Abstract:

AIMS: P-wave morphology correlates with the risk for atrial fibrillation (AF). Left atrial (LA) enlargement could explain both the higher risk for AF and higher P-wave terminal force (PTF) in lead V1. However, PTF-V1 has been shown to correlate poorly with LA size. We hypothesize that PTF-V1 is also affected by the earliest activated site (EAS) in the right atrium and its proximity to inter-atrial connections (IAC), which both show tremendous variability. METHODS AND RESULTS: Atrial excitation was triggered from seven different EAS in a cohort of eight anatomically personalized computational models. The posterior IACs were non-conductive in a second set of simulations. Body surface ECGs were computed and separated by left and right atrial contributions. Mid-septal EAS yielded the highest PTF-V1. More anterior/superior and more inferior EAS yielded lower absolute PTF-V1 values deviating by a factor of up to 2.0 for adjacent EAS. Earliest right-to-left activation was conducted via Bachmann's Bundle (BB) for anterior/superior EAS and shifted towards posterior IACs for more inferior EAS. Non-conducting posterior IACs increased PTF-V1 by up to 150% compared to intact posterior IACs for inferior EAS. LA contribution to the P-wave integral was 24% on average. CONCLUSION: The electrical contributor's site of earliest activation and intactness of posterior IACs affect PTF-V1 significantly by changing LA breakthrough sites independent from LA size. This should be considered for interpretation of electrocardiographical signs of LA abnormality and LA enlargement.

Abstract:

In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 211% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold.

Abstract:

AIMS: Human ether-a-go-go-related gene (hERG) missense mutations N588K and L532P are both associated with atrial fibrillation (AF). However, the underlying gain-of-function mechanism is different. The aim of this computational study is to assess and understand the arrhythmogenic mechanisms of these genetic disorders on the cellular and tissue level as a basis for the improvement of therapeutic strategies. METHODS AND RESULTS: The IKr formulation of an established model of human atrial myocytes was adapted by using the measurement data of wild-type and mutant hERG channels. Restitution curves of the action potential duration and its slope, effective refractory period (ERP), conduction velocity, reentry wavelength (WL), and the vulnerable window (VW) were determined in a one-dimensional (1D) tissue strand. Moreover, spiral wave inducibility and rotor lifetime in a 2D tissue patch were evaluated. The two mutations caused an increase in IKr regarding both peak amplitude and current integral, whereas the duration during which IKr is active was decreased. The WL was reduced due to a shorter ERP. Spiral waves could be initiated by using mutation models as opposed to the control case. The frequency dependency of the VW was reversed. CONCLUSION: Both mutations showed an increased arrhythmogenicity due to decreased refractory time in combination with a more linear repolarization phase. The effects were more pronounced for mutation L532P than for N588K. Furthermore, spiral waves presented higher stability and a more regular pattern for L532P. These in silico investigations unveiling differences of mutations affecting the same ion channel may help to advance genotype-guided AF prevention and therapy strategies.

Abstract:

Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today's high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration.

Abstract:

AIMS: 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 remodelled substrate induced by chronic AF (cAF) and patients suffering from familial AF. To date, the reasons for these phenomena are only incompletely understood. We analyse the effects of the drugs in a computational model of atrial electrophysiology. METHODS AND RESULTS: The Courtemanche-Ramirez-Nattel model was adapted to represent cAF remodelled 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 analysed 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. CONCLUSION: 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:

BACKGROUND: Complementary to clinical and experimental studies, computational cardiac modeling serves to obtain a comprehensive understanding of the cardiovascular system in order to analyze dysfunction, evaluate existing, and develop novel treatment strategies. OBJECTIVES: We describe the basics of multiscale computational modeling of cardiac electrophysiology from the molecular ion channel to the whole body scale. By modeling cardiac ischemia, we illustrate how in silico experiments can contribute to our understanding of how the pathophysiological mechanisms translate into changes observed in diagnostic tools such as the electrocardiogram (ECG). MATERIALS AND METHODS: Quantitative in silico modeling spans a wide range of scales from ion channel biophysics to ECG signals. For each of the scales, a set of mathematical equations describes electrophysiology in relation to the other scales. Integration of ischemia-induced changes is performed on the ion channel, single-cell, and tissue level. This approach allows us to study how effects simulated at molecular scales translate to changes in the ECG. RESULTS: Ischemia induces action potential shortening and conduction slowing. Hence, ischemic myocardium has distinct and significant effects on propagation and repolarization of excitation, depending on the intramural extent of the ischemic region. For transmural and subendocardial ischemic regions, ST segment elevation and depression, respectively, were observed, whereas intermediate ischemic regions were found to be electrically silent (NSTEMI). CONCLUSIONS: In silico modeling contributes quantitative and mechanistic insight into fundamental ischemia-related arrhythmogenic mechanisms. In addition, computational modeling can help to translate experimental findings at the (sub-)cellular level to the organ and body context (e. g., ECG), thereby providing a thorough understanding of this routinely used diagnostic tool that may translate into optimized applications.

Abstract:

Cardiologists measure electric signals inside the human heart aiming at a better diagnosis and optimized therapy of atrial arrhythmias like atrial flutter and atrial fibrillation. The catheters that are used for this purpose are improving: now they are able to pick up the electric signals at up to 64 positions inside the heart simultaneously. The patterns of electric depolarization are sometimes very simple, comparable to plane waves. But in case of patients with severe atrial arrhythmias they can be quite complex: U-turns around a line of block, ectopic centres, break throughs, reentry circuits, rotors, fractionated signals and chaotic patterns are often observed. Methods of biosignal analysis can support the cardiologists in classifying the signals and extract information of high diagnostic relevance. Computer models of the electrophysiology of the human heart can serve to design better algorithms for data analysis and to test algorithms, because the ground truth is known.

Abstract:

Objectives: This study hypothesized that P-wave morphology and timing under left atrial appendage (LAA) pacing change characteristically immediately upon anterior mitral line (AML) block. Background: Perimitral flutter commonly occurs following ablation of atrial fibrillation and can be cured by an AML. However, confirmation of bidirectional block can be challenging, especially in severely fibrotic atria. Methods: The study analyzed 129 consecutive patients (66 ± 8 years, 64% men) who developed perimitral flutter after atrial fibrillation ablation. We designed electrocardiography criteria in a retrospective cohort (n = 76) and analyzed them in a validation cohort (n = 53). Results: Bidirectional AML block was achieved in 110 (85%) patients. For ablation performed during LAA pacing without flutter (n = 52), we found a characteristic immediate V1 jump (increase in LAA stimulus to P-wave peak interval in lead V1) as a real-time marker of AML block (V1 jump ≥30 ms: sensitivity 95%, specificity 100%, positive predictive value 100%, negative predictive value 88%). As V1 jump is not applicable when block coincides with termination of flutter, absolute V1 delay was used as a criterion applicable in all cases (n = 129) with a delay of 203 ms indicating successful block (sensitivity 92%, specificity 84%, positive predictive value 90%, negative predictive value 87%). Furthermore, an initial negative P-wave portion in the inferior leads was observed, which was attenuated in case of additional cavotricuspid isthmus ablation. Computational P-wave simulations provide mechanistic confirmation of these findings for diverse ablation scenarios (pulmonary vein isolation ± AML ± roof line ± cavotricuspid isthmus ablation). Conclusions: V1 jump and V1 delay are novel real-time electrocardiography criteria allowing fast and straightforward assessment of AML block during ablation for perimitral flutter.

