Mimicking the Electromagnetic Distribution in the Human Brain: A Multi-frequency MRI Head Phantom View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-03

AUTHORS

Ana L. Neves, Lisa Leroi, Nicolas Cochinaire, Redha Abdeddaim, Pierre Sabouroux, Alexandre Vignaud

ABSTRACT

The purpose of this study was to fabricate and test a multi-frequency human brain-mimicking phantom for magnetic resonance imaging (MRI) assessment purposes. An anatomically realistic human head phantom was elaborated, for different Larmor frequencies, which allows rapid quantification of B1+. It is a simple alternative solution in time and cost as compared to numerical simulations to validate simulation when the coil geometry and components cannot be known as a unique solution. The permittivity ε′ and conductivity σ of sucrose/salt/agar aqueous solutions of varying concentrations were determined; a solution with these components and having the adequate concentration to obtain the brain’s dielectric properties at 3, 7 and 11.7T was manufactured. An anthropomorphic polymeric skull was filled with this mixture. To check the behavior of this phantom in a MRI configuration, both numerical and experimental validations were done: a B1+ field distribution inside the phantom was calculated with CST Microwave Studio inside a birdcage coil at 7T; the same mapping was assessed in a 7T MRI. The feasibility of a multi-MRI static field phantom was demonstrated. A solution composed by 54.7 wt% of sucrose, 3.1 wt% of salt and 3.1 wt% of agar was fabricated with good permittivity and conductivity matching for 3, 7 and 11.7T. The results were confirmed by both numerical simulation and MRI acquisition. This work has shown the possibility of manufacturing a head phantom with accessible and cheap components for MRI evaluation, having an adequate B1+ field distribution and the dielectric properties of the human brain. More... »

PAGES

213-226

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00723-017-0862-4

DOI

http://dx.doi.org/10.1007/s00723-017-0862-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1053840014


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