Principles and clinical methods of body surface gastric mapping: Technical review.

BACKGROUND AND PURPOSE: Chronic gastric symptoms are common, however differentiating specific contributing mechanisms in individual patients remains challenging. Abnormal gastric motility is present in a significant subgroup, but reliable methods for assessing gastric motor function in clinical practice are lacking. Body surface gastric mapping (BSGM) is a new diagnostic aid, employs multi-electrode arrays to measure and map gastric myoelectrical activity non-invasively in high resolution. Clinical adoption of BSGM is currently expanding following studies demonstrating the ability to achieve specific patient subgrouping, and subsequent regulatory clearances. An international working group was formed in order to standardize clinical BSGM methods, encompassing a technical group developing BSGM methods and a clinical advisory group. The working group performed a technical literature review and synthesis focusing on the rationale, principles, methods, and clinical applications of BSGM, with secondary review by the clinical group. The principles and validation of BSGM were evaluated, including key advances achieved over legacy electrogastrography (EGG). Methods for BSGM were reviewed, including device design considerations, patient preparation, test conduct, and data processing steps. Recent advances in BSGM test metrics and reference intervals are discussed, including four novel metrics, being the 'principal gastric frequency', BMI-adjusted amplitude, Gastric Alimetry Rhythm Index™, and fed: fasted amplitude ratio. An additional essential element of BSGM has been the introduction of validated digital tools for standardized symptom profiling, performed simultaneously during testing. Specific phenotypes identifiable by BSGM and the associated symptom profiles were codified with reference to pathophysiology. Finally, knowledge gaps and priority areas for future BSGM research were also identified by the working group.

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.

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.

Falling-edge, variable threshold (FEVT) method for the automated detection of gastric slow wave events in high-resolution serosal electrode recordings.

High resolution (HR) multi-electrode mapping is increasingly being used to evaluate gastrointestinal slow wave behaviors. To create the HR activation time (AT) maps from gastric serosal electrode recordings that quantify slow wave propagation, it is first necessary to identify the AT of each individual slow wave event. Identifying these ATs has been a time consuming task, because there has previously been no reliable automated detection method. We have developed an automated AT detection method termed falling-edge, variable threshold (FEVT) detection. It computes a detection signal transform to accentuate the high 'energy' content of the falling edges in the serosal recording, and uses a running median estimator of the noise to set the time-varying detection threshold. The FEVT method was optimized, validated, and compared to other potential algorithms using in vivo HR recordings from a porcine model. FEVT properly detects ATs in a wide range of waveforms, making its performance substantially superior to the other methods, especially for low signal-to-noise ratio (SNR) recordings. The algorithm offered a substantial time savings (>100 times) over manual-marking whilst achieving a highly satisfactory sensitivity (0.92) and positive-prediction value (0.89).

Detection of small bowel slow-wave frequencies from noninvasive biomagnetic measurements.

We report a novel method for identifying the small intestine electrical activity slow-wave frequencies (SWFs) from noninvasive biomagnetic measurements. Superconducting quantum interference device magnetometer measurements are preprocessed to remove baseline drift and high-frequency noise. Subsequently, the underlying source signals are separated using the well-known second-order blind identification (SOBI) algorithm. A simple classification scheme identifies and assigns some of the SOBI components to a section of small bowel. SWFs were clearly identified in 10 out of 12 test subjects to within 0.09-0.25 cycles per minute. The method is sensitive at the 40.3 %-55.9 % level, while false positive rates were 0 %-8.6 %. This technique could potentially be used to help diagnose gastrointestinal ailments and obviate some exploratory surgeries.

Surface current density mapping for identification of gastric slow wave propagation.

The magnetogastrogram (MGG) records clinically relevant parameters of the electrical slow wave of the stomach noninvasively. Besides slow wave frequency, gastric slow wave propagation velocity is a potentially useful clinical indicator of the state of health of gastric tissue, but it is a difficult parameter to determine from noninvasive bioelectric or biomagnetic measurements. We present a method for computing the surface current density from multichannel MGG recordings that allows computation of the propagation velocity of the gastric slow wave. A moving dipole source model with hypothetical as well as realistic biomagnetometer parameters demonstrates that while a relatively sparse array of magnetometer sensors is sufficient to compute a single average propagation velocity, more detailed information about spatial variations in propagation velocity requires higher density magnetometer arrays. Finally, the method is validated with simultaneous MGG and serosal electromyography measurements in a porcine subject.

Comparison of conventional filtering and independent component analysis for artifact reduction in simultaneous gastric EMG and magnetogastrography from porcines.