Abstract:

The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. For the purpose of finding the best suited filter for the removal of baseline wander, the ground truth about the ST change prior to the corrupting artifact and the subsequent filtering process is needed. In order to create the desired reference, we used a large simulation study that allowed us to represent the ischemic heart at a multiscale level from the cardiac myocyte to the surface ECG. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We found that the best performing method was the wavelet-based baseline cancellation. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered.

Abstract:

Whole-chamber mapping using a 64-pole basket catheter (BC) has become a featured approach for the analysis of excitation patterns during atrial fibrillation. A flexible catheter design avoids perforation but may lead to spline bunching and influence coverage. We aim to quantify the catheter deformation and endocardial coverage in clinical situations and study the effect of catheter size and electrode arrangement using an in silico basket model. Atrial coverage and spline separation were evaluated quantitatively in an ensemble of clinical measurements. A computational model of the BC was implemented including an algorithm to adapt its shape to the atrial anatomy. Two clinically relevant mapping positions in each atrium were assessed in both clinical and simulated data. The simulation environment allowed varying both BC size and electrode arrangement. Results showed that interspline distances of more than 20 mm are common, leading to a coverage of less than 50% of the left atrial (LA) surface. In an ideal in silico scenario with variable catheter designs, a maximum coverage of 65% could be reached. As spline bunching and insufficient coverage can hardly be avoided, this has to be taken into account for interpretation of excitation patterns and development of new panoramic mapping techniques.

Abstract:

Objective: Atrial tachycardia (AT) still pose a major challenge in catheter ablation. Although state-of-the-art electroanatomical mapping systems allow to acquire several thousand intracardiac electrograms (EGMs), algorithms for diagnostic analysis are mainly limited to the amplitude of the signal (voltage map) and the local activation time~(LAT map). We applied spatio-temporal analysis of EGM activity to generate maps indicating reentries and diastolic potentials, thus identifying and localizing the driving mechanism of AT. Methods: First, the time course of active surface area (ASA) is determined during one basic cycle length (BCL). The global cycle length coverage (gCLC) reflects the relative duration within one BCL for which activity was present in each individual atrium. A local cycle length coverage (lCLC) is computed for circular sub-areas with 20mm diameter. The simultaneous active surface area sASA is determined to indicate the spatial extent of depolarizing tissue. Results: Combined analysis of these spatial scales allowed to correctly identify and localize the driving mechanism: gCLC values of 100% were indicative for atria harbouring a reentrant driver. lCLC could detect micro reentries within an area of 1.65±1.28cm2 in simulated data and differentiate them against focal sources. Mid-diastolic potentials, being potential targets for catheter ablation, were identified as the areas showing confined activity based on sASA values. Conclusion: The concept of spatio-temporal activity analysis proved successful and correctly indicated the tachycardia mechanism in 20 simulated AT scenarios and three clinical data sets. Significance: Automatic interpretation of intracardiac mapping data could help to improve the treatment strategy in complex cases of AT.

Abstract:

Optical mapping is widely used as a tool to investigate cardiac electrophysiology in ex vivo preparations. Digital filtering of fluorescence-optical data is an important requirement for robust subsequent data analysis and still a challenge when processing data acquired from thin mammalian myocardium. Therefore, we propose and investigate the use of an adaptive spatio-temporal Gaussian filter for processing optical mapping signals from these kinds of tissue usually having low signal-to-noise ratio (SNR). We demonstrate how filtering parameters can be chosen automatically without additional user input. For systematic comparison of this filter with standard filtering methods from the literature, we generated synthetic signals representing optical recordings from atrial myocardium of a rat heart with varying SNR. Furthermore, all filter methods were applied to experimental data from an ex vivo setup. Our developed filter outperformed the other filter methods regarding local activation time detection at SNRs smaller than 3 dB which are typical noise ratios expected in these signals. At higher SNRs, the proposed filter performed slightly worse than the methods from literature. In conclusion, the proposed adaptive spatio-temporal Gaussian filter is an appropriate tool for investigating fluorescence-optical data with low SNR. The spatio-temporal filter parameters were automatically adapted in contrast to the other investigated filters.

Abstract:

Radiofrequency ablation has become a first-line approach for curative therapy of many cardiac arrhythmias. Various existing catheter designs provide high spatial resolution to identify the best spot for performing ablation and to assess lesion formation. However, creation of transmural and nonconducting ablation lesions requires usage of catheters with larger electrodes and improved thermal conductivity, leading to reduced spatial sensitivity. As trade-off, an ablation catheter with integrated mini electrodes was introduced. The additional diagnostic benefit of this catheter is still not clear. In order to solve this issue, we implemented a computational setup with different ablation scenarios. Our in silico results show that peak-to-peak amplitudes of unipolar electrograms from mini electrodes are more suitable to differentiate ablated and nonablated tissue compared to electrograms from the distal ablation electrode. However, in orthogonal mapping position, no significant difference was observed between distal electrode and mini electrodes electrograms in the ablation scenarios. In conclusion, catheters with mini electrodes bring about additional benefit to distinguish ablated tissue from nonablated tissue in parallel position with high spatial resolution. It is feasible to detect conduction gaps in linear lesions with this catheter by evaluating electrogram data from mini electrodes.

Abstract:

Background: During atrial fibrillation, heterogeneities and anisotropies result in a chaotic propagation of the depolarization wavefront. The electrophysiological parameter called conduction velocity (CV) influences the propagation pattern over the atrium. We present a method that determines the regional CV for deformed catheter shapes, which result due to the catheter movement and changing wall contact.Methods: The algorithm selects stable catheter positions, finds the local activation times (LAT), considers the wall contact and calculates all CV estimates within the area covered by the catheter. The method is evaluated with simulated data and then applied to four clinical data sets. Both sinus rhythm activity as well as depolarization wavefronts initiated by stimulation are analyzed. The regional CV is compared with the fractionation duration (FD) and peak-to-peak (P2P) voltages. A speed of 0.5 m/s was defined to create the simulated LAT.Results: After analyzing the simulated LAT with clinical catheter spatial coordinates, the median CV of 0.5 m/s with an interquartile range of 0.22 and exact CV direction vectors were obtained. For clinical cases, the CV magnitude range of 0.08 m/s to 1.0 m/s was obtained. The P2P amplitude of 0.7 mV to 3.7 mV and the mean FD from 40.79ms to 48.66ms was obtained. The correlation of 0.86 was observed between CV and P2P amplitude, and 0.62 between CV and FD.Conclusion: In this paper, a method is presented and validated which calculates the CV for the deformed catheter and changing wall contact. In an exemplary clinical data set correlation between regional CV with FD and the P2P voltage was observed.

