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Keywords:

  • coupling/uncoupling and electrogastro-gram;
  • gastric myoelectrical activity

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

Current methodology of single channel electrogastrography is unable to detect coupling or uncoupling of gastric slow waves, which is crucial for gastric emptying. In this study, a new methodology, called cross-spectral analysis method, was established to compute the coupling percentage of multi-channel gastric slow waves recorded using serosal electrodes and electrogastrogram (EGG). Two experiments were performed to validate the method and demonstrate its applications in clinical research. In experiment 1, simultaneous recordings of gastric slow waves were made in five dogs from serosal electrodes and cutaneous electrodes. In experiment 2, four-channel fasting EGGs were made in 10 volunteers for 30 min during waking and 30 min during non-rapid eye movement (REM) sleep. The validation study (experiment 1) showed that the slow wave coupling calculated from the EGGs was correlated with that computed from the serosal recordings. The gastric slow wave coupling percentages detected from both serosal and cutaneous recordings were significantly impaired during vasopressin infusion (6.3 ± 2.6 vs 62.4 ± 6.3, P < 0.001 for serosal recordings; 6.7 ± 3.0 vs 57.2 ± 2.7, P < 0.001 for cutaneous recordings), and the coupling percentages respectively calculated from serosal and cutaneous recordings were significantly correlated during the baseline recording period (R = 0.922, P < 0.05) and vasopressin infusion period (R = 0.916, P < 0.05). In experiment 2, the gastric slow wave became less coupled when healthy volunteers fell asleep. The percentage of slow wave coupling calculated from the EGGs was 68.2 ± 17.9% during waking but 41.9 ± 20.8 during non-REM sleep (P < 0.05). The method developed in this study is reliable for the detection of slow wave uncoupling from multi-channel EGGs. Gastric slow wave coupling is impaired during vasopressin infusion and sleep. These data suggest that this method has potential applications in physiological and clinical studies.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

Motility is one of the most important physiological functions in the human gut. Without coordinated motility, digestion and absorption of dietary nutrition could not take place.1–3 To accomplish its functions effectively, the gut needs to generate not only simple contractions but also coordinated contractions (peristalsis).

Gastric motility is regulated by gastric myoelectrical activity (GMA).2–12 Abnormalities in GMA are associated with gastric motility disorders.3,13–20 GMA is rhythmic in temporal evolution and ordered in spatial propagation. The regular frequency and spatial coordination of GMA are disrupted in a number of clinical settings, such as postoperative ileus and chronic intractable nausea and vomiting. The disruption in frequency regularity of the GMA is called dysrhythmia or temporal disorder. Three categories of dysrhythmia are usually observed: bradygastria (lower than normal rhythm), tachygastria (higher than normal rhythm) and dysrhythmia (no rhythm).3,6,14–20 The disruption in the spatial coordination of GMA is called discoordination or spatial disorder, which means that the contractions of the stomach would no longer begin in the corpus and propagate to the antrum. Both the temporal disorder and the spatial disorder lead to gastric motility disorders.

Gastric myoelectrical activity can be measured by using one of three methods: serosal electrodes implanted intraoperatively, intraluminal electrodes mounted on flexible tubes, and abdominal cutaneous electrodes.3 The serosal electrodes give the most reliable recording, which reflects the detailed information on GMA. However, this method is invasive and suitable only for experimental studies in animal models.3,21,22 Electrodes properly mounted on a flexible tube are able to record GMA with less invasiveness than serosal electrodes. However, they are difficult to affix and are unreliable due to a possible loss of contact with gastric mucosa.3,23,24 The measurement of GMA using cutaneous electrodes is termed electrogastrography and the obtained signal is called the electrogastrogram (EGG).3,25 Compared with the serosal and intraluminal methods, electrogastrography is more sensitive to noises, but it is non-invasive, does not affect on-going physiological process of the stomach, and thus is of an attractive potential for clinical applications.3,25–31

Current methodology used to analyse the gastric slow waves recorded via serosal electrodes or electrogastrography focuses on extracting spectral features of single-channel slow waves. The spatial propagation information of the gastric slow waves is unfortunately omitted. Therefore, the aims of this study were threefold: to develop a new method for the detection of slow wave coupling/uncoupling from the EGG, to validate the method using simultaneously recorded internal and cutaneous GMA signals and to demonstrate its application in studying electrophysiology of the stomach.

