Estimation Of Conduction Velocity Research Articles

Omnipolar conduction velocity mapping for ventricular substrate characterization: Impact of CV estimation method and EGM type on in vivo conduction velocity measurements

BackgroundAreas of abnormal or heterogeneous conduction velocity (CV) are important ablation targets for ventricular tachycardias, yet precise assessment of CV in clinical contact mapping remains challenging. Numerous different CV estimation methods have been proposed. ObjectiveThis study aimed to compare the automated local activation time (LAT)–independent omnipolar-based CV estimation method termed wave speed (WS) with 4 established LAT-based methods to formally establish the quantitative differences between them. MethodsHigh-density contact maps in patients with structurally normal hearts during sinus rhythm (SR) and ventricular ectopy (VE) were retrospectively analyzed. CV was assessed and compared by 5 methods: omnipolar WS, gradient method, planar wavefront fitting, circular wavefront fitting, and radial basis function. CV variations based on electrogram (EGM) type (unipolar, bipolar, and omnipolar), catheter movement, and surrogate markers for catheter contact were analyzed. ResultsThe study included 23 patients (47.8% male; 45.7 ± 17.3 years) with 22 SR maps (11 left ventricle, 11 right ventricle) and 16 VE maps (9 left ventricle, 7 right ventricle). The WS algorithm yielded statistically significant higher CV estimates in SR (mean, 1.41 ± 0.18 m/s) and VE (mean, 1.23 ± 0.18 m/s) maps compared with all LAT-based estimation methods, with absolute differences ranging from 0.1 m/s to 0.81 m/s. Median pointwise differences in SR and VE between WS and LAT-based methods were high, ranging from 0.55 ± 0.15 m/s (WS vs planar wavefront fitting) to 0.67 ± 0.16 m/s (WS vs radial basis function). For LAT-based methods, use of unipolar EGMs yielded significantly higher CV estimates than bipolar or omnipolar EGMs in SR. ConclusionThe CV estimation method has an important, statistically significant impact on ventricular CV measurements. Future work will focus on how these differences affect identification of pathologic conduction slowing in scar-related substrate.

Enhancing OpenEP: atrial conduction velocity and conduction velocity heterogeneity quantification through EP Workbench

Abstract Background Alterations in atrial conduction velocity have been implicated in the pathogenesis of atrial arrhythmias, with conduction velocity thought to be slower and more heterogeneous in areas promoting atrial fibrillation. However, clinical studies of conduction velocity are challenging since there are no available platforms that provide researchers and clinicians with the ability to quantify conduction velocity and analyse conduction heterogeneity from electroanatomic mapping data. Purpose In this paper we sought to address these limitations by enhancing the OpenEP Python library by (1) automating calculations using previously-published conduction velocity estimation algorithms; (2) providing an interactive graphical representing of conduction velocity and conduction heterogeneity and (3) implementing a histogram analysis tool to quantify conduction velocity and enable the identification of slow conduction regions. Method Two well-known and previously published methods for calculating cardiac conduction velocity, Triangulation and polynomial surface fitting, were implemented. Conduction velocity estimation was improved further by excluding regions with wave collisions and focal discharges. These regions were identified using the divergence of conduction velocity vector fields, with positive divergence representing focal sources and negative divergence representing areas of collision. Finally, calculated conduction velocities using electrogram data were interpolated over the surface mesh via Radial Basis Function (RBF) interpolation method. All algorithms were implemented in the OpenEP Python library (openep-py), with visualisation tools provided in the complementary graphical interface, EP Workbench. Results An extensible "Analysis" feature was created in openep-py, to provide conduction velocity and divergence calculations which are fully customisable through the graphical interface based on user preferences. The EP Workbench desktop application displays resulting cardiac surface maps to depict calculated conduction velocity and divergence fields, together with conventional activation and voltage maps (Figure 1). The histogram analysis tool can be used to identify regions of slow conduction velocity from electroanatomic mapping data. Using a threshold of <0.3m/s, two slow conducting channels are visualised on the posterior wall of a test case (Figure 2). The tool is not specific to conduction velocity and may also be used to quantify other data types in EP Workbench. Finally, computed conduction velocity and divergence values and surface maps are stored in the standard OpenEP data structure, allowing further analysis following data export. Conclusion We have extended OpenEP to provide a comprehensive set of tools for conduction velocity calculation and analysis which will facilitate investigation of the structural and functional basis of conduction velocity alterations in disease states.

