High-resolution in vivo monophasic gastric slow waves to quantify activation and recovery profiles

Background Gastric bio-electrical slow waves are, in part, responsible for coordinating motility. Spatial dynamics about the recovery phase of slow wave recordings have not been thoroughly investigated due to the lack of suitable experimental techniques. Methods A high-resolution multi-channel suction electrode array was developed and applied in pigs to acquire monophasic gastric slow waves. Signal characteristics were verified against biphasic slow waves recorded by conventional surface contact electrode arrays. Monophasic slow wave events were categorized into two groups based on their morphological characteristics, after which their amplitudes, activation to recovery intervals, and gradients were quantified and compared. Coverage of activation and recovery maps for both electrode types were calculated and compared. Key Results Monophasic slow waves had a more pronounced recovery phase with a higher gradient than biphasic slow waves (0.5 +/- 0.1 vs. 0.3 +/- 0.1 mV center dot s(-1)). Between the 2 groups of monophasic slow waves, there was a significant difference in amplitude (1.8 +/- 0.5 vs. 1.1 +/- 0.2 mV), activation time gradient (0.8 +/- 0.2 vs. 0.3 +/- 0.1 mV center dot s(-1)), and recovery time gradient (0.5 +/- 0.1 vs. 0.3 +/- 0.1 mV center dot s(-1)). For the suction and conventional contact electrode arrays, the recovery maps had reduced coverage compared to the activation maps (4 +/- 6% and 43 +/- 11%, respectively). Conclusions and Inferences A novel high-resolution multi-channel suction electrode array was developed and applied in vivo to record monophasic gastric slow waves. Slow wave recovery phase analysis could be performed more efficiently on monophasic signals compared with biphasic signals, due to the more identifiable recovery phases.

Automated summary

A high-resolution multi-channel suction electrode array was developed and applied in vivo to record monophasic gastric slow waves, which had a more pronounced recovery phase with a higher gradient compared to biphasic slow waves. The recovery phase analysis of monophasic signals could be performed more efficiently due to the more identifiable recovery phases.