In this study, we perform a comparative study of independent component analysis (ICA) and conventional filtering (CF) for the purpose of artifact reduction from simultaneous gastric EMG and magnetogastrography (MGG). EMG/MGG data were acquired from ten anesthetized pigs by obtaining simultaneous recordings using serosal electrodes (EMG) as well as with a superconducting quantum interference device biomagnetometer (MGG). The analysis of MGG waveforms using ICA and CF indicates that ICA is superior to the CF method in its ability to extract respiration and cardiac artifacts from MGG recordings. A signal frequency analysis of ICA- and CF-processed data was also undertaken using waterfall plots, and it was determined that the two methods produce qualitatively comparable results. Through the use of simultaneous EMG/MGG, we were able to demonstrate the accuracy and trustworthiness of our results by comparison and cross-validation within the framework of a porcine model.

Noninvasive assessment of the effects of glucagon on the gastric slow wave.

Hyperglycemic effects on the gastric slow wave are not well understood, and no studies have examined the effects that hyperglycemia has on gastric slow wave magnetic fields. We recorded multichannel magnetogastrograms (MGGs) before and after intravenous administration of glucagon and subsequent modest hyperglycemia in 20 normal volunteers. Normal slow waves were evident in baseline MGG recordings from all 20 subjects, but within 15 min after glucagon had been given, we noted significant effects on MGG signals. In addition to an overall decrease in the slow wave frequency from 2.9 +/- 0.5 cycles per min (cpm) to 2.2 +/- 0.1 cpm (P < 0.05), we observed significant changes in the number and range of spectral peaks recorded. Furthermore, the propagation velocity determined from surface current density maps computed from the multichannel MGG decreased significantly (7.1 +/- 0.8 mm/s to 5.0 +/- 0.3 mm/s, P < 0.05). This is the first study of biomagnetic effects of hyperglycemia in normal subjects. Our results suggest that the analysis of the MGG provides parameter quantification for gastric electrical activity specific to and characteristic of slow wave abnormalities associated with increased serum glucose by injection of glucagon.

Biomagnetic investigation of injury currents in rabbit intestinal smooth muscle during mesenteric ischemia and reperfusion.

A noninvasive, sensitive, and specific method of detecting mesenteric ischemia would be of great use in reducing the morbidity and mortality with which it is associated. Acute lesions in polarized electrically coupled tissues lead to injury currents driven by the transmembrane resting potential gradient. These injury currents are an effective indicator of pathophysiology. The presence of near-DC injury currents in rabbit intestinal smooth muscle has already been demonstrated using a Superconducting quantum interference device (SQUID), and the aim of this study was to evaluate the effect of arterial reperfusion upon these currents. We exteriorized the small bowel of 14 New Zealand white rabbits and placed a remotely operated vascular occluder around the distal most artery supplying a 3-in segment of the jejunum. Experiments were conducted in three groups, i.e., control (n=3), ischemia (n=6), and reperfusion following ischemia (n=5). The subject's position was modulated in and out of the biological field detection range of a SQUID magnetometer using a lift constructed of nonmagnetic material. The changes in magnetic field amplitude were 9.3 and 31.01% for the control and ischemia groups, respectively. The reperfusion group first exhibited a decrease of 17.35% from the pre-ischemic to the ischemic period, followed by an increase of 13.88% of the ischemic value after reestablishing perfusion. In conclusion, injury currents in GI smooth muscle that appear during ischemia are reduced to near-pre-ischemic levels during reperfusion.

An integrative software package for gastrointestinal biomagnetic data acquisition and analysis using SQUID magnetometers.

The study of bioelectric and biomagnetic activity in the human gastrointestinal (GI) tract is of great interest in clinical research due to the proven possibility to detect pathological conditions thereof from electric and magnetic field recordings. The magnetogastrogram (MGG) and magnetoenterogram (MENG) can be recorded using superconducting quantum interference device (SQUID) magnetometers, which are the most sensitive magnetic flux-to-voltage converters currently available. To address the urgent need for powerful acquisition and analysis software tools faced by many researchers and clinicians in this important area of investigation, an integrative and modular computer program was developed for the acquisition, processing and analysis of GI SQUID signals. In addition to a robust hardware implementation for efficient data acquisition, a number of signal processing and analysis modules were developed to serve in a variety of both clinical procedures and scientific investigations. Implemented software features include data processing and visualization, waterfall plots of signal frequency spectra as well as spatial maps of GI signal frequencies. Moreover, a software tool providing powerful 3D visualizations of GI signals was created using realistic models of the human torso and internal organs.

