Ayhan Gursan1, Arjan D. Hendriks1, Dimitri Welting1, Dennis W.J. Klomp1, and Jeanine J. Prompers1
1Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
Synopsis
Deuterium
metabolic imaging (DMI) is an emerging method to assess metabolism in vivo. In
this study, we applied dynamic 3D DMI with oral administration of deuterated
glucose to investigate the dynamics of hepatic glucose uptake and metabolism at
7T. After glucose intake, the signal from deuterated glucose logarithmically
increased in the liver and plateaued around 100 min, after which it decreased
again, as a result of its conversion through glycolysis, oxidative metabolism
and, probably the largest part, glycogen synthesis. DMI will be a valuable tool
to study disturbances of liver metabolism in metabolic diseases.
Introduction
In type 2 diabetes, hepatic glucose metabolism is dysregulated, resulting
in impaired glycogen synthesis. 13C
MRS has been used to measure the rate of hepatic glycogen synthesis upon
infusion of 13C-labeled glucose1,2. However,
because of the low intrinsic sensitivity of 13C MRS and the long T1
relaxation times, 3D mapping of 13C-labeled metabolites using MRS
imaging (MRSI) is not feasible. Deuterium metabolic imaging (DMI) is a new
technique to study metabolism in vivo, which relies on MRSI combined with the administration of deuterated compounds, such as
deuterated glucose3. Last year we demonstrated that using a
dedicated 4-channel body array, the naturally abundant deuterated water signal
could be detected in the liver with DMI at 7T. In this study, we applied
dynamic 3D DMI with oral administration of deuterated glucose to investigate
the dynamics of hepatic glucose uptake and metabolism.Methods
DMI
measurements were performed at a 7T whole-body MRI system (Philips Healthcare, Best, Netherlands),
using a 4-channel body array consisting of 4 2H transmit/receive
loop coils combined with 4 1H transmit/receive dipole antennas. Before
the DMI experiments, conventional MRI was performed to optimize the B0
field and to make anatomical reference images for DMI planning. Coronal and axial
T1w, and axial Dixon images were acquired with the same field of view as for the DMI measurements, which,
together with the preparation steps, took approximately 30min. All DMI
measurements were performed with a pulse-acquire sequence using a 1ms block
pulse, followed by phase encoding gradients for 3D spatial encoding, an effective
echo time of 1.95ms and repetition time of 333ms. DMI acquisitions were made using
Hamming-weighted k-space acquisition patterns with 4 averages and without
respiratory gating.
One healthy volunteer was scanned
twice, about 3 months apart, after an overnight fast. [6,6’-2H2]glucose (0.75g per kg body weight) was dissolved
in ~300ml water and administered orally.
During the first session, the deuterated glucose was administered while the
volunteer was in the scanner, after two baseline DMI scans, and DMI scans were
then continued up to 130min after glucose intake. DMI parameters: voxel size 30x30x30mm3, matrix
size 8(AP)x10(LR)x9(FH), temporal resolution 5:08min. During the second session,
the deuterated glucose was administered 30min before the volunteer went into
the scanner. The first DMI experiment was acquired 68min after glucose intake
and scans were continued up to 205min after intake. DMI parameters: voxel size 25x25x25mm3, matrix
size 10(AP)x12(LR)x12(FH), temporal resolution 10:35min.
Reconstruction and processing of the
raw DMI data was performed with an in-house
written MATLAB script (MathWorks, Natick, MA, USA). Channel combination was performed using the Roemer
equal noise algorithm4. For each
voxel, water (4.7ppm), glucose (3.8ppm) and lipid (1.3ppm) signals were fitted
using AMARES5. For visual purposes, 5-Hz exponential
apodization and zero-filling to 2048 points was applied in the spectral domain.
Glucose maps were created using the amplitude of the fitted glucose signals
with 2D interpolation and Gaussian smoothing.Results
Results from the first scan, during which deuterated glucose was administered while the volunteer was in the scanner, are shown in Figures 1 and 2. Immediately after intake of the deuterated glucose, a very strong glucose signal was observed in the stomach (Fig. 1D+2) and, to a lower extent, in the anterior part of the liver (superior to lower part of the stomach; Fig. 1B+2B), which rapidly decayed over time. In the liver, the deuterated glucose signal then increased over time (Fig. 1B/C+2), following more or less a logarithmic curve.
Results from the second scan, during which deuterated glucose was administered 30 min before the volunteer went into the scanner, are shown in Figures 3 and 4. In all voxels, the signal from deuterated glucose was highest in the first experiment, 68 min after intake, and gradually decayed thereafter (Fig. 3+4).
In Figure 5, fitted water and glucose peak amplitudes from the voxel in the posterior part of the liver are combined for both scan sessions. The deuterated water signal gradually increased over time, while the deuterated glucose signal increased up to about 100 min after intake and then decreased again. Discussion and Conclusion
We
showed the application of 3D DMI for dynamic and spatially-resolved monitoring
of deuterated glucose uptake and metabolism throughout the human body. In the
liver, the signal at 3.8 ppm increased and plateaued around 100 min after
intake of deuterated glucose, after which it decreased again. This signal most
likely originates solely from deuterated glucose, as it was shown that detection
of deuterated glycogen is likely not feasible in vivo6. The dynamics therefore represent the
hepatocellular uptake of glucose and its conversion through glycolysis,
oxidative metabolism and, probably the largest part, glycogen synthesis. The
small but gradual increase in deuterated water signal up to the latest time
point at 205 min is likely caused by oxidative metabolism of deuterated glucose
and glycogen (after it is broken down to glucose again). However, we did not
observe any signals from deuterated glutamate and glutamine in the liver. When
the DMI method is applied in patients with type 2 diabetes patients, it will advance
our understanding of the disturbances in liver metabolism in diabetes, at a
detail which cannot be achieved by any other technique.Acknowledgements
This work was funded by a HTSM grant from NWO TTW (project number 17134) and by a FET Innovation Launchpad grant from the EU (grant number 850488).References
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