Contrast detection in fluid‐saturated media with magnetic resonance poroelastography

Perríñez, Phillip R.; Pattison, Adam J.; Kennedy, Francis E.; Weaver, John B.; Paulsen, Keith D.

doi:10.1118/1.3443563

Cited by 34 publications

(30 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…VE inversions recovered µ s and µ L in all cases, 43 and also Re{K } 47 for cross-model inversions when an appropriate value was not known. PE inversions recovered µ p and λ p in all cases, 46 and also κ (Ref. 31) for cross model inversions where an appropriate value was not known.…”

Section: B Inversion Of Simulated Datamentioning

confidence: 99%

“…The OSS-SNR of the EA data exceeded the threshold of 3 required for accurate MRE inversion. 45 Poroelastic 46 and viscoelastic 43 mechanical property reconstruction algorithms were applied to each data source, and the variation of the shear modulus (µ s for VE and µ p for PE) images of the rigidly registered image volumes was analyzed over the repeated scans in terms of the coefficient of image variation (COIV),…”

Section: A Viscoelastic and Poroelastic Inversions Of Ea And Ia Brmentioning

confidence: 99%

See 1 more Smart Citation

Suitability of poroelastic and viscoelastic mechanical models for high and low frequency MR elastography

et al. 2015

View full text Add to dashboard Cite

Purpose: Descriptions of the structure of brain tissue as a porous cellular matrix support application of a poroelastic (PE) mechanical model which includes both solid and fluid phases. However, the majority of brain magnetic resonance elastography (MRE) studies use a single phase viscoelastic (VE) model to describe brain tissue behavior, in part due to availability of relatively simple direct inversion strategies for mechanical property estimation. A notable exception is low frequency intrinsic actuation MRE, where PE mechanical properties are imaged with a nonlinear inversion algorithm. Methods: This paper investigates the effect of model choice at each end of the spectrum of in vivo human brain actuation frequencies. Repeat MRE examinations of the brains of healthy volunteers were used to compare image quality and repeatability for each inversion model for both 50 Hz externally produced motion and ≈1 Hz intrinsic motions. Additionally, realistic simulated MRE data were generated with both VE and PE finite element solvers to investigate the effect of inappropriate model choice for ideal VE and PE materials. Results: In vivo, MRE data revealed that VE inversions appear more representative of anatomical structure and quantitatively repeatable for 50 Hz induced motions, whereas PE inversion produces better results at 1 Hz. Reasonable VE approximations of PE materials can be derived by equating the equivalent wave velocities for the two models, provided that the timescale of fluid equilibration is not similar to the period of actuation. An approximation of the equilibration time for human brain reveals that this condition is violated at 1 Hz but not at 50 Hz. Additionally, simulation experiments when using the "wrong" model for the inversion demonstrated reasonable shear modulus reconstructions at 50 Hz, whereas cross-model inversions at 1 Hz were poor quality. Attenuation parameters were sensitive to changes in the forward model at both frequencies, however, no spatial information was recovered because the mechanisms of VE and PE attenuation are different. Conclusions: VE inversions are simpler with fewer unknown properties and may be sufficient to capture the mechanical behavior of PE brain tissue at higher actuation frequencies. However, accurate modeling of the fluid phase is required to produce useful mechanical property images at the lower

show abstract

Section: B Inversion Of Simulated Datamentioning

confidence: 99%

Section: A Viscoelastic and Poroelastic Inversions Of Ea And Ia Brmentioning

confidence: 99%

Suitability of poroelastic and viscoelastic mechanical models for high and low frequency MR elastography

et al. 2015

View full text Add to dashboard Cite

show abstract

“…3 From the ears toward the center of the brain hydrocephalus [38,51,69,93]. In this study, the properties of the slow compression wave predicted by the Biot model [8] in the low-frequency range (< 70 Hz) were analyzed in healthy volunteers to assess and quantify volumetric strain effects in the brain with and without external mechanical stimulation, following pioneering work on poroelastic data analysis of cerebral MRE by Perriñez et al [71,72] and Pattison et al [68].…”

Section: Introductionmentioning

confidence: 99%

Compression-sensitive magnetic resonance elastography

et al. 2013

View full text Add to dashboard Cite

ZusammenfassungResults illustrate that compression-sensitive MRE is capable of quantifying volumetric strain in phantoms and in human organs. It was found that volumetric strain was sensitive toward pressure changes associated with different physiological states, whereas shear strain remained constant.In an additional study, pulsation of the human brain, driven by the heart cycle, was used as the actuation source instead of the external vibration generator. Volumetric strain velocity was tracked over the cardiac cycle. Results indicate local expansion of brain parenchyma upon the arrival of the arterial pulse wave, followed by a slow return to the initial state during the diastolic phase.Numerical values for the pressure wave modulus M were calculated from measured volumetric strain through inversion of the pressure wave equation. Measurement noise was identified as the primary effect causing a severe underestimation of M .

show abstract

“…It was comprised of a soft tofu background (which is known to have a higher damping ratio than gels due to the high proportion of mobile fluid [42]) with four inclusions of 0.75% agar, since silicone and tofu are incompatible as a mixed phantom. The dimensions of the phantom were approximately 100 mm × 50 mm × 38 mm.…”

Section: Methodsmentioning

confidence: 99%

Phantom evaluations of nonlinear inversion MR elastography

et al. 2018

View full text Add to dashboard Cite

This study evaluated non-linear inversion MRE (NLI-MRE) based on viscoelastic governing equations to determine its sensitivity to small, low contrast inclusions and interface changes in shear storage modulus and damping ratio. Reconstruction parameters identical to those used in recent in vivo MRE studies of mechanical property variations in small brain structures were applied. NLI-MRE was evaluated on four phantoms with contrast in stiffness and damping ratio. Image contrast to noise ratio was assessed as a function of inclusion diameter and property contrast, and edge and line spread functions were calculated as measures of imaging resolution. Phantoms were constructed from silicone, agar, and tofu materials. Reconstructed property estimates were compared with independent mechanical testing using dynamic mechanical analysis (DMA). The NLI-MRE technique detected inclusions as small as 8mm with a stiffness contrast as low as 14%. Storage modulus images also showed an interface edge response distance of 11mm. Damping ratio images distinguished inclusions with a diameter as small as 8mm, and yielded an interface edge response distance of 10mm. Property differences relative to DMA tests were in the 15%-20% range in most cases. In this study, NLI-MRE storage modulus estimates resolved the smallest inclusion with the lowest stiffness contrast, and spatial resolution of attenuation parameter images was quantified for the first time. These experiments and image quality metrics establish quantitative guidelines for the accuracy expected in vivo for MRE images of small brain structures, and provide a baseline for evaluating future improvements to the NLI-MRE pipeline.

show abstract

Contrast detection in fluid‐saturated media with magnetic resonance poroelastography

Cited by 34 publications

References 46 publications

Suitability of poroelastic and viscoelastic mechanical models for high and low frequency MR elastography

Suitability of poroelastic and viscoelastic mechanical models for high and low frequency MR elastography

Compression-sensitive magnetic resonance elastography

Phantom evaluations of nonlinear inversion MR elastography

Contact Info

Product

Resources

About