T R Angeli1, P Du1, N Paskaranandavadivel1, S Sathar1, A Hall2, S J Asirvatham3, G Farrugia4, J A Windsor2, L K Cheng1,5, G O'Grady1,2. 1. Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand. 2. Department of Surgery, University of Auckland, Auckland, New Zealand. 3. Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA. 4. Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA. 5. Department of Surgery, Vanderbilt University, Nashville, TN, USA.
Abstract
BACKGROUND: Gastric motility is coordinated by bioelectrical slow waves, and gastric dysrhythmias are reported in motility disorders. High-resolution (HR) mapping has advanced the accurate assessment of gastric dysrhythmias, offering promise as a diagnostic technique. However, HR mapping has been restricted to invasive surgical serosal access. This study investigates the feasibility of HR mapping from the gastric mucosal surface. METHODS: Experiments were conducted in vivo in 14 weaner pigs. Reference serosal recordings were performed with flexible-printed-circuit (FPC) arrays (128-192 electrodes). Mucosal recordings were performed by two methods: (i) FPC array aligned directly opposite the serosal array, and (ii) cardiac mapping catheter modified for gastric mucosal recordings. Slow-wave propagation and morphology characteristics were quantified and compared between simultaneous serosal and mucosal recordings. KEY RESULTS: Slow-wave activity was consistently recorded from the mucosal surface from both electrode arrays. Mucosally recorded slow-wave propagation was consistent with reference serosal activation pattern, frequency (P≥.3), and velocity (P≥.4). However, mucosally recorded slow-wave morphology exhibited reduced amplitude (65-72% reduced, P<.001) and wider downstroke width (18-31% wider, P≤.02), compared to serosal data. Dysrhythmias were successfully mapped and classified from the mucosal surface, accorded with serosal data, and were consistent with known dysrhythmic mechanisms in the porcine model. CONCLUSIONS & INFERENCES: High-resolution gastric electrical mapping was achieved from the mucosal surface, and demonstrated consistent propagation characteristics with serosal data. However, mucosal signal morphology was attenuated, demonstrating necessity for optimized electrode designs and analytical algorithms. This study demonstrates feasibility of endoscopic HR mapping, providing a foundation for advancement of minimally invasive spatiotemporal gastric mapping as a clinical and scientific tool.
BACKGROUND: Gastric motility is coordinated by bioelectrical slow waves, and gastric dysrhythmias are reported in motility disorders. High-resolution (HR) mapping has advanced the accurate assessment of gastric dysrhythmias, offering promise as a diagnostic technique. However, HR mapping has been restricted to invasive surgical serosal access. This study investigates the feasibility of HR mapping from the gastric mucosal surface. METHODS: Experiments were conducted in vivo in 14 weaner pigs. Reference serosal recordings were performed with flexible-printed-circuit (FPC) arrays (128-192 electrodes). Mucosal recordings were performed by two methods: (i) FPC array aligned directly opposite the serosal array, and (ii) cardiac mapping catheter modified for gastric mucosal recordings. Slow-wave propagation and morphology characteristics were quantified and compared between simultaneous serosal and mucosal recordings. KEY RESULTS: Slow-wave activity was consistently recorded from the mucosal surface from both electrode arrays. Mucosally recorded slow-wave propagation was consistent with reference serosal activation pattern, frequency (P≥.3), and velocity (P≥.4). However, mucosally recorded slow-wave morphology exhibited reduced amplitude (65-72% reduced, P<.001) and wider downstroke width (18-31% wider, P≤.02), compared to serosal data. Dysrhythmias were successfully mapped and classified from the mucosal surface, accorded with serosal data, and were consistent with known dysrhythmic mechanisms in the porcine model. CONCLUSIONS & INFERENCES: High-resolution gastric electrical mapping was achieved from the mucosal surface, and demonstrated consistent propagation characteristics with serosal data. However, mucosal signal morphology was attenuated, demonstrating necessity for optimized electrode designs and analytical algorithms. This study demonstrates feasibility of endoscopic HR mapping, providing a foundation for advancement of minimally invasive spatiotemporal gastric mapping as a clinical and scientific tool.
Authors: Timothy R Angeli; Peng Du; Niranchan Paskaranandavadivel; Patrick W M Janssen; Arthur Beyder; Roger G Lentle; Ian P Bissett; Leo K Cheng; Gregory O'Grady Journal: J Physiol Date: 2013-05-27 Impact factor: 5.182
Authors: Timothy R Angeli; Leo K Cheng; Peng Du; Tim Hsu-Han Wang; Cheryl E Bernard; Maria-Giuliana Vannucchi; Maria Simonetta Faussone-Pellegrini; Christopher Lahr; Ryash Vather; John A Windsor; Gianrico Farrugia; Thomas L Abell; Gregory O'Grady Journal: Gastroenterology Date: 2015-04-08 Impact factor: 22.682
Authors: G O'Grady; N Paskaranandavadivel; T R Angeli; P Du; J A Windsor; L K Cheng; A J Pullan Journal: Physiol Meas Date: 2011-01-21 Impact factor: 2.833
Authors: Madhusudan Grover; Gianrico Farrugia; Matthew S Lurken; Cheryl E Bernard; Maria Simonetta Faussone-Pellegrini; Thomas C Smyrk; Henry P Parkman; Thomas L Abell; William J Snape; William L Hasler; Aynur Ünalp-Arida; Linda Nguyen; Kenneth L Koch; Jorges Calles; Linda Lee; James Tonascia; Frank A Hamilton; Pankaj J Pasricha Journal: Gastroenterology Date: 2011-02-04 Impact factor: 22.682
Authors: Timothy R Angeli; Gregory O'Grady; Niranchan Paskaranandavadivel; Jonathan C Erickson; Peng Du; Andrew J Pullan; Ian P Bissett; Leo K Cheng Journal: J Neurogastroenterol Motil Date: 2013-04-16 Impact factor: 4.924
Authors: Tim H-H Wang; Timothy R Angeli; Grant Beban; Peng Du; Francesca Bianco; Simon J Gibbons; John A Windsor; Leo K Cheng; Gregory O'Grady Journal: Am J Physiol Gastrointest Liver Physiol Date: 2019-06-06 Impact factor: 4.052
Authors: Terence P Mayne; Niranchan Paskaranandavadivel; Jonathan C Erickson; Gregory OGrady; Leo K Cheng; Timothy R Angeli Journal: IEEE Trans Biomed Eng Date: 2018-02 Impact factor: 4.538
Authors: Atchariya Sukasem; Stefan Calder; Timothy R Angeli-Gordon; Christopher N Andrews; Gregory O'Grady; Armen Gharibans; Peng Du Journal: Biomed Eng Online Date: 2022-06-27 Impact factor: 3.903