Trunk extensor muscle endurance and its relationship to action potential conduction velocity and spectral parameters estimated using high-density electromyography

Trunk extensor muscle fatigue typically manifests as a decline in spectral content of surface electromyography. However, previous research on the relationship of this decline with trunk extensor muscle endurance have shown inconsistent results. The decline of spectral content mainly reflects the decrease in average motor unit action potential conduction velocity (CV). We evaluated whether the rate of change in CV, as well as two approaches employing the change in spectral content, are related to trunk extensor muscle endurance. Fourteen healthy male participants without a low-back pain history performed a non-strictly controlled static forward trunk bending trial until exhaustion while standing. For 13 participants, physiologically plausible CV estimates were obtained from high-density surface electromyography bilaterally from T6 to L5. Laterally between L1 and L2, the linear rate of CV change was strongly correlated to endurance time (R2 = 0.79), whereas analyses involving the linear rate of change in spectral measures showed a lower (R2 = 0.38) or no correlation. For medial electrode locations, estimating CV and its relationship with endurance time was less successful, while the linear rate of change in spectral measures correlated moderately to endurance time (R2 = 0.44; R2 = 0.56). This study provides guidance on monitoring trunk extensor muscle fatigue development using electromyography.

Performance of atrial conduction velocity algorithms: a comparative in-silico study

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): British Heart Foundation Background Atrial conduction velocity is a key determinant of re-entry. Measurement of conduction velocity from electroanatomic mapping data is challenging due to sparsity, distribution, and uncertainty of measurements. Several mathematical methods have been proposed to address these challenges but their relative sensitivity to the typical uncertainty of clinical data is unknown. Furthermore, prior clinical studies utilising these algorithms provide conflicting results. Purpose To assess the performance of conduction velocity methods (triangulation, planar fitting, and radial basis function interpolation) for the calculation of atrial conduction velocity. Method Atrial activation was simulated with known conduction velocity using the monodomain model, Courtemanche cell model and atrial geometry derived from cardiac magnetic resonance imaging with mapped fibre orientations. The model was paced from the pulmonary veins, the mid coronary sinus, and the insertion of Bachmann's bundle. Reconstructed electroanatomic maps were used for conduction velocity calculation in OpenEP[1]. To test the robustness of algorithms to electrogram sampling density, simulated sampling densities were reduced from 16.45 to 8.43 points/cm2 (1950-1000 points/map). To test the robustness to uncertainty in local activation time assignment, random uniform noises with the maximum amplitude of ± 20ms was added to the local activation times from simulations. Mean squared velocity error was calculated using the differences between the ground truth and estimated conduction velocities. Result In electroanatomic maps recreated with high electrogram sampling density (16.45 points/cm2), planar fitting showed a slightly higher error compared to triangulation and the radial basis function methods (0.16 ± 0.03 m/s, 0.11 ± 0.01 m/s and 0.12 ± 0.03 m/s, respectively, P < 0.05). As mapping density was decreased, the relative performance of the planar fitting method increased and in low-density maps (13.5 to 8.43 points/cm2) the planar fitting method resulted in the lowest error. When local activation times were accurately assigned, all methods performed well. However, when uncertainty in local activation time assignment increased, conduction velocities calculated using planar fitting had a significantly lower error compared to those calculated with the triangulation and radial basis function methods (0.19 ± 0.03 m/s, 0.36 ± 0.04 and 0.29 ± 0.04 m/s, respectively, P < 0.05). Conclusion This study highlights the importance of spatial and temporal accuracy for the assessment of conduction velocity. At high electroanatomic mapping sampling densities (>16.9 points/cm2), all methods performed well. Below 13.5 points/cm2 (~1600 points per map), the planar fitting method outperformed the triangulation and radial basis function methods. The differential effects of clinical measurement uncertainty on the accuracy of each method may explain the conflicting results of prior studies.

