Taisuke Harada1, Kohsuke Kudo1, Ryota Sato2, Masato Yoshikawa1, Satoshi Yabusaki1, Toru Shirai2, and Yoshitaka Bito3
1Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan, 2Research & Development Group, Hitachi, Ltd., Tokyo, Japan, 3Healthcare Business Unit, Hitachi, Ltd., Tokyo, Japan
Synopsis
We compared three QSM reconstruction algorithms for
use in the upper abdomen: the water-fat separation method (WF), MUDICK, and iLSQR. A healthy male was scanned nine
times, in different positions, and three QSM reconstructions from the same source data
were compared. The intra-scan SD, representing
image homogeneity among images, and the inter-scan SD, representing repeatability among scans, were lower in WF than in MUDICK and iLSQR.
Thus, the WF method yielded better homogeneity and repeatability for susceptibility values in the upper
abdomen. This forms the basis for further clinical studies and applications of
QSM in the abdomen.
Purposes
Quantitative susceptibility mapping (QSM) is a novel method for evaluating magnetic
susceptibility, which can be applied for differentiating between calcium and
hemorrhage, estimation of iron and deoxy-hemoglobin concentration, etc. QSM has
been developed for use in the brain, and several reconstruction algorithms have
been constructed mainly in the brain; for example, morphology-enabled dipole
inversion (MEDI), a method with multiple dipole-inversion combination with
k-space segmentation (MUDICK) and an improved sparse linear equation and
least-squares algorithm (iLSQR) [1,2]. However, imaging the upper abdomen is
challenging, due to magnetic field inhomogeneity, phase shifts due to
physiological motion, and calculation error due to fat tissues. Sharma et al.
[3] reported water-fat separation by
using chemical shift imaging in the liver, but the QSM reconstruction was not
separated for water and fat. We hypothesized that water-fat separation in QSM reconstruction [4] may
be more suitable for the upper abdomen, as it can minimize the effect of fat
tissues. This study compared the homogeneity and repeatability between three
reconstruction methods: the water-fat separation method
(WF), MUDICK, and iLSQR.Material and Method
A healthy male volunteer was scanned using 3T MRI (Hitachi, Ltd., Tokyo,
Japan) with a 3D-gradient echo sequence, with breath-holding (TR 22.8 ms, multi
TE 3.1/6.6/10.1/13.6/17.1/20.6 ms, FA 10, FOV 38 cm, matrix 256 × 256,
thickness 3 mm, 64 slices, NEX 1, scan time 19 s). Eleven scans were performed,
with a position change in every scan (two scans were excluded because of
incomplete breath holding).
Three QSM reconstructions from the same source data were compared. MUDICK
and iLSQR were implemented without water-fat separation. In the WF algorithm, the source
images were divided into fat (fat fraction > 80) and water images (< 80),
and QSM reconstructions were conducted with the MUDICK method for each of these;
the two reconstructed images were then combined to produce the final QSM image.
Susceptibility values in each organ were manually measured with five round regions
of interest (ROIs; 3 mm) using 3D Slicer
version 4.5.0 (https://www.slicer.org/) in the back muscles, liver, spleen,
pancreas, kidney, aorta, and inferior vena cava (IVC).
Intra-scan standard deviations (SDs) and inter-scan SDs were compared among
the three methods. The intra-scan SD was the SD of five ROIs, and the average
of nine scans were compared. The inter-scan SD was the SD of nine scans,
calculated after averaging the five ROIs. Intra-scan SDs represented image
homogeneity, and were compared by paired t-tests
with Bonferroni correction. Inter-scan SDs represented repeatability among
scans, and were compared by F-test of variance with Bonferroni correction. P
< 0.05 represented a statistically significant difference.
Results
The WF method produced more
homogenous susceptibility values than the two conventional methods, which had artifactual
low values near fat tissues, particularly in the spleen, pancreas, and kidneys
(Fig. 1). Susceptibility values of the liver and spleen were higher than those
of other organs, due to iron deposition of the reticuloendothelial system, and those
of the IVC were higher than those of the aorta due to the increased deoxy-hemoglobin
concentration (Fig. 2). All but the aorta intra-scan SDs and inter-scan SDs
were smaller in the WF than in the conventional methods. Inter-scan SDs of the
spleen, pancreas, and left kidney differed significantly (Fig. 3), as did
intra-scan SDs in all organs but the aorta and the right liver lobe (p <
0.05) (Fig. 4).
Discussion
Few studies have reported QSM reconstructions in the abdomen, and
algorithms have not yet been compared. The conventional methods, but not the WF
method, showed artifactual low values near fat tissues. Intra-scan SDs were
smaller in the WF method than in the conventional methods, suggesting that the WF
method had more homogenous susceptibility in the target organ. We assume that
large susceptibility and frequency difference in the fat tissues affected
conventional QSM reconstruction, while those artifacts were minimized by water-fat separation during reconstruction. Inter-SDs
were low in the WF method, suggesting better repeatability. Therefore, we
assumed that water-fat separation resulted
in more homogeneous and repeatable QSM images. This study had some limitations;
a single volunteer, manual ROI setting, and no gold standard for susceptibility
values. Kudo et al. [5] reported that the oxygen extraction fraction could be
measured by using QSM in the brain. Similar indices of oxygen metabolism might
be applicable in the abdomen, and evaluation of deposition of iron and other
substances.Conclusion
Separate QSM reconstruction of water and
fat improves homogeneity and repeatability of susceptibility values in the upper
abdomen over MUDICK and iLSQR. This can facilitate further clinical studies and
applications of QSM in the abdomen.Acknowledgements
We received research funding from Hitachi,
Ltd., and R.S, T.S, Y.B are employee of Hitachi, Ltd.
References
[1] Sato, R., et al., Quantitative
susceptibility mapping using multiple dipole-inversion combination with k-space
segmentation. Magnetic Resonance in Medical Sciences, 2017. 16(4): p. 340-350.
[2] Wei Li, et al., A method for estimating and
removing streaking artifacts in quantitative susceptibility mapping.
Neuroimage. 2015. 108: p. 111-122.
[3] Sharma, S.D., et al., Quantitative
susceptibility mapping in the abdomen as an imaging biomarker of hepatic iron
overload. Magn Reson Med, 2015. 74(3): p. 673-83.
[4] Sato, R., et al. Quantitative susceptibility
mapping with separate calculation in water and fat regions. in ISMRM 25th
Annual Meeting & Exhibition 2017. 2017. Honolulu, HI, USA.
[5] Kudo, K., et al., Oxygen extraction fraction
measurement using quantitative susceptibility mapping: Comparison with positron
emission tomography. J Cereb Blood Flow Metab, 2016. 36(8): p. 1424-33.