Subjects and surgical procedure in experiment 1 Five healthy female hound dogs (14.5–21.5 kg) were used in experiment 1. Internal electrodes were implanted on the serosa of the stomach under general anaesthesia. Anaesthesia was induced with Pentothal (sodium thiopental 5 mg kg−1, i.v.; Abbot Laboratories, North Chicago, IL, USA) and maintained on IsoFlo (isoflurane 1.5%, inhalation anaesthesia; Abbot) in oxygen–nitrous oxide (1 : 1) carrier gases delivered from a ventilator following endotreachael intubation. The dog was monitored via the assessment of tongue colour, pulse rate and breathing rate. Three pairs of 28-gauge cardiac pacing wires (A & E Medical, Farmingdale, NJ, USA) were implanted on the serosal surface of the stomach along the greater curvature by laparotomy. The most distal pair was 2 cm above the pylorus, and the distance between the adjacent pairs of electrodes was 4 cm. The most proximal pair of electrodes was located on the anatomical junction of the body and fundus, which is the area of pacemaker. The electrodes in each pair were 1 cm apart. The electrodes penetrated the subserosa and were affixed to the gastric serosa by unabsorbable sutures. The wires tunnelled through the anterior abdominal wall and subcutaneously along the right side of the trunk, and were placed outside the skin around the right hypochodrium for the attachment to the recorder or stimulator. Following completion of the operation, the anaesthetic gases were discontinued. Extubation was performed after the airway reflexes was retained. The dog received medication for postoperative pain control and then was transferred to a recovery cage.

The study was initiated after the dogs were completely recovered from the surgery. To simultaneously record internal and external (cutaneous) GMA signals, three active EKG electrodes were placed on the abdominal surface area right above the three pairs of serosal electrodes and each connected to a common reference electrode to derive three-channel EGG signals (Fig. 1). Before the placement of the electrodes, the abdominal skin where the electrodes were to be placed was shaved and cleaned with sandy skin prep paste (Omni pep Waver and Co., Aurora, CO, USA) to reduce impedance.

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Figure 1. The locations of cutaneous electrodes for the recording of three-channel electrogastrograms in the dog.

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Subjects in experiment 2 Ten healthy volunteers (four males and six females) participated in experiment 2. Subjects were between 22 and 55 years old. All participants were of normal weight with an average body mass index (BMI) of 22 ± 1.2. Subjects were screened for any evidence of gastrointestinal (GI) diseases, sleep disorders, or medication uses during a structured interview which included completion of various questionnaires addressing the frequency and intensity of GI symptoms and sleep problems. Six electrodes were placed on the abdominal surface over the stomach (Fig. 2) for the measurement of four-channel electrogastrograms (EGGs).

image

Figure 2. The locations of cutaneous electrodes for the recording of four-channel electrogastrograms in the human.

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Protocol of experiment 1 All dogs were studied in one session divided into three periods: a 20-min baseline period, a 20-min period with continuous i.v. infusion of vasopression (0.5 units kg−1 in 20 mL saline) and a 20-min recovery period after the termination of infusion. GMA was simultaneously recorded during all these periods via serosal and cutanous electrodes. The animal committee of the Veterans Affairs Medical Center, Oklahoma City, Oklahoma, approved the protocol.

Study protocol of experiment 2 Polysomnography and four-channel EGGs were performed during one night in the sleep laboratory, consisting of a 1-h presleep waking recording, and approximately 7 h of sleep recording. All subjects refrained from any over-the-counter medication for a minimum of 24 h prior to the study day, and from caffeine for at least 6 h prior to reporting to the laboratory. They consumed dinner prior to 17:00 p.m., after which time they restrained from all food and drink. Subjects reported to the laboratory at 20:30 p.m. Upon reporting to the laboratory, electrodes were placed for EGGs and polysomnographic recordings. The waking recording lasted from 22:00 p.m. to 23:00 p.m. During this period, subjects remained in the supine position and watched television. Subjects were monitored via polysomnographic recordings to ensure wakefulness. The sleep recording was started at 23:00 p.m., and subjects were allowed to sleep spontaneously until 06:00 a.m., the next morning. The study protocol was approved by the Institutional Review Board of the Baptist Medical Center of Oklahoma. All participants gave informed written consent prior to entering the study and were paid for their participation.