Non-invasive estimation of muscle fibre size from high-density electromyography.

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity could be a non-invasive index of muscle fibre size in humans. However, the relation between motor unit conduction velocity and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e. high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e. muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. We demonstrate the possibility of predicting muscle fibre diameter (R2 =0.66) and cross-sectional area (R2 =0.65) from conduction velocity estimates with low systematic bias (∼2% and ∼4% respectively) and a relatively low margin of individual error (∼8% and ∼16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, ageing, space and exercise physiology, although the applicability and validity of the proposed methodology need to be more directly assessed in these specific populations by future studies. KEY POINTS: Because of the biophysical relation between muscle fibre size and the propagation velocity of action potentials along the sarcolemma, motor unit conduction velocity could represent a potential non-invasive candidate for estimating muscle fibre size in vivo. This relation has been previously assessed in animal models and humans with invasive techniques, or it has been mathematically derived from simulations. By combining high-density surface EMG with muscle biopsy, here we explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy individuals. Our results confirmed that motor unit conduction velocity can be considered as a novel biomarker of fibre size, which can be adopted to predict muscle fibre diameter and cross-sectional area with low systematic bias and margin of individual error. The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling.

Abnormal Conduction Zone Detected by Isochronal Late Activation Mapping Accurately Identifies the Potential Atrial Substrate and Predicts the Atrial Fibrillation Ablation Outcome After Pulmonary Vein Isolation.

The presence of abnormal substrate of left atrium is a predictor of atrial fibrillation (AF) recurrence after pulmonary vein isolation. We aimed to investigate the isochronal late activation mapping to access the abnormal conduction velocity for predicting AF ablation outcome. Forty-five paroxysmal AF patients (30 males, 57.8±8.7 years old) who underwent pulmonary vein isolation were enrolled. Isochronal late activation mapping was retrospectively constructed with 2 different windows of interest: from onset of P wave to onset of QRS wave on surface electrocardiography (W1) and 74 ms tracking back from the end of P wave (W2). Deceleration zone was defined as regions with 3 isochrones (DZa) or ≥4 isochrones (DZb) within a 1 cm radius on the isochronal late activation mapping, and the estimated conduction velocity (ECV) are 0.27 m/s and <0.20 m/s for DZa and DZb, respectively in W2. The distribution of deceleration zone was compared with the location of low-voltage zone (bipolar voltage ≤0.5 mV). Any recurrence of atrial arrhythmias was defined as the primary end point during follow ups after a 3-month blanking period. Pulmonary vein isolation was performed in all patients, and there were 2 patients (4.4%) received additional extrapulmonary vein ablation. After a mean follow-up of 12.7±4.5 months, recurrence of AF occurred in 14 patients (31.1%). Patients with the presence of DZb in W2 had higher AF recurrence (Kaplan-Meier event rate estimates: HR, 9.41 [95% CI, 2.61-33.90]; log-rank P<0.0001). There were 52.6% of the DZb locations in W2 comparable to the distributions of low-voltage zone and 47.4% DZb were distributed in the area without low-voltage zone. Deceleration zone detected by isochronal late activation mapping represents a critical AF substrate, it accurately predicts the AF recurrence following ablation in patients with paroxysmal AF.

