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Automatic Assessment of Human Gastric Motility and Emptying from Dynamic 3D Magnetic Resonance Imaging

Kun-Han Lu, Zhongming Liu, Deborah Jaffey, John Wo, Kristine Mosier, Jiayue Cao, Xiaokai Wang, Terry L Powley
doi: https://doi.org/10.1101/2020.12.11.421743
Kun-Han Lu
1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
3Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
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  • For correspondence: tomkhlu@gmail.com powleyt@purdue.edu
Zhongming Liu
4Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
5Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
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Deborah Jaffey
2Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
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John Wo
6Indiana University School of Medicine, Indianapolis, IN, USA
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Kristine Mosier
6Indiana University School of Medicine, Indianapolis, IN, USA
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Jiayue Cao
4Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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Xiaokai Wang
4Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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Terry L Powley
2Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
3Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
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  • For correspondence: tomkhlu@gmail.com powleyt@purdue.edu
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Abstract

Background Time-sequenced magnetic resonance imaging (MRI) of the stomach is an emerging technique for non-invasive assessment of gastric emptying and motility. However, an automated and systematic image processing pipeline for analyzing dynamic 3D (i.e., 4D) gastric MRI data is not yet available. This study introduces an MRI protocol for imaging the stomach with high spatiotemporal isotropic resolution and provides an integrated pipeline for assessing gastric emptying and motility simultaneously.

Methods Diet contrast-enhanced MRI images were acquired from seventeen healthy humans after they consumed a naturalistic contrast meal. An automated image processing pipeline was developed to correct for respiratory motion, to segment and compartmentalize the lumen-enhanced stomach, to quantify total gastric and compartmental emptying, and to compute and visualize gastric motility on the surface of the stomach.

Key Results The gastric segmentation reached an accuracy of 91.10±0.43% with the Type-I error and Type-II error being 0.11±0.01% and 0.22±0.01%, respectively. Gastric volume decreased 34.64±2.8% over 1 hour where the emptying followed a linear-exponential pattern. The gastric motility showed peristaltic patterns with a median = 4 wave-fronts (range 3 - 6) and a mean frequency of 3.09±0.07 cycles per minute (CPM). Further, the contractile amplitude was stronger in the antrum than in the corpus (antrum vs. corpus: 5.18±0.24 vs. 3.30±0.16 mm; p < .001).

Conclusions & Inferences The automated, streamlined software can process dynamic 3D MRI images and produce comprehensive and personalized profiles of gastric motility and emptying. This software will facilitate the application of MRI for monitoring gastric dynamics in research and clinical settings.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted December 11, 2020.
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Automatic Assessment of Human Gastric Motility and Emptying from Dynamic 3D Magnetic Resonance Imaging
Kun-Han Lu, Zhongming Liu, Deborah Jaffey, John Wo, Kristine Mosier, Jiayue Cao, Xiaokai Wang, Terry L Powley
bioRxiv 2020.12.11.421743; doi: https://doi.org/10.1101/2020.12.11.421743
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Automatic Assessment of Human Gastric Motility and Emptying from Dynamic 3D Magnetic Resonance Imaging
Kun-Han Lu, Zhongming Liu, Deborah Jaffey, John Wo, Kristine Mosier, Jiayue Cao, Xiaokai Wang, Terry L Powley
bioRxiv 2020.12.11.421743; doi: https://doi.org/10.1101/2020.12.11.421743

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