Characterization of gastric electrical activity using magnetic field measurements: a simulation study

Computational models of autonomic regulation in gastric motility: Progress, challenges, and future directions

The stomach is extensively innervated by the vagus nerve and the enteric nervous system. The mechanisms through which this innervation affects gastric motility are being unraveled, motivating the first concerted steps towards the incorporation autonomic regulation into computational models of gastric motility. Computational modeling has been valuable in advancing clinical treatment of other organs, such as the heart. However, to date, computational models of gastric motility have made simplifying assumptions about the link between gastric electrophysiology and motility. Advances in experimental neuroscience mean that these assumptions can be reviewed, and detailed models of autonomic regulation can be incorporated into computational models. This review covers these advances, as well as a vision for the utility of computational models of gastric motility. Diseases of the nervous system, such as Parkinson’s disease, can originate from the brain-gut axis and result in pathological gastric motility. Computational models are a valuable tool for understanding the mechanisms of disease and how treatment may affect gastric motility. This review also covers recent advances in experimental neuroscience that are fundamental to the development of physiology-driven computational models. A vision for the future of computational modeling of gastric motility is proposed and modeling approaches employed for existing mathematical models of autonomic regulation of other gastrointestinal organs and other organ systems are discussed.

Effects of magnetogastrography sensor configurations in tracking slow wave propagation

Magnetogastrography (MGG) is a non-invasive method of assessing gastric slow waves (SWs) by recording the resultant magnetic fields. MGG can capture both SW frequency and propagation, and identify SW dysrhythmias that are associated with motility disorders. However, the impact of the restricted spatial coverage and sensor density on SW propagation tracking performance is unknown. This study simulated MGG using multiple anatomically specific torso geometries and two realistic SW propagation patterns to determine the effect of different sensor configurations on tracking SW propagation. The surface current density mapping and center-of-gravity tracking methods were used to compare four magnetometer array configurations: a reference system currently used in GI research and three hypothetical higher density and coverage arrays. SW propagation patterns identified with two hypothetical arrays (with coverage over at least the anterior of the torso) correlated significantly higher with simulated realistic 3 cycle-per-minute SW activity than the reference array (p = 0.016, p = 0.005). Furthermore, results indicated that most of the magnetic fields that contribute to the performance of SW propagation tracking were located on the anterior of the torso as further increasing the coverage did not significantly increase performance. A 30% decrease in sensor spacing within the same spatial coverage of the reference array also significantly increased correlation values by approximately 0.50 when the signal-to-noise ratio was 5 dB. This study provides evidence that higher density and coverage sensor layouts will improve the utility of MGG. Further work is required to investigate optimum sensor configurations across larger anatomical variations and other SW propagation patterns.

Characterization of Electrophysiological Propagation by Multichannel Sensors

OBJECTIVE

The propagation of electrophysiological activity measured by multichannel devices could have significant clinical implications. Gastric slow waves normally propagate along longitudinal paths that are evident in recordings of serosal potentials and transcutaneous magnetic fields. We employed a realistic model of gastric slow wave activity to simulate the transabdominal magnetogastrogram (MGG) recorded in a multichannel biomagnetometer and to determine characteristics of electrophysiological propagation from MGG measurements.

METHODS

Using MGG simulations of slow wave sources in a realistic abdomen (both superficial and deep sources) and in a horizontally-layered volume conductor, we compared two analytic methods (second-order blind identification, SOBI and surface current density, SCD) that allow quantitative characterization of slow wave propagation. We also evaluated the performance of the methods with simulated experimental noise. The methods were also validated in an experimental animal model.

RESULTS

Mean square errors in position estimates were within 2 cm of the correct position, and average propagation velocities within 2 mm/s of the actual velocities. SOBI propagation analysis outperformed the SCD method for dipoles in the superficial and horizontal layer models with and without additive noise. The SCD method gave better estimates for deep sources, but did not handle additive noise as well as SOBI.

CONCLUSION

SOBI-MGG and SCD-MGG were used to quantify slow wave propagation in a realistic abdomen model of gastric electrical activity.

SIGNIFICANCE

These methods could be generalized to any propagating electrophysiological activity detected by multichannel sensor arrays.

Mapping and modeling gastrointestinal bioelectricity: from engineering bench to bedside

A key discovery in gastrointestinal motility has been the central role played by interstitial cells of Cajal (ICC) in generating electrical slow waves that coordinate contractions. Multielectrode mapping and multiscale modeling are two emerging interdisciplinary strategies now showing translational promise to investigate ICC function, electrophysiology, and contractions in the human gut.

