Automated algorithm for GI spike burst detection and demonstration of efficacy in ischemic small intestine.

We present a novel, fully-automated gastrointestinal spike burst detection algorithm. Following pre-processing with SALPA (Wagenaar and Potter, J. Neurosci. Methods 120:113-120, 2002) and a Savitzky-Golay filter to remove unwanted low and high frequency components, candidate spike waveforms are detected utilizing the non-linear energy operator. Candidate waveforms are classified as spikes or artifact by a support vector machine. The new method achieves highly satisfactory performance with >90% sensitivity and positive prediction value. We also demonstrate an application of the new method to detect changes in spike rate and spatial propagation patterns upon induction of mesenteric ischemia in the small intestine. Spike rates were observed to transiently increase 10-20 fold for a duration of ≈600 s, relative to baseline conditions. In ischemic conditions, spike activity propagation patterns included retrograde-longitudinal wavefronts with occasional spontaneous conduction blocks, as well as self-terminating concentric-circumferential wavefronts. Longitudinal and circumferential velocities were 6.8-8.0 cm/s and 18.7 cm/s, respectively.

Noninvasive biomagnetic detection of isolated ischemic bowel segments.

The slow wave activity was measured in the magnetoenterogram (MENG) of normal porcine subjects (N = 5) with segmental intestinal ischemia. The correlation changes in enteric slow wave activity were determined in MENG and serosal electromyograms (EMG). MENG recordings show significant changes in the frequency and power distribution of enteric slow-wave signals during segmental ischemia, and these changes agree with changes observed in the serosal EMG. There was a high degree of correlation between the frequency of the electrical activity recorded in MENG and in serosal EMG (r = 0.97). The percentage of power distributed in brady- and normoenteric frequency ranges exhibited significant segmental ischemic changes. Our results suggest that noninvasive MENG detects ischemic changes in isolated small bowel segments.

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.

Noninvasive detection of small bowel electrical activity from SQUID magnetometer measurements using SOBI.

We report a robust method for noninvasive biomagnetic detection of small bowel electrical activity. Simultaneous Superconducting QUantum Interference Device (SQUID) magnetometer (MENG) and serosal electrode recordings were made on pig small bowel. The SOBI blind-source separation algorithm was used to separate the underlying source signals of the MENG. Comparison of identified SOBI components to the serosal recordings validated the underlying MENG sources as being enteric in origin. Non-invasive detection of small bowel electrical activity could have significant implications in a clinical setting.