The gastrointestinal electrical mapping suite (GEMS): software for analyzing and visualizing high-resolution (multi-electrode) recordings in spatiotemporal detail

BMC Gastroenterology

Jonathan C Erickson²  Leo K Cheng¹  Andrew J Pullan⁵  Timothy R Angeli³  Peng Du¹  Nira Paskaranandavadivel¹  Gregory O’Grady⁴  Rita Yassi¹ 

[1] Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand;Department of Physics-Engineering, Washington & Lee University, Lexington, VA, USA;Riddet Institute, Auckland, New Zealand;Department of Surgery, The University of Auckland, Private Bag 92019, Auckland, New Zealand;Department of Surgery, Vanderbilt University, Vanderbilt, TN, USA

关键词: Tachygastria;    Motility;    Electrophysiology;    Signal processing;    Spike;    Slow wave;   

Others  :  1113057
DOI  :  10.1186/1471-230X-12-60

 received in 2011-07-25, accepted in 2012-06-06,  发布年份 2012

【 摘 要 】

Background

Gastrointestinal contractions are controlled by an underlying bioelectrical activity. High-resolution spatiotemporal electrical mapping has become an important advance for investigating gastrointestinal electrical behaviors in health and motility disorders. However, research progress has been constrained by the low efficiency of the data analysis tasks. This work introduces a new efficient software package: GEMS (Gastrointestinal Electrical Mapping Suite), for analyzing and visualizing high-resolution multi-electrode gastrointestinal mapping data in spatiotemporal detail.

Results

GEMS incorporates a number of new and previously validated automated analytical and visualization methods into a coherent framework coupled to an intuitive and user-friendly graphical user interface. GEMS is implemented using MATLAB®, which combines sophisticated mathematical operations and GUI compatibility. Recorded slow wave data can be filtered via a range of inbuilt techniques, efficiently analyzed via automated event-detection and cycle clustering algorithms, and high quality isochronal activation maps, velocity field maps, amplitude maps, frequency (time interval) maps and data animations can be rapidly generated. Normal and dysrhythmic activities can be analyzed, including initiation and conduction abnormalities. The software is distributed free to academics via a community user website and forum (http://sites.google.com/site/gimappingsuite webcite).

Conclusions

This software allows for the rapid analysis and generation of critical results from gastrointestinal high-resolution electrical mapping data, including quantitative analysis and graphical outputs for qualitative analysis. The software is designed to be used by non-experts in data and signal processing, and is intended to be used by clinical researchers as well as physiologists and bioengineers. The use and distribution of this software package will greatly accelerate efforts to improve the understanding of the causes and clinical consequences of gastrointestinal electrical disorders, through high-resolution electrical mapping.

