing tools during the intervention. Recently, a new method based on periodic component analysis was proposed as an artifact removal technique. The method works satisfactorily with highly periodic atrial activities but fails to reconstruct not regularly repeating signals .In order to account for that case, we developed a new method based on orthogonal component analysis to reconstruct the corrupted atrial electrocardiograms obscured by ventricular far field. We tested the method on synthetic signals and proved it to be successful. The reconstructed signals were of higher quality and the computation time was drastically shorter than the already existing periodic component analysis. We conclude that the new method can be used in realistic scenarios in the future.

Abstract:

The clinical efficacy in preventing the recurrence of atrial fibrillation (AF) is higher for amiodarone than for dronedarone. Moreover, pharmacotherapy with these drugs is less successful in patients with remodeled substrate induced by chronic AF (cAF) and patients suffering from familial AF. To date, the reasons for these phenomena are only incompletely understood. We analyzed the effects of these two drugs in a computational model of atrial electrophysiology. The Courtemanche-Ramirez-Nattel model was adapted to represent cAF remodeled tissue and hERG mutations N588K and L532P. The pharmacodynamics of amiodarone and dronedarone were investigated with respect to their dose and heart rate dependence by evaluating 10 descriptors of action potential morphology and conduction properties. An arrhythmia score was computed based on a subset of these biomarkers and analyzed regarding circadian variation of drug concentration and heart rate. Action potential alternans at high frequencies was observed over the whole dronedarone concentration range at high frequencies, while amiodarone caused alternans only in a narrow range. The total score of dronedarone reached critical values in most of the investigated dynamic scenarios, while amiodarone caused only minor score oscillations. Compared with the other substrates, cAF showed significantly different characteristics resulting in a lower amiodarone but higher dronedarone concentration yielding the lowest score. Significant differences exist in the frequency and concentration-dependent effects between amiodarone and dronedarone and between different atrial substrates. Our results provide possible explanations for the superior efficacy of amiodarone and may aid in the design of substrate-specific pharmacotherapy for AF.

Abstract:

Vernakalant is a new antiarrhythmic agent for the treatment of atrial fibrillation. While it has proven to be effective in a large share of patients in clinical studies, its underlying mode of action is not fully understood. In this work, we aim to link experimental data from the subcellular, tissue, and system level using an in-silico approach. A Hills equation-based drug model was extended to cover the frequency dependence of sodium channel block. Two model variants were investigated: M1 based on subcellular data and M2 based on tissue level data. 6 action potential (AP) markers were evaluated regarding their dose, frequency and substrate dependence. M1 comprising potassium, sodium, and calcium channel block reproduced the reported prolongation of the refractory period. M2 not including the effects on potassium channels reproduced reported AP morphology changes on the other hand. The experimentally observed increase of ERP accompanied by a shortening of APD90 was not reproduced. Thus, explanations for the drug-induced changes are provided while none of the models can explain the effects in their entirety. These results foster the understanding of vernakalants cellular mode of action and point out relevant gaps in our current knowledge to be addressed in future in-silico and experimental research on this aspiring antiarrhythmic agent.

Abstract:

Baseline wander removal is one important part of electrocardiogram (ECG) filtering. This can be achieved by many different approaches. This work investigates the influence of three different baseline wander removal techniques on ST changes. The chosen filters were phase-free Butterworth filtering, median filtering and baseline correction with cubic spline interpolation. 289 simulated ECGs containing ischemia were used to determine the influence of these filtering processes on the ST segment. Synthetic baseline wander and offsets were added to the simulated signals. All methods proved to be good approaches by removing most of the baseline wander in all signals. Correlation coefficients between the original signals and the filtered signals were greater than 0.93 for all ECGs. Cubic spline interpolation performed best regarding the preservation of the ST segment amplitude change when compared to the original signal. The approach modified the ST segment by 0.10mV±0.06mV at elevated K points. Median filtering introduced a variation of 0.33mV±0.29mV, Butterworth filtering reached 0.16mV±0.14mV at elevated K points. Thus, all methods manipulate the ST segment.

Abstract:

ECG imaging as noninvasive method is aiming to reconstruct the distribution of the transmembrane voltage amplitudes (TMVs) from the body surface potential map (BSPM). Due to the ill-posedness, standard approaches like the Tikhonov regularization method cause blurring and artefacts in the solution. To suppress blurring and artefacts, this work investigated a model based approach, the unscented Kalman filter (UKF). The intention of this paper is to show the potential of an UKF approach by using an idealized parametrization.