Abstract:

P-wave morphology correlates with the risk for atrial fibrillation (AF). Left atrial (LA) enlargement could ex- plain both the higher risk for AF and higher P-wave ter- minal force (PTF) in ECG lead V1. However, PTF-V1 has been shown to correlate poorly with LA size. We hypoth- esize that LA hypertrophy, i.e. a thickening of the myocar- dial wall, also contributes to increased PTF-V1 and is part of the reason for the rather low specificity of increased PTF-V1 regarding LA enlargement. To show this, atrial excitation propagation was simulated in a cohort of four anatomically individualized models in- cluding rule-based myocyte orientation and spatial elec- trophysiological heterogeneity using the monodomain ap- proach. The LA wall was thickened symmetrically in steps of 0.66 mm by up to 3.96 mm. Interatrial conduction was possible via discrete connections at the coronary sinus, Bachmann’s bundle and posteriorly. Body surface ECGs were computed using realistic, heterogeneous torso mod- els. During the early P-wave stemming from sources in the RA, no changes were observed. Once the LA got activated, the voltage in V1 tended to lower values for higher degrees of hypertrophy. Thus, the amplitude of the late positive P- wave decreased while the amplitude of the subsequent neg- ative terminal phase increased. PTF-V1 and LA wall thick- ening showed a correlation of 0.95. The P-wave duration was almost unaffected by LA wall thickening (∆ ≤2 ms). Our results show that PTF-V1 is a sensitive marker for LA wall thickening and elucidate why it is superior to P-wave area. The interplay of LA hypertrophy and dilation might cause the poor empirical correlation of LA size and PTF- V1.

Abstract:

Atrial arrhythmias such as atrial flutter and atrial fibrillation are a burden for patients and a major challenge for modern healthcare systems. Identification of patients at risk to develop atrial arrhythmias at an early stage carries the potential to reduce the incidence by implementing appropriate strategies to mitigate the risks. Diagnostic methods based on the ECG are ideal risk markers due to their noninvasiveness and omnipresence. The left atrium (LA) plays a major role in the intiation and perpetuation of atrial reentry arrhythmias. However, the LA is not well represented in the P-wave derived through standard ECG leads. Here, we optimize ECG lead positions to maximize LA information content. Towards this end, we used a cohort of eight personalized computational models providing the unique opportunity to separate LA and right atrial (RA) contributions to the P-wave, which is not feasible in vivo. The location of maximum P-wave signal energy was located on the center of the chest for all subjects with marked overlap between regions of maximum LA and RA P-wave amplitude. The regions of highest ratio between LA and RA signal energy differed between patients. However, a region with LA signal energy being higher than that of the RA and providing a sufficiently large absolute P-wave amplitude was identified at the center of the back consistently across five models of the cohort. Optimized linear combinations of standard 12-lead signals yielded comparably good results. Our newly proposed electrode positions on the back as well as selected linear combinations of standard 12-lead signals improve the LA information content considerably. By using these, more relevant diagnostic information regarding the anatomical and electrophysiological properties of the LA can be derived in future.

Abstract:

P-wave morphology correlates with the risk for AF. Left atrial (LA) enlargement could explain both the higher risk for AF and higher P-wave terminal force (PTF) in lead V1. However, PTF-V1 has been shown to correlate poorly with LA size. We hypothesize that PTF-V1 is also affected by the earliest activated site (EAS) in the right atrium and its proximity to inter-atrial connections (IAC), which both show tremendous variability. Atrial excitation was triggered from seven different EAS on the epicardial surface around the sinus node region in eight anatomically personalized computational models including rule-based myocyte orientation and spatial electrophysiological heterogeneity. EAS1 was located midway between the tip of the right atrial appendage (RAA) and its junction with the superior vena cava (SVC), EAS2 at the superior part of the anterior wall, and EAS3 at the junction of the RAA and the SVC. EAS4 to EAS7 were uniformly distributed along the crista terminalis between EAS3 and orifice of the inferior vena cava (EAS7). IACs connected the atria at Bachmann’s bundle, coronary sinus and posteriorly. The posterior IACs were non-conductive in a second set of simulations. Body surface ECGs were computed using realistic, heterogeneous torso models. Mid-septal EAS yielded the highest PTF-V1 measured as the product of the duration and the maximal amplitude of the negative phase of the P-wave in V1. More anterior/superior and more inferior EAS yielded lower absolute values deviating by a factor of up to 2.0 for adjacent EAS. Earliest right-to-left activation was conducted via BB for EAS1-3 and shifted towards posterior IACs for EAS 4-7. Non-conducting posterior IACs increased PTF-V1 by up to 150%. The electrical contributors EAS and intactness of posterior IACs affect PTF-V1 significantly by changing LA breakthrough sites. This should be considered when assessing LA anatomy based on the ECG.

Abstract:

Aim: P-wave morphology correlates with the risk for AF. Left atrial enlargement could explain both the higher risk for AF and higher P-wave terminal force in lead V1 (PTF-V1). However, PTF-V1 has been shown to correlate poorly with left atrial size. We hypothesize that PTF-V1 is also affected by the earliest activated site (EAS) in the right atrium and its proximity to inter-atrial connections (IACs), which both show tremendous variability. Methods: Atrial excitation was triggered from seven different EASs (Fig 1A,B) in eight anatomically personalized computational models including rule-based fiber orientation and spatial electrophysiological heterogeneity. IACs connected the atria at Bachmann’s bundle, coronary sinus, and posteriorly. The posterior IACs were non-conductive in a second set of simulations. Body surface ECGs were computed using realistic, heterogeneous torso models of the same subjects. Results: Mid-septal EASs yielded the highest PTF-V1 measured as the product of the duration and the maximal amplitude of the negative phase of the P-wave in V1. More anterior/superior and more inferior EASs yielded lower absolute values deviating by a factor of up to 2.0 for adjacent EAS (Fig 1C). Earliest right-to-left activation was conducted via BB for EAS1-EAS3 and shifted towards posterior IACs for EAS4-EAS7. Non- conducting posterior IACs increased PTF-V1 by up to 150% (Fig 1D). Conclusions: Location of EAS in the right atrium and its proximity to functioning IACs affect PTF-V1 independently of the left atrial size and further support the caution that needs to be exercised when interpreting electrocardiographically signs of left atrial abnormality, which include PTF-V1.

