Jian Hou1, Vincent Wong2, Baiyan Jiang1, Yixiang Wang1, Anthony Chan3, Winnie Chu1, and Weitian Chen1
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong, 2Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong, 3Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong, Hong Kong
Synopsis
Macromolecular
Proton Fraction (MPF) is the relative amount of protons associated with
macromolecules involved in magnetization transfer
with free water protons. MPF is typically measured by quantitative
magnetization transfer methods. In this work, we reported that MPF can also be
measured based
on spin-lock. Compared
to the existing MPF methods, our method requires fewer parameter maps.
We demonstrated our method using simulation, phantom, and in
vivo experiments.
Intoduction
The Magnetization Transfer
(MT) effect caused by cross-relaxation between protons of water and those
associated with semi-solid macromolecules can provide a unique contrast to
probe tissue properties1. Among various approaches
developed to quantify the MT effect2–6, one approach which attracts special interest is quantitative imaging
of macromolecular proton fraction (MPF). MPF is defined as the relative amount
of protons associated with macromolecules involved in magnetization exchange
with free water protons. The existing quantitative MPF
imaging methods typically require acquisition
of multiple parameter maps, including B1, B0, and T1 map, in addition to the
imaging data. In this work, we reported an approach to quantify MPF based on spin-lock, termed
MPF-SL.
We demonstrate that our approach only requires a B1
map in addition to the imaging data for MPF quantification.Methods
The
relaxation rate during the spin-lock can be expressed as contributions from
three terms7: R1rho(Δw, w1)=Reff(Δw, w1)+Rcest(Δw, w1)+Rmt(Δw, w1), where Δw is the resonance frequency
offset; w1 is the RF amplitude. Reff, Rcest and Rmt are the relaxation of the free
water pool, relaxation due to chemical exchange, and relaxation due to MT, respectively.
The proposed MPF-SL approach measures the difference of
R1rho from two acquisitions: Rmpfsl=R1rho(Δw(2), w1(2))-R1rho(Δw(1), w1(1))=ΔReff+ΔRcest+ΔRmt. In
MPF-SL, we choose the parameters such that: Δw(2)/w1(2)=Δw(1)/w1(1), and Δw/w1>>1. Under these
conditions, we have ΔReff=0 and ΔRcest≈0. Consequently,
we have Rmpfsl=ΔRmt. Note our
measurement Rmpfsl is specific
to the MT pool and is insensitive to the change of the free water pool and the
chemical exchange pool. After we obtain Rmpfsl, MPF
can be calculated from Rmpfsl using
the existing theory7,8. Note only
a B1 map is needed to measure MPF from Rmpfsl.
To obtain Rmpfsl, we use the approach
described in references9,10. Four images were acquired to calculate Rmpfsl: Rmpfsl=-log((Mtg(2)-Mntg(2))/ (Mtg(1)-Mntg(1)))/TSL, where TSL is time-of-spinlock,
subscript tg and ntg represent the toggling RF pulse on
and off, respectively, and (1) and (2) corresponds to the parameters (Δw(1), w1(1)) and (Δw(2), w1(2)), respectively. We performed simulation,
phantom, and in vivo studies to demonstrate the proposed method.
For all
simulation, phantom and in vivo experiments, Δw(1)=-1000Hz, w1(1)=100Hz, Δw(2)=-4000Hz, w1(2)=400Hz. For the
simulation study, Bloch-McConnell
simulation was performed to investigate Rmpfsl as
a function of MPF for cartilage, muscle, and liver tissues11. All MRI scans were conducted using a 3.0 T MRI
scanner (Philips Achieva, Philips Healthcare, Best, Netherlands). We performed two phantom
experiments. Phantom data sets were acquired using the 8-channel head coil. The
first phantom experiment
was used to demonstrate that MPF-SL imaging is sensitive to the MT pool
population. Five agarose phantoms were prepared using different concentration
of agarose (1%, 2%, 3%, 4% and 5%). Imaging Parameters of MPF-SL include:
resolution 1.5mm*1.5mm, slice thickness 7mm, TR/TE 2000/15ms, TSL 50ms. The
second phantom experiment
was used
to demonstrate MPF-SL imaging is insensitive to the relaxation of free water
pool.
The
imaging parameters were the same as those used in the phantom experiment
1.
For
the in vivo study, two
volunteers were scanned under the approval of the
institutional review board. These
two volunteers are the patients attending the hepatology clinics of our institute with fibrosis stage confirmed by liver biopsy.
They were screened and referred
to receive MRI exam. One volunteer has METAVIR score F0 and the other F2. A 32-channel cardiac coil was used as the receiver and the body coil was
used as the RF transmitter. Imaging parameters include: resolution 1.5mm*1.5mm,
slice thickness 7mm, and TR/TE 2000/20ms. SPIR
was used for fat suppression. A
single slice imaging data was acquired in a single breath-hold of 8 seconds.