Abstract:

This handout describes the simulation dataset KIT-20-PVC_Simulation-1906-10-30, which was contributed by the Karlsruhe Institute of Technology (KIT) to the Experimental Data and Geometric Analysis Repository (EDGAR) database.

Abstract:

Diagnosis of atrial flutter caused by ablation of atrial fibrillation is complex due to ablation scars. This paper presents an approach to replicate the clinically measured flutter circuit in a dynamic computer model. In a first step, important anatomical features of the flutter circuit are extracted manually based on the clinical measurement. With the help of this information, the electrical excitation propagation is simulated on the atrial geometry using the fast marching method. The simulated flutter circuit is used to estimate the global and local conduction velocity by approximating it iteratively. The parameterized flutter simulation is supposed to support the physician during diagnosis and treatment of atrial flutter.

Abstract:

This work aimed at the detection of rotor centers within the atrial cavity during atrial fibrillation on the basis of phase singularities. A voxel based method was established which employs the Hilbert transform and the phase of unipolar electrograms. The method provides a 3D overview of phase singularities at the endocardial surface and within the blood volume. Mapping those phase singularities from the inside of the atria at the endocardium yielded rotor center trajectories.We discuss the results for an unstable and a more stable rotor. The side length of the areas covered by the trajectories varied from 1.5mm to 10 mm. These results are important for cardiologists who target rotors with RF ablation in order to cure atrial fibrillation.

Abstract:

The success rate of the cardiac ablation procedure to cure atrial fibrillation is moderate and depends on the experience and expertise of the physicians. It could be increased by precisely locating arrhythmogenic substrates. The aim of this work is to present a simple and feasible method to analyze intraatrial electrograms to identify the arrhythmogenic substrate on the atrium, under sinus rhythm and pacing sequences. The change in the depolarization wavefront propagation, resulting from consecutive triggering at a point in the coronary sinus (CS), can be an indication of the arrhythmogenic substrate. The region specific study enables the localization of critical sites in the patient specific atrial anatomy. This could aid the physicians in ascertaining the efficacy of cardiac therapies. In this work the point- to-point analysis of the intraatrial electrograms was carried out.

Abstract:

Catheter ablation is the most widely used minimum invasive technique to cure atrial arrhythmias. However, the success rate of the treatment is still moderate and depends on the experience and expertise of the physicians. The aim of this work is to present a simple and feasible method to identify the arrhythmogenic areas on the atrium based on the duration of atrial activities in the intraatrial electrograms. Depolarization waves are created by giving pacing impulses from coronary sinus (CS). The duration of the activity triggered from sinus node (SN) and pacing sequences are analysed by calculating the duration of the activity to mark regions with long atrial activitywaves. The intraatrial electrograms have been analysed on the basis of temporal and spatial information. The region specific study may favour the localization of the critical sites in the patient specific atrial anatomy and aid the physician in ascertaining the efficacy of the cardiac therapies. The identification of suitable markers for critical patterns of the depolarization waves may be crucial to guide an effective ablation treatment. In this work a novel study for point-to-point analysis of the intraatrial electrograms was carried out.

Abstract:

Using OpenCL, we developed a cross-platform software to compute electrical excitation conduction in cardiac tissue. OpenCL allowed the software to run parallelized and on different computing devices (e.g., CPUs and GPUs).We used the macroscopic mono-domain model for excitation conduction and an atrial myocyte model by Courtemanche et al. for ionic currents. On a CPU with 12 HyperThreading-enabled Intel Xeon 2.7 GHz cores, we achieved a speed-up of simulations by a factor of 1.6 against existing software that uses OpenMPI. On two high-end AMD FirePro D700 GPUs the OpenCL software ran 2.4 times faster than the OpenMPI implementation. The more nodes the discretized simulation domain contained, the higher speed-ups were achieved.

