Experimental and Automated Analysis Techniques for High-resolution Electrical Mapping of Small Intestine Slow Wave Activity.

BACKGROUND/AIMS: Small intestine motility is governed by an electrical slow wave activity, and abnormal slow wave events have been associated with intestinal dysmotility. High-resolution (HR) techniques are necessary to analyze slow wave propagation, but progress has been limited by few available electrode options and laborious manual analysis. This study presents novel methods for in vivo HR mapping of small intestine slow wave activity. METHODS: Recordings were obtained from along the porcine small intestine using flexible printed circuit board arrays (256 electrodes; 4 mm spacing). Filtering options were compared, and analysis was automated through adaptations of the falling-edge variable-threshold (FEVT) algorithm and graphical visualization tools. RESULTS: A Savitzky-Golay filter was chosen with polynomial-order 9 and window size 1.7 seconds, which maintained 94% of slow wave amplitude, 57% of gradient and achieved a noise correction ratio of 0.083. Optimized FEVT parameters achieved 87% sensitivity and 90% positive-predictive value. Automated activation mapping and animation successfully revealed slow wave propagation patterns, and frequency, velocity, and amplitude were calculated and compared at 5 locations along the intestine (16.4 ± 0.3 cpm, 13.4 ± 1.7 mm/sec, and 43 ± 6 µV, respectively, in the proximal jejunum). CONCLUSIONS: The methods developed and validated here will greatly assist small intestine HR mapping, and will enable experimental and translational work to evaluate small intestine motility in health and disease.

Gastric emptying and Ca(2+) and K(+) channels of circular smooth muscle cells in diet-induced obese prone and resistant rats.

OBJECTIVE: Accelerated gastric emptying that precipitates hunger and frequent eating could be a potential factor in the development of obesity. The aim of this study was to study gastric emptying in diet-induced obese-prone (DIO-P) and DIO-resistant (DIO-R) rats and explore possible differences in electrical properties of calcium (Ca(2+) ) and potassium (K(+) ) channels of antral circular smooth muscle cells (SMCs). DESIGN AND METHODS: Whole-cell patch-clamp technique was used to measure Ca(2+) and K(+) currents in single SMCs. Gastric emptying was evaluated 90 min after the ingestion of a solid meal. RESULTS: Solid gastric emptying in the DIO-P rats was significantly faster compared with that in the DIO-R rats. The peak amplitude of L-type Ca(2+) current (IBa,L ) at 10 mV in DIO-P rats was greater than that in DIO-R rats without alternation of the current-voltage curve and voltage-dependent activation and inactivation. The half-maximal inactivation voltage of transient outward K(+) current (IKto ) was more depolarized (∼4 mV) in DIO-P rats compared with that in DIO-R rats. No difference was found in the current density or recovery kinetics of IKto between two groups. The current density of delayed rectifier K(+) current (IKdr ), which was sensitive to tetraethylammonium chloride but not 4-aminopyridine, was lower in DIO-P rats than that in DIO-R rats. CONCLUSION: The accelerated gastric emptying in DIO-P rats might be attributed to a higher density of IBa,L , depolarizing shift of inactivation curve of IKto and lower density of IKdr observed in the antral SMCs of DIO-P rats.

Model-based identification of motion sensor placement for tracking retraction and elongation of the tongue.

Electromagnetic articulography (EMA) is designed to track facial and tongue movements. In practice, the EMA sensors for tracking the movement of the tongue's surface are placed heuristically. No recommendation exists. Within this paper, a model-based approach providing a mathematical analysis and a computational-based recommendation for the placement of sensors, which is based on the tongue's envelope of movement, is proposed. For this purpose, an anatomically detailed Finite Element (FE) model of the tongue has been employed to determine the envelope of motion for retraction and elongation using a forward simulation. Two optimality criteria have been proposed to identify a set of optimal sensor locations based on the pre-computed envelope of motion. The first one is based on the assumption that locations exhibiting large displacements contain the most information regarding the tongue's movement and are less susceptible to measurement errors. The second one selects sensors exhibiting each the largest displacements in the anterior-posterior, superior-inferior, medial-lateral and overall direction. The quality of the two optimality criteria is analysed based on their ability to deduce from the respective sensor locations the corresponding muscle activation parameters of the relevant muscle fibre groups during retraction and elongation by solving the corresponding inverse problem. For this purpose, a statistical analysis has been carried out, in which sensor locations for two different modes of deformation have been subjected to typical measurement errors. Then, for tongue retraction and elongation, the expectation value, the standard deviation, the averaged bias and the averaged coefficient of variation have been computed based on 41 different error-afflicted sensor locations. The results show that the first optimality criteria is superior to the second one and that the averaged bias and averaged coefficient of variation decrease when the number of sensors is increased from 2, 4 to 6 deployable sensors.

