Discriminating movements of liquid and gas in the rabbit colon with impedance manometry. Issue 5 (13th December 2017) - Mohd Rosli, R.; Leibbrandt, R. E.; Wiklendt, L.; Costa, M.; Wattchow, D. A.; Spencer, N. J.; Brookes, S. J.; Omari, T. I.; Dinning, P. G.
Abstract: Background: High‐resolution impedance manometry is a technique that is well established in esophageal motility studies for relating motor patterns to bolus flow. The use of this technique in the colon has not been established. Methods: In isolated segments of rabbit proximal colon, we recorded motor patterns and the movement of liquid or gas boluses with a high‐resolution impedance manometry catheter. These detected movements were compared to video recorded changes in gut diameter. Using the characteristic shapes of the admittance (inverse of impedance) and pressure signals associated with gas or liquid flow we developed a computational algorithm for the automated detection of these events. Key Results: Propagating contractions detected by video were also recorded by manometry and impedance. Neither pressure nor admittance signals alone could distinguish between liquid and gas transit, however the precise relationship between admittance and pressure signals during bolus flow could. Training our computational algorithm upon these characteristic shapes yielded a detection accuracy of 87.7% when compared to gas or liquid bolus events detected by manual analysis. Conclusions & inferences: Characterizing the relationship between both admittance and pressure recorded with high‐resolution impedance manometry can not only help in detecting luminal transit in real time, but also distinguishes between liquid and gaseous content. This technique holds promise for determining the propulsive nature of human colonic motor patterns. Abstract : Using a high‐resolution impedance manometry catheter in an isolated rabbit colon, we have characterized the relationship that exists between pressure and impedance to identify the passage of intraluminal liquid or gas. Using the characteristic shape of the pressure/impedances signals, we developed an automated approach to identify episodes of liquid or gas transit.