Magnetogastrographic detection of gastric electrical response activity in humans.

The detection and characterization of gastric electrical activity has important clinical applications, including the early diagnosis of gastric diseases in humans. In mammals, this phenomenon has two important features: an electrical control activity (ECA) that manifests itself as an electric slow wave (with a frequency of 3 cycles per minute in humans) and an electrical response activity (ERA) that is characterized by spiking potentials during the plateau phase of the ECA. Whereas the ECA has been recorded in humans both invasively and non-invasively (magnetogastrography-MGG), the ERA has never been detected non-invasively in humans before. In this paper, we report on our progress towards the non-invasive detection of ERA from the human stomach using a procedure that involves the application of principal component analysis to MGG recordings, which were acquired in our case from ten normal human patients using a Superconducting QUantum Interference Device (SQUID) magnetometer. Both pre- and post-prandial recordings were acquired for each patient and 20 min of recordings (10 min of pre-prandial and 10 min of post-prandial data) were analysed for each patient. The mean percentage of ECA slow waves that were found to exhibit spikes of suspected ERA origin was 41% and 61% for pre- and post-prandial recordings, respectively, implying a 47% ERA increase post-prandially (P < 0.0001 at a 95% confidence level). The detection of ERA in humans is highly encouraging and points to the possible use of non-invasive ERA recordings as a valuable tool for the study of human gastric disorders.

Separation of gastric electrical control activity from simultaneous MGG/EGG recordings using independent component analysis.

Spatiotemporal parameters of gastric electrical control activity such as its amplitude, direction and propagation velocity are physiological parameters of distinctive clinical interest due to their potential use for differentiating between the healthy and diseased states of the human stomach. Whereas their time evolution is relatively well behaved in the case of healthy subjects, significant deviations from normal have been observed in patients suffering from a number of gastric diseases such as gastroparesis and gastropathy. For this reason, monitoring ECA parameters noninvasively may offer a useful test for the presence of such diseases whose diagnosis remains problematic. Here, we describe a method for computing ECA direction and orientation from simultaneous, noninvasive magnetogastrographic (MGG) and electrogastrographic (EGG) recordings. We demonstrate how independent component analysis and standard frequency analysis methods can be used to predict the locations and orientations of gastric current dipoles from MGG/EGG data. We compare our MGG-based dipole parameters to analogous ones obtained from simultaneous EGG recordings within the experimental framework of a human model. We find that magnetic recordings are superior in their ability to portray the underlying physiology of the stomach.

Artifact reduction in magnetogastrography using fast independent component analysis.

The analysis of magnetogastrographic (MGG) signals has been limited to epochs of data with limited interference from extraneous signal components that are often present and may even dominate MGG data. Such artifacts can be of both biological (cardiac, intestinal and muscular activities, motion artifacts, etc) and non-biological (environmental noise) origin. Conventional methods-such as Butterworth and Tchebyshev filters-can be of great use, but there are many disadvantages associated with them as well as with other typical filtering methods because a large amount of useful biological information can be lost, and there are many trade-offs between various filtering methods. Moreover, conventional filtering cannot always fully address the physicality of the signal-processing problem in terms of extracting specific signals due to particular biological sources of interest such as the stomach, heart and bowel. In this paper, we demonstrate the use of fast independent component analysis (FICA) for the removal of both biological and non-biological artifacts from multi-channel MGG recordings acquired using a superconducting quantum intereference device (SQUID) magnetometer. Specifically, we show that the signal of gastric electrical control activity (ECA) can be isolated from SQUID data as an independent component even in the presence of severe motion, cardiac and respiratory artifacts. The accuracy of the method is analyzed by comparing FICA-extracted versus electrode-measured respiratory signals. It is concluded that, with this method, reliable results may be obtained for a wide array of magnetic recording scenarios.

Biomagnetic detection of injury currents in rabbit ischemic intestine.

The presence of direct current (DC) injury currents in ischemic tissue is an important diagnostic indicator of pathophysiology in cortical spreading depression and particularly in myocardial infarction. To date, no measurements of DC injury currents in the alimentary tract have been reported. We used a SQUID magnetometer to measure changes in the baseline of the magnetic field of intestinal electrical activity during induced segmental ischemia. We computed the magnetic field DC baseline by subtracting sequential recordings made while the bowel segment was first directly beneath the SQUID and then pulled away. We observed a significant baseline decrease of 38% +/- 4% in experimental animals, while the control group decreased by only 1% +/- 6%. This magnetic field baseline decrease is consistent with the flow of injury currents between normally perfused and hypoxic tissue regions. This study is the first report of DC injury currents in ischemic smooth muscle of the alimentary tract.