Gastric myoelectrical activity recordings

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

In experiment 1, a multi-channel recorder (MP100 System; Biopac Inc., Santa Barbara, CA, USA) was used to record GMA via serosal and surface electrodes in the dogs. Three-channel bipolar serosal electrodes were connected to the MP100 system as channels 1–3 and the other three-channel cutaneous electrodes were connected to the MP100 system as channels 4–6. All signals were displayed on a computer monitor and saved on the hard disk by an IBM-compatible 586 PC. The low and high cut-off frequencies of the amplifier were 0.05 and 35 Hz, respectively. For the analysis of gastric slow waves, the signal was low-pass filtered with a cut-off frequency of 1 Hz by an FIR digital filter and was down-sampled at 2 Hz.

In experiment 2, four-channel EGGs in each subject were measured using a specially designed four-channel device (Medtronic-Synectics, Shoreview, MN, USA). The device consisted of four identical amplifiers with a cut-off frequency of 16.0 cpm. A 12-bit analog-to-digital converter was installed in the recording device for the online digitization of the EGG. The sampling frequency was 4 Hz. Prior to the attachment of electrodes, the abdominal surface where electrodes were to be positioned was shaved, if hairy, and cleaned with sandy skin prep paste (Omni prep Weaver and Co.) to reduce impedance. Six silver/silver chloride electrodes (3M Red Dot, St Paul, MN, USA) were placed on the abdominal skin over the stomach (Fig. 2), including four active electrodes (electrodes 1–4), one reference electrode (electrode 0) and a ground electrode. Electrode 3 was placed 2 cm above the middle point between the xiphoid process and the umbilicus; electrode 4 was 4 cm on the right horizontal to electrode 3, electrodes 2 and 1 were placed 45 °C upper left to electrode 3 with an interval of 4–6 cm, depending on the size of the subject. The common reference electrode (electrode 0) was placed at the cross point of two lines, one horizontal-connecting electrode 1 and the one vertical-connecting electrode 3. The ground electrode was placed on the left coastal margin horizontal to electrode 3. By connecting each of the four active electrodes to the common reference electrode, four-channel EGG signals were derived.

Polysomnographic recordings

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

In experiment 2, standard polysomnographic recordings were used to determine sleep stages, and were carried out using an Alice 3 Polysomnographic System (Healthdyne, Marietta, GA, USA), which consisted of an integrated system of amplifiers and computerized data collection. Four channels of electroencephalogram (EEG) (centrals C3 & C4, occipital channels O1 & O2), two channels of electrooculogram (EOG), one channel of chin electromyogram (EMG), and a single channel of electrocardiogram (ECG) were collected at a sampling rate of 500 Hz. Body position was also recorded.

Detection of slow wave coupling

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

A running power spectrum can be formulated as a two-dimensional (2-D) time-frequency function, e.g. P (t, f), where t denotes time, f denotes frequency and thus P (t, f) denotes the power at time = t and frequency = f. To detect coupling information from the gastric slow waves, we introduced another spectrum concept, called cross running spectrum and denoted as Pcr(t, f). Let P1(t, f) denote the running power spectrum of the gastric slow wave recorded from channel 1, and P2(t, f) denote the running power spectrum of the gastric slow wave recorded from channel 2, then the cross running spectrum between channels 1 and 2 was defined as

  • image

We used Pcr(t, f) to visually investigate and quantitatively analyse the coupling/uncoupling between every two channels of gastric slow waves. For a given time t, if both P1(t, f) and P2(t, f) reached their peaks at frequency f, i.e. they had the same dominant frequency (the two channels were coupled), then, Pcr(t, f) = P1(t, f) × P2(t, f) would reach its peak. However, for a given time t, if P1(t, f) reached its peak, but P2(t, f) reached its minimum at frequency f, i.e. they had different dominant frequencies (the two channels were uncoupled), then, Pcr(t, f) = P1(t, f) × P2(t, f) would be of the minimum value. Therefore, the cross running spectrum was able to pick up the area with the same frequency and to suppress the area with different frequencies during the same time period visually.

The percentage of coupling between two channels of gastric slow waves was calculated on a minute-by-minute basis. The minute was defined as coupled if the difference in the dominant frequencies of the two channels was equal to or smaller than 0.2 cpm. Otherwise, the minute was defined as uncoupled. The average percentage of coupling was defined as the mean value of all exhaustive pairs of channels. For example, the average percentage of coupling for a three-channel recording was the average of the percentages of coupling between channels 1 and 2, channels 1 and 3 and channels 2 and 3.