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:

Background: For chronic kidney disease patients undergoing maintenance hemodialysis (HD), the risk to die from sudden cardiac death (SCD) is 14x higher compared to patients with a history of cardiovascular disease and normal kidney function. Traditional SCD risk factors cannot explain this high rate. Two recent human studies using implantable loop recorders surprisingly point towards bradycardia and asystole as the prevailing arrhythmias causing SCD in HD patients. This suggests a decisive role of the sinus node. Objective: To identify the effect of altered electrolyte levels (as systematically occurring in HD patients) on pacemaking in a computational model of human sinus node cells. Methods: We enhanced the Fabbri et al. model of human sinus node cells to account for the dynamic intracellular balance of all considered electrolytes. The model was exposed to clinically relevant extracellular electrolyte concentrations of potassium, sodium, and calcium to study their effect on spontaneous beating rate and underlying pacemaking mechanisms. The level of sympathetic stimulation was kept constant. Results: The beating rate showed a monotonic relationship with altered electrolyte concentrations starting from a baseline value of 72.5bpm. It increased with sodium (70.8-73.8bpm for [Na+]o from 120-150mM), with potassium (70.7-81.9bpm for [K+]o from 3-9mM), and most pronouncedly with calcium (33.5- 133.8bpm for [Ca2+]o from 0.8-3mM). The severe bradycardia under hypocalcemic conditions was due to hyperpolarized maximum diastolic potential and slower diastolic depolarization driven by attenuation of ICaT and INCX, the latter due to depletion of intracellular calcium. Conclusion: Our human computational study suggests that hypocalcemia causes a pronounced decrease of cellular sinus node pacing rate, which may be a relevant mechanism in HD patients. While increased sympathetic tone will likely compensate the lower basal beating rate, patients developing severe hypocalcaemia are at high risk to experience severe bradycardia and die from SCD during a sudden loss of sympathetic tone.

Abstract:

Pharmacological therapy of atrial fibrillation (AF) is still a major clinical challenge. Particularly AF of early onset has a significant familiar component and was asso- ciated with various gene mutations. In this study, we de- signed and optimized antiarrhythmic agents for atrial sub- strates affected by human ether-a`-go-go-related gene mu- tations L532P and N588K. A virtual multichannel blocker was designed aiming at a restoration of the wild-type (WT) action potential (AP) on the single cell and tissue level. Furthermore, the amiodarone and dronedarone concen- trations yielding the smallest difference between WT and mutated APs were identified. The WT AP at a basic cy- cle length (BCL) of 1000 ms could be restored by signifi- cant block of IK r and IK ur (\039%) and less pronounced block of IKs, ICa,L, Ib,Na, and Ib,Ca (17%) for both mutations. Effective dronedarone concentrations of 88 nM for L532P and 40 nM for N588K yielded matches almost as good while amiodarone could not sufficiently restore the WT AP. APD90 restitution was effectively restored by the tuned N588K agent whereas differences of up to 34 ms were observed for low BCLs using the tuned L532P agent. Our results provide insight into the pharmacodynamic re- sponse of mutated myocytes and may aid in the optimiza- tion of patient group-specific therapeutic approaches.

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:

The early detection of myocardial ischemia is an essential lever for its successful treatment. We investigated an ECG monitoring system with 3 electrodes. Optimal electrode positions are determined using a cellular automaton. The spatially heterogeneous effects of myocardial ischemia were modeled by altering 4 electrophysiological parameters: action potential amplitude and duration, conduction velocity as well as resting membrane voltage. Both, transmural heterogeneity and the influence of the border zone were considered in the simulations on three patient models. The detection of myocardial ischemia is based on ST segment deviation from the physiological case. The signals used to find the best electrode positions comprise ischemic regions with different transmural extents in all 17 AHA segments. We show which ischemic ECGs can be detected given a realistic signal-to-noise ratio, false positive rate and maximum response time of the system.

Abstract:

Atrial fibrillation (AF) is a common arrhythmia with progressive nature. This progression is partly caused by AF itself by modifying amongst others the electrophysiological properties of the myocytes. These changes are referred to as electrical remodeling and were integrated in a computational model of human atrial myocytes in this work.In particular, the maximum conductivities of Ito, IK1, IKs, IKur, ICa,L, INa,Ca, and the Ca2+ leak current from the sarcoplasmic reticulum, as well as the cell capacitance were altered. In an additional setup, the influence of potential gap junction remodeling was investigated.Wavelength was reduced from 225 mm to 110 mm, respectively 92 mm when considering gap junction remodeling at a basic cycle length of 400 ms. Action potential morphology was changed from spike-and-dome to a more triangular repolarization phase. However, our results show that including IKur remodeling prevents the plateau phase from disappearing completely.

Abstract:

While human ether-à-go-go-related gene (hERG) mutations N588K and K897T are associated with atrial fib- rillation (AF), the underlying arrhythmogenic mechanisms are understood only incompletely. In this work, an ap- proach integrating IKr measurement data from transgenic Xenopus oocytes into established computational models of cardiac electrophysiology is presented. Parameters are es- timated using a minimization formulation, which is handled by a hybrid particle swarm optimization (PSO) and trust- region-reflective (TRR) algorithm. Cell models adapted to the mutation measurements show a significantly shorter ac- tion potential (AP) with less pronounced spike-and-dome morphology. Results of single cell simulations compare with myocytes in chronic 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:

Atrial fibrillation and atrial flutter are the most common atrial arrhythmias placing a heavy burden on patients and posing a challenge on healthcare systems. If patients at risk to develop atrial arrhythmias can be identified at an early stage, the arrhythmia incidence can be lowered by implementing appropriate strategies to mitigate the risks. Diagnostic methods based on the ECG are ideal risk markers due to their noninvasiveness and omnipresence. The left atrium (LA) plays a major role in the initiation and perpetuation of atrial reentry arrhythmias. However, the LA is not well represented in the P-wave derived through standard ECG leads. Here, we optimize ECG leads to maximize LA information content. Towards this end, we used a cohort of eight personalized computational models providing the unique opportunity to separate LA and right atrial (RA) contributions to the P-wave, which is not feasible in vivo. The location of maximum P-wave signal energy was located on the center of the chest for all subjects with marked overlap between regions of maximum LA and RA P-wave amplitude. The regions of highest ratio between LA and RA signal energy differed between patients. However, a region with LA signal energy being higher than that of the RA and providing a sufficiently large absolute P-wave signal energy was identified at the lower left quadrant of the back consistently across most subjects of the cohort. Optimized linear combinations of standard 12-lead signals (considering the eight independent leads) yielded comparably good results amplifying LA information by more than one order of magnitude. Our newly proposed electrode positions on the back as well as selected combinations of standard ECG signals improve the LA information content considerably. By using these, more relevant diagnostic information regarding anatomical and electrophysiological properties of the LA can be derived in future.

Abstract:

Atrial arrhythmias like atrial fibrillation and atrial flutter are a major health challenge in developed countries. Radiofrequency ablation performed via intracardiac catheters is a curative therapy for these reentrant arrhythmias. However, the optimal location of ablation lesions is not straightforward to determine, particularly for complex activation patterns. Thus, a clinical need for tools to intuitively visualize complex activation patterns and to provide a platform to evaluate different ablation strategies in dry runs is apparent. Here, we present a virtual reality system that allows to interactively simulate atrial excitation propagation and place ablation lesions. Our software builds on the IMHOTEP framework for the Unity3D engine and implements a multithreaded model-view-controller design pattern. Excitation propagation is computed using a fast marching approach considering refractoriness. Interactive rewind and playback is supported through a combination of the flyweight pattern for simulation data with complete snapshots for key frames. The system was evaluated in a user study using the HTC ViveTM headset including two controllers. For high fidelity virtual reality interaction, a minimum frame rate of 60 per second is required. In a biatrial anatomical model comprising 36,059 nodes (Figure 1), even complex activation patterns with multiple wavefronts could be simulated and rendered down to 2x slow motion (1 sec activation sequence displayed during 2 sec wall time) on a desktop machine. Results of the user study suggest added value regarding the comprehension of arrhythmias and ablation options and very good intuitiveness of the user interface requiring almost no teach-in. The virtual reality tool is ready to be used for educational purposes and prepared to import personalized models supporting diagnosis and therapy planning for atrial arrhythmias in the future.

