Ultrashort Echo Time Magnetization Transfer (UTE-MT) Imaging: Two-Pool vs Three-Pool Modeling
Yajun Ma1, Graeme Bydder1, and Jiang Du1

1Department of Radiology, UCSD, San Diego, CA, United States

Synopsis

Conventional MT modeling can only be applied to long T2 tissues since short T2 tissues such as cortical bone show little or no signal with clinical sequences. Ultrashort echo time magnetization transfer (UTE-MT) imaging is likely to help with this difficulty. In this study we aimed to develop and utilize UTE-MT imaging and compare two-pool with three-pool modeling of bovine cortical bone samples using a clinical 3T scanner.

INTRODUCTION

Magnetization transfer (MT) is a MR technique that generates contrast based on the exchange of magnetization between several groups of spins in different molecular environments. Both two-pool and three-pool models have been proposed to characterize the different groups of spins. The three-pool MT model divides the spins within a biological tissue into three groups: 1) a free pool A, composed of mobile protons; 2) a bound water pool B, composed of water protons bound to macromolecules and 3) a semisolid pool C, that consists of macromolecular protons1. The two-pool MT model is highly simplified and only considers a water pool A and a macromolecule pool B. Theoretically, a three-pool model should be more accurate than the two-pool model for describing biological tissues.

Moreover, conventional MT modeling can only be applied to long T2 tissues since short T2 tissues such as cortical bone show litter or no signal with clinical sequences. Ultrashort echo time magnetization transfer (UTE-MT) imaging is likely to help with this difficulty. In this study we aimed to develop and utilize UTE-MT imaging and compare with two-pool and three-pool modeling of bovine cortical bone samples using a clinical 3T scanner.

MATERIALS AND METHODS

Both two-pool and three-pool MT models have been described in details in the literature1-4. Pool B is generally considered MR “invisible”. This is true with common clinical sequence but not correct with UTE sequences. With UTE-MT sequence, the signal equation is a combination of the steady-state longitudinal magnetization of pools A and B:$$S=M_z^Ae^{-TE/T_{2A}}+M_z^Be^{-TE/T_{2B}} [1]$$.

Where T2A and T2B are the T2 value of pools A and B. TE is the echo time. Data with different TEs can be useful in separating pools A and B. In addition, the continuous wave power equivalent (CWPE) method4 for pulsed wave MT saturation used for the two-pool MT model can also be used for the three-pool modeling. Here, Gauss spectral absorption lineshape for the pool C was employed.

Data were acquired from a sectioned bovine cortical bone specimen (thickness=2cm) using a 2D non-slice selective UTE-MT sequence on a clinical 3T scanner (GE Healthcare Technologies, Milwaukee, WI). The UTE sequence employed a short rectangular pulse (duration=32µs) excitation followed by 2D radial ramp sampling with a minimal nominal TE of 8µs. The MT preparation utilized a Fermi shaped RF pulse (duration=8ms) and a gradient crusher. The UTE-MT imaging protocol included: TR=100ms, TE=8µs, FOV=4cm, matrix=128×128, five saturation powers (300°, 600°, 900°, 1200° and 1500°) and five frequency offsets (2, 5, 10, 20 and 50 kHz) with a total of 25 different MT dataset. In addition, UTE data with sixteen TEs (i.e. 0.01, 0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8 ms) were acquired for bi-component T2* analysis.

For data processing, two-pool MT modeling was employed first to provide useful information for further three-pool modeling, such as the T2 value and fraction of semisolid pool C. These two parameters are fixed in the three-pool modeling in order to reduce the sensitivity to fitting errors. Finally the MT data and multiple TE data were combined together to fit Eq. [1].

RESULTS AND DISCUSSION

Fig. 1 shows a representative UTE image of a bovine cortical bone sample, and the region of interest used for MT analysis. Fig. 2 shows the two-pool MT model and excellent fitting curves. Table 1 shows the fitting results. The macromolecule pool has a short T2 of 14.5 µs and a fraction of 42.6%, consistent with results from NMR spectroscopy studies of cortical bone samples.

Fig. 3a shows the chain coupled three-pool model employed in this study. It is based on the assumption that the exchange rate between A and C is significantly less than the exchange rates between both A and B and B and C. The three-pool fitting curves are shown in the Fig. 3b and the corresponding fitting parameters are shown in Table 2. Pore water, bound water and macromolecule protons have T2s of 1.63 ms, 0.27ms and 14.5µs, with fractions of 13.2%, 44.2% and 42.6%. These values are largely consistent with the literature.

CONCLUSION

We have demonstrated that both two-pool and three-pool MT modeling can be accomplished in bovine cortical bone samples with the UTE-MT sequence. The two-pool modeling and UTE bi-component analysis provide prior information useful for the three-pool modeling and reduces fitting errors minimized. The two-pool and three-pool UTE-MT modeling approach can be applied to many other short T2 tissues such as menisci, ligaments, tendons, deep radial and calcified cartilage. It can provide a comprehensive evaluation of joint tissues degeneration in osteoarthritis (OA) and bone properties in osteoporosis (OP).

Acknowledgements

No acknowledgement found.

References

1. Kuwata K, Brooks D, Yang H, Schleich T. Relaxation-matrix formalism for rotating-frame spin-lattice proton NMR Relaxation and magnetization transfer in the presence of an off-resonance irradiation field. J Magn Reson 1994;104:11–25.

2. Henkelman RM, Huang X, Xiang QS, Stanisz GJ, Swanson SD, Bronskill MJ. Quantitative interpretation of magnetization transfer. Magn Reson Med 1993;29:759–766.

3. Tessier JJ, Dillon N, Carpenter TA, Hall LD. Interpretation of magnetization transfer and proton cross-relaxation spectra of biological tissues. J Magn Reson 1995;107:138–144.

4. Ramani A, Dalton C, Miller DH, Tofts PS, Barker GJ. Precise estimate of fundamental in-vivo MT parameters in human brain in clinically feasible times. Magn Reson Imaging 2002;20:721–731.

Figures

Figure 1. A representative UTE image of a section of bovine cortical bone and the region of interest (ROI) used for subsequent two-pool and three-pool modeling analysis.

Figure 2. The two-pool MT model (a) and fitting (b) of UTE-MT data acquired with five saturation powers (q = 300°, 600°, 900°, 1200° and 1500°) and five frequency offset (Δf = 2, 5, 10, 20 and 50 kHz). The theoretical two-pool model provides excellent fitting of the experimental data (b).

Figure 3. The three-pool MT model (a), fitting of UTE-MT data acquired with five saturation powers (q = 300°, 600°, 900°, 1200° and 1500°) and five frequency offsets (Δf = 2, 5, 10, 20 and 50 kHz) (b), and fitting of UTE data acquired with a series of TEs (C).

Table 1. T2 of water (T2w), T2 of macromolecule protons (T2m), fraction of macromolecule protons (fm), exchange rate from macromolecule to water (RM0w) and recover rate of longitudinal magnetization of water pool (Rw) derived from the two-pool modeling of UTE-MT data of a bovine cortical bone sample.

Table 2. T2 of pore water (T2A), T2 of bound water (T2B), T2 of macromolecule protons (T2C), fraction of pore water (fA), fraction of bound water (fB), fraction of macromolecule protons (fC), exchange rate from pore water to bound water (RAB), exchange rate from bound water to macromolecule (RBC), recovery rate of longitudinal magnetization of pore water (RA), bound water (RB) and macromolecule protons (RC) derived from the three-pool modeling of UTE-MT data of a bovine cortical bone sample.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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