Validation of the methodology using computer-generated signals

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

Figure 3 visually illustrates how the cross running spectrum could be used to detect the coupling between two computer-generated signals. Fig. 3A illustrates the running spectrum of simulated slow waves (channel 1) with a frequency of 3 cpm during the whole period of 30 min; Fig. 3B illustrates the running spectrum of simulated slow waves (channel 2) with a frequency of 3 cpm during the first 15 min and with a frequency of 3.5 cpm during the second 15 min. The cross running spectrum between channel 1 and channel 2 is illustrated in Fig. 3C (2-D representation) and in Fig. 3D (3-D representation). Both Fig. 3C and D clearly illustrate that there is a 50% coupling between the two channels.

image

Figure 3. Illustrations of cross running spectra in the detection of coupling from two-channel computer-simulated slow waves. (A) The running spectrum of the signal with a unique frequency of 3 cpm during 30 min. (B) The running spectrum of the signal with a frequency of 3 cpm during the first 15 min and another frequency of 3.5 cpm during the second 15 min. (C) The 2-D representation of the cross running spectrum between signal 1 and signal 2. (D) The 3-D representation of the cross running spectrum between signal 1 and signal 2.

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Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

An example showing slow wave uncoupling is presented in Fig. 4. The tracings in this figure represent eight-channel gastric slow waves recorded via serosal electrodes in one dog. It can be seen from this portion of the recording that (i) at the beginning, the stomach had normal slow waves propagating from the corpus to the antrum; (ii) about 1 min later, an ectopic pacemaker took place in the distal antrum in addition to the normal pacemaker in the corpus, and there were two pacemakers at the same time. The ectopic pacemaker generated slow waves with a frequency of about 15 cpm and these slow waves propagated retrogradely towards the corpus. They gradually overrode the normal slow waves. It can be visually assessed that during this period with two pacemakers, the slow waves in the different regions of the stomach were not coupled as they had different frequencies attributed to two different pacemakers. (iii) About another minute later, the ectopic tachygastrial pacemaker disappeared and normal slow waves resumed.

image

Figure 4. Eight channels GMA recordings from serosal electrodes in a dog. Channel 1 (the top) to Channel 8 (the bottom): GMA recorded from the proximal to the distal stomach using serosal electrodes with a distance of 2 cm between each adjacent pairs.

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Figure 5 illustrates typical tracings simultaneously recorded from a dog in the fasting state via serosal electrodes (channels 1–3) and cutaneous electrodes (channels 4–6). Three periods of data were recorded and analysed separately in this study for each dog, i.e. baseline recording period (fasting state), the period with vasopressin infusion and recovery period after termination of vasopressin infusion. For each period, the coupling percentages between channels 1 and 2, between channels 1 and 3 and between channels 2 and 3 were calculated and their average value was used as the final coupling percentage for the serosal recordings. The coupling percentages between channels 4 and 5, between channels 4 and 6 and between channels 5 and 6 were calculated and their average value was used as the final coupling percentage for the cutaneous recordings (EGGs). During the baseline recording period, the coupling percentage detected from serosal recordings was 62.4 ± 6.3%, whereas the coupling percentage detected from cutaneous recordings was 57.2 ± 2.7%, and they were significantly correlated (R = 0.922, P < 0.05) (Fig. 6A). During vasopressin infusion period, the coupling percentage detected from serosal recordings was reduced to 6.3 ± 2.6% (P < 0.001, in comparison with the baseline), and the coupling percentage detected from cutaneous recordings was reduced to 6.7 ± 3.0% (P < 0.001, in comparison with the baseline), and they were significantly correlated (R = 0.916, P < 0.05) (Fig. 6B). During the recovery period, the coupling percentage detected from serosal recordings recovered to 53.4 ± 9.5%, whereas the coupling percentage detected from cutaneous recordings recovered to 41.4 ± 14.9%, and they were correlated (R = 0.808, P = 0.09) (Fig. 6C).

image

Figure 5. One-minute tracings of the three-channel serosal recordings (channels 1–3) and the corresponding three-channel cutaneous electrogastrogram recordings (channels 4–6).

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image

Figure 6. Correlations of the coupling between the serosal recordings and the cutaneous recordings during the three periods of baseline, vasopressin infusion and recovery.