Effect of Body Mass Index on the sensitivity of Magnetogastrogram and Electrogastrogram

AIM

Gastric disorders affect the gastric slow wave. The cutaneous electrogastrogram (EGG) evaluates the electrical potential of the slow wave but is limited by the volume conduction properties of the abdominal wall. The magnetogastrogram (MGG) evaluates the gastric magnetic field activity and is not affected as much by the volume conductor properties of the abdominal wall. We hypothesized that MGG would not be as sensitive to body mass index as EGG.

METHODS

We simultaneously recorded gastric slow wave signals with mucosal electrodes, a Superconducting Quantum Interference Device magnetometer (SQUID) and cutaneous electrodes before and after a test meal. Data were recorded from representative pools of human volunteers. The sensitivity of EGG and MGG was compared to the body mass index and waist circumference of volunteers.

RESULTS

The study population had good linear regression of their Waist circumference (Wc) and Body Mass Index (BMI) (regression coefficient, R=0.9). The mean BMI of the study population was 29.2 ±1.8 kgm^-2 and mean Wc 35.7±1.4 inch. We found that while subjects with BMI≥25 showed significant reduction in post-prandial EGG sensitivity, only subjects with BMI≥30 showed similar reduction in post-prandial MGG sensitivity. Sensitivity of SOBI "EGG and MGG" was not affected by the anthropometric measurements.

CONCLUSIONS

Compared to electrogastrogram, the sensitivity of the magnetogastrogram is less affected by changes in body mass index and waist circumference. The use of Second Order Blind Identification (SOBI) increased the sensitivity of EGG and MGG recordings and was not affected by BMI or waist circumference.

Toward the virtual stomach: progress in multiscale modeling of gastric electrophysiology and motility

Experimental progress in investigating normal and disordered gastric motility is increasingly being complimented by sophisticated multiscale modeling studies. Mathematical modeling has become a valuable tool in this effort, as there is an ever-increasing need to gain an integrative and quantitative understanding of how physiological mechanisms achieve coordinated functions across multiple biophysical scales. These interdisciplinary efforts have been particularly notable in the area of gastric electrophysiology, where they are beginning to yield a comprehensive and integrated in silico organ modeling framework, or 'virtual stomach'. At the cellular level, a number of biophysically based mathematical cell models have been developed, and these are now being applied in areas including investigations of gastric electrical pacemaker mechanisms, smooth muscle electrophysiology, and electromechanical coupling. At the tissue level, micro-structural models are being creatively developed and employed to investigate clinically significant questions, such as the functional effects of ICC degradation on gastrointestinal (GI) electrical activation. At the organ level, high-resolution electrical mapping and modeling studies are combined to provide improved insights into normal and dysrhythmic gastric electrical activation. These efforts are also enabling detailed forward and inverse modeling studies at the 'whole body' level, with implications for diagnostic techniques for gastric dysrhythmias. These recent advances, together with several others highlighted in this review, collectively demonstrate a powerful trend toward applying mathematical models to effectively investigate structure-function relationships and overcome multiscale challenges in basic and clinical GI research.

Reconstruction of multiple gastric electrical wave fronts using potential-based inverse methods

One approach for non-invasively characterizing gastric electrical activity, commonly used in the field of electrocardiography, involves solving an inverse problem whereby electrical potentials on the stomach surface are directly reconstructed from dense potential measurements on the skin surface. To investigate this problem, an anatomically realistic torso model and an electrical stomach model were used to simulate potentials on stomach and skin surfaces arising from normal gastric electrical activity. The effectiveness of the Greensite-Tikhonov or the Tikhonov inverse methods were compared under the presence of 10% Gaussian noise with either 84 or 204 body surface electrodes. The stability and accuracy of the Greensite-Tikhonov method were further investigated by introducing varying levels of Gaussian signal noise or by increasing or decreasing the size of the stomach by 10%. Results showed that the reconstructed solutions were able to represent the presence of propagating multiple wave fronts and the Greensite-Tikhonov method with 204 electrodes performed best (correlation coefficients of activation time: 90%; pacemaker localization error: 3 cm). The Greensite-Tikhonov method was stable with Gaussian noise levels up to 20% and 10% change in stomach size. The use of 204 rather than 84 body surface electrodes improved the performance; however, for all investigated cases, the Greensite-Tikhonov method outperformed the Tikhonov method.