Spatio-temporal modeling of saltatory conduction in neurons using Poisson–Nernst–Planck treatment and estimation of conduction velocity

Action potential propagation along the axons and across the dendrites is the foundation of the electrical activity observed in the brain and the rest of the nervous system. Theoretical and numerical modeling of this action potential activity has long been a key focus area of electro-chemical neuronal modeling, and over the years, electrical network models of varying complexity have been proposed. Specifically, considering the presence of nodes of Ranvier along the myelinated axon, single-cable models of the propagation of action potential have been popular. Building on these models, and considering a secondary electrical conduction pathway below the myelin sheath, the double-cable model has been proposed. Such cable theory based treatments, including the classical Hodgkin–Huxley model, single-cable model, and double-cable model have been extensively studied in the literature. But these have inherent limitations in their lack of a representation of the spatio-temporal evolution of the neuronal electro-chemistry. In contrast, a Poisson–Nernst–Planck (PNP) based electro-diffusive framework accounts for the underlying spatio-temporal ionic concentration dynamics and is a more general and comprehensive treatment. In this work, a high-fidelity implementation of the PNP model is demonstrated. This electro-diffusive model is shown to produce results similar to the cable theory based electrical network models, and in addition, the rich spatio-temporal evolution of the underlying ionic transport is captured. Novel to this work is the extension of PNP model to axonal geometries with multiple nodes of Ranvier, its correlation with cable theory based models, and multiple variants of the electro-diffusive model — PNP without myelin, PNP with myelin, and PNP with the myelin sheath and peri-axonal space. Further, we apply this spatio-temporal model to numerically estimate conduction velocity in a rat axon using the three model variants. Specifically, spatial saltatory conduction due to the presence of myelin sheath and the peri-axonal space is investigated.Statement of Significance: In this work, we present a comprehensive PDE based treatment for modeling neuronal action potential generation and propagation and provide a first-of-its-kind framework for computationally estimating action potential conduction velocities. This electro-diffusive model, based on a Poisson-Nernst-Planck (PNP) formulation, is shown to produce results similar to the cable theory based electrical network models, and in addition, the rich spatio-temporal evolution of the underlying ionic transport is captured. Novel to this work is the extension of PNP model to axonal geometries with multiple nodes of Ranvier, its correlation with cable theory based models, and multiple variants of the electro-diffusive model - PNP without myelin, PNP with myelin, and PNP with the myelin sheath and periaxonal space. Further, we apply this spatio-temporal model to numerically estimate conduction velocity in a rat axon using the three model variants. Specifically, spatial saltatory conduction due to the presence of myelin sheath and the peri-axonal space is investigated.

Automated conduction velocity estimation based on isochronal activation of heart chambers

BackgroundSpatial differences in conduction velocity (CV) are critical for cardiac arrhythmias induction. We propose a method for an automated CV calculation to identify areas of slower conduction during cardiac arrhythmias and sinus rhythm.MethodsColor-coded representations of the isochronal activation map using data coming from the RHYTHMIA™ Mapping System were reproduced by applying a temporal isochronal window at 20 ms. Geodesic distances of the 3D mesh were calculated using an algorithm selecting the minimum distance pathway (MDP). The CV estimation was performed considering points on the boundary of two spatially and temporally adjacent isochrones. For each of the boundary points of a given isochrone, the nearest boundary point of the consecutive isochrone was chosen, the MDP was evaluated, and a map of CV was created. The proposed method has been applied to a population of 29 patients.ResultsIn all cases of perimitral atrial flutter (16 pts out of 29 (55%)), areas with significantly low CV (< 30 cm/s) were found. Half of the cases present regions with low CV located in the anterior wall. No case with low CV at the so-called LA isthmus was observed. Right atrial maps during common atrial flutters showed low CV areas mainly located in the inferior inter-atrial septum. No areas of low CV were observed in subjects without a history of atrial arrhythmia while pts affected by paroxysmal AF showed areas with a limited extension of low CV.ConclusionsThe proposed software for automated CV estimation allows the identification of low CV areas, potentially helping electrophysiologists to plan the ablation strategy.

In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data.

PurposeWe present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.TheoryThe proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β.MethodsMRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract.ResultsThe estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm−α.ConclusionThe estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.

