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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 μs 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 (Tshort2) 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 α1 = 90°, α2 ( 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(α2/2)2F0+e2iΦsin(α2/2)2F0ieiΦsin(α2)Z0,

with F0 and Z0 being functions of α1,α2, RF-phase Φ,n=TR2/TR1,TR2,TR1,Tlong1,Tlong2 and diffusion coefficient D. Since no trivial analytical expression exists for the F0 and Z0 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 F0 and Z0 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±8.1 ms, T2=70±2.5 ms, D=(0.328±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 Gspoil. Sequence parameters were: repetition time = 31.07 ms (TR1/TR2 = 5/25 ms (n = 5), τ1 = 1 ms, τ2 = 70 μs), 11 TE values from 8 μs to 1 ms for T2* quantification, tspoil = 3/15 ms, Gspoil = 66.3 mT/m, α1/α2 = 90°/50°, RF phase increment Φ0 = 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 μs (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)=S0et/T2+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 (R2=0.99) and CB (R2=0.99), with estimated values of 62.1 μs and 260.1 μs, 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 tSpoil=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 μs, and 260.1 μs 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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