Biomagnetic and bioelectric detection of gastric slow wave activity in normal human subjects--a correlation study

We measured gastric slow wave activity simultaneously with a Superconducting Quantum Interference Device (SQUID) magnetometer, mucosal electrodes and cutaneous electrodes in 18 normal human subjects (11 women and 7 men). We processed signals with Fourier spectral analysis and SOBI blind-source separation techniques. We observed a high waveform correlation between the mucosal electromyogram (EMG) and multichannel SQUID magnetogastrogram (MGG). There was a lower waveform correlation between the mucosal EMG and cutaneous electrogastrogram (EGG), but the correlation improved with the application of SOBI. There was also a high correlation between the frequency of the electrical activity recorded in the MGG and in mucosal electrodes (r = 0.97). We concluded that SQUID magnetometers noninvasively record gastric slow wave activity that is highly correlated with the activity recorded by invasive mucosal electrodes.

Influence of body parameters on gastric bioelectric and biomagnetic fields in a realistic volume conductor

Electrogastrograms (EGG) and magnetogastrograms (MGG) provide two complementary methods for non-invasively recording electric or magnetic fields resulting from gastric electrical slow wave activity. It is known that EGG signals are relatively weak and difficult to reliably record while magnetic fields are, in theory, less attenuated by the low-conductivity fat layers present in the body. In this paper, we quantified the effects of fat thickness and conductivity values on resultant magnetic and electric fields using anatomically realistic torso models and trains of dipole sources reflecting recent experimental results. The results showed that when the fat conductivity was increased, there was minimal change in both potential and magnetic fields. However, when the fat conductivity was reduced, the magnetic fields were largely unchanged, but electric potentials had a significant change in patterns and amplitudes. When the thickness of the fat layer was increased by 30 mm, the amplitude of the magnetic fields decreased 10% more than potentials but magnetic field patterns were changed about four times less than potentials. The ability to localize the underlying sources from the magnetic fields using a surface current density measure was altered by less than 2 mm when the fat layer was increased by 30 mm. In summary, results confirm that MGG provides a favorable method over EGG when there are uncertain levels of fat thickness or conductivity.

Reconstruction of multiple gastric electrical wave fronts using potential based inverse methods

The ability to reconstruct gastric electrical activity (termed slow waves) non-invasively from potential field measurements made on the torso surface would be a useful tool to aid in the clinical diagnosis of a number of gastric disorders. This is mathematically akin to the inverse problem of electrocardiography. To investigate this problem, an anatomically realistic torso model and an electrical stomach model were used to simulate potentials on the stomach and skin surfaces arising from normal gastric electrical activity. Gaussian noise was added to the torso potentials to represent experimental signal noise. The stomach potentials, activation profiles and gastric slow wave velocities were inversely reconstructed from the torso potentials, using the Tikhonov-Greensite inverse method with regularisation determined using an L-curve method. The inverse solutions were then compared with the known input solutions. The reconstructed solutions were able to represent the presence of multiple propagating wave fronts, determine average activation times to within 5 s and average velocities to within 1 mm/s. When more virtual body surface electrodes were used in the inverse calculations, the accuracy of the reconstructed activity improved.

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.

Origin, propagation and regional characteristics of porcine gastric slow wave activity determined by high-resolution mapping

BACKGROUND

The pig is a popular model for gastric electrophysiology studies. However, its normal baseline gastric activity has not been well characterized. High-resolution (HR) mapping has recently enabled an accurate description of human and canine gastric slow wave activity, and was employed here to define porcine gastric slow wave activity.

METHODS

Fasted pigs underwent HR mapping following anesthesia and laparotomy. Flexible printed-circuit-board arrays were used (160-192 electrodes; spacing 7.62 mm). Anterior and posterior surfaces were mapped simultaneously. Activation times, velocities, amplitudes and frequencies were calculated, and regional differences evaluated.

KEY RESULTS

Mean slow wave frequency was 3.22 ± 0.23 cpm. Slow waves propagated isotropically from the pacemaker site (greater curvature, mid-fundus). Pacemaker activity was of higher velocity (13.3 ± 1.0 mm s(-1)) and greater amplitude (1.3 ± 0.2 mV) than distal fundal activity (9.0 ± 0.6 mm s(-1), 0.9 ± 0.1 mV; P < 0.05). Velocities and amplitudes were similar in the distal fundus, proximal corpus (8.4 ± 0.8 mm s(-1), 1.0 ± 0.1 mV), distal corpus (8.3 ± 0.8 mm s(-1), 0.9 ± 0.2 mV) and antrum (6.8 ± 0.6 mm s(-1), 1.1 ± 0.2 mV). Activity was continuous across the anterior and posterior gastric surfaces.

CONCLUSIONS & INFERENCES

This study has quantified normal porcine gastric slow wave activity at HR during anesthesia and laparotomy. The pacemaker region was associated with high-amplitude, high-velocity slow wave activity compared to the activity in the rest of the stomach. The increase in distal antral slow wave velocity and amplitude previously described in canines and humans is not observed in the pig. Investigators should be aware of these inter-species differences.