A B1 map was collected to calculate MPF.Results
Figure 1 shows the results from simulation. Note Rmpfsl is approximately a linear function of MPF. Figure
2 is the results from the phantom experiment
1. Note the proposed MPF-SL
can detect
the changes of MPF. Figure 3 shows the results of phantom experiment
2. Note MPF-SL resulted in comparable
quantification when agarose concentration was the same, regardless of the
concentration of MnCl2. In contrast, T1rho quantification was
affected by the concentration of both agarose and MnCl2. Figure
4 shows the in
vivo results. Note obvious MPF accumulation in the liver of the volunteer with
early stage liver fibrosis (F2) compared to the normal subject (F0). This
is due to the fact that liver fibrosis is associated with collagen deposition,
which has strong MT effect and can be measured by MPF.Discussion & Conclusion
We proposed a novel approach
to quantify MPF. Our method is based on R1rho relaxation, but it removes the
confounding factors and is specific to MPF. Compared to the existing MPF
imaging methods, our method requires fewer parameter maps. Only a B1 map is
needed in addition to the imaging data. In contrast, the state-of-the-art MPF imaging approach requires acquisition of B1, B0, and T1 map in addition to the imaging data to quantify MPF8. It also assumes the product of the longitudinal and the transverse relaxation of the water pool is a constant. Such assumption is not required in the proposed approach.Acknowledgements
This
study is supported by a grant from
the Hong Kong General Research Fund (GRF) 14201817, a grant from the Innovation and
Technology Commission of the Hong Kong SAR (Project MRP/001/18X), a grant
from the Research Grants Council of the Hong Kong SAR (Project SEG
CUHK02), and a grant from the Hong Kong Health and Medical
Research Fund (HMRF) 06170166.References
- Henkelman, R. M.; Stanisz, G. J.;
Graham, S. J. Magnetization Transfer in MRI: A Review. NMR in Biomedicine
2001, 14 (2), 57–64. https://doi.org/10.1002/nbm.683.
- Sled, J. G.; Pike, G. B. Quantitative Imaging of Magnetization
Transfer Exchange and Relaxation Properties in Vivo Using MRI. Magnetic
Resonance in Medicine 2001, 46 (5), 923–931.
https://doi.org/10.1002/mrm.1278.
- Ramani, A.; Dalton, C.; Miller, D. H.; Tofts, P. S.; Barker, G.
J. Precise Estimate of Fundamental In-Vivo MT Parameters in Human Brain in
Clinically Feasible Times. Magnetic Resonance Imaging 2002, 20
(10), 721–731. https://doi.org/10.1016/S0730-725X(02)00598-2.
- Yarnykh, V. L. Pulsed Z-Spectroscopic Imaging of
Cross-Relaxation Parameters in Tissues for Human MRI: Theory and Clinical
Applications. Magnetic Resonance in Medicine 2002, 47 (5),
929–939. https://doi.org/10.1002/mrm.10120.
- Gochberg, D. F.; Gore, J. C. Quantitative Magnetization
Transfer Imaging via Selective Inversion Recovery with Short Repetition Times. Magn.
Reson. Med. 2007, 57 (2), 437–441.
https://doi.org/10.1002/mrm.21143.
- Li, K.; Zu, Z.; Xu, J.; Janve, V. A.; Gore, J. C.; Does, M. D.;
Gochberg, D. F. Optimized Inversion Recovery Sequences for Quantitative T1 and
Magnetization Transfer Imaging. Magnetic Resonance in Medicine 2010,
64 (2), 491–500. https://doi.org/10.1002/mrm.22440.
- Zaiss, M.; Zu, Z.; Xu, J.; Schuenke, P.; Gochberg, D. F.; Gore,
J. C.; Ladd, M. E.; Bachert, P. A Combined Analytical Solution for Chemical
Exchange Saturation Transfer and Semi-Solid Magnetization Transfer. NMR in
Biomedicine 2015, 28 (2), 217–230.
https://doi.org/10.1002/nbm.3237.
- Yarnykh, V. L. Fast Macromolecular Proton Fraction Mapping from
a Single Off-Resonance Magnetization Transfer Measurement. Magnetic
Resonance in Medicine 2012, 68 (1), 166–178.
https://doi.org/10.1002/mrm.23224.
- Jin, T.; Kim, S.-G. Quantitative Chemical Exchange Sensitive
MRI Using Irradiation with Toggling Inversion Preparation. Magnetic
Resonance in Medicine 2012, 68 (4), 1056–1064.
https://doi.org/10.1002/mrm.24449.
- Jiang, B.; Jin, T.; Blu, T.; Chen, W. Probing Chemical Exchange
Using Quantitative Spin-Lock R1ρ Asymmetry Imaging with Adiabatic RF Pulses. Magnetic
Resonance in Medicine 2019, 82 (5), 1767–1781.
https://doi.org/10.1002/mrm.27868.
- Stanisz,
G. J.; Odrobina, E. E.; Pun, J.; Escaravage, M.; Graham, S. J.; Bronskill, M.
J.; Henkelman, R. M. T1, T2 Relaxation and Magnetization Transfer in Tissue at
3T. Magnetic Resonance in Medicine 2005, 54 (3), 507–512.
https://doi.org/10.1002/mrm.20605.