【 授权许可】

   
2012 Yassi et al.; licensee BioMed Central Ltd

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Huizinga JD, Lammers WJEP: Gut peristalsis is coordinated by a multitude of cooperating mechanisms. Am J Physiol Gastrointest Liver Physiol 2009, 296:1-8.
• [2]Chen JD, Lin Z, Yin Y: Electrogastrography. In In GI Motility Testing: A Laboratory and Office Handbook. Edited by Parkman HP, McCallum RW, Rao SC. SLACK Incorporated, Thorofare; 2011:81-92.
• [3]Leahy A, Besherdas K, Clayman C, Mason I, Epstein O: Abnormalities of the electrogastrogram in functional gastrointestinal disorders. Am J Gastroenterol 1999, 94:1023-1028.
• [4]Grover M, Farrugia G, Lurken MS, et al.: Cellular changes in diabetic and idiopathic gastroparesis. Gastroenterology 2011, 140:1575-1585. e8
• [5]Du P, O'Grady G, Egbuji JU, et al.: High-resolution mapping of in vivo gastrointestinal slow wave activity using flexible printed circuit board electrodes: methodology and validation. Ann Biomed Eng 2009, 37:839-846.
• [6]Egbuji JU, O'Grady G, Du P, et al.: Origin, propagation and regional characteristics of porcine gastric slow wave activity determined by high-resolution mapping. Neurogastroenterol Motil 2010, 22:e292-e300.
• [7]Lammers WJ, Ver Donck L, Stephen B, Smets D, Schuurkes JA: Origin and propagation of the slow wave in the canine stomach: the outlines of a gastric conduction system. Am J Physiol Gastrointest Liver Physiol 2009, 296:1200-1210.
• [8]O'Grady G, Du P, Cheng LK, et al.: The origin and propagation of human gastric slow wave activity defined by high-resolution mapping. Am J Physiol Gastrointest Liver Physiol 2010, 299:585-592.
• [9]Lammers WJEP, Ver Donck L, Stephen B, Smets D, Schuurkes JAJ: Focal activities and re-entrant propagations as mechanisms of gastric tachyarrhythmias. Gastroenterology 2008, 135:1601-1611.
• [10]O'Grady G, Egbuji JU, Du P, et al.: High-resolution spatial analysis of slow wave initiation and conduction in porcine gastric dysrhythmia. Neurogastroenterol Motil 2011, 23:e345-e355.
• [11]O'Grady G, Du P, Lammers WJ, et al.: High-resolution entrainment mapping for gastric pacing: a new analytic tool. Am J Physiol Gastrointest Liver Physiol 2010, 298:314-321.
• [12]O'Grady G, Angeli TR, Cheng LK, et al.: Aberrant initiation and conduction of slow wave activity in diabetic and idiopathic gastroparesis. Gastroenterology 2011, 140:S705-S706.
• [13]Erickson JC, O'Grady G, Du P, et al.: Falling-edge, variable threshold (FEVT) method for the automated detection of gastric slow wave events in serosal high-resolution electrical recordings. Ann Biomed Eng 2010, 38:1511-1529.
• [14]Erickson JC, O'Grady G, Du P, Egbuji JU, Pullan AJ, Cheng LK: Automated cycle partitioning and visualization of high-resolution activation time maps of gastric slow wave recordings: the Region Growing Using Polynomial Surface-estimate stabilization (REGROUPS) Algorithm. Ann Biomed Eng 2011, 39:469-483.
• [15]Paskaranandavadivel N, O'Grady G, Du P, Pullan AJ, Cheng LK: An improved method for the estimation and visualization of velocity fields from gastric high-resolution electrical mapping. IEEE Trans Biomed Eng 2012.
• [16]Ideker RE, Smith WM, Wolf P, Danieley ND, Bartram FR: Simultaneous multichannel cardiac mapping systems. Pacing Clin Electrophysiol 1987, 10:281-292.
• [17]Rogers JM, Bayly PV, Ideker RE, Smith WM: Quantitative techniques for analyzing high-resolution cardiac-mapping data. IEEE Eng Med Biol Mag 1998, 17:62-72.
• [18]Potse M, Linnenbank AC, Grimbergen CA: Software design for analysis of multichannel intracardial and body surface electrocardiograms. Comp Meth Prog Biomed. 2002, 69:225-236.
• [19]Shenasa M, Hindricks G, Borggrefe M, Breithardt G: Cardiac Mapping 3rd Edition. Blackwell Publishing Ltd, Oxford; 2009.
