John Thomas Spear1,2 and John Gore1,2,3,4
1Physics and Astronomy, Vanderbilt University, Nashville, TN, United States, 2Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 3Radiology, Vanderbilt University, Nashville, TN, United States, 4Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
Synopsis
R1ρ
dispersion provides insight into the rates of molecular processes that give
rise to relaxation, and a technique called Exchange Rate Contrast (ERC) can
differentiate proton pools based on chemical exchange rates. Double dispersion
phenomena may occur when three exchanging proton pools are present, and parametric
images may be calculated in which the image intensity scales with the
concentration of the exchanging pools. A theoretical equation was derived for
this contrast and shown to align well with Bloch-McConnell simulations. Various
applications with exogenous contrast agents present a great deal of potential
for utilizing this technique in practice.Purpose
Chemical
exchange between the bulk water pool and labile protons in solute pools in
tissues increases the spin-lattice relaxation rate in the rotating frame R
1ρ
(=1/T
1ρ), which can be evaluated using spin-locking pulse sequences.
Moreover, exogenous contrast agents may be designed that have specific exchange
rates that differ from endogenous tissue compounds. Exchange has been widely
studied recently using CEST techniques
1, but such methods
distinguish protons according to their chemical shifts whereas appropriate
spin-locking techniques may be selectively sensitized to specific rates of
exchange, especially at high fields. When three proton pools are present, the
variation of R
1ρ with locking field amplitude will display a “double
dispersion” with two inflections indicative of the exchange rates between the
pools. The Exchange Rate Contrast (ERC), which we have described previously
2,
can theoretically be used to distinguish each pool and create parametric images
in which the contrast reflects pool sizes which could potentially be used to
quantify metabolite concentrations non-invasively.
Methods
A theoretical expression for the ERC amplitude for a
three-pool mixture was derived by combining three values of R
1ρ at
locking fields of ~0, ω
1, and ~∞ using the approximate equation
derived from the Chopra model
3, $$$R_{1\rho}(\omega_1)\approx R_2^a+p_b\left[R_2^b+ \frac{k_{ba}\Delta \omega_b^2}{k_{ba}^2+\Delta\omega_b^2+\omega_1^2}\right]+p_c\left[R_2^c+ \frac{k_{ca}\Delta \omega_c^2}{k_{ca}^2+\Delta\omega_c^2+\omega_1^2}\right]$$$. This is valid under the reasonable assumptions that $$$k_{ba}\gg R_2^b>R_1^b$$$ and $$$k_{ca}\gg R_2^c>R_1^c$$$. Here $$$R_2^{a,b,c}$$$ are the
transverse relaxation rates of each pool, $$$p_{b,c}$$$ are the pool
fractions, $$$k_{ba}$$$ is the exchange
rate from pool b to pool a, $$$\Delta \omega_{b,c}$$$ are the chemical
shifts of the respective pools, and $$$\omega_1$$$ is the spin-lock
amplitude. The ERC equation may then be derived by combining the three R
1ρ
values as $$$ERC=4\frac{\left[R_{1\rho}\left(0\right)- R_{1\rho}\left(\omega_1\right)\right]\left[R_{1\rho}\left(\omega_1\right)- R_{1\rho}\left(\infty\right)\right]}{\left[R_{1\rho}\left(0\right)- R_{1\rho}\left(\infty\right)\right]^2}$$$. The ERC expression can be written as Eq. 1: $$ERC=4\omega_1^2\alpha\frac{\beta\delta}{\epsilon^2}$$ Here, $$$\alpha=\frac{\left(k_{ba}^2+\Delta\omega_b^2\right)\left(k_{ca}^2+\Delta\omega_c^2\right)}{\left(k_{ba}^2+\Delta\omega_b^2+\omega_1^2\right)^2\left(k_{ca}^2+\Delta\omega_c^2+\omega_1^2\right)^2}$$$, $$$\beta=\left[p_bk_{ba}\Delta\omega_b^2\left(k_{ca}^2+\Delta\omega_c^2+\omega_1^2\right)+p_ck_{ca}\Delta\omega_c^2\left(k_{ba}^2+\Delta\omega_b^2+\omega_1^2\right)\right]$$$, $$$\delta=\left[p_bk_{ba}\Delta\omega_b^2\left(k_{ca}^2+\Delta\omega_c^2\right)\left(k_{ca}^2+\Delta\omega_c^2+\omega_1^2\right)+p_ck_{ca}\Delta\omega_c^2\left(k_{ba}^2+\Delta\omega_b^2\right)\left(k_{ba}^2+\Delta\omega_b^2+\omega_1^2\right)\right]$$$, and $$$\epsilon=\left[p_bk_{ba}\Delta\omega_b^2\left(k_{ca}^2+\Delta\omega_c^2\right)+p_ck_{ca}\Delta\omega_c^2\left(k_{ba}^2+\Delta\omega_b^2\right)\right]$$$. The magnitude of the ERC
