High-resolution mapping of gastric slow-wave recovery profiles: biophysical model, methodology, and demonstration of applications.

Slow waves play a central role in coordinating gastric motor activity. High-resolution mapping of extracellular potentials from the stomach provides spatiotemporal detail on normal and dysrhythmic slow-wave patterns. All mapping studies to date have focused exclusively on tissue activation; however, the recovery phase contains vital information on repolarization heterogeneity, the excitable gap, and refractory tail interactions but has not been investigated. Here, we report a method to identify the recovery phase in slow-wave mapping data. We first developed a mathematical model of unipolar extracellular potentials that result from slow-wave propagation. These simulations showed that tissue repolarization in such a signal is defined by the steepest upstroke beyond the activation phase (activation was defined by accepted convention as the steepest downstroke). Next, we mapped slow-wave propagation in anesthetized pigs by recording unipolar extracellular potentials from a high-resolution array of electrodes on the serosal surface. Following the simulation result, a wavelet transform technique was applied to detect repolarization in each signal by finding the maximum positive slope beyond activation. Activation-recovery (ARi) and recovery-activation (RAi) intervals were then computed. We hypothesized that these measurements of recovery profile would differ for slow waves recorded during normal and spatially dysrhythmic propagation. We found that the ARi of normal activity was greater than dysrhythmic activity (5.1 ± 0.8 vs. 3.8 ± 0.7 s; < 0.05), whereas RAi was lower (9.7 ± 1.3 vs. 12.2 ± 2.5 s; < 0.05). During normal propagation, RAi and ARi were linearly related with negative unit slope indicating entrainment of the entire mapped region. This relationship was weakened during dysrhythmia (slope: -0.96 ± 0.2 vs -0.71 ± 0.3; < 0.05). The theoretical basis of the extracellular gastric slow-wave recovery phase was defined using mathematical modeling. A novel technique utilizing the wavelet transform was developed and validated to detect the extracellular slow-wave recovery phase. In dysrhythmic wavefronts, the activation-to-recovery interval (ARi) was shorter and recovery-to-activation interval (RAi) was longer compared with normal wavefronts. During normal activation, RAi vs. ARi had a slope of -1, whereas the weakening of the slope indicated a dysrhythmic propagation.