Literature DB >> 19643697

A tissue framework for simulating the effects of gastric electrical stimulation and in vivo validation.

Peng Du1, Greg O'Grady, John A Windsor, Leo K Cheng, Andrew J Pullan.   

Abstract

Gastric pacing is used to modulate normal or abnormal gastric slow-wave activity for therapeutic purposes. New protocols are required that are optimized for motility outcomes and energy efficiency. A computational tissue model was developed, incorporating smooth muscle and interstitial cell of Cajal layers, to enable predictive simulations of slow-wave entrainment efficacy under different pacing frequencies. Concurrent experimental validation was performed via high-resolution entrainment mapping in a porcine model (bipolar pacing protocol: 2 mA amplitude; 400 ms pulsewidth; 17-s period; midcorpus). Entrained gastric slow-wave activity was found to be anisotropic (circular direction: 8.51 mm x s(-1); longitudinal: 4.58 mm x s(-1)), and the simulation velocities were specified accordingly. Simulated and experimental slow-wave activities demonstrated satisfactory agreement, showing similar propagation patterns and frequencies (3.5-3.6 cycles per minute), and comparable zones of entrainment (ZOEs; 64 cm(2)). The area of ZOE achieved was found to depend on the phase interactions between the native and entrained activities. This model allows the predictions of phase interactions between native and entrained activities, and will be useful for determining optimal frequencies for gastric pacing, including multichannel pacing studies. The model provides a framework for the development of more sophisticated predictive gastric pacing simulations in future.

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Year:  2009        PMID: 19643697      PMCID: PMC4169301          DOI: 10.1109/TBME.2009.2027690

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  33 in total

1.  Retrograde gastric pacing reduces food intake and delays gastric emptying in humans: a potential therapy for obesity?

Authors:  Shukun Yao; Meiyun Ke; Zhifeng Wang; Dabo Xu; Yanli Zhang; J D Z Chen
Journal:  Dig Dis Sci       Date:  2005-09       Impact factor: 3.199

2.  Efficiency and efficacy of multi-channel gastric electrical stimulation.

Authors:  J D Z Chen; X Xu; J Zhang; M Abo; X Lin; R W McCallum; B Ross
Journal:  Neurogastroenterol Motil       Date:  2005-12       Impact factor: 3.598

3.  Cardiac electrophysiology and tissue structure: bridging the scale gap with a joint measurement and modelling paradigm.

Authors:  Mark L Trew; Bryan J Caldwell; Gregory B Sands; Darren A Hooks; Dean C-S Tai; Travis M Austin; Ian J LeGrice; Andrew J Pullan; Bruce H Smaill
Journal:  Exp Physiol       Date:  2006-01-23       Impact factor: 2.969

4.  The slow wave does not propagate across the gastroduodenal junction in the isolated feline preparation.

Authors:  W J Lammers; B Stephen; E Adeghate; S Ponery; O Pozzan
Journal:  Neurogastroenterol Motil       Date:  1998-08       Impact factor: 3.598

5.  Computer model of gastric electrical stimulation.

Authors:  M Mintchev; K Bowes
Journal:  Ann Biomed Eng       Date:  1997 Jul-Aug       Impact factor: 3.934

6.  Role of the gastric pacesetter potential defined by electrical pacing.

Authors:  K A Kelly; R C La Force
Journal:  Can J Physiol Pharmacol       Date:  1972-10       Impact factor: 2.273

7.  Efficacy of electrical stimulation at frequencies higher than basal rate in canine stomach.

Authors:  B O Familoni; T L Abell; D Nemoto; G Voeller; B Johnson
Journal:  Dig Dis Sci       Date:  1997-05       Impact factor: 3.199

8.  Slow waves actively propagate at submucosal surface of circular layer in canine colon.

Authors:  K M Sanders; R Stevens; E Burke; S W Ward
Journal:  Am J Physiol       Date:  1990-08

9.  Pacemaker potentials generated by interstitial cells of Cajal in the murine intestine.

Authors:  Yoshihiko Kito; Sean M Ward; Kenton M Sanders
Journal:  Am J Physiol Cell Physiol       Date:  2004-11-10       Impact factor: 4.249

Review 10.  Anatomically realistic multiscale models of normal and abnormal gastrointestinal electrical activity.