• [20]Lammers WJ: SmoothMap [Computer Program]. Version 3.05. Al Ain, United Arab Emirates. 2009. http://www.smoothmap.org webcite
• [21]Paskaranandavadivel N, Cheng LK, Du P, O'Grady G, Pullan AJ: Improved signal processing techniques for the analysis of high resolution serosal slow wave activity in the stomach. Conf Proc IEEE Eng Med Biol Soc 2011, 1737-1740.
• [22]O'Grady G: Gastrointestinal extracellular electrical recordings: fact or artifact? Neurogastroenterol Motil 2012, 24:1-6.
• [23]Zhang D: Wavelet approach for ECG baseline wander correction and noise reduction. Conf Proc IEEE Eng Med Biol Sci 2005, 1212-1215.
• [24]Savitzky A, Golay MJE: Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 1964, 36:1627-1639.
• [25]Park SB, Noh YS, Park SJ, Yoon HR: An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation. Med Biol Eng Comput 2008, 46:147-158.
• [26]O'Grady G, Paskaranandavadivel N, Angeli T, et al.: A comparison of gold vs silver electrode contacts for high-resolution gastric electrical mapping using flexible printed circuit board electrodes. Physiol Meas 2011, 32:N13-N22.
• [27]Rogers JM, Bayly PV: Quantitative Analysis of Complex Rhythms. In In Quantitative Cardiac Electrophysiology. Edited by Cabo C, Rosenbaum DS. Marcel Decker Inc, New York; 2002:403-428.
• [28]O'Grady G, Angeli TR, Cheng LK, et al.: Emergence of circumferential slow wave propagation during gastric dysrhythmias in diabetic gastroparesis. Gastroenterology 2011, 140:705.
• [29]Du P, O'Grady G, Paskaranandavadivel N, et al.: Quantification of velocity anisotropy during gastric electrical arrhythmia. Conf Proc IEEE Eng Med Biol Soc 2011, 4402-4405.
• [30]Du P, Qiao W, O'Grady G, et al.: Automated detection of gastric slow wave events and estimation of propagation velocity vector fields from serosal high-resolution mapping. Conf Proc IEEE Eng Med Biol Sci 2009, 2527-2530.
• [31]Hazewinkel M: Point of inflection. Springer, New York; 2001.
• [32]Bull S, O'Grady G, Cheng LK, Pullan AJ: A framework for the online analysis of multi-electrode gastric slow wave recordings. Conf Proc IEEE Eng Med Biol Soc 2011, 1741-1744.
• [33]Angeli TR, O'Grady G, Erickson JC, et al.: Mapping small intestine bioelectrical activity using high-resolution printed-circuit-board electrodes. Conf Proc IEEE Eng Med Biol Soc 2011, 4951-4954.
• [34]Ideker RE, Smith WM, Blanchard SM, et al.: The assumptions of isochronal cardiac mapping. Pacing Clin Electrophysiol 1989, 12:456-478.
• [35]de Bakker JM, Wittkampf FH: The pathophysiologic basis of fractionated and complex electrograms and the impact of recording techniques on their detection and interpretation. Circ Arrhythm Electrophysiol 2010, 3:204-213.
• [36]Potse M, Linnenbank AC, Grimbergen CA: Automated generation of isochronal maps in the presence of activation block. Int J Bioelectromagnetism. 2002, 4:115-116.
• [37]Lammers WJ, Ver Donck L, Schuurkes JA, Stephen B: Peripheral pacemakers and patterns of slow wave propagation in the canine small intestine in vivo. Can J Physiol Pharmacol 2005, 83:1031-1043.
• [38]Lammers WJ, Stephen B, Slack JR, Dhanasekaran S: Anisotropic propagation in the small intestine. Neurogastroenterol Motil 2002, 14:357-364.
• [39]Hammad FT, Lammers WJ, Stephen B, Lubbad L: Propagation characteristics of the electrical impulse in the normal and obstructed ureter as determined at high electrophysiological resolution. BJU Int 2011, 108:E36-E42.
• [40]Lammers WJ, Donck LV, Schuurkes JA, Stephen B: Longitudinal and circumferential spike patches in the canine small intestine in vivo. Am J Physiol Gastrointest Liver Physiol 2003, 285:G1014-G1027.
• [41]Du P, O'Grady G, Cheng LK, Pullan AJ: A multi-scale model of the electrophysiological basis of the human electrogastrogram. Biophys J 2010, 99:2784-2792.