Neuromuscular interfacing: establishing an EMG-driven model for the human elbow joint.

Assistive devices aim to mitigate the effects of physical disability by aiding users to move their limbs or by rehabilitating through therapy. These devices are commonly embodied by robotic or exoskeletal systems that are still in development and use the electromyographic (EMG) signal to determine user intent. Not much focus has been placed on developing a neuromuscular interface (NI) that solely relies on the EMG signal, and does not require modifications to the end user's state to enhance the signal (such as adding weights). This paper presents the development of a flexible, physiological model for the elbow joint that is leading toward the implementation of an NI, which predicts joint motion from EMG signals for both able-bodied and less-abled users. The approach uses musculotendon models to determine muscle contraction forces, a proposed musculoskeletal model to determine total joint torque, and a kinematic model to determine joint rotational kinematics. After a sensitivity analysis and tuning using genetic algorithms, subject trials yielded an average root-mean-square error of 6.53° and 22.4° for a single cycle and random cycles of movement of the elbow joint, respectively. This helps us to validate the elbow model and paves the way toward the development of an NI.

Simulating a dual-array electrode configuration to investigate the influence of skeletal muscle fatigue following functional electrical stimulation.

A novel, anatomically-accurate model of a tibialis anterior muscle is used to investigate the electro-physiological properties of denervated muscles following functional electrical stimulation. The model includes a state-of-the-art description of cell electro-physiology. The main objective of this work is to develop a computational framework capable of predicting the effects of different stimulation trains and electrode configurations on the excitability and fatigue of skeletal muscle tissue. Utilizing a reduced but computationally amenable model, the effects of different electrode sizes and inter-electrode distances on the number of activated muscle fibers are investigated and qualitatively compared to existing literature. To analyze muscle fatigue, the sodium current, specifically the K+ ion concentrations within the t-tubule and the calcium release from the sarcoplasmic reticulum, is used to quantify membrane and metabolic fatigue. The simulations demonstrate that lower stimulation frequencies and biphasic pulse waveforms cause less fatigue than higher stimulation frequencies and monophasic pulses. A comparison between single and dual electrode configurations (with the same overall stimulation surface) is presented to locally investigate the differences in muscle fatigue. The dual electrode configuration causes the muscle tissue to fatigue quicker.

The gastrointestinal electrical mapping suite (GEMS): software for analyzing and visualizing high-resolution (multi-electrode) recordings in spatiotemporal detail.

BACKGROUND: Gastrointestinal contractions are controlled by an underlying bioelectrical activity. High-resolution spatiotemporal electrical mapping has become an important advance for investigating gastrointestinal electrical behaviors in health and motility disorders. However, research progress has been constrained by the low efficiency of the data analysis tasks. This work introduces a new efficient software package: GEMS (Gastrointestinal Electrical Mapping Suite), for analyzing and visualizing high-resolution multi-electrode gastrointestinal mapping data in spatiotemporal detail. RESULTS: GEMS incorporates a number of new and previously validated automated analytical and visualization methods into a coherent framework coupled to an intuitive and user-friendly graphical user interface. GEMS is implemented using MATLAB®, which combines sophisticated mathematical operations and GUI compatibility. Recorded slow wave data can be filtered via a range of inbuilt techniques, efficiently analyzed via automated event-detection and cycle clustering algorithms, and high quality isochronal activation maps, velocity field maps, amplitude maps, frequency (time interval) maps and data animations can be rapidly generated. Normal and dysrhythmic activities can be analyzed, including initiation and conduction abnormalities. The software is distributed free to academics via a community user website and forum (http://sites.google.com/site/gimappingsuite). CONCLUSIONS: This software allows for the rapid analysis and generation of critical results from gastrointestinal high-resolution electrical mapping data, including quantitative analysis and graphical outputs for qualitative analysis. The software is designed to be used by non-experts in data and signal processing, and is intended to be used by clinical researchers as well as physiologists and bioengineers. The use and distribution of this software package will greatly accelerate efforts to improve the understanding of the causes and clinical consequences of gastrointestinal electrical disorders, through high-resolution electrical mapping.

