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Evaluation of wave delivery methodology for brain MRE: Insights from computational simulations

McGrath, Deirdre, Ravikumar, Nishant, Beltrachini, Leandro, Wilkinson, Iain, Frangi, Alejandro and Taylor, Zeike 2016. Evaluation of wave delivery methodology for brain MRE: Insights from computational simulations. Magnetic Resonance in Medicine 78 (1) , pp. 341-356. 10.1002/mrm.26333

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Abstract

Purpose MR elastography (MRE) of the brain is being explored as a biomarker of neurodegenerative disease such as dementia. However, MRE measures for healthy brain have varied widely. Differing wave delivery methodologies may have influenced this, hence finite element-based simulations were performed to explore this possibility. Methods The natural frequencies of a series of cranial models were calculated, and MRE-associated vibration was simulated for different wave delivery methods at varying frequency, using simple isotropic viscoelastic material models for the brain. Displacement fields and the corresponding brain constitutive properties estimated by standard inversion techniques were compared across delivery methods and frequencies. Results The delivery methods produced widely different MRE displacement fields and inversions. Furthermore, resonances at natural frequencies influenced the displacement patterns. Consequently, some delivery methods led to lower inversion errors than others, and the error on the storage modulus varied by up to 11% between methods. Conclusion Wave delivery has a considerable impact on brain MRE reliability. Assuming small variations in brain biomechanics, as recently reported to accompany neurodegenerative disease (e.g., 7% for Alzheimer's disease), the effect of wave delivery is important. Hence, a consensus should be established on a consistent methodology to ensure diagnostic and prognostic consistency.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Physics and Astronomy
Cardiff University Brain Research Imaging Centre (CUBRIC)
Psychology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: Wiley-Blackwell
ISSN: 0740-3194
Date of First Compliant Deposit: 12 June 2017
Date of Acceptance: 17 June 2016
Last Modified: 03 Jul 2019 10:56
URI: http://orca.cf.ac.uk/id/eprint/101022

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