Electroneurography abnormality in Parkinson’s disease: a potential biomarker to help diagnosis

Parkinson’s disease (PD) is a common neurodegenerative disease, pathologically characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra. Although various biomarkers and imaging criteria for PD have been established, objective and reliable evaluation methods are still lacking. Electroneurography, as an objective measurement of evoked compound muscle action potentials, is used to assess the integrity of the peripheral nerve and is important in the diagnosis and differential diagnosis of PD with neuromuscular injury. Moreover, it provides references for the evaluation and quantification of the motor function in PD. Here, we summarize recent advances in clinical research of electroneurography in PD, including the peripheral nerve conduction velocity, needle electromyography, surface electromyography, and motion unit number estimation. The potential values of electroneurography in PD diagnosis are also involved.

Identification of local atrial conduction heterogeneities using high-density conduction velocity estimation.

AimsAccurate determination of intra-atrial conduction velocity (CV) is essential to identify arrhythmogenic areas. The most optimal, commonly used, estimation methodology to measure conduction heterogeneity, including finite differences (FiD), polynomial surface fitting (PSF), and a novel technique using discrete velocity vectors (DVV), has not been determined. We aim (i) to identify the most suitable methodology to unravel local areas of conduction heterogeneities using high-density CV estimation techniques, (ii) to quantify intra-atrial differences in CV, and (iii) to localize areas of CV slowing associated with paroxysmal atrial fibrillation (PAF).Methods and resultsIntra-operative epicardial mapping (>5000 sites, interelectrode distances 2 mm) of the right and left atrium and Bachmann’s bundle (BB) was performed during sinus rhythm (SR) in 412 patients with or without PAF. The median atrial CV estimated using the DVV, PSF, and FiD techniques was 90.0 (62.4–116.8), 92.0 (70.6–123.2), and 89.4 (62.5–126.5) cm/s, respectively. The largest difference in CV estimates was found between PSF and DVV which was caused by smaller CV magnitudes detected only by the DVV technique. Using DVV, a lower CV at BB was found in PAF patients compared with those without atrial fibrillation (AF) [79.1 (72.2–91.2) vs. 88.3 (79.3–97.2) cm/s; P < 0.001].ConclusionsAreas of local conduction heterogeneities were most accurately identified using the DVV technique, whereas PSF and FiD techniques smoothen wavefront propagation thereby masking local areas of conduction slowing. Comparing patients with and without AF, slower wavefront propagation during SR was found at BB in PAF patients, indicating structural remodelling.

Estimation and Validation of Cardiac Conduction Velocity and Wavefront Reconstruction Using Epicardial and Volumetric Data.

In this study, we have used whole heart simulations parameterized with large animal experiments to validate three techniques (two from the literature and one novel) for estimating epicardial and volumetric conduction velocity (CV). We used an eikonal-based simulation model to generate ground truth activation sequences with prescribed CVs. Using the sampling density achieved experimentally we examined the accuracy with which we could reconstruct the wavefront, and then examined the robustness of three CV estimation techniques to reconstruction related error. We examined a triangulation-based, inverse-gradient-based, and streamline-based techniques for estimating CV cross the surface and within the volume of the heart. The reconstructed activation times agreed closely with simulated values, with 50-70% of the volumetric nodes and 97-99% of the epicardial nodes were within 1 ms of the ground truth. We found close agreement between the CVs calculated using reconstructed versus ground truth activation times, with differences in the median estimated CV on the order of 3-5% volumetrically and 1-2% superficially, regardless of what technique was used. Our results indicate that the wavefront reconstruction and CV estimation techniques are accurate, allowing us to examine changes in propagation induced by experimental interventions such as acute ischemia, ectopic pacing, or drugs. We implemented, validated, and compared the performance of a number of CV estimation techniques. The CV estimation techniques implemented in this study produce accurate, high-resolution CV fields that can be used to study propagation in the heart experimentally and clinically.