Abstract:

ECG markers derived from the P-wave are used frequently to assess atrial function and anatomy, e.g. left atrial enlargement. While having the advantage of being routinely acquired, the processes under- lying the genesis of the P-wave are not understood in their entirety. Particularly the distinct contributions of the two atria have not been analyzed mechanistically. We used an in silico approach to simulate P-waves originating from the left atrium (LA) and the right atrium (RA) separately in two realistic models. LA contribution to the P-wave integral was limited to 30% or less. Around 20 % could be attributed to the first third of the P-wave which reflected almost only RA depolarization. Both atria contributed to the second and last third with RA contribution being about twice as large as LA contribution. Our results foster the comprehension of the difficulties related to ECG-based LA assessment.

Abstract:

Atrial fibrillation is a common irregular heart rhythm. Until today there is still a need for research to quantify typical signal characteristics of rotors, which can induce atrial fibrillation. In this work, signal characteristics of a stable and a more unstable rotor in a realistic heart model including fiber orientation were analyzed with the following methods: peak-to-peak amplitude, Hilbert phase, approximate entropy and RS-difference. In this simulation model the stable rotor rotated with a cycle length of 145 ms and stayed in an area of 1.5 mm x 3 mm. Another more unstable rotor with a cycle length of 190 ms moved in an area of 10 mm × 4 mm. In a distance of 2 mm to the rotor tip, the peak-to-peak amplitude decreased significantly, whereas the RS-difference and the approximate entropy were maximal. The rotor center trajectories were detected by phase singularity points determined by the Hilbert transform. We showed that more unstable rotors resulted in more amplitude changes over time and also the cycle length differed more. Furthermore, we presented typical activation time patterns of the Lasso catheter centered at the rotor tip and in different distances to the rotor tip. We suggest that cardiologists use a combination of the described methods to determine a rotor tip position in a more robust manner.

Abstract:

Eine Positionierungsvorrichtung (100) für ein chirurgisches Gerät, insbesondere ein Operationsmikroskop (3), umfasst: – ein erstes Element (102), welches an einem Körperteil eines Benutzers des chirurgischen Geräts anbringbar ist; – ein zweites Element (101), welches an dem chirurgischen Gerät angebracht ist; und – eine Kupplung, welche das erste und das zweite Element (101, 102) lösbar miteinander verbindet, so dass ein Benutzer mittels der Positionierungsvorrichtung (100) eine Kraft zum Positionieren des chirurgischen Geräts von seinem Körperteil auf das chirurgische Gerät übertragen kann.

Abstract:

In a system and a method for examining an object containing a fluid liquid, the object is illuminated with measuring light and images are temporarily shortly subsequently recorded. The images are evaluated per pixel to determine perfusion data from a high frequency portion above 1 kHz and to determine further information about properties of the object from a low frequency portion below 100 Hz, such as a degree of oxygenation of hemoglobin, a concentration of hemoglobin or a concentration of ICG. This information determined by evaluation is displayed in a form of an image in superposition with a white light image of the object.

Abstract:

A biomechanical simulation framework has been developed which allows to simulate the contraction of the whole human heart. Further, an inverse solving algorithm has been developed, which works in an opposite manner and allows to reconstruct the active tension distribution from provided data of the motion of the heart surfaces, which can for example be extracted from medical imaging data. This allows for a personalization of the model based on clinical data.

Abstract:

ECG imaging was performed in humans to reconstruct ventricular activation patterns and localize their excitation origins. The precision of the non-invasive reconstructions was evaluated against invasive measurements and found to be in line with the state-of-the-art literature. Statistics were produced for various excitation origins and reveal the beat-to-beat robustness of the imaging method.

Abstract:

The disease pattern of stroke has a huge impact on today's society. It is the fourth most frequent cause of death in Germany and causes long-lasting effects for the affected person. The degree of irreversible damage majorly depends on the idle time until a differential diagnosis of the disease is performed. Currently such a diagnosis can only be executed by the imaging techniques MRT (Magnetic Resonance Tomography) and CT (Computer Tomography). Both techniques are cost-intensive and can only be used in certain locations, i.e. in hospitals or special stroke units. The transport of the patient to these locations takes a significant amount of valuable time. Therefore research for a technology which is faster, cheaper and usable in a mobile system is brought forward. Microwave imaging shows promise in these aspects. Systems using microwave imaging are under developement and the mode of action needs to be verified through tests on realistic human head phantoms. In a previous bachelor thesis, a phantom of the human head has been developed which has dielectric properties similar to those of the different tissues of a human head. The materials used were clay for the scull and compositions of water, sugar and gelatine for soft tissues.Different permittivity values for different tissues are essential for high-contrast measurements with microwave imaging technology. On this account an important factor for the phantom and the dominant topic of this thesis is diffusion between the materials for soft tissues. In addition skull as well as the border between skin and the measuring antennas were analysed regarding its permittivity.

