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Myelin and cortical bone short-T2 quantification using saturation and diffusion-based long-T2 suppression in a steady-state 3D-UTE sequence
Lucas Soustelle1, Paulo Loureiro de Sousa1, Julien Lamy1, Mathieu D. Santin2, François Rousseau3, and Jean-Paul Armspach1

1Université de Strasbourg, CNRS, ICube, FMTS, Strasbourg, France, 2ICM, CENIR, UPMC-Inserm U1127, CNRS 7225, Paris, France, 3Institut Mines Télécom, Télécom Bretagne, INSERM LaTIM, Brest, France

### Synopsis

Imaging of the very-short T2 tissues in the head is challenging in that the signals decay very rapidly (T2 < 1 ms), as well as their signal quantity being often overwhelmed by long-T2 relaxing components (fat, free-water). In this work, we explore the feasibility of short-T2 quantification in the white matter and in the cortical bone using a novel method for long-T2 suppression based on diffusion and coherence effects in a steady-state 3D-UTE sequence.

### Purpose

Fast decaying signals of cortical bone and myelin in the central nervous system are challenging to acquire since long relaxing signals remain dominant, and a short-acquisition start is mandatory. Myelin is especially more complex to directly image since white matter (WM) content is mainly composed of free-water, as well as phospholipids and proteins (with an expected T2* range from 50 $\mu$s to 1 ms)1,2. Globally, employing a long-T2 suppressing scheme along with a UTE acquisition module has shown to allow short-T2 quantification in biological tissues3,4. Numerous methods to highlight these species exist using a proper preparation to minimize the undesired signal contamination (Inversion-Recovery modules3 or more complex and specific long-T2 suppression pulses5). In this work, we use a novel method for long-T2 suppression in a steady-state 3D-UTE sequence, allowing short-T2 quantification in a mouse head. Simulations and analysis were performed using the Extended Phase Graph (EPG) formalism6.

### Theory

The pulse sequence employed (fig. 1) consists in a long ($\gg$$T_2^{short}$) saturation rectangular-pulse followed by a short one, whose flip angle will be computed to maximize the short-T2 signal. Gradient spoiling, RF spoiling and delays are optimized to ensure a steady-state of the long-T2 component to be suppressed, and a minimal impact of potential static gradients (e.g. B0 inhomogeneities)7,8.

Given a first flip angle $\alpha_1$ = 90°, $\alpha_2$ ($\leq$ 90°) is computed to maximize the short-T2 component by using the Bloch equations (accounting for relaxation occurring during excitation9), and using myelin semi-solid T1 and T2* values found in [4]. Then, using the expression of configuration states in [6], the signal to be suppressed can be written:

$$F_0^+=\cos(\alpha_2/2)^2F_{0}^-+e^{2i\Phi}\sin(\alpha_2/2)^2F_0^{-*}-ie^{i\Phi}\sin(\alpha_2)Z_{0}^{-},$$

with $F_0$ and $Z_0$ being functions of $\alpha_1,\alpha_2$, RF-phase $\Phi,n=TR_2/TR_1,TR_2,TR_1,T_1^{long},T_2^{long}$ and diffusion coefficient $D$. Since no trivial analytical expression exists for the $F_0^-$ and $Z_0^-$ states in steady-state, we numerically explored the tissues and sequence parameters space in order to assess whether the diffusion effect induced by the spoiling gradients would combine the $F_0^-$ and $Z_0^-$ states in order to satisfy $|F_0^+|=0$, corresponding to a signal cancellation. This condition has been met in simulations using an EPG implementation (fig. 2).

### Method

Experiments were conducted on a 7T BioSpec 70/30 USR small animal MRI system (Bruker BioSpin MRI GmbH, Ettlingen, Germany). A mouse head soaked in PFPE (Galden, Solvay) was scanned with a 86 mm diameter transmitter and a mouse surface coil for reception. T1, T2 and D values were previously established in WM (T1=923$\pm$8.1 ms, T2=70$\pm$2.5 ms, D=(0.328$\pm$0.011).10-9 m²/s over the same spoiling direction), and used as an initial value computed in EPG to iteratively find the optimal $G_{spoil}$. Sequence parameters were: repetition time = 31.07 ms (TR1/TR2 = 5/25 ms (n = 5), $\tau_{1}$ = 1 ms, $\tau_{2}$ = 70 $\mu$s), 11 TE values from 8 $\mu$s to 1 ms for T2* quantification, $t_{spoil}$ = 3/15 ms, $G_{spoil}$ = 66.3 mT/m, $\alpha_1/\alpha_2$ = 90°/50°, RF phase increment $\Phi_0$ = 0°, receiver bandwidth = 138.88 kHz, matrix size = 128x128x128, voxel dimension = 0.156 mm isotropic, number of radial lines = 51530, dummy scans = 200 and 4 averaging for a total scan time of 19h58min. An additional scan with 16 averaging was performed with the same parameters at TE = 50 $\mu$s (scan duration = 7h05min). A ROI-based mono-T2* estimation was performed in the corpus callosum (CC) and in the cortical bone (CB)3,10, following the model $S(t)=S_0e^{-t/T_2*}+C$, where $C$ accounts for background noise, residual long-T2 signal and potential radial artifacts.