Quantifying the spatiotemporal influence of acute myocardial ischemia on volumetric conduction velocity

IntroductionAcute myocardial ischemia occurs when coronary perfusion to the heart is inadequate, which can perturb the highly organized electrical activation of the heart and can result in adverse cardiac events including sudden cardiac death. Ischemia is known to influence the ST and repolarization phases of the ECG, but it also has a marked effect on propagation (QRS); however, studies investigating propagation during ischemia have been limited. MethodsWe estimated conduction velocity (CV) and ischemic stress prior to and throughout 20 episodes of experimentally induced ischemia in order to quantify the progression and correlation of volumetric conduction changes during ischemia. To estimate volumetric CV, we 1) reconstructed the activation wavefront; 2) calculated the elementwise gradient to approximate propagation direction; and 3) estimated conduction speed (CS) with an inverse-gradient technique. ResultsWe found that acute ischemia induces significant conduction slowing, reducing the global median speed by 20 cm/s. We observed a biphasic response in CS (acceleration then deceleration) early in some ischemic episodes. Furthermore, we noted a high temporal correlation between ST-segment changes and CS slowing; however, when comparing these changes over space, we found only moderate correlation (corr. = 0.60). DiscussionThis study is the first to report volumetric CS changes (acceleration and slowing) during episodes of acute ischemia in the whole heart. We showed that while CS changes progress in a similar time course to ischemic stress (measured by ST-segment shifts), the spatial overlap is complex and variable, showing extreme conduction slowing both in and around regions experiencing severe ischemia.

Influence of Spectral Peaks on EMG Parameter Estimation for Vibration-Exercise Analysis

Many studies have proposed vibration exercise (VE) as a novel training modality for neuromuscular conditioning and rehabilitation. Surface electromyography (sEMG) is widely used for effective measurement of muscle activity. Unfortunately, sharp spectral peaks (SSP) are usually present in the EMG signals recorded during VE. The explanation of these sharp peaks, as muscle activity or motion artifacts, is controversial, complicating EMG parameter extraction for the analysis of VE. The present study aims to quantify the impact of these SSP on the estimation of EMG parameters irrespective of their nature. High-density sEMG was therefore recorded from the biceps brachii muscle during VE with different vibration amplitudes (VA) and frequencies (VF). The power around (±0.5 Hz) VF and its first harmonic was calculated and normalized with the entire EMG power in order to obtain a relative power ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> ) of these peaks. In addition, before and after excluding the SSP, three EMG parameters, i.e., mean frequency (MF), root mean square (RMS), and conduction velocity (CV), were estimated and compared. Our results reveal an average P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> of 21.18± 15.68 %. The relative difference in EMG RMS and MF are 12.2± 3.8 % and 2.10± 1.04 %, respectively. In addition, the impact of these peaks on the MF and RMS seems also to be affected by vibration conditions, such as VA and VF. However, the CV estimation seems not to be significantly influenced by these peaks, indicating these peaks to be primarily reflecting muscle activity and therefore should be included in VE EMG analysis.

Sensitivity of the surrogate analysis method to synchronization and conduction velocity of muscular fibers

This paper shows that conduction velocity (CV) and motor unit action potential (MUAPs) synchronization affects the results of Surrogate Analysis (SA) of the surface electromyography (sEMG) signal. It will be verified if the SA can extract information from the sEMG signal. Also, it is the first time that the SA is interpreted from a physiological point-of-view. To illustrate the relationships between the CV, the synchronization and the SA, a simple dipole-based model for (sEMG) signal simulation is used. It is composed of multiple fibers superposed at the same location, leaving aside any complex geometrical considerations, but putting the emphasis on the timing of the MUAPs firing. Single-pulse synchronization as well as impulse train synchronization are studied. To highlight the difference between spectral (linear) features, nonlinear features and SA relation with the model parameters, the Median Frequency (MDF), the Kurtosis, the Higuchi’s Fractal Dimension (FD) and the FD based SA are compared. The simulation results show that the SA is jointly influenced by CV and the MUAPs synchronization, almost in a multiplicative way. These relations are also more pronounced for an impulse train than for a single pulse. Overall, the SA is shown to be a good feature to consider for CV and MUAPs synchronization estimation. It is moreover uncorrelated with spectral features and moderately with nonlinear features. These findings can be used to 1) help evaluate the CV and MUAPs synchronization and 2) interpret the result of the surrogate analysis.