Abstract:

Atrial fibrillation represents the most frequent cardiac arrhythmia in the western world. One of the medical treatments for atrial fibrillation is the radiofrequency ablation (RFA) therapy. Unfortunately, a recurrence rate of RFA of about 35-45% exists. In order to improve the efficiency of the therapy a precise knowledge about the electrophysiological properties of the ablation lesions is necessary. With the help of an experimental setup the electrical activity of cardiac tissue can be measured by using optical and electrical techniques. The goal of this project is to set an ablation lesion under defined conditions and measure the extracellular potentials around the acute ablation lesion less than 1s after the ablation, to determine electrophysiological changes around the acute lesion. In order to realise this goal an extension of the setup is necessary. First, a Protection Circuit board (PCB), which is connected to a preamplifier and main amplifier system, is imple- mented. The main function of the PCB is to ensure, that either the ablation lesion is set or the extracellular potentials are measured with the help of a multielectrode array on a cardiac tissue and forwarded via the PCB to the preamplifier.Second, a Control board (CB) with a &#956;C and GUI for user inputs is integrated. One part of the CB regulates the connection of the ablation electrode with the HF generator for the ablation, another functions as external control for this generator. At last a &#956;C is competent for the activation of the relays on both boards and checks the switching state of the relays on the PCB.The order of the activation of the relays, as well as specific waiting times are implemented in the &#956;C following a sequence planning. The ablation and waiting times can be defined in a Matlab GUI by the user. Both boards are integrated in the experimental setup and are tested in a test phase with a saline solution instead of cardiac tissue.The switching times of the relays, as well as the communication between all components are successfully tested. Therefore, the boards are integrated effectively in the setup and their functionality is proven by performing the procedure of ablation and measurement with the same settings as during a process with cardiac tissue.

Abstract:

Radiofrequency ablation is a widely used treatment for many types of cardiac arrhythmias. However, complications and arrhythmia recurrence still arise frequently. An essential criterion for a favorable therapy outcome is the creation of transmural lesion lines with the absence of gaps. Intracardiac electrograms provide real-time information regarding the state of the cardiac tissue surrounding the catheter tip. Therefore, intracardiac electrograms may have the potential to offer beneficial contributions for the therapy success. Formation and interpretation of intracardiac electrograms is complex and yet not fully understood. Computational models try to bridge this gap by reconstructing underlying mechanism and phenomena. The clear separation of causalities and the possibility to vary parameters provide valuable knowledge. In this thesis, an existing computational model for point- shaped acute ablation scars was refined. Hereby, electrophysiological parameters were varied. Four parametersets of isotropic and anisotropic excitation propagation were investigated. Clinical measurements from five patients undergoing radiofrequency ablation to treat atrial fibrillation were compared to the computed intracardiac electrograms. Compared to the existing model, the refinements were able to improve congruence with clinical measurements. Subsequently, complex ablation scars were simulated for a parameterset with isotropic excitation propagation. The presence of a necrotic core in the near field of an acute ablation had minor impact on the computed intracardiac electrograms. Further research may lead to robust markers for gapless and transmural lesions in the intracardiac electrogram.

Abstract:

