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• W2912985163 abstract "Intrinsic activation MR elastography (IA-MRE) is a novel technique which seeks to estimate brain mechanical properties non-invasively and without external mechanical drivers. The method eliminates actuation hardware and patient discomfort while capitalizing on the brain's intrinsic low frequency motion. This study explores low frequency actuation (1 Hz) MR elastography in phantoms and analyzes performance of non-linear inversion (NLI) of viscoelastic and poroelastic mechanical models as a framework for assessing clinical results from IA-MRE. We present results from four gelatin phantoms and report stiffness resolution of 6 mm (two measurement voxels) with a stiffness contrast ratio of 4.21 relative to the background and 9 mm (three measurement voxels) with a lower stiffness contrast ratio of near 1.77. Stiffness edge resolution was also evaluated using edge spread and line spread functions and yielded a stiffness edge response distance of 9 mm. The intraclass correlation coefficient was high (0.93) between mechanical testing and poroelastic estimates, although quantitative agreement was affected by model-data mismatch. Viscoelastic MRE at low frequencies has issues with non-uniqueness due to small inertial forces, and performed worse than poroelastic MRE in terms of inclusion detection and consistency with mechanical testing. These results present the first evaluation of MR elastography using displacement measurements from an actuation frequency less than 5 Hz and support the validity of brain IA-MRE to recover spatially resolved stiffness changes. They provide a baseline of performance in terms of standard metrics for future animal and human brain stiffness studies and analyses based on intrinsic motion." @default.
• W2912985163 created "2019-02-21" @default.
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• W2912985163 date "2019-03-12" @default.
• W2912985163 modified "2023-09-23" @default.
• W2912985163 title "Phantom evaluations of low frequency MR elastography" @default.
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• W2912985163 doi "https://doi.org/10.1088/1361-6560/ab0290" @default.
• W2912985163 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30695755" @default.
• W2912985163 hasPublicationYear "2019" @default.
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