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Detection of slow wave coupling during waking and sleep

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

After the identification of sleep stages via using the EEG and EOG recordings, the four-channel EGG data recorded from each subject were divided into two periods of 30 min, i.e. waking and non-rapid eye movement (REM) sleep. For each period, the coupling percentages of gastric slow waves in the four-channel EGGs between channels 1 and 2, between channels 1 and 3, between channels 1 and 4, between channels 2 and 3, between channels 2 and 4 and between channels 3 and 4 were calculated and their average values were used as the final coupling percentage for waking or non-REM sleep. The percentage of gastric slow wave coupling was significantly lower during non-REM sleep than during waking (41.9 ± 20.8 vs 68.2 ± 17.9, P < 0.05) (Fig. 7).

image

Figure 7. The percentage of slow wave coupling during awake and sleep in healthy volunteers.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References

In this paper, we have proposed a new method to detect coupling/uncoupling of gastric slow waves and presented its validation and application. Firstly, the cross running spectrum was introduced. The simulation experiment using two computer-generated signals clearly demonstrated that the proposed cross running spectrum is able to visually represent and quantitatively detect the coupling information between two channels of signals. To practically calculate the number of percentage of coupling between two channels of gastric slow waves, we have proposed that the dominant-frequency difference between two running spectrums of the two channels at every time period (minute basis) be compared. If the difference during a time period t is smaller than 0.2 cpm, the slow waves in the two channels is defined as being coupled at this time period, otherwise as being uncoupled.

To validate the methodology developed in this paper, an experiment was designed to record gastric slow waves simultaneously from the internal serosal electrodes and the cutaneous electrodes. As vasopressin is known to induce gastric myoelectrical dysrhythmia,32,33 it was used in the validation experiment, where the data demonstrated that the percentage of slow wave coupling calculated from the EGG was significantly correlated with that calculated from the serosal recording and that uncoupling induced by vasopressin could be accurately detected. This finding supports that the method developed in this paper is applicable to the non-invasive EGG and is capable of detecting uncoupling of slow waves.

It should be pointed out that the sensitivity of the proposed method is related to the selected threshold in determining the difference in frequency between two compared EGG channels. The threshold of 0.2 cpm was decided based on numerous experiments and the validation study. If this value is set too low, the assessment could be affected by (i) noise/interference contained in the EGG and (ii) frequency resolution of the spectral analysis. In this method, the frequency resolution was set at 0.02 cpm, i.e. the frequency changes were represented by a multiple of 0.02 cpm. If the threshold were set too close to the frequency resolution, the computed percentage of slow wave coupling could be erratic. However, if the threshold were set too big, the method would then be less sensitive in detecting uncoupling.

The sleep study was designed to demonstrate the application of the developed method in the electrophysiological studies of the stomach. Previous studies have shown disturbances in GMA during sleep.34,35 However, no information regarding slow wave coupling has been available in the literature. In this current study, we found that in addition to gastric dysrhythmias as reported in the previous study,34 slow waves became less coupled during sleep. One may have noted that the percentage of slow wave coupling in these normal subjects during awake had a mean value of 70% instead of 100%. This could be attributed to (i) the precision of the EGG. As it is known that the EGG is a cutaneous measurement of slow waves and thus subjected to noise and interferences. A degradation in slow wave rhythmicity is unavoidable and this would yield a reduced percentage of slow wave coupling; (ii) the actual motility status. The recording was made in the fasting state, it is possible that coordinated contractions are not all important in the fasting state except during phase III of the migrating motor complex. Our recent unpublished data seem to suggest that the coupling of gastric slow waves is increased in the postprandial state.

Clinical applications of the method developed in this paper have been recently explored. In one study, we found that the coupling of the gastric slow wave was significantly impaired in patients with dyspepsia in comparison with the healthy controls.36 In another study, a substantially reduced gastric slow wave coupling was noted in patients with connective tissue disorder.37 These studies suggest that the proposed method for the detection and quantification of slow wave coupling may have diagnostic potential in patients with functional or motility disorders.

Gastric myoelectrical activity includes temporal evolution from endogenous rhythmic oscillations controlled by the pacemaker to spatial propagation of the oscillating wave driven by the coupling mechanisms from cell to cell. The rhythmic nature of the pacemaker activity and the entrainment of intrinsic frequencies has led to modelling of the gastric slow waves as a population of coupled relaxation oscillators.38 The experiments using coupled relaxation oscillators clearly demonstrate that coupling plays a key role to drive the slow wave propagation from the proximal to the distal stomach.38 Although some other investigators have previously recorded multi-channel EGGs, the results were reported only based on the analysis of one single channel selected.39,40 With the methodology of multi-channel electrogastrography, the information about propagation and coordination of the gastric slow waves becomes available. The percentage of slow wave coupling introduced in this paper represents the consistency of the slow wave frequency and its propagation along gastric axis and thus may be crucial to gastric motility and gastric emptying. More studies are needed to closely investigate the correlation/association between the percentage of slow wave coupling and gastric motility/emptying.

