Turbo spin echo (TSE) imaging with variable flip angle (VFA) is commonly used for three-dimensional (3D) high resolution intracranial vessel wall imaging. However, different tissues may experience various blurring effects particularly for longer TSE factor. In this study, a deep convolutional neural network is trained to provide a solution for this special deblurring problem. Combined with a signal-to-noise ratio (SNR)-priority VFA design scheme, the developed technique can provide a better tradeoff across scan efficiency, point spread function and SNR for 3D TSE acquisitions. Preliminary results have demonstrated its improvement for sharper delineation of intracranial vessel wall and plaque boundaries at isotropic 0.5mm resolution.
Optimization for T1 weighted TSE sequence: To further improve the SNR, the echoes generated through the entire Carr-Purcell-Meiboom-Gill echo train are acquired8 so that the echo time (TE) can be reduced to 5.4ms for isotropic 0.5mm resolution. The signal evolutions in the entire echo train are modulated by tuning the VFA design to achieve a desired PSF profile (e.g. Butterworth low-pass or all-pass filtering profile) for the vessel wall (T1/T2 = 844ms/39ms)9. The attenuation ratio of PSF gains between highest and lowest frequency component was 10, while the TSE factor of 40 was considered as a reasonable choice for scan efficiency (figure 1).
Deep CNN architecture for image super-resolution: A residual learning based deep CNN10, consisting of 20 convolutional layers with 64 channel of 3x3 filters in each layer (figure 2), is trained to synthesize the residuals or high frequency differences between different simulated low-pass filtered images and its original ones. The stochastic gradient descent with Nesterov momentum and the gradient clipping approach are used for training the parameters of this deep CNN. The training and testing of CNN were implemented with MatConvNet on a single GPU (NVIDIA, TITAN X).
MR experiments: All of the data acquisitions were performed on a Philips Ingenia 3.0T MR scanner with 32-channel head coil. An orange was scanned for 4 times with different VFA schemes by configuring various cutoff frequencies from 0.5 to 1.0 (1.0 means all-pass filtering). The trained deep CNN was applied to enhance the low-pass filtered images and the restored results were compared with the acquired all-pass filtered images. Two healthy volunteers were also recruited to evaluate the performance of the developed technique in comparison to one of the existing methods11 for intracranial VWI. In addition, one image dataset from a previously recruited patient with intracranial atherosclerosis was retrospectively enhanced with deep CNN to assess its performance for plaque delineation.
This study is supported by the grant from National Institutes of Health (5R01NS092207).
1. Qiao Y, Steinman DA, Qin Q, Etesami M, Schär M, Astor BC, Wasserman BA. Intracranial arterial wall imaging using three-dimensional high isotropic resolution black blood MRI at 3.0 Tesla. J Magn Reson Imaging. 2011;34(1):22-30.
2. Qiao Y, Steinman DA, Qin Q, Etesami M, Schär M, Astor BC, Wasserman BA. Intracranial plaque enhancement in patients with cerebrovascular events on high-spatial-resolution MR images. Radiology. 2014;271(2):534-42.
3. Yang H, Zhang X, Qin Q, Liu L, Wasserman BA, Qiao Y. Improved cerebrospinal fluid suppression for intracranial vessel wall MRI. J Magn Reson Imaging. 2016;44(3):665-72.
4. Fan Z, Yang Q, Deng Z, Li Y, Bi X, Song S, Li D. Whole-brain intracranial vessel wall imaging at 3 Tesla using cerebrospinal fluid-attenuated T1-weighted 3D turbo spin echo. Magn Reson Med. 2017;77(3):1142-1150.
5. Yang Q, Deng Z, Bi X, Song SS, Schlick KH, Gonzalez NR, Li D, Fan Z. Whole-brain vessel wall MRI: A parameter tune-up solution to improve the scan efficiency of three-dimensional variable flip-angle turbo spin-echo. J Magn Reson Imaging. 2017;46(3):751-757.
6. Hennig J, Weigel M, Scheffler K. Calculation of flip angles for echo trains with predefined amplitudes with the extended phase graph (EPG)-algorithm: principles and applications to hyperecho and TRAPS sequences. Magn Reson Med. 2004;51(1):68-80.
7. Busse RF, Hariharan H, Vu A, Brittain JH. Fast spin echo sequences with very long echo trains: design of variable refocusing flip angle schedules and generation of clinical T2 contrast. Magn Reson Med. 2006;55(5):1030-7.
8. Mugler JP 3rd. Optimized three-dimensional fast-spin-echo MRI. J Magn Reson Imaging. 2014;39(4):745-67.
9. Coolen BF, Poot DH, Liem MI, Smits LP, Gao S, Kotek G, Klein S, Nederveen AJ. Three-dimensional quantitative T1 and T2 mapping of the carotid artery: Sequence design and in vivo feasibility. Magn Reson Med. 2016;75(3):1008-17.
10. Kim J, Lee JK, Lee KM. Accurate image super-resolution using very deep convolutional networks. CVPR 2016.
11. Balu N, Zhou Z, Hatsukami T, Mossa-Basha M, Yuan C. Accelerated Multi-Contrast High Isotropic Resolution 3D Intracranial Vessel Wall MRI Using a Tailored K-Space Undersampling and Partially Parallel Reconstruction Strategy. ISMRM 2017, p2790.