Ellipsoidal electrogastrographic forward modelling.

The theoretical and computational study of the electromagnetic forward and inverse problems in ellipsoidal geometry is important in electrogastrography because the geometry of the human stomach can be well approximated using this idealized body. Moreover, the anisotropies inherent to this organ can be highlighted by the characteristics of the electric potential associated with current dipoles in an ellipsoid. In this paper, we present a forward simulation for the stomach using an analytic expression of the gastric electric potential that employs a truncated expansion of ellipsoidal harmonics; we then demonstrate that an activation front of dipoles propagating along the body of an ellipsoid can simulate gastric electrical activity. In addition to the usefulness of our model, we also discuss its limitations and accuracy.

Theoretical and computational methods for the noninvasive detection of gastric electrical source coupling.

The ability to study the pathology of the stomach noninvasively from magnetic field measurements is important due to the significant practical advantages offered by noninvasive methods over other techniques of investigation. The inverse biomagnetic problem can play a central role in this process due to the information that inverse solutions can yield concerning the characteristics of the gastric electrical activity (GEA). To analyze gastrointestinal (GI) magnetic fields noninvasively, we have developed a computer implementation of a least-squares minimization algorithm that obtains numerical solutions to the biomagnetic inverse problem for the stomach. In this paper, we show how electric current propagation and the mechanical coupling of gastric smooth muscle cells during electrical control activity can be studied using such solutions. To validate our model, two types of numerical simulations of the GEA were developed and successfully used to demonstrate the ability of our computer algorithm to detect and accurately analyze these two phenomena. We also describe our analysis of experimental, noninvasively acquired gastric biomagnetic data as well as the information of interest that our numerical method can yield in clinical studies. Most importantly, we present experimental evidence that the coupling of gastric electrical sources can be observed using noninvasive techniques of measurement, in our case with the use of a superconducting quantum interference device magnetometer. We discuss the relevance and implications of our achievement to the future of GI research.

Theoretical and computational multiple regression study of gastric electrical activity using dipole tracing from magnetic field measurements.

The biomagnetic inverse problem has captured the interest of both mathematicians and physicists due to its important applications in the medical field. As a result of our experience in analyzing the electrical activity of the gastric smooth muscle, we present here a theoretical model of the magnetic field in the stomach and a computational implementation whereby we demonstrate its realism and usefulness. The computational algorithm developed for this purpose consists of dividing the magnetic field signal input surface into centroid-based grids that allow recursive least-squares approximations to be applied, followed by comparison tests in which the locations of the best-fitting current dipoles are determined. In the second part of the article, we develop a multiple-regression analysis of experimental gastric magnetic data collected using Superconducting QUantum Interference Device (SQUID) magnetometers and successfully processed using our algorithm. As a result of our analysis, we conclude on statistical grounds that it is sufficient to model the electrical activity of the GI tract using only two electric current dipoles in order to account for the magnetic data recorded non-invasively with SQUID magnetometers above the human abdomen.

Theoretical ellipsoidal model of gastric electrical control activity propagation.

A theoretical model of electric current propagation in the human stomach is developed using an approach in which the shape of the organ is assumed to be a truncated ellipsoid whose dimensions can be determined from anatomic measurements. The gastric electrical activity is simulated using a ring of isopotential electric current dipoles that are generated by a pacemaker situated in the gastric corpus. The dipoles propagate in the direction of the pylorus at a frequency of three cycles per minute. The advantages of employing ellipsoids in the analytical formulation of this gastric model are discussed in addition to the realism and usefulness of the approach.

A spatio-temporal dipole simulation of gastrointestinal magnetic fields.

We have developed a simulation of magnetic fields from gastrointestinal (GI) smooth muscle. Current sources are modeled as depolarization dipoles at the leading edge of the isopotential ring of electrical control activity (ECA) that is driven by coupled cells in the GI musculature. The dipole moment resulting from the known transmembrane potential distribution varies in frequency and phase depending on location in the GI tract. Magnetic fields in a homogeneous volume conductor are computed using the law of Biot-Savart and characterized by their spatial and temporal variation. The model predicts that the natural ECA frequency gradient may be detected by magnetic field detectors outside the abdomen. It also shows that propagation of the ECA in the gastric musculature results in propagating magnetic field patterns. Uncoupling of gastric smooth muscle cells disrupts the normal magnetic field propagation pattern. Intestinal ischemia, which has been experimentally characterized by lower-than-normal ECA frequencies, also produces external magnetic fields with lower ECA frequencies.