At the 7T MRI field, the absence of a volume reference coil results in inter channel phase offsets. It is therefore important to understand the impact of using different phase offset correction methods for producing combined phase images. We quantitatively analysed multi-channel offset corrected 7T GRE-MRI phase images of a phantom obtained using five established methods. Magnetic susceptibility images of a brain were assessed qualitatively in addition. We found that methods which phase offset correct using echo time dependent signal phases contain systematic errors, whereas single echo time methods produce more accurate results.
Introduction
A number of methods have been described in the literature for phase-offset correcting multi-channel MRI phase images. Hammond et al. propose the setting of the phase at the centre voxel of each channel in the imaging volume to zero [1]. Parker et al. create a virtual-reference coil (VRC), generated as a shifted weighted complex sum of the multi-channel signal, and used as a reference for each channel phase [2]. In COMPOSER, the measured phase at a very short echo time is used to correct the phase offset of each channel in the GRE-MRI data [3]. While in MCPC-3D, the offset correction is performed using the phase offsets calculated utilizing multiple echo time GRE-MRI data [4]. We investigate the impact of the choice of the phase offset correction method on combined phase images using a phantom and its impact on QSM images generated from 7T GRE-MRI data in a human brain.Methods
Multi-echo 3D GRE-MRI flow-compensated data were collected for a phantom (Fig. 1) and a male human brain using a whole-body 7T MRI research scanner (Siemens Healthcare, Erlangen, Germany) equipped with a 32-channel head coil (Nova Medical, Wilmington, USA) with the following parameters: TE = 4.4, 7.25, 10.2, 13.25, 16.40, 19.65 and 23ms, TR = 25ms, flip angle = 13o, voxel size = 0.75 x 0.75 x 0.75mm3 and matrix size = 280 x 242 x 128 (phantom) and 280 x 242 x 160 (brain).
We also used a prototype PETRA (Pointwise Encoding Time Reduction with Radial Acquisition) sequence to acquire data for the phantom and brain using the following parameters: TE = 0.07ms, TR = 1.99ms, flip angle = 2o, voxel size = 1 x 1 x 1mm3 and matrix size = 288 x 288 x 288. The multi-echo time multi-channel phase data were phase offset corrected using the following methods:
In each case, combined complex images were generated using the sum-of-squares approach. The combined data were used to generate quantitative susceptibility maps (QSM) from the brain data. QSM images were obtained using MRPhaseUnwrap, V-SHARP and iLSQR functions available in STI Suite v2.2 2015 [5, 6] and implemented in MATLAB® 2017b (MathWorks Inc., MA, USA).
Results
Fig. 3 and 4 provide the results of phase value changes, averaged over a 9 x 9 region, as a function of coil sensitivity measured using the amplitude of signal magnitude for ROI-1 (a region of relatively high signal amplitude variability) and ROI-2 (the low variability region) shown in Fig. 2(A). The VRC method produced the least amount of variability as a function of channel.
Fig. 5 provides zoomed-in results for two selected regions within the brain. COMPOSER and MCPC-3D methods were found to perform similarly, with the Hammond method producing generally less noisy results. From Fig. 4 we conclude that the impact of the choice of the reference may not necessarily deteriorate the quality of phase offset correction, but from Fig. 5 we can infer that the effect is non-trivial on the quality of QSM results. Overall, the quality of the VRC produced QSM images appears to be better than others.
Discussion
COMPOSER and MCPC-3D assume phase values evolve linearly with echo time, which may not hold in grey and white matter [7-10]. Whilst the method of Hammond et al. is computational efficient, the VRC approach was able to produce higher quality images [1, 2].
We have analysed how the choice of a certain coil for reference change the result with respect to the VRC method and we conclude that in cases involving receiver coils with dissimilar coil sensitivity profiles (Parker-8 for low, and Parker-12 for high), single-channel referencing could be used as a viable method for producing VRC quality images without the computational cost associated with deriving the virtual reference coil.
Conclusion
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