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Hydration imaging of skeletal muscle tissue based on fat referenced water-fat separated MRI
Thobias Romu1,2, Patrik Tunón3, Fredrik Uhlin 4,5,6, Micael Gylling4, Mårten Segelmark4,6, Anders Fernström4,6, and Olof Dahlqvist Leinhard2,6

1Department of Biomedical Engineering, Linköping University, Linköping, Sweden, 2Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden, 3Advanced MR Analytics AB, Linköping, Sweden, 4Department of Nephrology, Region Östergötland, Sweden, 5Biomedical Engineering, Tallinn University of Technology, Estonia, 6Department of Medical and Health Sciences, Linköping University, Sweden

Synopsis

This work introduces a signal model for imaging of the local hydration of lean tissue, based on water-fat separated MRI. The signal model is calibrated on a healthy cohort and then evaluated on a cohort of hemodialysis patients.

Introduction

Currently there are no good quantitative imaging methods for determining the hydration of soft tissue. On a systematic level hydration imaging can help to better describe the dynamic water regulation of the body, and potentially determine the dry weight of hemodialysis patients. On a local level, hydration imaging can help to locate and characterize inflammation, and increase the precision of volumetric measurements of organs by removing variations induced by the current tissue hydration.

The aim of this pilot study was to show that the hydration, relative to a reference value, of muscle tissue can be detected based on water-fat MRI.

Theory

The aim is to construct the relative hydration ratio Hϕ of a tissue ϕ based on T2 and lipid spectrum corrected water-fat MRI, where Hϕ=1 if normally hydrated, Hϕ<1 if under hydrated and Hϕ>1 if over hydrated.

From a water-fat MRI perspective the tissue distribution within a voxel can be described as Vϕf+Vϕw+Vϕi=1, where Vϕx are the fat, water and MR invisible volume fractions. Thus a lean tissue water concentration (LTW) can be defined:

LTW=VϕwVϕw+Vϕi=Vϕw1Vϕf

and Hϕ can be determined by a LTW reference:

Hϕ=LTWϕLTWϕref

Assuming a global T1 saturation factor for fat the water-fat signals can be described as:

w(r)=k(r)sϕwρw(r)

f(r)=k(r)sfρf(r)

where k(r) is a unknown scale factor, s the saturation and ρ the number of lipid or water bound protons.

The Vϕf can be determined by using the fat signal of nearby adipose tissue fAT as a signal reference, these calibrated images are defined as:

fc(r)=f(r)fAT,wc(r)=w(r)fAT

and, assuming k(r1)k(r2) and compensating fro non-lean tissue:

fc(r)VATf=k(r)sfρf(r)k(rAT)sfρATf/VATfρf(r)ρATfVATf=Vf(r)

Provided that the proton density of the water and lipid compartments are identical, as in the liver1, Vϕw relation to wc becomes:

wϕ(r)fAT/VATf=k(r)sϕwρw(r)k(rAT)sfρATf/VATfsϕwρf(r)sfρATfVATf=sfsϕwVw(r)

thus

LTWϕ=Vϕw1Vϕf=sfsϕwwϕcVATf1fϕcVATf=sfsϕwwϕc1/VATffϕc

and assuming that the LTWϕref saturations are equal to that in LTWϕ, then Hϕ is only dependent on wϕc, fϕc and VATf.

Methods

The volume fraction VATf was assumed to be constant and set to 0.86, based on the average distribution of water, fat and protein observed by Thomas2 and densities reported by Siri2.

A skeletal muscle reference LTWMref was established from whole-body scans of 19 postmenopausal women, using 10 axial 3D spoiled GRE stacks acquired on a Philips Ingenia 3T with, flip angle = 10°, TE = 1.15/2.3/3.35/4.6 ms, TR = 5.8 ms, FOVs 340x560 mm3 and voxel size of 2.5x2.5x4 mm3. Water-fat images were separated by a 2-point reconstruction4 that initialized a reconstruction using a complete signal model5. The water-fat images were calibrated6,7 and the abdominal and leg skeletal muscles segmented8, so the average LTWMref could be computed, see figure 1.

