Detection of the Recovery Phase of in vivo gastric slow wave recordings

The gastric conduction system in health and disease: a translational review

Gastric peristalsis is critically dependent on an underlying electrical conduction system. Recent years have witnessed substantial progress in clarifying the operations of this system, including its pacemaking units, its cellular architecture, and slow-wave propagation patterns. Advanced techniques have been developed for assessing its functions at high spatiotemporal resolutions. This review synthesizes and evaluates this progress, with a focus on human and translational physiology. A current conception of the initiation and conduction of slow-wave activity in the human stomach is provided first, followed by a detailed discussion of its organization at the cellular and tissue level. Particular emphasis is then given to how gastric electrical disorders may contribute to disease states. Gastric dysfunction continues to grow in their prevalence and impact, and while gastric dysrhythmia is established as a clear and pervasive feature in several major gastric disorders, its role in explaining pathophysiology and informing therapy is still emerging. New insights from high-resolution gastric mapping are evaluated, together with historical data from electrogastrography, and the physiological relevance of emerging biomarkers from body surface mapping such as retrograde propagating slow waves. Knowledge gaps requiring further physiological research are highlighted.

Detection of Monophasic Slow-wave Activation Phase Using Wavelet Decomposition

Gastric bio-electric slow-waves are in part responsible for generating motility. Extracellular recordings of the slow-wave activation phase have yielded significant physiological insight about its spatio-temporal characteristics. With the growth of multi-electrode data and long recording periods, there is a need for automated methods to detect the activation phase in a reliable and accurate manner. In this study, the Variable Threshold Wavelet (VTW) algorithm was developed, featuring wavelet decomposition, to compute the derivative to detect the slow-wave activation phase of monophasic signals. The performance of the VTW algorithm was compared against an existing Falling-Edge, Variable Threshold (FEVT) algorithm. Varying levels of synthetic noise representing ventilator and high-frequency noise were added to in vivo slow-wave recordings. Sensitivity, positive-predictive value, area under the curve (A_roc) metric and percentage improvement metric (PIM) of activation phase identification accuracy were calculated. Compared to the existing FEVT algorithm, the VTW algorithm achieved similar performance in identifying the activation phase of slow-waves with various levels of ventilator noise. In the presence of high-frequency noise, the VTW algorithm improved the A_roc of the existing FEVT algorithm by 11.1%. The VTW algorithm can now be applied to analyze normal and abnormal slow-wave recordings.

Methods for High-Resolution Electrical Mapping in the Gastrointestinal Tract

Over the last two decades, high-resolution (HR) mapping has emerged as a powerful technique to study normal and abnormal bioelectrical events in the gastrointestinal (GI) tract. This technique, adapted from cardiology, involves the use of dense arrays of electrodes to track bioelectrical sequences in fine spatiotemporal detail. HR mapping has now been applied in many significant GI experimental studies informing and clarifying both normal physiology and arrhythmic behaviors in disease states. This review provides a comprehensive and critical analysis of current methodologies for HR electrical mapping in the GI tract, including extracellular measurement principles, electrode design and mapping devices, signal processing and visualization techniques, and translational research strategies. The scope of the review encompasses the broad application of GI HR methods from in vitro tissue studies to in vivo experimental studies, including in humans. Controversies and future directions for GI mapping methodologies are addressed, including emerging opportunities to better inform diagnostics and care in patients with functional gut disorders of diverse etiologies.

Improved Visualization of Gastrointestinal Slow Wave Propagation Using a Novel Wavefront-Orientation Interpolation Technique

OBJECTIVE

High-resolution mapping of gastrointestinal (GI) slow waves is a valuable technique for research and clinical applications. Interpretation of high-resolution GI mapping data relies on animations of slow wave propagation, but current methods remain as rudimentary, pixelated electrode activation animations. This study aimed to develop improved methods of visualizing high-resolution slow wave recordings that increases ease of interpretation.

METHODS

The novel method of "wavefront-orientation" interpolation was created to account for the planar movement of the slow wave wavefront, negate any need for distance calculations, remain robust in atypical wavefronts (i.e., dysrhythmias), and produce an appropriate interpolation boundary. The wavefront-orientation method determines the orthogonal wavefront direction and calculates interpolated values as the mean slow wave activation-time (AT) of the pair of linearly adjacent electrodes along that direction. Stairstep upsampling increased smoothness and clarity.

RESULTS

Animation accuracy of 17 human high-resolution slow wave recordings (64-256 electrodes) was verified by visual comparison to the prior method showing a clear improvement in wave smoothness that enabled more accurate interpretation of propagation, as confirmed by an assessment of clinical applicability performed by eight GI clinicians. Quantitatively, the new method produced accurate interpolation values compared to experimental data (mean difference 0.02 ± 0.05 s) and was accurate when applied solely to dysrhythmic data (0.02 ± 0.06 s), both within the error in manual AT marking (mean 0.2 s). Mean interpolation processing time was 6.0 s per wave.

CONCLUSION AND SIGNIFICANCE

These novel methods provide a validated visualization platform that will improve analysis of high-resolution GI mapping in research and clinical translation.