Abstract:

Atrial fibrillation (AF) ablation guided by basket catheter mapping has shown to be beneficial. Yet, the initial excitement is mitigated by a growing skepticism due to the difficulty in verifying the protocol in multicenter studies. Overall, the underlying assumptions of rotor ablation require further verification. The aim of this study was therefore to test such hypotheses by using computational modeling. The 3D left atrial geometry of an AF patient was segmented from a pre-operative MR scan. Atrial activation was simulated on the 3D anatomy using the monodomain approach and a variant of the Courtemanche action potential model. Ablated tissue was assigned zero conductivity. Reentry was successfully initialized by applying a single suitably delayed extra stimulus. Unipolar electrograms were computed at the simulated electrode positions. The final dataset was generated by varying location of reentry and catheter position within the LA. The effect of inter-electrode distance and distance to the atrial wall was studied in relation to the ability to recover rotor trajectory, as computed by a novel algorithm described here. The effect of rotor ablation was also assessed.

Abstract:

P-wave assessment is frequently used in clinical practice to recognize atrial abnormalities. However, the use of P-wave criteria to diagnose specific atrial abnormalities such as left atrial enlargement has shown to be of limited use since these abnormalities can be difficult to distinguish using P-wave criteria to date. Hence, a mechanistic understanding how specific atrial abnormalities affect the P-wave is desirable. In this study, we investigated the effect of left atrial hypertrophy on P-wave morphology using an in silico approach. In a cohort of four realistic patient models, we homogeneously increased left atrial wall thickness in up to seven degrees of left atrial hypertrophy. Excitation conduction was simulated using a monodomain finite element approach. Then, the resulting transmembrane voltage distribution was used to calculate the corresponding extracellular potential distribution on the torso by solving the forward problem of electrocardiography. In our simulation setup, left atrial wall thickening strongly correlated with an increased absolute value of the P-wave terminal force (PTF) in Wilson lead V1 due to an increased negative amplitude while P-wave duration was unaffected. Remarkably, an increased PTF-V1 has often been associated with left atrial enlargement which is defined as a rather increased left atrial volume than a solely thickened left atrium. Hence, the observed contribution of left atrial wall thickness changes to PTF-V1 might explain the poor empirical correlation of left atrial enlargement with PTF-V1.

Abstract:

Generating meshes of complex structures in the human body like the heart organ is a prerequisite for computational simulations of of organ function. The quality of the conclusions derived from these simulations greatly depends on the quality and accuracy of the mesh they are based on. Volumetric computation domain can be represented by an equally-spaced voxel grid, or – in case of more sophisticated partial differential equation discretization methods (finite elements, finite volumes) – first, second or even higher order tetrahedral meshes. Here, we present a workflow that is capable of creating high quality meshes for such simulations. The workflow contains segmentation, surface mesh generation, volume mesh generation, and patient-specific parameter fitting to produce the desired results. While segmentation itself is a more or less unique mapping from a grayscale DICOM data set to a labeled, three-dimensional voxel mesh, different approaches exist for their transformation to a surface mesh. Our process involves a two-level approach for obtaining triangular or mixed rectangular surface meshes of desired quality and resolution. Both are crucial for the next step: obtaining a volumetric tetrahedral grid with the desired degrees of freedom. In the last step, a derivative-free parameter estimation approach is used to calibrate the dynamic behavior and tailor the model patient-specifically. All software used in the workflow is published under open source licenses and freely available. Its capability is demonstrated by means of an elastomechanical simulation of a human heart and yields measurable validation quantities in physiological ranges. We want to stress that the presented approach is generic and can easily be used for the model generation of other organs like liver, lungs or the aortic arch as well. The resulting meshes can be used for various types of simulations (electrical excitation propagation, blood flow) and use cases (clinical diagnostics, therapy planning etc.).

Abstract:

Numerical modelling enables a quantitative evaluation of physiological and patho-physiological relationships within the human heart and the circulatory system. Surgical planning and optimisation of medical equipment using a virtual heart become possible by merging of empirical studies with physical and mathematical knowl- edge. These goals motivate a multi-physical coupling between electro-physiology, elasto-mechanics, blood flow and the circulatory system. In a first step a one-way coupling of all four relevant physical domains is considered. Simulation of electro- physiological excitation spread in conjunction with excitation contraction coupling yields the spatio-temporal distribution of cardiac active tension. This, as well as a closed loop model of the circulatory system, drive the continuum mechanics simulation of cardiac deformation and pressure, which in turn serve as a boundary condition for blood flow simulation. Physiological blood flow dynamics are dominated by the formation of a ring vortex that washes out the ven- tricles and thereby reduces the risk of thrombogenesis and flow stasis. This process is strongly affected by the heart valves. However, including the three dimensional leaflets and their interaction with the blood flow is computationally expensive. Further, the effort for construction is not negligible. Therefore, a simpler model is implemented as a first step. It comprises of three layers of porous cells that move with the valve plane and time dependently block or open the plane respectively. First results illustrate a high potential of the model to reliably reproduce the physiological vortex formation in the ventricles.

Abstract:

Today, patients suffering from atrial arrhythmias like atrial flutter (AFlut) or atrial fibrillation (AFib) are examined in the EP-lab (electrophysiology lab) in order to understand and treat the disease. Multichannel catheters are advanced into the atria in order to measureelectric signals at manyintracardiacpositions simultaneously. Complementary to clinical learning,comprehension of the disease and therapeutic strategies can be improved with computer modeling of the heart. This way, hypotheses about initiation and perpetuation of the arrhythmia can be tested and ablation strategies can be assessed in-silico. Modeling and biosignal analysis can benefit from mutual fertilization. On the one hand, modeling can be improved and personalization can be achieved via high density mapping of the atria. On the other hand, new algorithms for the interpretation of multichannel electrograms can be developed and evaluated with synthetic signals from computer models of the atria. This article illustrates the synergetic potential by examples and highlights challenges to be addressed in the future.

Abstract:

The sinoatrial node (SAN) is the natural pacemaker of our heart. How this small tissue is able to drive a remarkably larger number of intrinsically quiescent atrial cells is still debated; a computational investigation of the underlying mechanisms can help to better understand the SAN’s ability to pace-and-drive the surrounding atrium. Aim of this work is to elucidate how the human SAN action potential can successfully be captured by and propagate into the surrounding atrial tissue. The Fabbri et al. and the Courtemanche et al. models were used to describe the human SAN and atrial cells, respectively. The behaviour of two coupled regions was investigated varying the interregional conductivity (σ) and relative size. Simulations showed that it requires at least an isopotential SAN region 2.85 times wider than the atrial one. A 1D strand of homogeneously coupled SAN and atrial elements was used to identify an interval for σ showing pace-and-drive behaviour (100 SAN vs 100 atrial elements) and to investigate the source-sink interplay (10, 50 or 100 SAN elements vs 100 atrial elements). The 1D strand showed pace-and-drive behaviour for 𝜎 = 0.08 − 36 S/m; a stronger source, with a higher number of SAN elements, led to a wider 𝜎 range that allowed pace-and-drive behaviour, whereas a stronger sink did not affect the behaviour of the tissue. This preliminary work shows the ability of a small human SAN region to pace-and-drive the surrounding atrial tissue. Further investigations are needed to explore different conductivity configurations, including spatial gradients.

