Literature DB >> 28318888

Characterization of the Lung Parenchyma Using Ultrasound Multiple Scattering.

Kaustav Mohanty1, John Blackwell2, Thomas Egan2, Marie Muller3.   

Abstract

The purpose of the study described here was to showcase the application of ultrasound to quantitative characterization of the micro-architecture of the lung parenchyma to predict the extent of pulmonary edema. The lung parenchyma is a highly complex and diffusive medium for which ultrasound techniques have remained qualitative. The approach presented here is based on ultrasound multiple scattering and exploits the complexity of ultrasound propagation in the lung structure. The experimental setup consisted of a linear transducer array with an 8-MHz central frequency placed in contact with the lung surface. The diffusion constant D and transport mean free path L* of the lung parenchyma were estimated by separating the incoherent and coherent intensities in the near field and measuring the growth of the incoherent diffusive halo over time. Significant differences were observed between the L* values obtained in healthy and edematous rat lungs in vivo. In the control rat lung, L* was found to be 332 μm (±48.8 μm), whereas in the edematous lung, it was 1040 μm (±90 μm). The reproducibility of the measurements of L* and D was tested in vivo and in phantoms made of melamine sponge with varying air volume fractions. Two-dimensional finite difference time domain numerical simulations were carried out on rabbit lung histology images with varying degrees of lung collapse. Significant correlations were observed between air volume fraction and L* in simulation (r = -0.9542, p < 0.0117) and sponge phantom (r = -0.9932, p < 0.0068) experiments. Ex vivo measurements of a rat lung in which edema was simulated by adding phosphate-buffered saline revealed a linear relationship between the fluid volume fraction and L*. These results illustrate the potential of methods based on ultrasound multiple scattering for the quantitative characterization of the lung parenchyma.
Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Edema; Fibrosis; Interstitial syndrome; Lung parenchyma; Multiple scattering; Quantitative ultrasound

Mesh:

Year:  2017        PMID: 28318888     DOI: 10.1016/j.ultrasmedbio.2017.01.011

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  12 in total

1.  Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.

Authors:  Kaustav Mohanty; Omid Yousefian; Yasamin Karbalaeisadegh; Micah Ulrich; Quentin Grimal; Marie Muller
Journal:  Comput Biol Med       Date:  2019-09-20       Impact factor: 4.589

2.  Ultrasound multiple scattering with microbubbles can differentiate between tumor and healthy tissue in vivo.

Authors:  Kaustav Mohanty; Virginie Papadopoulou; Isabel G Newsome; Sarah Shelton; Paul A Dayton; Marie Muller
Journal:  Phys Med Biol       Date:  2019-05-31       Impact factor: 3.609

3.  Detecting pulmonary nodules by using ultrasound multiple scattering.

Authors:  Roshan Roshankhah; John Blackwell; Mir H Ali; Behrooz Masuodi; Thomas Egan; Marie Muller
Journal:  J Acoust Soc Am       Date:  2021-12       Impact factor: 1.840

4.  Investigating training-test data splitting strategies for automated segmentation and scoring of COVID-19 lung ultrasound images.

Authors:  Roshan Roshankhah; Yasamin Karbalaeisadegh; Hastings Greer; Federico Mento; Gino Soldati; Andrea Smargiassi; Riccardo Inchingolo; Elena Torri; Tiziano Perrone; Stephen Aylward; Libertario Demi; Marie Muller
Journal:  J Acoust Soc Am       Date:  2021-12       Impact factor: 2.482

Review 5.  What Is COVID 19 Teaching Us about Pulmonary Ultrasound?

Authors:  Gino Soldati; Marcello Demi
Journal:  Diagnostics (Basel)       Date:  2022-03-29

Review 6.  Current Ultrasound Technologies and Instrumentation in the Assessment and Monitoring of COVID-19 Positive Patients.

Authors:  Xuejun Qian; Robert Wodnicki; Haochen Kang; Junhang Zhang; Hisham Tchelepi; Qifa Zhou
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2020-08-28       Impact factor: 2.725

7.  Lung mass density prediction using machine learning based on ultrasound surface wave elastography and pulmonary function testing.

Authors:  Boran Zhou; Brian J Bartholmai; Sanjay Kalra; Thomas Osborn; Xiaoming Zhang
Journal:  J Acoust Soc Am       Date:  2021-02       Impact factor: 1.840

8.  Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

Authors:  Jiangang Chen; Chao He; Jintao Yin; Jiawei Li; Xiaoqian Duan; Yucheng Cao; Li Sun; Menghan Hu; Wenfang Li; Qingli Li
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2021-06-29       Impact factor: 2.725

9.  Operative Use of Thoracic Ultrasound in Respiratory Medicine: A Clinical Study.

Authors:  Gino Soldati; Renato Prediletto; Marcello Demi; Stefano Salvadori; Massimo Pistolesi
Journal:  Diagnostics (Basel)       Date:  2022-04-11

10.  Determination of a potential quantitative measure of the state of the lung using lung ultrasound spectroscopy.

Authors:  Libertario Demi; Wim van Hoeve; Ruud J G van Sloun; Gino Soldati; Marcello Demi
Journal:  Sci Rep       Date:  2017-10-06       Impact factor: 4.379

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