Jorge Chacon-Caldera1, Alexander Fischer1, Matthias Malzacher1, and Lothar R. Schad1
1Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
Synopsis
Increasing
signal-to-noise-ratio (SNR) in prostate MRI could facilitate the diagnosis and
characterization of prostate cancers. In this work, we built a quadrature
posterior surface array that aims to increase local SNR at the prostate. The
coil was compared to 3 and 9 channels of the standard spine array using phantom
measurements. Respectively, SNR gains of 12 and 9% were obtained using a
realistic region-of-interest (ROI). Further work will be undertaken to translate the
SNR gains to in-vivo prostate imaging at 3T.
Purpose
MRI
is an important tool in the diagnosis and characterization of prostate cancer1.
However, prostate cancer remains largely underestimated and its diagnosis could
benefit from tailored-hardware that provides high SNR prostate images. This
could be, in principle, achieved using endorectal coils but they are invasive
and generic surface arrays are often preferred. In this work, we present a
surface 3-channel posterior array tailored to the application of prostate
imaging. In our approach, quadrature detection is employed to increase SNR
locally at the region-of-interest (ROI) as proposed in previous works using EM
simulations2. Performance was evaluated and compared to a standard spine array
using phantom measurements.Methods
An RF
coil array composed of two single loop coils and a butterfly (B2SL) was built
using 3mm-wide copper tape. The single loops were octagonal (16cm across, 5.1cm
corners). The butterfly was built with two squared lobes of 17.5cm in length.
Decoupling between the loops was achieved using overlap and between the loops
and the butterfly using magnetic flux compensation. The latter was done by
concentric placement of the elements along the x-axis (Fig. 1A). Additionally,
a 5mm distance in the y-axis between the loops and the butterfly was added to
increase decoupling. All coils were actively decoupled. Additional passive
decoupling was also employed in the butterfly due to its large size. Reception
paths included cable traps and low-noise pre-amplifiers (Fig 1B). The housing
of the array was built with the dimensions 45x50x5.5cm³ (LRxHFxAPcm³) to fit
the patient table (Fig. 1C). The thickness of the housing cover was 0.5cm and a
distance of 0.4cm was added between the phantom and the coil to simulate a
cushion expected to be used for patient comfort. 5 cylindrical containers
(radius=57.5mm, length=200mm) with a solution of 3.75g NiSO4x6H2O+5g NaCL per
1000g distilled water were used as phantom (Fig.1D). For comparison, 3 and 9
elements (SP3c and SP9c) of the system’s spine array were used. Measurements
were performed in a 3T MAGNETOM Trio system (Siemens Healthcare, Erlangen,
Germany). 2D sagittal and coronal scans were acquired using a gradient echo
sequence with the parameters: TE/TR=10/100ms, flip angle=90°, field-of-view=200x200mm,
matrix size=320x320, thickness=5mm and BW=260Hz/pixel. For the calculation of
SNR maps and noise matrices, noise scans were acquired using the same
parameters without transmission power. Complex SNR maps were calculated
per-channel and combined by adaptive combination3. A reference scan of a healthy male volunteer (186cm, 83kg) was
acquired for a realistic determination of the ROI. The scan was acquired using:
Siemens spine (12 channels) + Siemens body (6 channels) arrays, sequence:
2D-TSE, parameters: TE/TR=101/3500ms, flip-angle=137°, Turbo-factor=27,
field-of-view=200x2200mm, matrix size=320x320, thickness=3mm, Averages=2,
GRAPPA4=2, ACS=32. For evaluation,
SNR profiles of the three axes were plotted going through the phantoms at positions
where the center of the prostate was located in the reference image.
Quantitative comparisons were obtained using mean SNR values measured in a
rectangular ROI (36x24px²) centered using the prostate in the reference scan.Results
Noise correlations were found to be 51/42% between the upper/lower loop
and the butterfly. 28% was found between the single loops. Profiles plotted
show increased SNR values in B2SL in comparison to the spine array using 3 and
9 channels. Using the proposed array, mean SNR gains of approximately 1.12 and
1.09-fold were obtained (SP3c and SP9c, respectively) in both planes (transversal and
sagittal) at the ROI. Mean SNR values can be observed in Figure 2.Discussion
Prostate MRI is a very particular application where the imaging target
is almost an order of magnitude smaller than the field-of-view used for
abdominal imaging. Moreover, the central location of the prostate within the
abdomen requires adequate local SNR to ensure diagnostic quality of the images.
Out experiments showed that quadrature detection is well suited for these
purposes. Moreover, SNR gains were found using the proposed array compared to
the spine array. However, fuses are yet to be inserted in our design which
could decrease the SNR gains and further optimization might be required. The
further optimization and the assessment of parallel imaging performance in the
scope of our future work. We envision complementing our design with an anterior
quadrature array also tailored for the prostate to enhance SNR in-vivo. With these SNR gains we expect
increase image quality that could contribute to the diagnostic value of MRI in
prostate cancer.Conclusion
SNR gains in the prostatic region were obtained using a quadrature array
using phantom measurements. This concept should be further explored to increase
diagnostic values of prostate scans at 3T. Acknowledgements
No acknowledgement found.References
1. Shukla-Dave A and Hricak H. Role of MRI in prostate cancer detection. NMR in Biomedicine, 2014. 27.1, 16-24.
2. Chacon-Caldera
J, Uranga Solchanga J, Koziol P, and Schad LR. Numerical Comparison of
Stacked and Planar Coil Reception Arrays for Prostate MRI at 3 T. In
Proceedings of the 24th Annual Meeting of ISMRM, Singapore, 2016. p. 2166.
3. Walsh
D.O., Gmitro A.F. and Marcellin M.W. Adaptive reconstruction of phased array MR
imagery. Magn. Reson. Med., 2000. 43, 682-690.
4. Griswold, M. A. et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA).
Magn. Reson. Med., 2000. 47, 1202-1210.