Inverse modelling to reduce crosstalk in high density surface electromyogram

Surface electromyogram (EMG) has a relatively large detection volume, so that it could include contributions both from the target muscle of interest and from nearby regions (i.e., crosstalk). This interference can prevent a correct interpretation of the activity of the target muscle, limiting the use of surface EMG in many fields. To counteract the problem, selective spatial filters have been proposed, but they reduce the representativeness of the data from the target muscle. A better solution would be to discard only crosstalk from the signal recorded in monopolar configuration (thus, keeping most information on the target muscle). An inverse modelling approach is here proposed to estimate the contributions of different muscles, in order to focus on the one of interest. The method is tested with simulated monopolar EMGs from superficial nearby muscles contracted at different force levels (either including or not model perturbations and noise), showing statistically significant improvements in information extraction from the data. The median over the entire dataset of the mean squared error in representing the EMG of the muscle under the detection electrode was reduced from 11.2% to 4.4% of the signal energy (5.3% if noisy data were processed); the median bias in conduction velocity estimation (from 3 monopolar channels aligned to the muscle fibres) was decreased from 2.12 to 0.72 m/s (1.1 m/s if noisy data were processed); the median absolute error in the estimation of median frequency was reduced from 1.02 to 0.67 Hz in noise free conditions and from 1.52 to 1.45 Hz considering noisy data.

Transient Hypothyroidism During Lactation Alters the Development of the Corpus Callosum in Rats. An in vivo Magnetic Resonance Image and Electron Microscopy Study.

Magnetic resonance imaging (MRI) data of children with late diagnosed congenital hypothyroidism and cognitive alterations such as abnormal verbal memory processing suggest altered telencephalic commissural connections. The corpus callosum (CC) is the major inter-hemispheric commissure that contra-laterally connects neocortical areas. However, in late diagnosed neonates with congenital hypothyroidism, the possible effect of early transient and chronic postnatal hypothyroidism still remains unknown. We have studied the development of the anterior, middle and posterior CC, using in vivo MRI and electron microscopy in hypothyroid and control male rats. Four groups of methimazole (MMI) treated rats were studied. One group, as a model for early transient hypothyroidism, was MMI-treated from postnatal day (P) 0 to P21; some of these rats were also treated with L-thyroxine (T4) from P15 to 21. Another group modeling chronic hypothyroid, were treated with MMI from P0 to 150 and from embryonic day 10 to P170. The results obtained from these groups were compared with same age control rats. The normalized T2 signal obtained using MRI was higher in MMI-treated rats and correlated with a low number and percentage of myelinated axons. The number and density of myelinated axons decreased in transient and chronic hypothyroid rats at P150. The g-ratio (inner to outer diameter ratio) and the estimated conduction velocity of myelinated axons were similar between MMI-treated and controls, but the conduction delay decreased in the posterior CC of MMI-treated rats compared to controls. These data show that early postnatal transient and chronic hypothyroidism alters CC maturation in a way that may affect the callosal transfer of information. These alterations cannot be reversed after delayed T4-treatment. Our data support the findings of neurocognitive delay in late T4-treated children with congenital hypothyroidism.

Reproducibility of muscle fibre conduction velocity during linearly increasing force contractions