Abstract:

The Purkinje system is part of the fast-conducting ventricular excitation system. The anatomy of the Purkinje system varies from person to person and imposes a unique excitation pattern on the ventricular myocardium, which defines the morphology of the QRS complex of the ECG to a large degree. While it cannot be imaged in-vivo, it plays an important role for personalizing computer simulations of cardiac electrophysiology. Here, we present a new method to automatically model and customize the Purkinje system based on the measured electrocardiogram (ECG) of a patient. A graphbased algorithm was developed to generate Purkinje systems based on the parameters fibre density, minimal distance from the atrium, conduction velocity, and position and timing of excitation sources mimicking the bundle branches. Based on the resulting stimulation profile, the activation times of the ventricles were calculated using the fast marching approach. Predescribed action potentials and a finite element lead field matrix were employed to obtain surface ECG signals. The root mean square error (RMSE) between the simulated and measured QRS complexes of the ECGs was used as cost function to perform optimization of the Purkinje parameters. One complete evaluation from Purkinje tree generation to the simulated ECG could be computed in about 10 seconds on a standard desktop computer. The measured ECG of the patient used to build the anatomical model was matched via parallel simplex optimization with a remaining RMSE of 4.05 mV in about 16 hours. The approach presented here allows to tailor the structure of the Purkinje system through the measured ECG in a patient-specific way. The computationally efficient implementation facilitates global optimization.

Abstract:

Background: Perimitral flutter commonly occurs following ablation of atrial fibrillation (AF) and can be cured by an anterior mitral line (AML). However, confirmation of bidirectional block can be challenging. Objective: We hypothesized that P-wave morphology and timing under left atrial appendage (LAA) pacing changes upon AML- block. Methods: We analyzed 129 consecutive patients (66±8 y, 64%male) who developed perimitral flutter after AF ablation. We designed ECG-criteria in a retrospective cohort (n=76) and analyzed them in a validation cohort (n=53). Results: Bidirectional AML-block was achieved in 110 patients (85%). For ablation performed during LAA-pacing without flutter (n=52), we found an immediate V1-jump (increase in LAA- stimulus to P-wave peak in lead V1) as a real-time marker of AML-block (V1-jump ≥30ms: sensitivity 95%, specificity 100%, PPV 100%, NPV 88%). Since V1-jump is not applicable when block coincides with termination of flutter, absolute V1-delay was used as a criterion applicable in all cases (n=129) with a delay of 203ms indicating block (sensitivity 92%, specificity 84%, PPV 90%, NPV 87%). Furthermore, an initial negative P-wave portion in the inferior leads was observed, which was attenuated in case of additional cavotricuspid isthmus (CTI) ablation. Computational P-wave simulations provide mechanistic confirmation of these findings for diverse ablation scenarios (pulmonary vein isolation±AML±roof-line±CTI ablation). Conclusion: V1-jump and V1-delay are novel real-time ECG- criteria allowing fast and straightforward assessment of AML- block during ablation for perimitral flutter.

Abstract:

Chronic kidney disease (CKD) affects more than 30 million patients in the European Union. CKD causes alterations in the extracellular plasma electrolyte concentrations, which affect cardiac electrophysiology. A total of 25% of all deaths of CKD patients are due to sudden cardiac death (SCD). Until recently, ventricular fibrillation was assumed to be the main reason. In a 2015 study, Wong et al. observed bradycardia and asystole as the predominant mechanisms of SCD in patients with CKD. This shows that the influence of electrolyte changes on the underlying mechanisms of pacemaking in the sinoatrial node (SAN) needs to be better understood. In this work, we have updated the computational model of the human SAN given by Fabbri et al. and investigated the CKD-induced change of [Ca2+]o (0.6-3mM), [K+]o (3-9mM) and [Na+]o (120-150mM) on pacemaking. [Ca2+]o had the most dominant effects on SAN function. Low [Ca2+]o caused severe bradycardia in the model (down to 17 bpm) for 0.6 mM. A critical concentration range of calcium in the subspace [Ca2+]sub was identified as the possible underlying mechanism for pacemaking. For increasing [Ca2+]o, the heart rate (HR) increased, resulting in 142 bpm for the highest calcium concentration. The effect of [K+]o variation was similar to the one for [Ca2+]o, but caused less pronounced change. The resultant changes due to variation of [Na+]o were relatively small. In this work, several potential mechanisms for SCD in CKD patients could be identified. The low HR for low [Ca2+]o is seen as a possible link to the observed bradycardia in CKD patients. The findings in this work could lead to a better surveillance of [Ca2+]o in hemodialysis patients, and therefore to a decrease in the SCD rate.

Abstract:

Atrial fibrillation (AF) is still a major health problem in the western society. Especially for familial AF, the pharmacological therapy is still not sufficiently successful. In this work, channel blocker properties were in-silico adapted to optimize drug therapy for patients suffering from familial AF. The Courtemanche-Ramirez-Nattel (CRN) cell model was the basis for the simulations. Adaptations in the model due to familial AF were implemented using an existing description of the L532P mutation. A fitting algorithm was designed which adapted all conductivities of the ion channels described in the CRN model to restore the healthy action potential (AP). To find the minimal deviation of the healthy AP and the AP of the L532P mutation, the trust-region-reflective algorithm was used. The best matched APs were achieved by a significant blockade of the IKr and the IKur current. 1D tissue strand simulations were performed using different basic cycle lengths (BCL) to evaluate the results of the optimization. It was shown that for the found adaptation of the conductivities, the AP duration, and the progressions of the conduction velocity, effective refractory period, and wavelength (WL) could be restored. The WL was increased by 53.37% compared to the mutation and had a value of 233.48 mm (BCL = 1 s).

Abstract:

Cardiac excitation during atrial fibrillation (AFib) is changing dynamically, compromising the ability to identify underlying mechanisms by intracardiac catheter mapping. Statistical analysis of dominant excitation patterns may help to identify and subsequently eliminate the drivers of this tachycardia. As the morphology of local bipolar intracardiac electrograms (EGMs) depends on the orientation of the propagating excitation wave, its evaluation for a fixed multichannel catheter position can provide information about the stability of the depolarization pattern. Up to date, analysis of morphology is most often done by computing a similarity index or the recurrence rate of individual EGMs, reflecting how often similar excitations appear. We sougth to extend this approach to a classification based analysis technique. In each multichannel EGM, local activation waves (LAWs) were automatically detected by assessing instantaneous signal energy. A greedy algorithm was implemented to cluster LAWs based on their similiarity. New clusteres were formed when similarity fell below a predefined threshold. The concept was tested using simulated EGM data (quadratic patch of cardiac tissue, bidomain simulation, both planar and focal excitations, various catheter types). Results demonstrated that the algorithm correctly identified and classified the simulated excitation patterns. Subsequent quantitative analysis allowed to both discard singular classes of excitation and identify dominant excitations. The presented method forms the basis for statistical assessment of prevailing depolarization patterns, and for computation of additional features like conduction velocity, presence of focal sources, or dissociation when applied on multichannel data.