### Results

Fig. 3 shows axial and coronal views of the acquired head using the proposed method. A suitable suppression is obtained over the long-T2 component, offering a positive contrast over myelinated areas in WM (CC, anterior and posterior commissures, cerebellar peduncle, striatum, optic tract, internal capsule and fimbria) and in CB. Fig. 4 shows accurate T2* estimations of the fast relaxing component in CC ($R^2$=0.99) and CB ($R^2$=0.99), with estimated values of 62.1 $\mu$s and 260.1 $\mu$s, respectively.

### Conclusion

We have shown that a T2* quantification over short-T2 components while suppressing the undesired long-T2 component in a 3D experiment in a mouse head was made possible using the proposed method. The long scan time is a consequence of the small voxel dimension and the low relative proton density of myelin semi-solid pool in the WM (~4% in a human WM, implying a mandatory averaging to yield a reasonable SNR). The method shows to be compatible with high performance scanner, therefore lifting these limitations in a clinical application (e.g. because of a wider myelin volume).

### Acknowledgements

The authors thank Dr. Arnaud Duchon for mouse head preparation.

### References

1. Horch, R. et al., Origins of the ultrashort-T2 1H NMR signals in myelinated nerve: A direct measure of myelin content?, MRM 2011; 66:24-31

2. Wilhelm, M. et al., Direct MR detection of myelin and prospects for quantitative imaging of myelin density, PNAS 2012; 109:9605-9610

3. Du, J. et al., Ultrashort echo time (UTE) magnetic resonance imaging of the short T2 components in white matter of the brain using a clinical 3T scanner, NeuroImage 2014; 87:32-41

4. Du, J. et al., Measurement of T1 of the Ultrashort T2* Components in White Matter of the Brain at 3T, 2014 PLoS ONE; 9:e103296

5. Larson, P. et al., Designing long-T2 suppression pulses for ultrashort echo time imaging, MRM 2006; 56:94-103

6. Weigel, M., Extended phase graphs: Dephasing, RF pulses, and echoes - pure and simple, JMRI 2015; 41:266-295

7. Yarnykh, V. et al., Actual flip-angle imaging in the pulsed steady state: A method for rapid three-dimensional mapping of the transmitted radiofrequency field, MRM 2007; 57:192-200

8. Nehrke, K., On the steady-state properties of actual flip angle imaging (AFI), MRM 2009; 61:84-92

9. Sussman, M., Design of practicalT2-selective RF excitation (TELEX) pulses, MRM 1998; 40:890-899

10. Chen, J. et al., Fast volumetric imaging of bound and pore water in cortical bone using 3D-UTE and inversion recovery UTE sequences, NMR in Biomedicine 2016; 29:1373-1380

### Figures

Pulse sequence

Simulated signal vs. spoiling gradient amplitude. Explored parameters are T2, T1, D, TR and B1, with TR2/TR1=5 and $t_{Spoil}$=3/15 ms. Signal pit occurrences have a monotonic behavior with respect to the value of every parameter. As T2 is increasing, the diffusion effect prevails, making the pit position shifts less. T1 doesn’t have a significant impact in the tested range, unlike D as the latter controls the damping. TR also has an impact due to its involvement in the steady-state evolution through relaxation effects. B1 deviations also shift the pit, and even multiply occurrences for low gradient amplitudes.

Coronal (a-f) and axial (g-i) views of the mouse head using the proposed method. (a), (b) and (g-i) show CC, parts of the anterior commissure and internal capsule. Striatum, superior commisure, cerebellar peduncle, fimbria and optic tract can be found in figures (c-f). Cortical bone is well highlighted due to its relatively high proton density and longer T2*.

With a single exponential non-linear fitting, T2* value in CC was found to be 62.1 $\mu$s, and 260.1 $\mu$s in CB, with respective tight confidence interval. CB signal and corresponding fitted curve were divided by a factor of 3 for display purpose.

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)
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