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Implementation of Non-invasive Point of Care Transient Elastography for Evaluation of Liver Disease in Pediatric Populations with Cystic Fibrosis
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Image reconstruction utilizing median filtering applied to elastography.

Rubem P Carbente1, Joaquim M Maia2, Amauri A Assef2

  • 1Electrical Engineering Department and the Graduate School of Electrical Engineering (DAELT), Federal University of Technology-Paraná (UTFPR), Curitiba, PR, Brazil. rubem@utfpr.edu.br.

Biomedical Engineering Online
|March 15, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a new ultrasound elastography method for assessing tissue viscoelasticity. The technique accurately quantifies mechanical properties, aiding in noninvasive disease diagnosis and monitoring.

Keywords:
ElastographyShear waveSignal processingUltrafast imagingUltrasound

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Ultrasound Technology

Background:

  • Ultrafast ultrasound imaging enables assessment of tissue viscoelasticity by detecting shear waves.
  • This elastography technique allows for noninvasive diagnosis and monitoring of diseases through mechanical property quantification.

Purpose of the Study:

  • To present a novel method for estimating viscoelastic properties and rigidity using shear wave elasticity imaging (SWEI).
  • To validate the technique's accuracy using an elastography phantom with known mechanical properties.

Main Methods:

  • Utilized Verasonics Vantage 128 research platform and L11-4v transducer for radio frequency signal acquisition.
  • Employed an elastography phantom (model 049A, CIRS) for data collection.
  • Processed and analyzed data using MATLAB, applying a novel filtering function for elastographic image generation.

Main Results:

  • The proposed SWEI technique successfully generated qualitative images reflecting altered viscoelastic properties in phantom inclusions.
  • Results demonstrated good agreement with manufacturer-indicated margins of error, with mean percentage errors ranging from -6.5% to -28.2%.
  • Median filtering characteristics were observed to smooth velocity variations, enhancing elastographic image quality.

Conclusions:

  • The developed SWEI technique optimizes elastographic images through a unique filtering function that considers local mean velocity.
  • This method allows for accurate adjustments based on phantom inclusion characteristics, improving diagnostic potential.