In dieser vorliegenden Arbeit handelt es sich um die Evaluierung des bestehenden Ansatzes und den Vergleich zweier Methodiken der Parameteranpassung. Die erste Methodik involviert metaheuristische Gradientenverfahren (Partikelschwarmoptimierung und Trust-Region-Verfahren), die die bestehende Problemstellung als Optimierungsproblem betrachtet. Die zweite Methodik beruht auf Stichprobenbasierte Ansätze: eine Look-up Ansatz, der die Minimierung einer komplexen Zielfunktion bei der Anpassungsaufgabe zum Ziel gesetzt hat und ein regressionsbasierter Ansatz bzw. die Metamodellierung in ihren beiden Richtungen (klassische und inverse Metamodellierung), die auf der einen Seite die Sensitivität des CRN-Modells gegenüber den Parametern und auf der der anderen die Schätzfähigkeit dieser Parameter zwecks ihrer Untersuchung auf Identifizierbarkeit überprüft.Bei der Anpassung der IKr und IKs synthetischen Messkurven ist die Look-up Funktion in der neuen statistischen Methodik dem Problem der lokalen Minima entkommen. Folglich lassen sich die daraus geschätzten Werte der gemäß der Metamodellierung identifizierbaren Parameter für plausibel erklären. Der Ansatz der Metamodellierung war im Allgemeinen fähig, die meisten Parameter, die für den CRN-Modell-Verhältnis im Bezug auf die Ströme IKr und IKs für wichtig gehalten wurden, zu identifizieren.Eine genaue Untersuchung der hierarchischen Metamodellierung (Untersuchung der einzelnen Cluster) kann wichtige Informationen über die Paramater, die im Rahmen der globalen Metamodellierung nicht identifiziert geworden sind, verraten (Tøndel et al. [36]). Eine Anwendung anderer Spannungsprotokolle für die Identifizierbarkeit dieser Parameter ist auch empfehlenswert.Eine Vorstellung von dem optimalen Algorithmus ist eine logische Schlussfolgerung aus der Durcharbeitung beider Algorithmen. Die Idee besteht darin, beide Algorithmen zu kombinieren: die statistische Pipeline wird verwendet, um die Identifizierbarkeit der Modellparameter zu untersuchen und der Optimierungsbasierte Algorithmus wird angewendet um eine genaue Schätzung der Parameter zu liefern, denn er war bei der Anpassung der Stromkurven (der realen und der synthetischen Stromkurven) robuster und zuverlässiger.

Abstract:

Atrial fibrillation is the most common type of cardiac dysrhythmia. A catheter based ablation of abnormal heart tissue has become a popular method to treat and possibly terminate this arrhythmia. For better treatment, it is important to improve the automated analysis and preprocessing of these signals. In this work, two sets of clinical data of a patient recorded during atrial fibrillation were analyzed to characterize, differentiate, and detect signals showing properties of clinical interest. Therefore, the information of unipolar as well as bipolar electrograms were taken into account. According to questions of clinical interest, a workflow using different methods was implemented.A useful analysis of the electrograms was enabled by the detection of segments with a constant catheter position. Therefore, the x-, y-, and z-coordinates of all 20 mapping electrodes were analyzed. In so doing, 9 segments with a mean length of 4.78 seconds of a 60 second signal respectively 4 segments with a mean length of 4 seconds of a 30 second signal were each detected as being stable. A distinction between signal segments containing clear activation waves and segments with a greater degree of fractionation could be made by the analysis of the signal activity. Therefore, active segments were detected using a wavelet-based approach. Non-fractionated signal segments were labeled as segments with an activity ratio less or equal than 20 %. Drivers of atrial fibrillation are supposed to be identifiable by the detection of highly organized areas. For this purpose, the similarity of activation waves was analyzed and similar activation waves (metric less or equal than 0.6) were then color-coded and highlighted in the signal. Knowledge about the excitation patterns can guide the ablation therapy. Therefore, local activation times of adjacent unipolar signals were detected and assigned to each other to determine spatio- temporal wavefronts. Complex dynamics of cardiac fibrillation can be understood by mapping the spatial distribution of the reconstructed phase. The phase was reconstructed correctly, if unipolar signals containing clear activation waves were recomposed with a sum of sinusoidal wavelets. Since bipolar electrograms originate from the difference of two unipolar measurements, another interesting analysis was the fractionation of associated unipolar signals.

Abstract:

In this work it is shown that electromechanical coupling has a major influence on a whole heart level.It is shown that a higher tension development due to ion channel density variations on a single cell level does not subsequently lead to a higher or lower tension development in a cellular complex but rather in a faster or respectively slower tension development. A change in heterogeneities of ion channel density in the ventricles might therefore be identified by a change in the duration of the systole in relation to the heart cycle length. Hence, the incorporation of the stretch based influences on the tension development shows to be very promising. \\Additionally, heterogeneities which have a major influence on the electrophysiological behavior, such as the blocking of \IKr\ which leads to a prolonged QT-interval as it is the case in LQT2, might not influence the tension development directly. Changes in the behavior of the ventricles during contraction might result from either a different excitation pattern or changes in the intracellular calcium release at the beginning of the action potential due to remodeling. \\During the systole of the heart cycle, the modeled behavior is not far away from measured data. Nevertheless, during the diastole the modeled relaxation of the ventricles showed little likeliness to measured data, thus no real conclusion could be made on the impact of heterogeneities during this time interval. Without a doubt, the model still has room for improvement but this work can be seen as more than just a simple proof of concept. Further investigations into the subject of electrophysiological heterogeneities and their respective influence on the behavior of the ventricles during contraction are highly likely to one day aid physicians diagnosing diseases such as Long-QT-Syndrome.

