Gastric disorders are increasingly prevalent, but reliable noninvasive tools to objectively assess gastric function are lacking. Body-surface gastric mapping (BSGM) is a noninvasive method for the detection of gastric electrophysiological features, which are correlated with symptoms in patients with gastroparesis and functional dyspepsia. Previous studies have validated the relationship between serosal and cutaneous recordings from limited number of channels. This study aimed to comprehensively evaluate the basis of BSGM from 64 cutaneous channels and reliably identify spatial biomarkers associated with slow-wave dysrhythmias. High-resolution electrode arrays were placed to simultaneously capture slow waves from the gastric serosa (32 × 6 electrodes at 4 mm spacing) and epigastrium (8 × 8 electrodes at 20 mm spacing) in 14 porcine subjects. BSGM signals were processed based on a combination of wavelet and phase information analyses. A total of 1,185 individual cycles of slow waves were assessed, out of which 897 (76%) were classified as normal antegrade waves, occurring in 10 (71%) subjects studied. BSGM accurately detected the underlying slow wave in terms of frequency ( = 0.99, = 0.43) as well as the direction of propagation ( = 0.41, -measure: 0.92). In addition, the cycle-by-cycle match between BSGM and transitions of gastric slow wave dysrhythmias was demonstrated. These results validate BSGM as a suitable method for noninvasively and accurately detecting gastric slow-wave spatiotemporal profiles from the body surface. Gastric dysfunctions are associated with abnormalities in the gastric bioelectrical slow waves. Noninvasive detection of gastric slow waves from the body surface can be achieved through multichannel, high-resolution, body-surface gastric mapping (BSGM). BSGM matched the spatiotemporal characteristics of gastric slow waves recorded directly and simultaneously from the serosal surface of the stomach. Abnormal gastric slow waves, such as retrograde propagation, ectopic pacemaker, and colliding wavefronts can be detected by changes in the phase of BSGM.

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http://dx.doi.org/10.1152/ajpgi.00049.2022DOI Listing

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