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)2F−0+e2iΦsin(α2/2)2F−∗0−ieiΦsin(α2)Z−0,
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 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±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)=S0e−t/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
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