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:

Chronic kidney disease appears worldwide. In the United States, the number of patients suffering from kid- ney failure doubled from 1998 to 2010. A common treat- ment for these patients is haemodialysis. However, the frequency of deaths caused by cardiovascular diseases is up to 10% to 30% higher in patients undergoing dialysis than in the general population. To analyse the underly- ing effects and for a possible risk prediction, a continuous monitoring of the ionic concentrations that are influenced by dialysis is desired. In this work, a method for the re- construction of the ionic concentrations of calcium and potassium from the ECG is proposed. In a first step, 91 monodomain simulations with the ten Tusscher ventricular cell model were performed for different extracellular ionic concentrations. From there, a standard 12-lead ECG was extracted. Calcium and potassium changes yielded ECGs clearly differing in amplitude and morphology. In a second step, the simulated ECG signals were used for reconstruc- ting the ionic concentrations directly from the ECG. Fea- tures were extracted from the signals designed to describe changes caused by varied ionic concentrations. The in- verse problem, i.e. coming back from the ECG features to the ionic concentrations was solved by regression with an artificial neural network. Results for potassium estimation yield an error of 0.00±0.28 mmol/l (mean±standard de- viation) calculated with 7-fold cross validation. The esti- mation error for calcium was 0.00±0.08 mmol/l. Although these results underline the suitability of the method, the used ECGs differed from the observed in a clinical envi- ronment. However, simulations allow an evaluation un- der controlled conditions of a particular effect that was intended to be investigated. As the application to clinical data is yet missing, this study can be seen as a proof of concept showing that an artificial neural network is capa- ble of exactly estimating potassium and calcium concen- trations from ECG features. 1. Introduction Haemodialysis therapy is a common treatment method for patients suffering from chronic kidney disease (CKD) in the terminal stage. The amount of people in the United States suffering from kidney failure increased from 320,000 in 1998 to 650,000 in 2010. The frequency of deaths caused by cardiovascular events within the dialysis patient group is up to 10% to 30% higher than in gene- ral population [1]. Patients suffering from end-stage CKD experience high variations of blood electrolyte concentra- tions. These can directly influence the functioning of the heart. Thus, research on cardiovascular links could im- prove therapy and risk stratification. One tool which is capable of capturing the electrophysiological properties of the heart in a non-invasive way is the electrocardiogram (ECG). It is known, that electrolyte concentrations of po- tassium (K+) and calcium (Ca2+) affect the ECG [2]. Un- til now, a determination of the concentrations is connec- ted to a blood test. Hence, continuous monitoring of the ionic concentration is impracticable. However, the ECG as a continuous, non-invasive monitoring tool could shed a light on the relation between heart diseases and changes in the ionic concentration particularly after leaving the strictly supervised clinical area where dialysis takes place, i.e allowing a monitoring at home. Articles have been pub- lished showing that the reconstruction of extracellular K+ concentration can be done using just one feature from the ECG with a quadratic regression [3]. In this study, we tried to estimate both K+ and Ca2+ concentrations from the ECG. Therefore, we examined simulated ECGs at dif- ferent concentration levels and designed features descri- bing the observed changes in the ECG. A subset of these was used in connection with a machine learning method to reconstruct the concentrations. 2. Methods 2.1. Simulations A total number of 91 computer simulations of the car- diac electrophysiology were performed at whole heart

Abstract:

One promising application of electrocardiographic (ECG) imaging is noninvasive reconstruction of atrial activities. However, despite numerous clinical studies, which are mostly concerned with complex irregular excitation patterns, there are relatively few in silico investigations on the imaging of ectopic activation. In the present work, we explore the localization accuracy of ECG imaging regarding atrial focal sites. For the forward calculations, we used four realistic geometrical models with complex anatomical structure and a rule-based fiber orientation embedded into the atrial model. Excitation propagation was simulated with the monodomain model. For each geometrical model, 20 activation sequences originating from the posterior wall of the left atrium were simulated. Based on the bidomain theory, the body surface potential maps resulting from these focal events were computed. For the inverse reconstructions, we employed a full-search procedure based on the fastest route algorithm assuming uniform excitation propagation. Localization errors were revealed to be dependent on the model-specific atrial geometry. We also performed similarity analysis for the first halves of the P wave duration, which improved the results in three models.

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 190msmovedinanareaof10mmx4mm. Inadistance 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:

Modelling the interaction of the heart and the vascular system allows to study the pumping efficiency of the heart in a controlled environment under various cardiac and vascular conditions such as arrhythmias, dyssynchronies, regions of stiffened myocardium, valvular stenoses or decreased vascular compliances. To pose realistic hemodynamic boundary conditions to a four-chambered elastomechanical heart model, we developed a lumped element model of the closed loop human vascular system. Systemic and pulmonary circulations were each represented by a three-element Windkessel model emptying into a venous compliance. Both circulations were coupled by connecting the venous compliances to the corresponding atrium via venous resistances. Cardiac valves were represented by ideal diodes and resistances. Strong coupling between the heart and the vascular system model was accomplished by estimating the cardiac pressures that lead to continuous flows across the model interfaces. Active regulatory mechanisms were not considered. Pressures, flows and volumes throughout the circulatory system were simulated until a steady state was reached and the effects of model parameters on these hemodynamic parameters were evaluated in a sensitivity analysis. Increasing the systemic peripheral resistance by 50% caused an 8% decrease in stroke volume (SV) and a 33% increase in mean arterial pressure. Increased venous resistance descreased the E/A wave ratio of the atrioventricular flow and led to a reduced SV by impeding passive cardiac filling. Increasing the arterial compliance decreased mean cardiac pressures, while only slightly reducing the SV. Larger arterial resistances mainly caused higher peak systolic pressures. Furthermore, we show that embedding the heart model into surrounding elastic tissue by forcing permanent contact at the pericardial surface leads to more realistic time courses of atrial volumes and atrial pressure-volume curves composed of an A and a V loop as found in measurements. In conclusion, this work enables simulations of diseases that involve significant cardiovascular interaction.

Abstract:

ECG imaging is a non-invasive technique of characterizing the electrical activity and the corresponding excitation conduction of the heart using body surface ECG. The method may provide great opportunities in the planning of cardiac interventions and in the diagnosis of cardiac diseases. This work introduces an algorithm for the imaging of transmembrane voltages that is based on a Kalman filter with an augmented measurement model. In the latter, a regularization term is integrated as additional measurement. The filter is trained using a-priori-knowledge from a simulation model. Two effects are investigated: the influence of the training data on the reconstruction quality and the representation of a-priori knowledge in the trained covariance matrices. The proposed algorithm shows a promising quality of reconstruction and may be used in the future to introduce generic physiological knowledge in solutions of cardiac source imaging.