To show that the relative hydration of skeletal muscle HM is dependent on the current hydration, 11 hemodialysis patients were imaged and analyzed as above pre/post hemodialysis. The relative hydration HM was computed based on LTWMref. Furthermore, the pre/post dialysis weight and the net fluid drawn during dialysis were recorded, see figure 2.

The HM and muscle volume of both cohorts were measured and compared using t-tests. The change in HM and muscle volume following hemodialysis was analyzed using paired t-tests. The agreement between MRI and external measurements were assessed using linear regression.

Results

The observed measurements and standard deviations can be found in figure 3. The between cohorts t-tests showed significant differences in HM between healthy volunteers and hemodialysis patients pre (p < 0.001) and post (p < 0.001) hemodialysis. In the hemodialysis cohort paired t-tests showed a significant reduction in HM (p = 0.009), muscle volume (p < 0.001) and weight (p < 0.001). The results of the linear regression between MRI and external measurements are found in figure 4.

Discussion

The relative hydration HM is sensitive to the hydration level, as illustrated by the difference between healthy subjects and hemodialysis patients, and the delta HM caused by hemodialysis. The study also shows that the muscle volume can vary significantly based on hydration, which is a potential confounder for muscle volume measurement of any population.

The findings in this study are limited by the assumed constant VATf, for increased accuracy the method should take adipose hydration into account. Furthermore, the reference cohort does not represent the general population. Although HM has been shown to be hydration dependent, further work is needed to properly calibrate and verify the method before applying it for over/under hydration predictions.

Conclusion

The hydration level relative to a reference can be measured by water-fat MRI with adipose tissue as a signal reference. This method can potentially improve hemodialysis care by accurate and objective dry weight measurement.

Acknowledgements

No acknowledgement found.

References

1. Longo, R., Pollesello, P., Ricci, C., Masutti, F., Kvam, B. J., Bercich, L., Croce, L. S., Grigolato, P., Paoletti, S., De Bernard, B., Tiribelli, C. and Dalla Palma, L. (1995), Proton MR spectroscopy in quantitative in vivo determination of fat content in human liver steatosis. J. Magn. Reson. Imaging, 5: 281–285. doi:10.1002/jmri.1880050311

2. Thomas, Lorette W., (1962), THE CHEMICAL COMPOSITION OF ADIPOSE TISSUE OF MAN AND MICE. Experimental Physiology, 47 doi: 10.1113/expphysiol.1962.sp001589.

3. Siri, William E. "Body composition from fluid spaces and density: analysis of methods." Techniques for measuring body composition 61 (1961): 223-44.

4. Romu, T., Dahlström, N., Leinhard, O. D. and Borga, M. (2016), Robust water fat separated dual-echo MRI by phase-sensitive reconstruction. Magn. Reson. Med.. doi:10.1002/mrm.26488

5. 1.Yu H, Shimakawa A, McKenzie CA, Brodsky E, Brittain JH, Reeder SB. Multi-Echo Water-Fat Separation and Simultaneous R2* Estimation with Multi-Frequency Fat Spectrum Modeling. Magnetic resonance in medicine?: official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 2008;60(5):1122-1134. doi:10.1002/mrm.21737.

6. T. Romu, M. Borga and O. Dahlqvist, "MANA - Multi scale adaptive normalized averaging," 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Chicago, IL, 2011, pp. 361-364. doi: 10.1109/ISBI.2011.5872424

7. O. D. Leinhard et al., "Quantitative abdominal fat estimation using MRI," Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, Tampa, FL, 2008, pp. 1-4. doi: 10.1109/ICPR.2008.4761764

8. Karlsson, A., Rosander, J., Romu, T., Tallberg, J., Grönqvist, A., Borga, M. and Dahlqvist Leinhard, O. (2015), Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water–fat MRI. J. Magn. Reson. Imaging, 41: 1558–1569. doi:10.1002/jmri.24726

Figures

The image analysis chain.

The experimental setup of the hemodialysis experiment.

Average measurements and standard deviations of the healthy cohort and the hemodialysis cohort per/post dialysis.

Regression analysis between MRI delta derived hydration, delta muscle volume against delta weight and net fluid drawn at dialysis.

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)
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