Abstract:

Atrial fibrillation (AFib) is the most common type of cardiac arrhythmia worldwide. However, mechanisms for the initiation and maintenance of AFib are still not completely understood. Different theories favoring multiple wavelets, ectopic foci and rotational sources as potential drivers for the maintenance of AFib are present. To find those drivers clinicians use different kinds of intracardiac mapping catheters including Singleloop, Doubleloop and PentaRay catheters.Virtual models of those catheters were used to extract information in form of the local activation times (LATs) of each catheter electrode from simulated electrograms (EGMs). The resulting LAT patterns consisting of the LATs of all electrodes were used as input information for different features that were introduced to separate four different excitation patterns during AFib. Those four excitation patterns were plane wave, ectopic focus (spherical wave), rotor (spiral wave) and block. A feature selection algorithm was introduced to investigate the features concerning their usefulness to classify the different simulated excitation patterns. The scores of the selected features were used to train and optimize a Support Vector Machine (SVM). This trained SVM model was used to classify the artificial data as proof of concept and different clinical databases afterwards.For the artificial data an overall classification accuracy of 97.4 % was achieved for the optimized SVM. When the LAT patterns for the artificial data were artificially corrupted by additive Gaussian noise a reduction of the classification accuracy dependent on the noise level was observable. For three clinical databases different results were obtained. For the atrial flutter (AFL) database with LAT patterns similar to the noise-free artificial data a high predictive accuracy was achieved. For another database containing pacing episodes misclassifications occurred. LAT patterns with outliers were often misclassified as block or rotor excitation patterns. For the AFib database LAT patterns very different from those in the noise-free artificial data were observed. Most of the AFib data records were classified as block or rotor excitation patterns.

Abstract:

Accurately describing and understanding the myocardial structure as well as the me- chanic cardiac properties would provide crucial knowledge about normal and abnormal cardiac electro-mechanics. Several studies have quantified the cardiac fiber orientation using a local coordinate system with which the helix angles were determined. The most used approaches to fulfill this task include rule-based and image-based methods.First, fiber orientations were assessed by using a novel global coordinate system. The aim of establishing such a new coordinate system is to compare it to the local coordinate system defined by Bayer. The results demonstrate that the greatest difference between the two coordinate systems is 23.2&#9702;. The lowest fiber angle deviation has a value of 6.94&#9702;.Second, the hyperelastic material law of Costa, which takes into account the fully three dimensional architecture of the myocardium, was implemented and then compared to the material law of Guccione. These laws have been using anisotropic strain energy functions that best fit the stress-strain behavior of the myocardium obtained from uniaxial tests. Hence the theory of continuum mechanics is used in conjunction with simulations of uni- axial tests in order to generate stress-strain curves of respectively the Costa and Guccione law. This yielded further insights into the mechanical features of the heart muscle and allowed a comparison between the two material laws mentioned above.

Abstract:

The fiber orientation in the atria has a significant contribution to the electrophysiologic behavior of the heart and to the genesis of arrhythmia. Atrial fiber orientation has a direct effect on excitation propagation, activation patterns and the P-wave. In this diploma thesis, a rule-based algorithm that works robustly on different volumetric meshes composed of either isotropic hexahedra or arbitrary tetrahedra as well as on 3-dimensional triangular surface meshes in patient-specific geometric models is presented. Furthermore, a rule-based algorithm is presented that can place different ablation scars with four ablationtypes in these meshes. The fiber orientation was annotated in eight patients and inthree different mesh types. All meshes could be annotated. The ablation scars were also annotated in eight different meshes and in three different mesh types using four different ablation types. All meshes could be annotated.Finally, an analysis of the influence of fiber orientation on the flutter paths was performed. It could be shown that there is an influence of the fiber orientation on the flutter paths.