Abstract:

Atrial fibrillation is a common cardiac arrhythmia. The disturbance of the normal repolarization process due to heterogeneous myocyte-fibroblast coupling might play a role for this disease. We investigate this interaction in the heterogeneous atrium using a computational approach. Human atrial myocyte computational models represent- ing 10 different regions of the atrium were each coupled to a human atrial fibroblast model and the impact of the myocyte-fibroblast coupling on action potential measures was investigated. Myocytes from the pulmonary vein are affected most by the coupling to fibroblasts. Action potential amplitude is reduced from 105 mV to 94 mV and the upstroke velocity changes from 192 V/s to 152 V/s, potentially reducing the conduction velocity. In general, the action potential dura- tion of myocytes with short action potentials is prolonged and that of those with long is shortened. The large effect on pulmonary vein action potentials is mainly due to reduced IK1 in these cells compared to other regions of the atrium. The strong effects of fibroblast cou- pling to pulmonary vein myocytes are likely to be an addi- tional reason for the crucial role of the pulmonary veins in atrial fibrillation.

Abstract:

The sinoatrial node (SAN) is the normal pacemaker of the mammalian heart. Over several decades, a large amount of data on the ionic mechanisms underlying the spontaneous electrical activity of SAN pacemaker cells has been obtained, mostly in experiments on single cells isolated from rabbit SAN. This wealth of data has allowed the development of mathematical models of the electrical activity of rabbit SAN pacemaker cells. However, the translation of animal data/models to humans is not straightforward. Even less so for SAN pacemaker cells than working myocar- dial cells given the big di↵erence in their main output (i.e. pacing rate) between human and laboratory animals. The development of a comprehensive model of the electrical activity of a human SAN pacemaker cell strictly based on and constrained by the available electrophysiological data will be presented. We started from the Severi-DiFrancesco rabbit SAN model, which integrates the two principal mecha- nisms that determine the beating rate: the ”membrane clock” and ”calcium clock”. Several current formulations were updated based on available measurements. A set of parameters, for which no specific data were available, were automatically opti- mized to reproduce the measured AP and calcium transient data. The model was then validated by assessing the e↵ects of several mutations a↵ecting heart rate and rate modulation. Moreover, two recent applications of the model will be presented: i) We used our SAN AP computational model to assess the e↵ects of the inclu- sion of the small conductance K+ current (ISK) on the biomarkers that describe the AP waveform and calcium transient; ii) We analysed the e↵ect of altered elec- trolyte levels (as systematically occurring in hemodialysis patients) on pacemaking to investigate the possible mechanisms of the bradycardic sudden cardiac deaths pointed out by two recent human studies using implantable loop recorders.

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:

Acquiring adequate mapping data in patients with atrial fibrillation is still one of the main obstacles in the treatment of this atrial arrhythmia. Due to the lack of catheters with both a panoramic field of view and sufficient electrode density for simultaneous mapping, electrophysiologists are forced to fall back on sequential mapping techniques. But, because activation patterns change rapidly during atrial fibrillation, they cannot be mapped sequentially. We propose that mapping tissue properties which are time independent, in contrast, allows a sequential approach. Here, we use the shortest measured electrogram cycle length to estimate the effective refractory period of the underlying tissue in a simulation study. Atrial fibrillation was simulated in a spherical model of the left atrium comprised of regions with varied refractory period. We found that the minimal measured electrogram cycle length correlates with the effective refractory period of the underlying tissue if the regions with distinct refractory properties are large enough and if the absolute difference in effective refractory periods is sufficient. This approach is capable of identifying regions of lowered effective refractory period without the need for cardioversion. Those regions are likely to harbor drivers of atrial fibrillation, which emphasizes the necessity of their localization.

Abstract:

Atrial fibrillation (AF) is the most common type of arrhythmia encountered in clinical practice but its maintaining mechanisms remain elusive. Over the last years, various theories have been proposed to target AF mechanisms. Recently, there has been an increasing interest in understanding how spiral waves and rotors sustain AF and how they might be therapeutic targets for catheter-based ablation. Phase mapping has recently been used as a robust method to characterize the spatiotemporal variability of electrical activities. In this study, we propose an independent approach for basket catheter electrogram (EGM) processing to detect rotors in AF. An improved version of the sinusoidal recomposition method for the local activation timings (LATs) has been developed and 3D phase maps have been reconstructed. An algorithm able to detect stable and meandering rotors on the left atrium (LA) surface was then developed. This workflow has been validated on synthetic EGMs and in silico showing excellent results. On in vivo data, we found 4.0±3.4 and 4.6±5.0 localized and meandering rotors with a persistence in time: 303.2 ±58.2ms and 302.3±52.0ms respectively.

Abstract:

Atrial arrhythmia is the most common cardiac arrhythmia. Parameters such as conduction velocity (CV), CV restitution etc. are under analysis in order to understand the cardiac arrhythmias. A number of methods have been proposed for CV calculation in simulation as well as clinical environments. Regional CV gives the information about the magnitude and direction of the propagating depolarization wavefronts on the atrium with homogeneous and heterogeneous tissue. The CV in different regions can provide important quantitative electrophysiological information about the underlying tissue. In this work the regional CV has been calculated using simulated local activation times (LAT) on clinical atrial geometries. Regions with homogeneous and heterogeneous propagation were manually selected for LAT simulation and later the regional CV has been calculated. The calculated CV for both the homogeneous and heterogeneous cases for all the clinical cases have been visualized on the atrial geometries. The visualization of the CV on the atrium represents insight into the regional behavior of the atrial substrate. The benefit of the region-specific study in clinical context is that it could enable the localization of critical sites in the patient specific atrial anatomies. Thus, this could aid physicians in cardiac therapies.

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:

A computer-implemented method for calculating a multi-dimensional wavelet transform in an image processing system comprising a plurality of computation units includes receiving multi-dimensional image data. An overlap value corresponding to a number of non-zero filter coefficients associated with the multi-dimensional wavelet transform is identified. Then the multi-dimensional image data is divided into a plurality of multi-dimensional arrays, wherein the multi-dimensional arrays overlap in each dimension by a number of pixels equal to the overlap value. A multi-dimensional wavelet transform is calculated for each multi-dimensional array, in parallel, across the plurality of computation units

Abstract:

A computer-implemented method for reconstruction of a magnetic resonance image includes acquiring a first incomplete k-space data set comprising a plurality of first k-space lines spaced according to an acceleration factor and one or more calibration lines. A parallel imaging reconstruction technique is applied to the first incomplete k-space data to determine a plurality of second k-space lines not included in the first incomplete k-space data set, thereby yielding a second incomplete k-space data set. Then, the parallel imaging reconstruction technique is applied to the second incomplete k-space data to determine a plurality of third k-space lines not included in the second incomplete k-space data, thereby yielding a complete k-space data set.

Abstract:

Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This thesis presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF.