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Introduction: Electrical activity of the myocardium is recorded with the 12-lead ECG. ECG simulations can improve our understanding of the relation between abnormal ventricular activation in diseased myocardium and body surface potentials (BSP). However, in equivalent dipole layer (EDL)-based ECG simulations, the presence of diseased myocardium breaks the equivalence of the dipole layer. To simulate diseased myocardium, patches with altered electrophysiological characteristics were incorporated within the model. The relation between diseased myocardium and corresponding BSP was investigated in a simulation study. Methods: Activation sequences in normal and diseased myocardium were simulated and corresponding 64-lead BSP were computed in four models with distinct patch locations. QRS-complexes were compared using correlation coefficient (CC). The effect of different types of patch activation was assessed. Of one patient, simulated electrograms were compared to electrograms recorded during invasive electro-anatomical mapping. Results: Hundred-fifty-three abnormal activation sequences were simulated. Median QRS-CC of delayed versus dyssynchronous were significantly different (1.00 vs. 0.97, p < 0.001). Depending on the location of the patch, BSP leads were affected differently. Within diseased regions, fragmentation, low bipolar voltages and late potentials were observed in both recorded and simulated electrograms. Discussion: A novel method to simulate cardiomyopathy in EDL-based ECG simulations was established and evaluated. The new patch-based approach created a realistic relation between ECG waveforms and underlying activation sequences. Findings in the simulated cases were in agreement with clinical observations. With this method, our understanding of disease progression in cardiomyopathies may be further improved and used in advanced inverse ECG procedures., Competing Interests: Peter M van Dam is owner of ECG Excellence BV. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Boonstra, Oostendorp, Roudijk, Kloosterman, Asselbergs, Loh and Van Dam.)

Inverse electrocardiography (iECG) estimates epi- and endocardial electrical activity from body surface potentials maps (BSPM). In individuals at risk for cardiomyopathy, non-invasive estimation of normal ventricular activation may provide valuable information to aid risk stratification to prevent sudden cardiac death. However, multiple simultaneous activation wavefronts initiated by the His-Purkinje system, severely complicate iECG. To improve the estimation of normal ventricular activation, the iECG method should accurately mimic the effect of the His-Purkinje system, which is not taken into account in the previously published multi-focal iECG. Therefore, we introduce the novel multi-wave iECG method and report on its performance. Multi-wave iECG and multi-focal iECG were tested in four patients undergoing invasive electro-anatomical mapping during normal ventricular activation. In each subject, 67-electrode BSPM were recorded and used as input for both iECG methods. The iECG and invasive local activation timing (LAT) maps were compared. Median epicardial inter-map correlation coefficient (CC) between invasive LAT maps and estimated multi-wave iECG versus multi-focal iECG was 0.61 versus 0.31. Endocardial inter-map CC was 0.54 respectively 0.22. Modeling the His-Purkinje system resulted in a physiologically realistic and robust non-invasive estimation of normal ventricular activation, which might enable the early detection of cardiac disease during normal sinus rhythm., (© 2022. The Author(s).)

Transcranial direct current stimulation (tDCS) is a promising tool to improve and speed up motor rehabilitation after stroke, but inconsistent clinical effects refrain tDCS from clinical implementation. Therefore, this study aimed to assess the need for individualized tDCS configurations in stroke, considering interindividual variability in brain anatomy and motor function representation. We simulated tDCS in individualized MRI-based finite element head models of 21 chronic stroke subjects and 10 healthy age-matched controls. An anatomy-based stimulation target, i.e. the motor hand knob, was identified with MRI, whereas a motor function-based stimulation target was identified with EEG. For each subject, we simulated conventional anodal tDCS electrode configurations and optimized electrode configurations to maximize stimulation strength within the anatomical and functional target. The normal component of the electric field was extracted and compared between subjects with stroke and healthy, age-matched controls, for both targets, during conventional and optimized tDCS. Electrical field strength was significantly lower, more variable and more frequently in opposite polarity for subjects with stroke compared to healthy age-matched subjects, both for the anatomical and functional target with conventional, i.e. non-individualized, electrode configurations. Optimized, i.e. individualized, electrode configurations increased the electrical field strength in the anatomical and functional target for subjects with stroke but did not reach the same levels as in healthy subjects. Considering individual brain structure and motor function is crucial for applying tDCS in subjects with stroke. Lack of individualized tDCS configurations in subjects with stroke results in lower electric fields in stimulation targets, which may partially explain the inconsistent clinical effects of tDCS in stroke trials., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The detection and localization of electrophysiological substrates currently involve invasive cardiac mapping. Electrocardiographic imaging (ECGI) using the equivalent dipole layer (EDL) method allows the noninvasive estimation of endocardial and epicardial activation and repolarization times (AT and RT), but the RT validation is limited to in silico studies. We aimed to assess the temporal and spatial accuracy of the EDL method in reconstructing the RTs from the surface ECG under physiological circumstances and situations with artificially induced increased repolarization heterogeneity. Methods: In four Langendorff-perfused pig hearts, we simultaneously recorded unipolar electrograms from plunge needles and pseudo-ECGs from a volume-conducting container equipped with 61 electrodes. The RTs were computed from the ECGs during atrial and ventricular pacing and compared with those measured from the local unipolar electrograms. Regional RT prolongation (cooling) or shortening (pinacidil) was achieved by selective perfusion of the left anterior descending artery (LAD) region. Results: The differences between the computed and measured RTs were 19.0 ± 17.8 and 18.6 ± 13.7 ms for atrial and ventricular paced beats, respectively. The region of artificially delayed or shortened repolarization was correctly identified, with minimum/maximum RT roughly in the center of the region in three hearts. In one heart, the reconstructed region was shifted by ~2.5 cm. The total absolute difference between the measured and calculated RTs for all analyzed patterns in selectively perfused hearts ( n = 5) was 39.6 ± 27.1 ms. Conclusion: The noninvasive ECG repolarization imaging using the EDL method of atrial and ventricular paced beats allows adequate quantitative reconstruction of regions of altered repolarization., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 van der Waal, Meijborg, Belterman, Streekstra, Oostendorp and Coronel.)

The inconsistent response to transcranial electric stimulation in the stroke population is attributed to, among other factors, unknown effects of stroke lesion conductivity on stimulation strength at the targeted brain areas. Volume conduction models are promising tools to determine optimal stimulation settings. However, stroke lesion conductivity is often not considered in these models as a source of inter-subject variability. The goal of this study is to propose a method that combines MRI, EEG, and transcranial stimulation to estimate the conductivity of cortical stroke lesions experimentally. In this simulation study, lesion conductivity was estimated from scalp potentials during transcranial electric stimulation in 12 chronic stroke patients. To do so, first, we determined the stimulation configuration where scalp potentials are maximally affected by the lesion. Then, we calculated scalp potentials in a model with a fixed lesion conductivity and a model with a randomly assigned conductivity. To estimate the lesion conductivity, we minimized the error between the two models by varying the conductivity in the second model. Finally, to reflect realistic experimental conditions, we test the effect rotation of measurement electrode orientation and the effect of the number of electrodes used. We found that the algorithm converged to the correct lesion conductivity value when noise on the electrode positions was absent for all lesions. Conductivity estimation error was below 5% with realistic electrode coregistration errors of 0.1° for lesions larger than 50 ml. Higher lesion conductivities and lesion volumes were associated with smaller estimation errors. In conclusion, this method can experimentally estimate stroke lesion conductivity, improving the accuracy of volume conductor models of stroke patients and potentially leading to more effective transcranial electric stimulation configurations for this population., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 van der Cruijsen, Piastra, Selles and Oostendorp.)

This study presents a novel non-invasive equivalent dipole layer (EDL) based inverse electrocardiography ( i ECG) technique which estimates both endocardial and epicardial ventricular activation sequences. We aimed to quantitatively compare our i ECG approach with invasive electro-anatomical mapping (EAM) during sinus rhythm with the objective of enabling functional substrate imaging and sudden cardiac death risk stratification in patients with cardiomyopathy. Thirteen patients (77% males, 48 ± 20 years old) referred for endocardial and epicardial EAM underwent 67-electrode body surface potential mapping and CT imaging. The EDL-based i ECG approach was improved by mimicking the effects of the His-Purkinje system on ventricular activation. EAM local activation timing (LAT) maps were compared with i ECG-LAT maps using absolute differences and Pearson's correlation coefficient, reported as mean ± standard deviation [95% confidence interval]. The correlation coefficient between i ECG-LAT maps and EAM was 0.54 ± 0.19 [0.49-0.59] for epicardial activation, 0.50 ± 0.27 [0.41-0.58] for right ventricular endocardial activation and 0.44 ± 0.29 [0.32-0.56] for left ventricular endocardial activation. The absolute difference in timing between i ECG maps and EAM was 17.4 ± 7.2 ms for epicardial maps, 19.5 ± 7.7 ms for right ventricular endocardial maps, 27.9 ± 8.7 ms for left ventricular endocardial maps. The absolute distance between right ventricular endocardial breakthrough sites was 30 ± 16 mm and 31 ± 17 mm for the left ventricle. The absolute distance for latest epicardial activation was median 12.8 [IQR: 2.9-29.3] mm. This first in-human quantitative comparison of i ECG and invasive LAT-maps on both the endocardial and epicardial surface during sinus rhythm showed improved agreement, although with considerable absolute difference and moderate correlation coefficient. Non-invasive i ECG requires further refinements to facilitate clinical implementation and risk stratification., Competing Interests: PD is owner of ECG Excellence BV. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Roudijk, Boonstra, Brummel, Kassenberg, Blom, Oostendorp, te Riele, van der Heijden, Asselbergs, van Dam and Loh.)

We describe and evaluate our practice-based learning approach for research in undergraduate students studying Biomedical Sciences at Radboud University Nijmegen, the Netherlands. First-year students who started their study between 2015 and 2018 actively participated in data collection and measurements, including anthropometry, electrocardiogram findings, genetic variants, and lifestyle habits. All data were entered into one anonymous database , which was used by students to analyze their research questions. In 2019, 44 of the 87 students (50%) valued active measurements better than questionnaires. Most students (strongly) agreed that they have learned about data collection and were inspired to learn more about biomedical research., (© The Author(s) 2021.)

Objective: Implantable electrodes, such as electrocorticography (ECoG) grids, are used to record brain activity in applications like brain computer interfaces. To improve the spatial sensitivity of ECoG grid recordings, electrode properties need to be better understood. Therefore, the goal of this study is to analyze the importance of including electrodes explicitly in volume conduction calculations., Approach: We investigated the influence of ECoG electrode properties on potentials in three geometries with three different electrode models. We performed our simulations with FEMfuns, a volume conduction modeling software toolbox based on the finite element method., Main Results: The presence of the electrode alters the potential distribution by an amount that depends on its surface impedance, its distance from the source and the strength of the source. Our modeling results show that when ECoG electrodes are near the sources the potentials in the underlying tissue are more uniform than without electrodes. We show that the recorded potential can change up to a factor of 3, if no extended electrode model is used. In conclusion, when the distance between an electrode and the source is equal to or smaller than the size of the electrode, electrode effects cannot be disregarded. Furthermore, the potential distribution of the tissue under the electrode is affected up to depths equal to the radius of the electrode., Significance: This paper shows the importance of explicitly including electrode properties in volume conduction models for accurately interpreting ECoG measurements.

Applications such as brain computer interfaces require recordings of relevant neuronal population activity with high precision, for example, with electrocorticography (ECoG) grids. In order to achieve this, both the placement of the electrode grid on the cortex and the electrode properties, such as the electrode size and material, need to be optimized. For this purpose, it is essential to have a reliable tool that is able to simulate the extracellular potential, i.e., to solve the so-called ECoG forward problem, and to incorporate the properties of the electrodes explicitly in the model. In this study, this need is addressed by introducing the first open-source pipeline, FEMfuns (finite element method for useful neuroscience simulations), that allows neuroscientists to solve the forward problem in a variety of different geometrical domains, including different types of source models and electrode properties, such as resistive and capacitive materials. FEMfuns is based on the finite element method (FEM) implemented in FEniCS and includes the geometry tessellation, several electrode-electrolyte implementations and adaptive refinement options. The Python code of the pipeline is available under the GNU General Public License version 3 at https://github.com/meronvermaas/FEMfuns . We tested our pipeline with several geometries and source configurations such as a dipolar source in a multi-layer sphere model and a five-compartment realistically-shaped head model. Furthermore, we describe the main scripts in the pipeline, illustrating its flexible and versatile use. Provided with a sufficiently fine tessellation, the numerical solution of the forward problem approximates the analytical solution. Furthermore, we show dispersive material and interface effects in line with previous literature. Our results indicate substantial capacitive and dispersive effects due to the electrode-electrolyte interface when using stimulating electrodes. The results demonstrate that the pipeline presented in this paper is an accurate and flexible tool to simulate signals generated on electrode grids by the spatiotemporal electrical activity patterns produced by sources and thereby allows the user to optimize grids for brain computer interfaces including exploration of alternative electrode materials/properties.

Electrocardiographic Imaging (ECGI) requires robust ECG forward simulations to accurately calculate cardiac activity. However, many questions remain regarding ECG forward simulations, for instance: there are not common guidelines for the required cardiac source sampling. In this study we test equivalent double layer (EDL) forward simulations with differing cardiac source resolutions and different spatial interpolation techniques. The goal is to reduce error caused by undersampling of cardiac sources and provide guidelines to reduce said source undersampling in ECG forward simulations. Using a simulated dataset sampled at 5 spatial resolutions, we computed body surface potentials using an EDL forward simulation pipeline. We tested two spatial interpolation methods to reduce error due to undersampling triangle weighting and triangle splitting. This forward modeling pipeline showed high frequency artifacts in the predicted ECG time signals when the cardiac source resolution was too low. These low resolutions could also cause shifts in extrema location on the body surface maps. However, these errors in predicted potentials can be mitigated by using a spatial interpolation method. Using spatial interpolation can reduce the number of nodes required for accurate body surface potentials from 9,218 to 2,306. Spatial interpolation in this forward model could also help improve accuracy and reduce computational cost in subsequent ECGI applications.

The blood-brain barrier (BBB) limits the access of drugs to the brain. Intensive research is being conducted on the development of nanoparticulate drug carriers that mediate transfer across the BBB. A question that has been neglected so far is the potential accumulation of the carrier in the brain upon long-term exposure. Here, we address this question by implementing a kinetic model to relate drug loading, required concentration of drug in the brain, and drug clearance to the degradation half-life of the carrier. As a test case with clinical relevance we chose poly-lactic-co-glycolic-acid (PLGA) as a carrier material and a chemotherapeutic for which the required parameters could be recovered from the literature. For methotrexate with a drug load of 8.5 %, a required concentration of free drug of 1 μm, a release from PLGA of 6 hours, a drug clearance from the brain of 3 hours and a half-life of polymer degradation of 28 days, a steady-state accumulation of 1.3 g polymer would be reached in the brain (1.5 L) after seven months. While this number is surprisingly small, further physiological research is warranted to assess to which degree this will be in a tolerable range., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

Background: Noninvasive imaging of cardiac activation before ablation of the arrhythmogenic substrate can reduce electrophysiological procedure duration and help choosing between an endocardial or epicardial approach. A noninvasive imaging technique was evaluated that estimates both endocardial and epicardial activation from body surface potential maps. We performed a study in isolated and in situ pig hearts, estimating activation from body surface potential maps during sinus rhythm and localizing endocardial and epicardial stimulation sites., Methods and Results: From 3 Langendorff-perfused pig hearts, 180 intramural unipolar electrograms were recorded during sinus rhythm and ectopic activation, together with pseudo-body surface potential map ECGs in 2 of them. From 4 other anesthetized pigs, 64-lead body surface potential maps were recorded during sinus rhythm and ventricular stimulation from 27 endocardial and epicardial sites. The ventricular activation pattern was computed from the recorded QRS complexes. For both Langendorff-perfused hearts, the calculated epicardial and endocardial activation patterns showed good qualitative correspondence to the patterns obtained with needle electrodes. Absolute timing difference for sinus rhythm was 10±5 and 11±8 ms respectively, and for ectopic activation 6±5 and 7±6 ms, respectively. Calculated activation for the in situ hearts in sinus rhythm was similar to patterns recorded in Langendorff-perfused hearts. During stimulation, the distance between the stimulation site and calculated site of earliest activation was 18 (15-27) mm, and 23 of 27 stimulation sites were correctly mapped to either endocardium or epicardium., Conclusions: Noninvasive activation imaging is able to determine earliest ventricular activation and discriminate endocardial from epicardial origin of activation with clinically relevant accuracy., (© 2016 American Heart Association, Inc.)

Background: Characteristics of the ventricular fibrillation (VF) waveform reflect arrest duration and have been incorporated in studies on algorithms to guide resuscitative interventions. Findings in animals indicate that VF characteristics are also affected by the presence of a previous myocardial infarction (MI). As studies in humans are scarce, we assessed the impact of a previous MI on VF characteristics in ICD-patients., Methods: Prospective cohort of ICD-patients (n=190) with defibrillation testing at the Radboudumc (2010-2013). VF characteristics of the 12-lead surface ECG were compared between three groups: patients without a history of MI (n=88), with a previous anterior (n=47) and a previous inferior MI (n=55)., Results: As compared to each of the other groups, the mean amplitude and amplitude spectrum area were lower, for an anterior MI in lead V3 and for an inferior MI in leads II and aVF. Across the three groups, the bandwidth was broader in the leads corresponding with the infarct localisation. In contrast, the dominant and median frequencies only differed between previous anterior MI and no history of MI, being lower in the former., Conclusions: The VF waveform is affected by the presence of a previous MI. Amplitude-related measures were lower and VF was less organised in the ECG-lead(s) adjacent to the area of infarction. Although VF characteristics of the surface ECG have so far primarily been considered a proxy for arrest duration and metabolic state, our findings question this paradigm and may provide additional insights into the future potential of VF-guided resuscitative interventions., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Background: The effectiveness of transcranial magnetic stimulation (TMS) depends highly on the coil orientation relative to the subject's head. This implies that the direction of the induced electric field has a large effect on the efficiency of TMS. To improve future protocols, knowledge about the relationship between the coil orientation and the direction of the induced electric field on the one hand, and the head and brain anatomy on the other hand, seems crucial. Therefore, the induced electric field in the cortex as a function of the coil orientation has been examined in this study., Methods: The effect of changing the coil orientation on the induced electric field was evaluated for fourteen cortical targets. We used a finite element model to calculate the induced electric fields for thirty-six coil orientations (10 degrees resolution) per target location. The effects on the electric field due to coil rotation, in combination with target site anatomy, have been quantified., Results: The results confirm that the electric field perpendicular to the anterior sulcal wall of the central sulcus is highly susceptible to coil orientation changes and has to be maximized for an optimal stimulation effect of the motor cortex. In order to obtain maximum stimulation effect in areas other than the motor cortex, the electric field perpendicular to the cortical surface in those areas has to be maximized as well. Small orientation changes (10 degrees) do not alter the induced electric field drastically., Conclusions: The results suggest that for all cortical targets, maximizing the strength of the electric field perpendicular to the targeted cortical surface area (and inward directed) optimizes the effect of TMS. Orienting the TMS coil based on anatomical information (anatomical magnetic resonance imaging data) about the targeted brain area can improve future results. The standard coil orientations, used in cognitive and clinical neuroscience, induce (near) optimal electric fields in the subject-specific head model in most cases.

Background: Ventricular fibrillation (VF) waveform characteristics are associated with cardiac arrest duration and defibrillation success. Recent animal studies found that VF characteristics and shock success also depend on the presence of myocardial infarction (MI). In patients, VF induction after implantable cardioverter defibrillator (ICD) implantation offers a unique setting to study early VF characteristics: we studied the relation with cardiac disease--either presence or absence of a previous MI--and with shock success., Methods: Retrospective cohort study of ICD-patients who underwent defibrillation testing, 117 (63%) with and 69 (37%) without a previous MI. Intracardiac recordings of induced VF were analysed using Fourier analysis., Results: In previous MI-patients, the fundamental frequency and organisation index of the VF signal were significantly lower as compared with patients without a previous MI: 4.9 Hz ± 0.6 vs. 5.2 Hz ± 0.6 (p = 0.005) and 56% ± 10 vs. 60% ± 9 (p = 0.001), respectively. The median frequency was not different (p = 0.25). We found no association between VF characteristics and ICD shock success., Conclusions: In analogy with observations in animals, we found that a history of a previous MI was associated with slower and less organised VF. In our cohort of ICD-patients, early VF waveform characteristics were not associated with shock outcomes. Further study is warranted to determine to what extent VF characteristics are influenced by the underlying aetiology on the one hand, and time delay on the other. These findings could improve insight into the potential value of VF analysis to guide shock delivery., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)