Muscle fibre conduction velocity (MFCV) is a basic physiological parameter biophysically related to the diameter of muscle fibres and properties of the sarcolemma. The aim of this study was to assess the intersession reproducibility of the relation between voluntary force and estimates of average muscle fibre conduction velocity (MFCV) from multichannel high-density surface electromyographic recordings (HDsEMG). Ten healthy men performed six linearly increasing isometric ankle dorsiflexions on two separate experimental sessions, 4 weeks apart. Each session involved the recordings of voluntary force during maximal isometric (MViF) and submaximal ramp contractions at 35–50–70% of MViF. Concurrently, the HDsEMG activity was detected from the tibialis anterior muscle and MFCV estimates were derived in 250-ms epochs. Absolute and relative reproducibility of MFCV initial value (intercept) and rate of change (regression slope) as a function of force were assessed by within-subject coefficient of correlation (CVw) and with intraclass correlation coefficient (ICC). MFCV was positively correlated with voluntary force (R2 = 0.75 ± 0.12) in all individuals and test conditions (P < 0.001). Average CVw for MFCV intercept and slope were of 2.6 ± 2.0% and 11.9 ± 3.2% and ICC values of 0.96 and 0.94, respectively.Overall, MFCV regression coefficients showed a high degree of intersession reproducibility in both absolute and relative terms. These results may have important practical implications in the tracking of training-induced neuromuscular changes and/or in the monitoring of the progress of neuromuscular disorders when a full sEMG signal decomposition is problematic or not possible.

Accurate Conduction Velocity Maps and Their Association With Scar Distribution on Magnetic Resonance Imaging in Patients With Postinfarction Ventricular Tachycardias.

Characterizing myocardial conduction velocity (CV) in patients with ischemic cardiomyopathy (ICM) and ventricular tachycardia (VT) is important for understanding the patient-specific proarrhythmic substrate of VTs and therapeutic planning. The objective of this study is to accurately assess the relation between CV and myocardial fibrosis density on late gadolinium-enhanced cardiac magnetic resonance imaging (LGE-CMR) in patients with ICM. We enrolled 6 patients with ICM undergoing VT ablation and 5 with structurally normal left ventricles (controls) undergoing premature ventricular contraction or VT ablation. All patients underwent LGE-CMR and electroanatomic mapping (EAM) in sinus rhythm (2960 electroanatomic mapping points analyzed). We estimated CV from electroanatomic mapping local activation time using the triangulation method that provides an accurate estimate of CV as it accounts for the direction of wavefront propagation. We evaluated the association between LGE-CMR intensity and CV with multilevel linear mixed models. Median CV in patients with ICM and controls was 0.41 m/s and 0.65 m/s, respectively. In patients with ICM, CV in areas with no visible fibrosis was 0.81 m/s (95% CI, 0.59-1.12 m/s). For each 25% increase in normalized LGE intensity, CV decreased by 1.34-fold (95% CI, 1.25-1.43). Dense scar areas have, on average, 1.97- to 2.66-fold slower CV compared with areas without dense scar. Ablation lesions that terminated VTs were localized in areas of slow conduction on CV maps. CV is inversely associated with LGE-CMR fibrosis density in patients with ICM. Noninvasive derivation of CV maps from LGE-CMR is feasible. Integration of noninvasive CV maps with electroanatomic mapping during substrate mapping has the potential to improve procedural planning and outcomes. Visual Overview: A visual overview is available for this article.

Validation of Intramural Wavefront Reconstruction and Estimation of 3D Conduction Velocity.

Changes in conduction velocity are indicative of a wide variety of cardiac abnormalities yet measuring conduction velocity is challenging, especially within the myocardial volume. In this study we investigated a novel technique to reconstruct activation fronts and estimate three-dimensional (3D) conduction velocity (CV) from experimental intramural recordings. From the intermittently sampled electrograms we both reconstruct the activation profile and compute the reciprocal of the gradient of activation times and a series of streamlines that allows for the CV estimation. The reconstructed activation times agreed closely with simulated values, with 50% to 70% of the nodes ≤ 1ms of absolute error. We found close agreement between the CVs calculated using reconstructed versus simulated activation times. Across the reconstructed stimulation sites we saw that the reconstructed CV was on average 3.8% different than the ground truth CV. This study used simulated datasets to validate our methods for reconstructing 3D activation fronts and estimating conduction velocities. Our results indicate that our method allows accurate reconstructions from sparse measurements, thus allowing us to examine changes in activation induced by experimental interventions such as acute ischemia, ectopic pacing, or drugs.