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MRI-MECH: mechanics-informed MRI to estimate esophageal health

Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique that generates image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the esophagus has only been demonstrated in few feasibility studies...

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Autores principales: Halder, Sourav, Johnson, Ethan M., Yamasaki, Jun, Kahrilas, Peter J., Markl, Michael, Pandolfino, John E., Patankar, Neelesh A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289887/
https://www.ncbi.nlm.nih.gov/pubmed/37362445
http://dx.doi.org/10.3389/fphys.2023.1195067
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author Halder, Sourav
Johnson, Ethan M.
Yamasaki, Jun
Kahrilas, Peter J.
Markl, Michael
Pandolfino, John E.
Patankar, Neelesh A.
author_facet Halder, Sourav
Johnson, Ethan M.
Yamasaki, Jun
Kahrilas, Peter J.
Markl, Michael
Pandolfino, John E.
Patankar, Neelesh A.
author_sort Halder, Sourav
collection PubMed
description Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique that generates image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the esophagus has only been demonstrated in few feasibility studies and is relatively unexplored. In this work, we present a computational framework called mechanics-informed MRI (MRI-MECH) that enhances that capability, thereby increasing the applicability of dynamic MRI for diagnosing esophageal disorders. Pineapple juice was used as the swallowed contrast material for the dynamic MRI, and the MRI image sequence was used as input to the MRI-MECH. The MRI-MECH modeled the esophagus as a flexible one-dimensional tube, and the elastic tube walls followed a linear tube law. Flow through the esophagus was governed by one-dimensional mass and momentum conservation equations. These equations were solved using a physics-informed neural network. The physics-informed neural network minimized the difference between the measurements from the MRI and model predictions and ensured that the physics of the fluid flow problem was always followed. MRI-MECH calculated the fluid velocity and pressure during esophageal transit and estimated the mechanical health of the esophagus by calculating wall stiffness and active relaxation. Additionally, MRI-MECH predicted missing information about the lower esophageal sphincter during the emptying process, demonstrating its applicability to scenarios with missing data or poor image resolution. In addition to potentially improving clinical decisions based on quantitative estimates of the mechanical health of the esophagus, MRI-MECH can also be adapted for application to other medical imaging modalities to enhance their functionality.
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spelling pubmed-102898872023-06-25 MRI-MECH: mechanics-informed MRI to estimate esophageal health Halder, Sourav Johnson, Ethan M. Yamasaki, Jun Kahrilas, Peter J. Markl, Michael Pandolfino, John E. Patankar, Neelesh A. Front Physiol Physiology Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique that generates image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the esophagus has only been demonstrated in few feasibility studies and is relatively unexplored. In this work, we present a computational framework called mechanics-informed MRI (MRI-MECH) that enhances that capability, thereby increasing the applicability of dynamic MRI for diagnosing esophageal disorders. Pineapple juice was used as the swallowed contrast material for the dynamic MRI, and the MRI image sequence was used as input to the MRI-MECH. The MRI-MECH modeled the esophagus as a flexible one-dimensional tube, and the elastic tube walls followed a linear tube law. Flow through the esophagus was governed by one-dimensional mass and momentum conservation equations. These equations were solved using a physics-informed neural network. The physics-informed neural network minimized the difference between the measurements from the MRI and model predictions and ensured that the physics of the fluid flow problem was always followed. MRI-MECH calculated the fluid velocity and pressure during esophageal transit and estimated the mechanical health of the esophagus by calculating wall stiffness and active relaxation. Additionally, MRI-MECH predicted missing information about the lower esophageal sphincter during the emptying process, demonstrating its applicability to scenarios with missing data or poor image resolution. In addition to potentially improving clinical decisions based on quantitative estimates of the mechanical health of the esophagus, MRI-MECH can also be adapted for application to other medical imaging modalities to enhance their functionality. Frontiers Media S.A. 2023-06-09 /pmc/articles/PMC10289887/ /pubmed/37362445 http://dx.doi.org/10.3389/fphys.2023.1195067 Text en Copyright © 2023 Halder, Johnson, Yamasaki, Kahrilas, Markl, Pandolfino and Patankar. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Halder, Sourav
Johnson, Ethan M.
Yamasaki, Jun
Kahrilas, Peter J.
Markl, Michael
Pandolfino, John E.
Patankar, Neelesh A.
MRI-MECH: mechanics-informed MRI to estimate esophageal health
title MRI-MECH: mechanics-informed MRI to estimate esophageal health
title_full MRI-MECH: mechanics-informed MRI to estimate esophageal health
title_fullStr MRI-MECH: mechanics-informed MRI to estimate esophageal health
title_full_unstemmed MRI-MECH: mechanics-informed MRI to estimate esophageal health
title_short MRI-MECH: mechanics-informed MRI to estimate esophageal health
title_sort mri-mech: mechanics-informed mri to estimate esophageal health
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289887/
https://www.ncbi.nlm.nih.gov/pubmed/37362445
http://dx.doi.org/10.3389/fphys.2023.1195067
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