In conclusion, we have developed a method for the detection and quantification of gastric slow wave coupling/uncoupling. The data obtained from the canine and human experiments suggest that the method is applicable in the multi-channel EGG and capable of detecting slow wave uncoupling under both physiological and pathophysiological conditions.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Subjects
  6. Study protocols
  7. Gastric myoelectrical activity recordings
  8. Polysomnographic recordings
  9. Detection of slow wave coupling
  10. Statistical analysis
  11. Results
  12. Validation of the methodology using computer-generated signals
  13. Validation of the methodology using simultaneously recorded gastric slow waves via serosal and cutaneous electrodes in dogs
  14. Detection of slow wave coupling during waking and sleep
  15. Discussion
  16. References
  • 1
    Code CF, Szurszewski JH, Kelly KA, Smith IB. A concept of control of gastrointestinal motility. In: CodeCF, ed. Handbook of Physiology: Alimentary Canal. New York: Raven Press, 1968: 288196.
  • 2
    Dubois A. The stomach. In: ChristensenJ, WingateDL, eds. A Guide to Gastrointestinal Motility. Bristol: Wright, PSG, 1983: 10127.
  • 3
    Schuster MM. Atlas of Gastrointestinal Motility in Health and Disease. Baltimore: Williams & Wilkins, 1993.
  • 4
    Sarna SK. Gastrointestinal electrical activity: terminology. Gastroenterology 1975; 68: 16315.
  • 5
    Wang ZS, Chen JDZ. Blind separation of slow waves and spikes from gastrointestinal myoelectrical recordings. IEEE Trans Inf Technol Biomed 2001; 5: 1337.
  • 6
    Szurszewski JH. Electrical basis for gastrointestinal motility. In: JonhsonLR, ed. Physiology of the Gastrointesinal Tract. New York: Raven Press, 1987: 383422.
  • 7
    Daniel EE, Chapman KM. Electrical activity of the gastrointestinal tract as an indication of mechanical activity. Am J Dig Dis 1963; 8: 54102.
  • 8
    Sharkawy TY, Morgan KG, Szurszewski JH. Intracellular electrical activity of canine and human gastric smooth muscle. J Physiol 1978; 279: 291307.
  • 9
    Daniel EE. Gap junctions in smooth muscle. In: De MelloWC, ed. Cell-to-Cell Communication. New York: Plenum Press, 1987.
  • 10
    Bortoff A. Propagation of electrical activity in gastrointestinal smooth muscle: the case for propagation by local circuit current flow. J Gastrointest Motil 1991; 3: 5763.
  • 11
    Bauer AJ, Publicover NG, Sanders KM. Origin and spread of slow waves in canine gastric antral circular muscle. Am J Physiol 1985; 249: G8006.
  • 12
    Publicover NG, Sanders KM. Myogenic regulation of propagation in gastric smooth muscle. Am J Physiol 1985; 248: 51220.
  • 13
    Wang ZS, Cheung JY, Gao SK, Chen JDZ. Spatio-temporal nonlinear modeling of gastric myoelectrical activity. In: The 3rd International Workshop on Biosignal Interpretation (BSI99), Chicago, IL, USA, 1214, June 1999.
  • 14
    Chen JDZ, Pan J, McCallum RW. Clinical significance of gastric myoelectrical dysrhythmia. Dig Dis Sci 1995; 13: 27590.
  • 15
    Abell TL, Malagelada JR. Glucagon evoked gastric dysrhythmias in humans shown by an improved electrogastrographic technique. Gastroenterology 1985; 88: 193240.
  • 16
    Kim CH, Azpiroz F, Malagelada J-R. Characteristics of spontaneous and drug-induced gastric dysrhythmias in a chronic canine model. Gastroenterology 1986; 90: 4217.
  • 17
    Stoddard CJ, Smallwood RH, Duthie HL. Electrical arrhythmias in the human stomach. Gut 1981; 22: 70512.
  • 18
    You CH, Lee KY, Menguy WY. Electrogastrographic study of patients with unexplained nausea, bloating and vomiting. Gastroenterology 1980; 79: 31114.
