Quantitative 3D magnetic resonance elastography: Comparison with dynamic mechanical analysis

Arunachalam, Shivaram P.; Rossman, Phillip J.; Arani, Arvin; Lake, David S.; Glaser, Kevin J.; Trzasko, Joshua D.; Manduca, Armando; McGee, Kiaran P.; Ehman, Richard L.; Araoz, Philip A.

doi:10.1002/mrm.26207

Cited by 30 publications

(43 citation statements)

References 26 publications

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“…They reported an ICC of 0.99 for the magnitude of the complex shear modulus between DI-MRE of large homogeneous phantoms and DMA using 8 polyvinyl chloride samples. [45] In our study, the NLI-MRE and DMA techniques also revealed consistency with an ICC of 0.72 between the storage modulus of the silicone, agar, and tofu samples and the heterogeneous phantoms.…”

Section: Discussionsupporting

confidence: 77%

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Phantom evaluations of nonlinear inversion MR elastography

et al. 2018

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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.

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Section: Discussionsupporting

confidence: 77%

“…[45]. Intraclass correlation coefficient (ICC) was also computed to measure the consistency between the NLI estimates and DMA measurements with a one-way random effects model.…”

Section: Methodsmentioning

confidence: 99%

Phantom evaluations of nonlinear inversion MR elastography

et al. 2018

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“…1 of Arunachalam et al 41 ) was 8.1 in the soft material, whereas N was between 17 and 25 for in vivo data. Because N and SNR have adverse effects on the apparent SWS, the ratio N / SNR is plotted on the x‐axis. Dependent on the ratio N / SNR , the dispersion‐by‐inversion bias can cause either an overshoot or undershoot of values, both enhanced by second‐order finite derivative methods such as AHI.…”

Section: Resultsmentioning

confidence: 99%

Fast tomoelastography of the mouse brain by multifrequency single‐shot MR elastography

Bertalan

Guo

Tzschätzsch

et al. 2018

Magnetic Resonance in Med

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Purpose To introduce in vivo multifrequency single‐shot magnetic resonance elastography for full‐FOV stiffness mapping of the mouse brain and to compare in vivo stiffness of neural tissues with different white‐to‐gray matter ratios. Methods Viscous phantoms and 10 C57BL‐6 mice were investigated by 7T small‐animal MRI using a single‐shot spin‐echo planar imaging magnetic resonance elastography sequence with motion‐encoding gradients positioned before the refocusing pulse. Wave images were acquired over 10 minutes for 6 mechanical vibration frequencies between 900 and 1400 Hz. Stiffness maps of shear wave speed (SWS) were computed using tomoelastography data processing and compared with algebraic Helmholtz inversion (AHI) for signal‐to‐noise ratio (SNR) analysis. Different brain regions were analyzed including cerebral cortex, corpus callosum, hippocampus, and diencephalon. Results In phantoms, algebraic Helmholtz inversion–based SWS was systematically biased by noise and discretization, whereas tomoelastography‐derived SWS was consistent over the full SNR range analyzed. Mean in vivo SWS of the whole brain was 3.76 ± 0.33 m/s with significant regional variation (hippocampus = 4.91 ± 0.49 m/s, diencephalon = 4.78 ± 0.78 m/s, cerebral cortex = 3.53 ± 0.29 m/s, and corpus callosum = 2.89 ± 0.17 m/s). Conclusion Tomoelastography retrieves mouse brain stiffness within shorter scan times and with greater detail resolution than classical algebraic Helmholtz inversion–based magnetic resonance elastography. The range of SWS values obtained here indicates that mouse white matter is softer than gray matter at the frequencies investigated.

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“…The different ROI sizes used in the five MRE sequences may have an effect on the stability of the stiffness measurements because of the liver parenchyma stiffness heterogeneity often observed in MRE elastograms. While previous work has established the validity of 3D MRE when compared to mechanical testing of phantoms, it has also been observed that 3D hepatic MRE stiffness values can be lower than 2D MRE values, while having comparable diagnostic accuracy and fewer failures …”

Section: Discussionmentioning

confidence: 98%