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B-Lines Lung Ultrasonography Simulation Using Finite Element Method.

Fellipe Allevato Martins da Silva¹, Eduardo Moreno², Wagner Coelho de Albuquerque Pereira¹

¹Engineering Program-COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil.

Diagnostics (Basel, Switzerland)

|November 11, 2022

Summary

This summary is machine-generated.

This study developed a numerical model to simulate lung ultrasound (LUS) images, accurately replicating B-lines caused by lung conditions. The model aids in understanding how lung infiltration affects LUS imaging results.

Keywords:

B-lines COMSOL finite element method lung ultrasonography simulation

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Area of Science:

Biomedical Engineering
Medical Imaging
Computational Physics

Background:

Lung Ultrasonography (LUS) is a rapid diagnostic tool for respiratory syndromes.
B-lines in LUS indicate fluid accumulation or thickening in lung tissues.
Mathematical models are crucial for predicting biological responses to signal parameters.

Purpose of the Study:

To propose a Finite-Element numerical model for simulating radio frequency ultrasonic waves in normal and infiltrated lung structures.
To utilize a randomized inhomogeneous data method for tissue medium representation.
To implement Acoustic Pressure and Time-Explicit models based on the discontinuous Galerkin method (dG) in COMSOL®.

Main Methods:

A Finite-Element numerical model was developed using COMSOL®.
Randomized inhomogeneous data represented the lung tissue medium.
Radio frequency (RF) signals were processed using MATLAB® to generate A-lines and B-lines.

Main Results:

The simulation successfully generated horizontal A-lines and vertical B-lines.
The simulated B-lines showed reasonable similarity to real-world LUS images.
The use of inhomogeneous materials effectively simulated scattering responses.

Conclusions:

The developed numerical model accurately simulates lung infiltration effects on LUS images.
The model's ability to mimic scattering responses validates its use of inhomogeneous materials.
This tool is valuable for studying how lung infiltration characteristics influence LUS imaging.