Abnormal initiation and conduction of slow-wave activity in gastroparesis, defined by high-resolution electrical mapping.

BACKGROUND & AIMS: Interstitial cells of Cajal (ICC) generate slow waves. Disrupted ICC networks and gastric dysrhythmias are each associated with gastroparesis. However, there are no data on the initiation and propagation of slow waves in gastroparesis because research tools have lacked spatial resolution. We applied high-resolution electrical mapping to quantify and classify gastroparesis slow-wave abnormalities in spatiotemporal detail. METHODS: Serosal high-resolution mapping was performed using flexible arrays (256 electrodes; 36 cm(2)) at stimulator implantation in 12 patients with diabetic or idiopathic gastroparesis. Data were analyzed by isochronal mapping, velocity and amplitude field mapping, and propagation animation. ICC numbers were determined from gastric biopsy specimens. RESULTS: Mean ICC counts were reduced in patients with gastroparesis (2.3 vs 5.4 bodies/field; P < .001). Slow-wave abnormalities were detected by high-resolution mapping in 11 of 12 patients. Several new patterns were observed and classified as abnormal initiation (10/12; stable ectopic pacemakers or diffuse focal events; median, 3.3 cycles/min; range, 2.1-5.7 cycles/min) or abnormal conduction (7/10; reduced velocities or conduction blocks; median, 2.9 cycles/min; range, 2.1-3.6 cycles/min). Circumferential conduction emerged during aberrant initiation or incomplete block and was associated with velocity elevation (7.3 vs 2.9 mm s(-1); P = .002) and increased amplitudes beyond a low base value (415 vs 170 µV; P = .002). CONCLUSIONS: High-resolution mapping revealed new categories of abnormal human slow-wave activity. Abnormalities of slow-wave initiation and conduction occur in gastroparesis, often at normal frequency, which could be missed by tests that lack spatial resolution. Irregular initiation, aberrant conduction, and low amplitude activity could contribute to the pathogenesis of gastroparesis.

An image-based model of atrial muscular architecture: effects of structural anisotropy on electrical activation.

BACKGROUND: Computer models that capture key features of the heterogeneous myofiber architecture of right and left atria and interatrial septum provide a means of investigating the mechanisms responsible for atrial arrhythmia. The data necessary to implement such models have not previously been available. The aims of this study were to characterize surface geometry and myofiber architecture throughout the atrial chambers and to investigate the effects of this structure on atrial activation. METHODS AND RESULTS: Atrial surface geometry and myofiber orientations were reconstructed in 3D at 50×50×50-µm(3) resolution from serial images acquired throughout the sheep atrial chambers. Myofiber orientations were determined by Eigen-analysis of the structure tensor. These data have been incorporated into an anatomic model that provides the first quantitative representation of myofiber architecture throughout the atrial chambers. By simulating activation on this 3D structure, we have confirmed the roles of specialized myofiber tracts such as the crista terminalis, pectinate muscles, and the Bachman bundle on the spread of activation from the sinus node. We also demonstrate how the complex myocyte arrangement in the posterior left atrium contributes to activation time dispersion adjacent to the pulmonary veins and increased vulnerability to rhythm disturbance generated by ectopic stimuli originating in the pulmonary vein sleeves. CONCLUSIONS: We have developed a structurally detailed, image-based model of atrial anatomy that provides deeper understanding of the role that myocyte architecture plays in normal and abnormal atrial electric function.

An improved method for the estimation and visualization of velocity fields from gastric high-resolution electrical mapping.

High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented.

A preliminary model of gastrointestinal electromechanical coupling.

Gastrointestinal (GI) motility is coordinated by several cooperating mechanisms, including electrical slow wave activity, the enteric nervous system (ENS), and other factors. Slow waves generated in interstitial cells of Cajal (ICC) depolarize smooth muscle cells (SMC), generating basic GI contractions. This unique electrical coupling presents an added layer of complexity to GI electromechanical models, and a current barrier to further progress is the lack of a framework for ICC-SMC-contraction coupling. In this study, an initial framework for the electromechanical coupling was developed in a 2-D model. At each solution step, the slow wave propagation was solved first and [Ca(2+)](i) in the SMC model was related to a Ca(2+)-tension-extension relationship to simulate active contraction. With identification of more GI-specific constitutive laws and material parameters, the ICC-SMC-contraction approach may underpin future GI electromechanical models of health and disease states.

