Add like
Add dislike
Add to saved papers

A theoretical analysis of electrogastrography (EGG) signatures associated with gastric dysrhythmias.

Routine screening and accurate diagnosis of chronic gastrointestinal motility disorders represents a significant problem in current clinical practice. The electrogastrography (EGG) provides a non-invasive option for assessing gastric slow waves, as a means of diagnosing gastric dysrhythmias, but its uptake in motility practice has been limited partly due to an incomplete sensitivity and specificity. This paper presents the development of a human whole-organ gastric model to enable virtual (insilico) testing of gastric electrophysiological dispersion in order to improve the diagnostic accuracy of EGG. The model was developed to simulate normal gastric slow wave conduction as well as three types of dysrhythmias identified in recent highresolution gastric mapping studies: conduction block, re-entry, and ectopic pacemaking. The stomach simulations were then applied in a torso model to identify predicted EGG signatures of normal and dysrhythmic slow wave profiles. The resulting EGG data were compared using percentage differences and correlation coefficients. Virtual EGG channels that demonstrated a percentage difference over 100% and a correlation coefficient less than 0.2 (threshold relaxed to 0.5 for the ectopic pacemaker case) were further investigated for their specific distinguishing features. In particular, anatomical locations from the epigastric region and specific channel configurations were identified that could be used to clinically diagnose the three classes of human gastric dysrhythmia. These locations and channels predicted by simulations present a promising methodology for improving the clinical reliability and applications of EGG.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app