Authors:  Leo K Cheng; Rie Komuro; Travis M Austin; Martin L Buist; Andrew J Pullan
Journal:  World J Gastroenterol       Date:  2007-03-07       Impact factor: 5.742

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  13 in total

Review 1.  Multiscale modeling of gastrointestinal electrophysiology and experimental validation.

Authors:  Peng Du; Greg O'Grady; John B Davidson; Leo K Cheng; Andrew J Pullan
Journal:  Crit Rev Biomed Eng       Date:  2010

2.  A multiscale model of the electrophysiological basis of the human electrogastrogram.

Authors:  Peng Du; Gregory O'Grady; Leo K Cheng; Andrew J Pullan
Journal:  Biophys J       Date:  2010-11-03       Impact factor: 4.033

3.  Effects of electrical stimulation on isolated rodent gastric smooth muscle cells evaluated via a joint computational simulation and experimental approach.

Authors:  P Du; S Li; G O'Grady; L K Cheng; A J Pullan; J D Z Chen
Journal:  Am J Physiol Gastrointest Liver Physiol       Date:  2009-08-06       Impact factor: 4.052

4.  High-resolution entrainment mapping of gastric pacing: a new analytical tool.

Authors:  Gregory O'Grady; Peng Du; Wim J E P Lammers; John U Egbuji; Pulasthi Mithraratne; Jiande D Z Chen; Leo K Cheng; John A Windsor; Andrew J Pullan
Journal:  Am J Physiol Gastrointest Liver Physiol       Date:  2009-11-19       Impact factor: 4.052

5.  Tissue-specific mathematical models of slow wave entrainment in wild-type and 5-HT(2B) knockout mice with altered interstitial cells of Cajal networks.

Authors:  Peng Du; Greg O'Grady; Simon J Gibbons; Rita Yassi; Rachel Lees-Green; Gianrico Farrugia; Leo K Cheng; Andrew J Pullan
Journal:  Biophys J       Date:  2010-05-19       Impact factor: 4.033

6.  Cellular automaton model for simulating tissue-specific intestinal electrophysiological activity.

Authors:  Jerry Gao; Peng Du; Greg O'Grady; Rosalind Archer; Simon J Gibbons; Gianrico Farrugia; Leo K Cheng
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

7.  Origin, propagation and regional characteristics of porcine gastric slow wave activity determined by high-resolution mapping.

Authors:  J U Egbuji; G O'Grady; P Du; L K Cheng; W J E P Lammers; J A Windsor; A J Pullan
Journal:  Neurogastroenterol Motil       Date:  2010-07-06       Impact factor: 3.598

8.  Falling-edge, variable threshold (FEVT) method for the automated detection of gastric slow wave events in high-resolution serosal electrode recordings.

Authors:  Jonathan C Erickson; Gregory O'Grady; Peng Du; Chibuike Obioha; Wenlian Qiao; William O Richards; L Alan Bradshaw; Andrew J Pullan; Leo K Cheng
Journal:  Ann Biomed Eng       Date:  2009-12-19       Impact factor: 3.934

Review 9.  Gastrointestinal system.

Authors:  Leo K Cheng; Gregory O'Grady; Peng Du; John U Egbuji; John A Windsor; Andrew J Pullan
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2010 Jan-Feb

10.  A biophysically based finite-state machine model for analyzing gastric experimental entrainment and pacing recordings.

Authors:  Shameer Sathar; Mark L Trew; Peng Du; Greg O'Grady; Leo K Cheng
Journal:  Ann Biomed Eng       Date:  2013-11-26       Impact factor: 3.934

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