A stochastic multi-scale model of electrical function in normal and depleted ICC networks.

Multi-scale modeling has become a productive strategy for quantifying interstitial cells of Cajal (ICC) network structure-function relationships, but the lack of large-scale ICC network imaging data currently limits modeling progress. The single normal equation simulation (SNESIM) algorithm was utilized to generate realistic virtual images of small real wild-type (WT) and 5-HT(2B)-receptor knockout (Htr2b(-/-)) mice ICC networks. Two metrics were developed to validate the performance of the algorithm: 1) network density, which is the proportion of ICC in the tissue; and 2) connectivity, which reflects the degree of connectivity of the ICC network. Following validation, the SNESIM algorithm was modified to allow variation in the degree of ICC network depletion. ICC networks from a range of depletion severities were generated, and the electrical activity over these networks was simulated. The virtual ICC networks generated by the original SNESIM algorithm were similar to that of their real counterparts. The electrical activity simulations showed that the maximum current density magnitude increased as the network density increased. In conclusion, the SNESIM algorithm is an effective tool for generating realistic virtual ICC networks. The modified SNESIM algorithm can be used with simulation techniques to quantify the physiological consequences of ICC network depletion at various physical scales.

Biophysically based modeling of the interstitial cells of cajal: current status and future perspectives.

Gastrointestinal motility research is progressing rapidly, leading to significant advances in the last 15 years in understanding the cellular mechanisms underlying motility, following the discovery of the central role played by the interstitial cells of Cajal (ICC). As experimental knowledge of ICC physiology has expanded, biophysically based modeling has become a valuable tool for integrating experimental data, for testing hypotheses on ICC pacemaker mechanisms, and for applications in in silico studies including in multiscale models. This review is focused on the cellular electrophysiology of ICC. Recent evidence from both experimental and modeling domains have called aspects of the existing pacemaker theories into question. Therefore, current experimental knowledge of ICC pacemaker mechanisms is examined in depth, and current theories of ICC pacemaking are evaluated and further developed. Existing biophysically based ICC models and their physiological foundations are then critiqued in light of the recent advances in experimental knowledge, and opportunities to improve these models are identified. The review concludes by examining several potential clinical applications of biophysically based ICC modeling from the subcellular through to the organ level, including ion channelopathies and ICC network degradation.

Automated gastric slow wave cycle partitioning and visualization for high-resolution activation time maps.

High-resolution (HR) multi-electrode mapping has become an important technique for evaluating gastrointestinal (GI) slow wave (SW) behaviors. However, the application and uptake of HR mapping has been constrained by the complex and laborious task of analyzing the large volumes of retrieved data. Recently, a rapid and reliable method for automatically identifying activation times (ATs) of SWs was presented, offering substantial efficiency gains. To extend the automated data-processing pipeline, novel automated methods are needed for partitioning identified ATs into their propagation cycles, and for visualizing the HR spatiotemporal maps. A novel cycle partitioning algorithm (termed REGROUPS) is presented. REGROUPS employs an iterative REgion GROwing procedure and incorporates a Polynomial-surface-estimate Stabilization step, after initiation by an automated seed selection process. Automated activation map visualization was achieved via an isochronal contour mapping algorithm, augmented by a heuristic 2-step scheme. All automated methods were collectively validated in a series of experimental test cases of normal and abnormal SW propagation, including instances of patchy data quality. The automated pipeline performance was highly comparable to manual analysis, and outperformed a previously proposed partitioning approach. These methods will substantially improve the efficiency of GI HR mapping research.

Electropathological substrate detection of persistent atrial fibrillation--a novel method to analyze unipolar electrograms of noncontact mapping.

Radiofrequency catheter ablation as a curative method for atrial fibrillation (AF) has become increasingly popular. Patients with paroxysmal AF have been treated by catheter ablation with great success, but so far this treatment has been less effective for patients with persistent AF. Usually there are multiple triggers or substrates during persistent AF and their exact locations are unclear. On the other hand, the non-contact mapping system (Ensite 3000, St Jude Medical) producing thousands of virtual endocardial electrograms, has gradually become accepted as a powerful tool to use on patients before and after ablation. Effective mathematical tools to detect the substrates of AF from unipolar electrograms produced by the non-contact mapping are few, though many methods are available for performing this task with bipolar electrograms. In this work, we introduce for the first time a simple and efficient approach to automatically and systematically determine the substrate of persistent AF in order to guide catheter ablation via the non-contact mapping.