expression will be governed heavily by the frequency spread between the peaks
of each separate pool, with the maximum theoretical contrast being $$$\Delta ERC_{max}=1-4\frac{\left(k_{ba}^2+\Delta\omega_b^2\right)\left(k_{ca}^2+\Delta\omega_c^2\right)}{\left(k_{ba}^2+\Delta\omega_b^2+k_{ca}^2+\Delta\omega_c^2\right)}$$$. Subsequently, three pool
Bloch-McConnell simulations were run using the following parameters: B0
= 7T, Δω
b = 1 ppm, Δω
c = 0.5 ppm, k
ba = 20
kHz, k
ca = 0.5 kHz, $$$R_1^a=R_1^b=R_1^c=0.1$$$ Hz, $$$R_2^a=R_2^b=R_2^c=0.4$$$ Hz, ω
1 = 2π*(40 – 5,000)
rad/sec, p
b = 1%, and p
c = 0-1%. The simulated ERC points
were plotted against the theoretical ERC curves calculated from Eq. 1 and the
values corresponding to the ω
1 at the peak of the pool c ERC curve
were plotted for all pool fractions to produce a concentration dependent curve.
R
1ρ experiments will be performed in ex-vivo solutions to verify the
feasibility of the technique under various conditions.
Results
Simulated
R
1ρ dispersion curves are shown in Figure 1a in which the low
frequency dispersion curve increases as the slower exchanging pool fraction
increases. The corresponding ERC points are plotted in Figure 1b and the theoretical
curves calculated from Eq. 1 are plotted as solid lines. The thick vertical
black line indicates the ω
1 value at which the ERC peak of pool c
(dotted black line) displays the peak value of 1 ($$$\omega_1=\sqrt{k_{ca}^2+\Delta\omega_c^2}=160$$$ Hz). The value of each ERC
peak along the thick vertical black line is plotted in figure 1c to provide
insight into how the concentration affects ERC.
Discussion
Exchange
Rate Contrast derived from combinations of spin-lock images provides parametric
images in which the image intensity depends on the concentration of the
exchanging pools, the exchange rate of those pools, and the applied spin-lock
amplitude. Fixing the locking field to the frequency of the peak of one
exchanging pool effectively compares the magnitudes of the two separate
dispersions. Smaller pool fractions produce the largest change in ERC values,
demonstrating the region of highest sensitivity for the technique as shown in Figure
1c. This sensitivity may prove advantageous in experimental settings, but
certain limitations are anticipated. When the ERC peaks of the individual pools
are very close, the overall ERC cannot significantly shift and the available
contrast becomes limited. Also, if the dispersion magnitudes are not
significantly greater than the uncertainty in R
1ρ measurements, the
corresponding ERC image could become very noisy and make quantifying exchange
or concentration parameters difficult in practice. Injecting a very fast
exchanging exogenous agent would produce a higher frequency dispersion than
those caused by native metabolites and make the technique more effective in
practice.
Conclusion
A
novel theoretical expression for Exchange Rate Contrast was derived for three
exchanging pools that has been shown through simulations to produce
concentration dependent contrast that may prove useful for identifying some
exchange agents in the presence of a background of other exchanging protons.
Acknowledgements
This material is based upon work supported
by the National Science Foundation Graduate
Research Fellowship Program under Grant No.
DGE-0909667.References
1. Van Zijl et. al. Chemical Exchange Saturation
Transfer: What is in a Name and What Isn’t? Mag. Res. Med. 2011; 65(4): 927-948.
2. Cobb et al.
Exchange-Mediated Contrast in CEST and Spin-Lock Imaging. Mag. Res. Img. 2013;
32: 28-40.
3. Chopra et al. Rotating
Frame Relaxation Rates of Solvent Molecules in Solutions of Paramagnetic Ions
Undergoing Solvent Exchange. J. Mag. Res. 1984; 59(3):361-372.