A Laplacian-based SNR measure: Shear stiffness estimation in MR elastography

Rehman S. Eon, Khang T. Huynh, David S. Lake, Armando Manduca

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Magnetic resonance elastography (MRE) is a phase-contrast MRI based technique that allows quantitative, noninvasive assessment of the mechanical properties of tissues by the introduction of shear waves into the body and measurement of the resulting displacements. In MRE, the calculated stiffness values are affected by noise, which is amplified by the inversion process. It would be useful to know that beyond some SNR threshold, the stiffness values are accurate within some confidence limit. The most common methods to calculate SNR values in MRE are variations of displacement SNR, which estimate the noise in the measured displacement. However, the accuracy of stiffness determination depends not only on the displacement SNR, but also on the wavelength of the shear wave, in turn dependent on the stiffness of the underlying material. More recently, the SNR of the octahedral shear strain (OSS) has been proposed as a more appropriate measure, since shear deformation is the signal in MRE. We also propose here another measure based on the SNR of the Laplacian of the data, since this is the most noise sensitive quantity calculated when performing direct inversion of the Helmholtz equation. The three SNR measures were compared on simulated data for materials of different stiffness with varying amounts of noise using three inversion algorithms commonly used in MRE (phase gradient, local frequency estimation, and direct inversion). We demonstrate that the proper SNR measure for MRE depends on the inversion algorithm used, and, more precisely, on the order of derivatives used in the inversion process.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
PublisherSPIE
Volume9417
ISBN (Print)9781628415070
DOIs
StatePublished - 2015
EventMedical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging - Orlando, United States
Duration: Feb 24 2015Feb 26 2015

Other

OtherMedical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CityOrlando
Period2/24/152/26/15

Fingerprint

Elasticity Imaging Techniques
Magnetic resonance
magnetic resonance
stiffness
Stiffness
inversions
shear
Noise
Shear waves
S waves
confidence limits
Frequency estimation
Helmholtz equation
Helmholtz equations
shear strain
Shear strain
phase contrast
Magnetic resonance imaging
Shear deformation
mechanical properties

Keywords

  • Direct inversion
  • Helmholtz equation
  • Laplacian
  • Local frequency estimation
  • Magnetic resonance elastography
  • Octahedral shear strain
  • Phase gradient
  • Shear stiffness
  • Signal-to-noise ratio

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Eon, R. S., Huynh, K. T., Lake, D. S., & Manduca, A. (2015). A Laplacian-based SNR measure: Shear stiffness estimation in MR elastography. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 9417). [94171K] SPIE. https://doi.org/10.1117/12.2083371

A Laplacian-based SNR measure : Shear stiffness estimation in MR elastography. / Eon, Rehman S.; Huynh, Khang T.; Lake, David S.; Manduca, Armando.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9417 SPIE, 2015. 94171K.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Eon, RS, Huynh, KT, Lake, DS & Manduca, A 2015, A Laplacian-based SNR measure: Shear stiffness estimation in MR elastography. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 9417, 94171K, SPIE, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, Orlando, United States, 2/24/15. https://doi.org/10.1117/12.2083371
Eon RS, Huynh KT, Lake DS, Manduca A. A Laplacian-based SNR measure: Shear stiffness estimation in MR elastography. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9417. SPIE. 2015. 94171K https://doi.org/10.1117/12.2083371
Eon, Rehman S. ; Huynh, Khang T. ; Lake, David S. ; Manduca, Armando. / A Laplacian-based SNR measure : Shear stiffness estimation in MR elastography. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9417 SPIE, 2015.
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AB - Magnetic resonance elastography (MRE) is a phase-contrast MRI based technique that allows quantitative, noninvasive assessment of the mechanical properties of tissues by the introduction of shear waves into the body and measurement of the resulting displacements. In MRE, the calculated stiffness values are affected by noise, which is amplified by the inversion process. It would be useful to know that beyond some SNR threshold, the stiffness values are accurate within some confidence limit. The most common methods to calculate SNR values in MRE are variations of displacement SNR, which estimate the noise in the measured displacement. However, the accuracy of stiffness determination depends not only on the displacement SNR, but also on the wavelength of the shear wave, in turn dependent on the stiffness of the underlying material. More recently, the SNR of the octahedral shear strain (OSS) has been proposed as a more appropriate measure, since shear deformation is the signal in MRE. We also propose here another measure based on the SNR of the Laplacian of the data, since this is the most noise sensitive quantity calculated when performing direct inversion of the Helmholtz equation. The three SNR measures were compared on simulated data for materials of different stiffness with varying amounts of noise using three inversion algorithms commonly used in MRE (phase gradient, local frequency estimation, and direct inversion). We demonstrate that the proper SNR measure for MRE depends on the inversion algorithm used, and, more precisely, on the order of derivatives used in the inversion process.

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