Improved signal processing techniques for the analysis of high resolution serosal slow wave activity in the stomach.

High resolution electrical mapping of slow waves on the stomach serosa has improved our understanding of gastric electrical activity in normal and diseased states. In order to assess the signals acquired from high resolution mapping, a robust framework is required. Our framework is semi-automated and allows for rapid processing, analysis and interpretation of slow waves via qualitative and quantitative measures including isochronal activation time mapping, and velocity and amplitude mapping. Noise removal techniques were validated for raw recorded signals, where three filters were evaluated for baseline drift removal and three filters for removal of high frequency interference. For baseline drift removal, the Gaussian moving median filter was most effective, while for eliminating high frequency interference the Savitzky Golay filter was the most effective. Methods for assessing slow wave velocity and amplitude were investigated. To estimate slow wave velocity, a finite difference approach with interpolation and smoothing was used. To evaluate the slow wave amplitude and width, a peak and trough method based on Savitzky Golay derivative filters was used. Together, these methods constitute a significantly improved framework for analyzing gastric high resolution mapping data.

A framework for the online analysis of multi-electrode gastric slow wave recordings.

High resolution mapping of electrical activity is becoming an important technique for analysing normal and dysrhythmic gastrointestinal (GI) slow wave activity. Several methods are used to extract meaningful information from the large quantities of data obtained, however, at present these methods can only be used offline. Thus, all analysis currently performed is retrospective and done after the recordings have finished. Limited information about the quality or characteristics of the data is therefore known while the experiments take place. Building on these offline analysis methods, an online implementation has been developed that identifies and displays slow wave activations working alongside an existing recording system. This online system was developed by adapting existing and novel signal processing techniques and linking these to a new user interface to present the extracted information. The system was tested using high resolution porcine data, and will be applied in future high resolution mapping studies allowing researchers to respond in real time to experimental observations.

Quantification of velocity anisotropy during gastric electrical arrhythmia.

In this study, an automated algorithm was developed to identify the arrhythmic gastric slow wave activity that was recorded using high-resolution mapping technique. The raw signals were processed with a Savitzky-Golay filter, and the slow wave activation times were identified using a threshold-varying method and grouped using a region-growing method. Slow wave amplitudes and velocities were calculated for all cycles. Arrhythmic events were identified when the orientation of a slow wave at an electrode exceeded the 95% confidence interval of the averaged orientation of several normal cycles. A second selection criterion was further developed to identify the arrhythmic events by an anisotropy ratio. In both pig and human studies, arrhythmias were associated with the emergence of circumferential velocity components and higher amplitudes.

Mapping small intestine bioelectrical activity using high-resolution printed-circuit-board electrodes.

In this study, novel methods were developed for the in-vivo high-resolution recording and analysis of small intestine bioelectrical activity, using flexible printed-circuit-board (PCB) electrode arrays. Up to 256 simultaneous recordings were made at multiple locations along the porcine small intestine. Data analysis was automated through the application and tuning of the Falling-Edge Variable-Threshold algorithm, achieving 92% sensitivity and a 94% positive-predictive value. Slow wave propagation patterns were visualized through the automated generation of animations and isochronal maps. The methods developed and validated in this study are applicable for use in humans, where future studies will serve to improve the clinical understanding of small intestine motility in health and disease.

Multiscale modeling of gastrointestinal electrophysiology and experimental validation.

Normal gastrointestinal (GI) motility results from the coordinated interplay of multiple cooperating mechanisms, both intrinsic and extrinsic to the GI tract. A fundamental component of this activity is an omnipresent electrical activity termed slow waves, which is generated and propagated by the interstitial cells of Cajal (ICCs). The role of ICC loss and network degradation in GI motility disorders is a significant area of ongoing research. This review examines recent progress in the multiscale modeling framework for effectively integrating a vast range of experimental data in GI electrophysiology, and outlines the prospect of how modeling can provide new insights into GI function in health and disease. The review begins with an overview of the GI tract and its electrophysiology, and then focuses on recent work on modeling GI electrical activity, spanning from cell to body biophysical scales. Mathematical cell models of the ICCs and smooth muscle cell are presented. The continuum framework of monodomain and bidomain models for tissue and organ models are then considered, and the forward techniques used to model the resultant body surface potential and magnetic field are discussed. The review then outlines recent progress in experimental support and validation of modeling, and concludes with a discussion on potential future research directions in this field.