Abstract:

Laparoscopic surgery, which offers considerable benefits to patients, has been steadily gaining popularity. In addition to reducing blood loss and post-operative pain, the recovery time can be reduced. However, a laparoscopy is a complex intervention with several disadvantages for the surgeon. The endoscope, for example, covers only a small part of the body inside, resulting in a reduced field of view for the surgeon. The aim of a context- aware assistance system is to overcome some of these drawbacks by providing the surgeon relevant information at the right time. This can be achieved if the current intervention phase is known. To this effect, information about the laparoscopic instruments involved is required. There is already a method that can detect and identify the instruments. However, this method still shows some shortcomings, for example, when two instruments are in close proximity to each other. In this thesis, an image-based method for tracking laparoscopic instruments is developed that both builds on the detector and complements it. The temporal component provides new information that deals more effectively with difficult situations than the detector does. First, features are extracted for each detected instrument. Using the Lucas-Kanade algorithm, the optical flow for these features is determined and used to propagate the instruments in time. The method is evaluated on videos from both in-vivo surgeries and ex-vivo experiments with the DaVinci system for robotic surgery. In addition to the accuracy, the runtime of the method was examined. With an average of 10.1 ms per frame, the tracking can be done in real time and is significantly faster than the detection.

Abstract:

The spread of electrical activity through the ventricular myocardium produces the QRS complex on the ECG and the Purkinje tree is the major component in the correct elec- trical sequence initiation of the ventricles. Unfortunately, no in-vivo imaging system can visualize the Purkinje system and its activity in individual patients. On the other hand, the precise activation sequence of the ventricles is needed in order to reconstruct proper- ly the depolarization and repolarization process in the individuals heart and therefore the proper ECG waveforms. The aim of this Bachelor thesis is to use ECG imaging (the inverse problem of ECG) to estimate local activation times (activation time imaging) based on body surface potential maps (BSPM). The task of the thesis is to prove the concept: to use a predefined stimulation protocol for simulating the electrical excitation propagation in the heart and to perform a forward calculation in the corresponding torso model in order to generate a synthetic BSPM during the QRS complex (see Chapter 3.2). The monodomain model is selected as an excitation propagation model (see Chap- ter 3.1.2). The synthetic BSPM data will be used to calculate local activation times by solving the inverse problem of ECG (see Chapter 3.5.3). For solving the inverse problem the Multi-Foci Search Algorithm of [1] has been applied (see Chapter 3.5.3.2). As a final point, it follows the evaluation of activation times reconstructions during the excitation propagation.

Abstract:

In order to understand the mechanisms causing and maintaining atrial fibrillation (AFib) and atrial flutter (AFlut), the intraatrial excitation is measured with multi-electrode map- ping catheters. The unorganized excitation propagation during atrial fibrillation makes an interpretation of measured intracardiac electrogram data very difficult. Frequency do- main analysis methods are an approach to extract valuable diagnostic information.In this thesis, an approach for the statistical analysis of intracardiac mapping data was implemented and evaluated. With the partial directed coherence function (PDC), direc- tional couplings between electrodes are determined. It is a method to measure Granger causality in the frequency domain. Before computation of the PDC, a multivariate autore- gressive model (MVAR model) is fitted on the measured data by sparse modeling. The approach was implemented and evaluated on simulated and clinical data. Simulations of AFlut were realized with an implementation of the fast marching algorithm for which a graphical user interface was implemented. The intraatrial electrograms were forward cal- culated with an adapted implementation of the boundary element method. Furthermore, methods for the 3D visualization and evaluation of coupling information resulting from the statistical electrogram analysis were developed.The application of the statistical modeling approach on intracardiac electrogram data showed that recurrent propagation patterns could successfully be detected. The selected time window was found to have a strong influence on the result, especially during AFib, where the propagation patterns often stay only stable for several seconds.During the analysis of basket catheter data, the results were often limited by bad coverage of the atrium by the catheters. Due to spline deformation and the specific geometry of the catheter, large areas were frequently badly covered and no satisfactory results could be obtained for these areas. In the well covered areas, basket catheters were found to be very suitable for the detection of global patterns, whereas for the detection of localized patterns smaller catheter geometries were more appropriate.