Synopsis
Existing
CEST methodologies have difficulties in discriminating agents with small difference
in chemical shift. As CEST signal is very sensitive to saturation power (B1)
and length (tsat), indicating a second route to indentify agents by
modulating the saturation conditions. We utilized the Multi-echo Parametric
VARiation Saturation (MePaVARS), to separate faster and slower exchanging endogeneous
CEST metabolites and molecules according to their differences response to B1.
In simulations and phantoms, MePaVARS allowed extraction of faster-exchanging Glutamate
from the slower-exchanging Creatine, based on its oscillation patterns. A
preliminary study for mice bearing prostate tumor further validated the
feasibility of MePaVARS in vivo. Purpose:
CEST imaging provides
the benefit of enabling detection of low concentration solute molecules through
amplifying their signal onto water. However, discriminating between agents with
small chemical shift differences using existing methodology which relies on
saturation frequency profiles is still quite difficult. CEST contrast is very
sensitive to saturation power (B
1), length (t
sat) and frequency
offset (∆ω), which provides a potential second route to discriminate between
agents based on modulating the saturation conditions. Herein we utilized this
dependence to identify CEST agents according to their different response to B1
due to variances in exchange rate (K
ex) and ∆ω, and termed this the
Multi-echo Parametric VARiation Saturation (MePaVARS).
Methods:
MePOVARS Sequence: Similar to our MeLOVARS method
1,2, the
MePaVARS sequence (
Fig.1a) places
gradient-echo image readouts in between
N saturation (sat.) pulses,
which may have a different B
1. As shown, the sat. pulses are the
same length but alternate between a higher B
1 (B
1_high)
and a lower one (B
1_low).
Simulations
and phantom experiments: Conventional MTR
asym spectra were
acquired for Glutamate (Glu) and Creatine (Cr) solutions with pH = 7.4, with B
0
= 11.7T, B
1 = 3.6uT and T
sat = 3.5s. Their exchange
rates (k
ex) were then fitted using a 2-pool Bloch-equation model.
The MePaVARS data with 8 module readouts were then simulated.
In vivo mice imaging: PC3 human prostate cancer cells were subcutaneously transplanted
in nude mice at the lower flank near the right thigh. MRI was performed in
an 11.7T Bruker horizontal scanner, with a 72-mm volume coil as the transmitter
and a phase-array surface coil as the receiver. Mice were anesthetized by isoflurane
with breath rate monitored during MRI.
MePaVARS sequence acquired 6 modules, each including a saturation pulse
of 0.5 sec. in length followed by a 4-shots EPI readout. Other parameters:
B
1low
= 1.8 uT (Module 1, 3, 5) and B
1high = 2.8 uT (Module 2, 4,
6); TR/TE = 3500ms/5ms, EPI module time = 7.2 ms, Flip Angle =25
o,
Matrix size = 96X64, FOV = 19.5mm X 16mm and slice thickness = 10mm.
Results:
We first performed Bloch-equation
simulations and the phantom studies for two endogenous Metabolites,
Glu and
Cr. Their conventional CEST spectra (
Fig.1b) shows a broader spectrum for Glu due to the faster exchange
(k
ex was fitted as ~6000/s) while a sharper peak for Cr with a
slower exchange (k
ex = ~360/s). MePaVARS sequence enable fast acquisition of 8 modules, each
weighted with different sat. parameters (B
1 and T
sat). Although in
Fig.1b Glu and Cr shows very similar MTR
asym values
~2.2ppm, MePaVARS produces an additional signal patterns given the 8-module MTR
asym
values at this frequency offset. The fast-exchanging Glu produced a
more-oscillated pattern than the slow-exchanging Cr, as its saturation
efficiency responds very different to B
1high and B
1low. Next, when
tested
MePaVARS
in vivo
on a mouse model of prostate tumor, we were able to acquire 6 modules of
readout, with CEST MTR
asym spectra of Module 2 & 4 shown in
Fig.2a. As seen, module 2 spectrum
displays significant difference from module 4 spectrum for tumor region, i.e.
signal at ~ 3.5 ppm and ~2.5 ppm increases from module 2 to module 4 while ~1
ppm it descrease. In contrast, control muscle region did not display such an
obvious change between the two MTR
asym curves. We plotted the MTR
asym
(~2.4ppm) as a function of module number as in
Fig.2b, where tumor region displaying a similar high-frequency
oscillation pattern as Glu, indicating the fast-exchanging amine protons. This
could also easily figured out from the two CEST maps, where averaging module 2&4
displays a much higher MTR
asym in tumor than the averaged map of 3&5 although with longer
saturation. We further did a voxel-by-voxel FFT for the signal series as
module#, with the magnitude map of 3 oscillations highlighting only a portion
of tumor (
Fig.2c right).
Conclusion:
Using simulations and
phantom studies of endogenous metabolites, e.g. Glu and Cr., we proved that
MePaVARS allow separation of slower exchange species from the faster ones. A
preliminary study for mice bearing prostate tumor further validate the
feasibility of MePaVARS
in vivo and
also indicate that parts of tumor contains molecules with faster exchange
Acknowledgements
No acknowledgement found.References
1. Song, X., Gilad, A. A., Joel, S., Liu, G., Bar-Shir, A., Liang, Y., Gorelik, M., Pekar, J. J., van Zijl, P. C. M., Bulte, J. W. M. and McMahon, M. T. (2012), CEST phase mapping using a length and offset varied saturation (LOVARS) scheme. Magn Reson Med, 68: 1074–1086. doi: 10.1002/mrm.23312
2. Song, X., Xu, J., Xia, S., Yadav, N. N., Lal, B., Laterra, J., Bulte, J. W.M., van Zijl, P. C.M. and McMahon, M. T. (2015), Multi-echo Length and Offset VARied Saturation (MeLOVARS) method for improved CEST imaging. Magn Reson Med, 73: 488–496. doi: 10.1002/mrm.25567