  • 19
    You CH, Chey WY. Study of electromechanical activity of the stomach in human and in dogs with particular attention to tachygastria. Gastroenterology 1985; 86: 14608.
  • 20
    Geldof H, der Schee EJ, van Blankenstein V, Grasuis JL. Electrogastrographic study of gastric myoelectrical activity in patients with unexplained nausea and vomiting. Gut 1986; 27: 799808.
  • 21
    Morgan KG, Angel F, Schmalz PF. Intracellular electrical activity of muscularis mucosae of the dog stomach. Am J Physiol 1985; 249: 25663.
  • 22
    Hara Y, Ito Y. The electrical activity recorded from smooth muscle of the circular of the human stomach. Eur J Physiol 1979; 382: 14553.
  • 23
    Hamilton JW, Bellahsene BE, Reichelder M, Webster JG, Bass P. Human electrogastrograms: Comparison of surface and mucosal recordings. Dig Dis 1986; 31: 3339.
  • 24
    Familoni BO, Kingma YJ, Bowes KL. A study of transcutaneous and intraluminal measurement of gastric electrical activity in humans. Med Biol Eng Comput 1987; 25: 397402.
  • 25
    Alvarez WC. The electrogastrogram and what it shows. J Am Med Assoc 1922; 78: 111619.
  • 26
    Stern RM, Koch KL, Stewart WR, Vasey MW. Electrogastrography: current issues in validation and methodology. Psychophysiology 1987; 24: 5564.
  • 27
    Familoni BO, Kingma YJ, Bowes KL. Noninvasive assessment of human gastric motor function. IEEE Trans Biomed Eng BME 1987; 34: 306.
  • 28
    Abell TL, Malagelada JR. Electrogastrography: current assessment and future perspectives. Dig Dis Sci 1988; 33: 98292.
  • 29
    Chen JDZ, McCallum RW. Electrogastrography – Principles and Applications. New York: Raven Press, 1994.
  • 30
    Chen JDZ, Vandeewalle J, Sansen W et al. Observation of the propagation direction of human electrogastric activity from cutaneous recordings. Med Biol Eng Comput 1989; 27: 53842.
  • 31
    Wang ZS, He ZY, Chen JDZ. Filter banks and neural network-based features extraction and automatic classification of electrogastrogram. Ann Biomed Eng 1999; 27: 8895.
  • 32
    Qian LW, Wang ZS, Abo M, Chen JDZ. Vasopressin induces jejunal dysrhythmia and slow wave uncoupling in dogs. Gastroenterology 1999; 116 (Pt 2): G4632.
  • 33
    Kim MS, Chey WD, Chung OY, Hasler WL. Role of plasma vasopressin as a mediator of nausea and gastric slow wave dysrhythmias in motion sickness. Am J Gastroenterol 1997; 272: G85362.
  • 34
    Elsenbruch S, Orr WC, Harnish MJ, Chen JDZ. Disruption of normal gastric myoelectric functioning by sleep. Sleep 1999; 22: 4538.
  • 35
    Orr WC, Crowell MD, Lin B, Harnish MJ, Chen JDZ. Sleep and gastric function in irritable bowel syndrome: derailing the brain-gut axis. Gut 1997; 41: 3903.
  • 36
    Lin XM, Chen JDZ. Abnormal gastric slow waves in patients with functional dyspepsia assessed by multichannel electrogastrography. Am J Physiol 2001; 280: G13705.
  • 37
    McNearney T, Lin XM, Shrestha J, Lisse J, Chen JDZ. Characterization of gastric myoelectrical rhythms in patients with systemic sclerosis using multichannel surface electrogastrography. Dig Dis Sci 2002; 47: 6908.
  • 38
    Sarna SK, Daniel EE, Kingma YJ. Simulation of the electric-control activity of the stomach by an array of relaxation oscillators. Dig Dis Sci 1972; 17: 299310.
  • 39
    Desvarannes SB, Mizrahi M, Dubois A. Relation between postprandial gastric-emptying and cutaneous electrogastrogram in primates. Am J Physiol 1991; 261: G24855.
  • 40
    Brzana RJ, Koch KL, Bingaman S. Gastric myoelectrical activity in patients with gastric outlet obstruction and idiopathic gastroparesis. Am J Gastroenterol 1998; 93: 18039.
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