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Multi-parameter Analytical Method for B1 and SNR Analysis (MAMBA): An open source RF coil design tool


Tesfai, Agazi Samuel; Fischer, Johannes; Özen, Ali Caglar; Eppenberger, Patrick; Oehrstroem, Lena; Rühli, Frank; Ludwig, Ute; Bock, Michael (2020). Multi-parameter Analytical Method for B1 and SNR Analysis (MAMBA): An open source RF coil design tool. Journal of Magnetic Resonance, 319:106825.

Abstract

In Magnetic Resonance Imaging (MRI), radio frequency (RF) coils of different forms and shapes are used to maximize signal-to-noise ratio (SNR). RF coils are designed for clinical applications and have dimensions comparable with the target body part to be imaged, and they perform best when loaded by human tissue majority of which have conductivity values higher than 0.5 S/m. However, they are not properly tuned and matched for samples having low conductivity such as solid samples with low water content. Moreover, for samples with low filling factor and low conductivity, the noise in MRI is dominated by RF coil losses. In this case, RF coil design can be optimized to improve image SNR. Here, a new software tool (Multi-parameter Analytical Method for B1 and SNR Analysis) MAMBA is presented to design and compare volume coils of birdcage, solenoid, and loop-gap design for these samples. The input parameters of the tool are the sample properties, the coil design and the hardware properties, of which a relative SNR is determined. For that, a figure of merit is calculated from the coil sensitivity, applied resonant frequency and the resistive losses of sample, coil and capacitive components. The tool was tested in an ancient Egyptian mummy head which represents an extreme case of MRI with short T2*. Two optimized birdcage coils were designed using MAMBA, constructed and compared to a commercial transmit receive head coil. Calculated relative SNR values are in good agreement with the measurements.

Abstract

In Magnetic Resonance Imaging (MRI), radio frequency (RF) coils of different forms and shapes are used to maximize signal-to-noise ratio (SNR). RF coils are designed for clinical applications and have dimensions comparable with the target body part to be imaged, and they perform best when loaded by human tissue majority of which have conductivity values higher than 0.5 S/m. However, they are not properly tuned and matched for samples having low conductivity such as solid samples with low water content. Moreover, for samples with low filling factor and low conductivity, the noise in MRI is dominated by RF coil losses. In this case, RF coil design can be optimized to improve image SNR. Here, a new software tool (Multi-parameter Analytical Method for B1 and SNR Analysis) MAMBA is presented to design and compare volume coils of birdcage, solenoid, and loop-gap design for these samples. The input parameters of the tool are the sample properties, the coil design and the hardware properties, of which a relative SNR is determined. For that, a figure of merit is calculated from the coil sensitivity, applied resonant frequency and the resistive losses of sample, coil and capacitive components. The tool was tested in an ancient Egyptian mummy head which represents an extreme case of MRI with short T2*. Two optimized birdcage coils were designed using MAMBA, constructed and compared to a commercial transmit receive head coil. Calculated relative SNR values are in good agreement with the measurements.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Evolutionary Medicine
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Biophysics
Life Sciences > Biochemistry
Physical Sciences > Nuclear and High Energy Physics
Physical Sciences > Condensed Matter Physics
Language:English
Date:8 September 2020
Deposited On:21 Sep 2020 07:33
Last Modified:22 Sep 2020 20:00
Publisher:Elsevier
ISSN:1090-7807
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.jmr.2020.106825
PubMed ID:32947127

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