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Related Experiment Video

Updated: May 14, 2026

Coordinate Mapping of Hyolaryngeal Mechanics in Swallowing
14:13

Coordinate Mapping of Hyolaryngeal Mechanics in Swallowing

Published on: May 6, 2014

Three-dimensional analysis of pharyngeal high-resolution manometry data.

Zhixian Geng1, Matthew R Hoffman, Corinne A Jones

  • 1Department of Surgery, Division of Otolaryngology-Head and Neck Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

The Laryngoscope
|February 19, 2013
PubMed
Summary

A new 3D analysis of high-resolution manometry (HRM) data improves the classification of swallowing disorders. This advanced method, combined with artificial neural networks, offers significant potential for clinical diagnosis.

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Area of Science:

  • Gastroenterology and Hepatology
  • Medical Imaging and Instrumentation
  • Swallowing Physiology

Background:

  • High-resolution manometry (HRM) is crucial for quantifying pharyngeal pressure events during swallowing.
  • Traditional HRM analysis is primarily 2D, focusing on single sensor data.
  • A novel 3D approach integrating data from adjacent sensors is proposed.

Purpose of the Study:

  • To develop and evaluate a 3D analysis method for pharyngeal HRM data.
  • To compare the diagnostic accuracy of 2D versus 3D HRM analysis in classifying normal and disordered swallows.
  • To assess the utility of artificial neural networks (ANNs) in conjunction with 2D and 3D HRM data.

Main Methods:

  • A case series design was employed to evaluate the new 3D data analysis technique.

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Related Experiment Videos

Last Updated: May 14, 2026

Coordinate Mapping of Hyolaryngeal Mechanics in Swallowing
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Coordinate Mapping of Hyolaryngeal Mechanics in Swallowing

Published on: May 6, 2014

Visualization and Analysis of Pharyngeal Arch Arteries using Whole-mount Immunohistochemistry and 3D Reconstruction
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Published on: March 31, 2020

Simultaneous Laryngopharyngeal and Conventional Esophageal pH Monitoring
06:46

Simultaneous Laryngopharyngeal and Conventional Esophageal pH Monitoring

Published on: December 14, 2020

  • 1,324 swallows from 16 healthy subjects and 61 patients with dysphagia were analyzed.
  • 2D single-sensor pressure integrals and 3D multi-sensor pressure volumes were calculated for the velopharynx, tongue base, and upper esophageal sphincter (UES).
  • An artificial neural network (ANN) was used to compare the classification accuracy of 2D and 3D parameters.

    • Main Results:

    • The 3D analysis achieved a maximal classification accuracy of 86.71% ± 1.47%, outperforming the 2D analysis which reached 83.36% ± 1.42%.
    • Combining both 2D and 3D parameters with an ANN resulted in a high classification accuracy of 96.99% ± 0.51%.
    • The inclusion of 2D parameters alongside 3D parameters further enhanced classification accuracy to 96.32% ± 1.05%.

    Conclusions:

    • Three-dimensional analysis of pharyngeal HRM data significantly improves the classification of normal versus disordered swallows.
    • Artificial neural network analysis demonstrates high effectiveness with both 2D and 3D HRM data.
    • The combined 2D/3D HRM analysis shows considerable potential for clinical application in diagnosing swallowing disorders.