Mechanics informed fluoroscopy of esophageal transport

Halder, Sourav; Acharya, Shashank; Kou, Wenjun; Kahrilas, Peter J.; Pandolfino, John E.; Patankar, Neelesh A.

doi:10.1007/s10237-021-01420-0

Original Paper
Published: 02 March 2021

Mechanics informed fluoroscopy of esophageal transport

Biomechanics and Modeling in Mechanobiology volume 20, pages 925–940 (2021)Cite this article

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Abstract

Fluoroscopy is a radiographic procedure for evaluating esophageal disorders such as achalasia, dysphasia and gastroesophageal reflux disease. It performs dynamic imaging of the swallowing process and provides anatomical detail and a qualitative idea of how well swallowed fluid is transported through the esophagus. In this work, we present a method called mechanics informed fluoroscopy (FluoroMech) that derives patient-specific quantitative information about esophageal function. FluoroMech uses a convolutional neural network to perform segmentation of image sequences generated from the fluoroscopy, and the segmented images become input to a one-dimensional model that predicts the flow rate and pressure distribution in fluid transported through the esophagus. We have extended this model to identify and estimate potential physiomarkers such as esophageal wall stiffness and active relaxation ahead of the peristaltic wave in the esophageal musculature. FluoroMech requires minimal computational time and hence can potentially be applied clinically in the diagnosis of esophageal disorders.

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Acknowledgements

We acknowledge the support provided by Public Health Service Grants R01-DK079902 and P01-DK117824, and National Science Foundation Grants OAC 1450374 and OAC 1931372 in the completion of this work. We also acknowledge the computational resources provided by Northwestern University’s Quest High Performance Computing Cluster. For this work, we have also utilized the Extreme Science and Engineering Discovery Environment (XSEDE) cluster Comet, at the San Diego Supercomputer Center through allocation TG-ASC170023, which is supported by National Science Foundation Grant Number ACI-1548562 (Towns et al. 2014).

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Authors and Affiliations

Theoretical and Applied Mechanics, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, USA
Sourav Halder & Neelesh A. Patankar
Department of Mechanical Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, USA
Shashank Acharya & Neelesh A. Patankar
Department of Medicine, Feinberg School of Medicine, Northwestern University, 676 North Saint Clair St., Chicago, IL, 60611, USA
Wenjun Kou, Peter J. Kahrilas & John E. Pandolfino

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Sourav Halder
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Shashank Acharya
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Wenjun Kou
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Peter J. Kahrilas
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John E. Pandolfino
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Neelesh A. Patankar
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Correspondence to Neelesh A. Patankar.

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Halder, S., Acharya, S., Kou, W. et al. Mechanics informed fluoroscopy of esophageal transport. Biomech Model Mechanobiol 20, 925–940 (2021). https://doi.org/10.1007/s10237-021-01420-0

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Received: 07 June 2020
Accepted: 07 January 2021
Published: 02 March 2021
Issue Date: June 2021
DOI: https://doi.org/10.1007/s10237-021-01420-0

Keywords

Flexible tube
Image segmentation
Convolutional neural network
One-dimensional flow
Esophageal wall stiffness
Esophageal active relaxation