Tiago Martins1, Tales Santini1, Jacob Berardinelli1, Anthony DeFranco1, and Tamer S Ibrahim1
1University of Pittsburgh, Pittsburgh, PA, United States
Synopsis
In this work, we explore a conformal Tic Tac Toe (TTT) head coil
design for ultra-high field MRI. By conforming the antennas to the human
head, we can extract better homogeneity allowing for better
radiofrequency shimming. The comparison between the traditional TTT
design and the conformal TTT design shows expanded coverage, reduction
of the coefficient of variation by 0.4% and same intensity for the
16-channel version. The conformal designs are extremely flexible as its
advantages can be explored for different configurations and sizes.
Introduction
The Tic-Tac-Toe (TTT) coil design for 7 Tesla (T) magnetic resonance
imaging (MRI) is an array of antennas that are highly coupled and load
insensitive1-6. Many research clinical studies are using the 16-channel
TTT design transmit array (Figure 1a) with 32-channel receive head
coil6. The conformal Tic Tac Toe (TTT) head coil design goes a step
further by opening the possibility for better placement of the antennas
around the head, allowing improvements in the homogeneity, SAR, and
power efficiency of the coil, beyond the values currently obtained and
flexibility of design. Analysis of multiple conformal designs were
conducted to obtain evaluate the efficacy of the conformal TTT model.Methods
Digitally describing a physical model of a coil is simple for
rectangular shapes. For curved and conformal structures and shapes
describing a 3D geometry is more complex and time intensive. The
creation of an optimized coil design requires several simulations and
design iterations. That process can take a long time if any modification
requires a manual recreation of each digital point of the 3D geometry.
To simplify and speed up the design process, an in-house developed
software were used to generate coil models (Figure 1a-d) based on a
minimal geometry description such as width, height, and length.
To guarantee performance and safety of the new design, simulations of
the magnetic and electric field interactions were be performed using an
in-house FDTD validated software7 (calculation of the Maxwell’s
equations) with a precise transmission line modelling. The resultant
circularly polarized 𝐵1+ field, which is the magnetic field that
excites the protons, and the Electrical fields, for specific absorption
rate (SAR) calculations, are thus obtained8.
The in-house optimization software able to perform nonlinear function
minimization for coefficient of variation (CV), maximum over minimum
and the coefficient of variation over minimum was used for this work.
Additionally, SAR constrains were added to the optimization to guarantee
operation within safe limits.
After radiofrequency (RF) shimming9.10 was performed with the
optimization for both phase and amplitude. The current TTT design
(Figure 1a) was compare with a conformal version (Figure 1b) with the
same simulation conditions. The comparison is shown on Figure 2 for both
B1+ field and SAR across different axial slices and a coronal and
sagittal slice.
For implementation, a 32-channels conformal coil (Figure 1c) with
4.25 inches panels (Figure 1d) with a total of 16 panels (2 channels per
panel) was selected. A single panel was built (Figure 1e) and tested
against a similar panel using the traditional flat TTT design using same
test condition for both. The magnitude of the reflection coefficient
for channel 1 of each panel and its respective smith chart showing the
impedance vs. frequency can be seen on Figure 3.
To compare the field distribution of each panel the experimental
dataset was calculated from an acquisition using a 7T Siemens MAGNETOM
of a Turbo-Flash sequence with 6 different flip-angles variating from 0
to 90 degrees with TE of 1.16ms and TE of 2s, total time of acquisition
was 12 minutes. The B1+ field distribution is shown in Figure 4 for all 3
orientations (axial, sagittal and coronal).Results
The result for the magnetic field (B1) from one sample case of RF
shimming shows similar homogeneity and coverage between the regular
(Figure 1a) and the conformal 16-channels (Figure 1b) TTT head coils.
The CV for the current 16-channel TTT coil (Figure 2a) is 15.6% and the
max/min is 2.86 with a mean of 2.71µT/100V. For the 16-channels
conformal TTT coil (Figure 2b) further improved the CV to 15.2% and
max/min to 2.85 with mean of 2.71µT/100V. These simulations were
performed using a 16kW of power for the optimization software.
The SAR calculations for both the conformal and regular 16-channels
TTT head coils are shown in Figure 2. For the implemented 16-channels
TTT head coil (Figure 2c), the peak SAR is 7.44W/Kg/10g and the average
SAR is 2.33W/Kg/10g. For the conformal 16-channels TTT head coil (Figure
2d), the peak SAR is 9.04W/Kg/10g and the average SAR is 2.42W/Kg/10g.
The higher SAR of the conformal designs were expected since the sources
are closer to the surface of the head. By increasing the physical size
of the coil, the sources will be far from the head decreasing SAR.
For both homogeneity and SAR, the arrows in Figure 2 show areas with
better coverage or lower SAR due to use of a conformal TTT design. That
can be validated with the experimental B1+ maps that show similar
intensities between both panels (Figure 4), but the distribution of the
conformal panel has better penetration and wider coverage. The tuning
and matching of the conformal TTT panel match the flat panel (Figure 3)
as expected with both having a reflection inferior to -20dB.Discussion and Conclusion
The new TTT head coil will have 32 channels (Figure 1c) using 2
channels per panel (Figure 1d,e) with a total of 16 panels. The
conformal TTT design show better coverage (Figure 4) and therefor allows
better RF shimming (Figure 2). Combining with a larger coil size
to improve field homogeneity, this new device will be expected to be a
significant improvement from past generations.Acknowledgements
This work was supported by NIH R01MH111265 and R01AG063525. The
author Tiago Martins was partially supported by the CAPES Foundation,
Ministry of Education of Brazil, 88881.128222/2016-01. This research was
also supported in part by the University of Pittsburgh Center for
Research Computing (CRC) through the resources provided.References
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