Synopsis

This study proposes a simple and accurate dictionary creation method for MR fingerprinting using a fast Bloch image simulator. A typical MR fingerprinting sequence based on a FISP sequence and a numerical phantom were used for dictionary generation. Cartesian and spiral readout gradients were used for the Bloch image simulation of the numerical phantoms. MR fingerprinting parameter maps obtained by pattern matching with the dictionaries generated by the proposed method demonstrated validity and usefulness of the method. The proposed method is simple and useful for creation of accurate dictionaries in MR fingerprinting.

Introduction

Methods

A FISP-based MRF sequence³ consisted of 1000 TR units was designed for the Bloch image simulator. The TR unit consisted of a selective-excitation pulse (hamming-windowed sinc: ±2π, 3.2ms duration) with unbalanced slicing gradient and a variable-density spiral readout gradient (TE=3ms, 7.47ms sampling window, 5µs dwell-time) with 0-th moment compensation. FA was varied as sinusoidal function of 0~π for the TR_index of 0~200, 250~450, 500~700, and 750~950, and the maximum of the FA was π/4, π/2, π/4, and π/2. To enhance the T1 contrast, an inversion pulse was applied 100ms before the acquisition. The spiral trajectory was designed for 256×256 image matrices with 256mm square FOV to fill the k-space using the 48 segments separated by 7.5° rotation angle. In the MRF sequence, the rotation angle of the trajectory was incremented by 120°, 120°, 127.5°, 120°, 120°, 127.5° … to utilize the sliding window reconstruction. The MRF dictionary was acquired with the 48 repetitions of the MRF sequence with increasing the rotation angle by 7.5° (full spiral-sampling). For comparison, Cartesian sampling (TE=3ms, 1.28ms sampling window, 5μs dwell-time) MRF sequence was also used for dictionary calculation.

Figure 1A-C shows a relaxation-time phantom that simulated ten cylindrical containers filled with materials having identical PD, T₁ from 228 to 1666ms, and T₂ from 37 to 150ms. Figure 1D-F shows a dictionary phantom filled with materials having identical PD and all possible combinations of relaxation times. In the dictionary phantom, T₁ varied from 100 to 1000 by 10ms steps, from 1000 to 2000 by 20ms steps, and from 2000 to 5000 by 100ms steps, and T₂ varied from 10 to 200 by 2.5ms steps and from 200 to 500 by 25ms steps. 9,219,072 and 13,464,000 isochromats were used for the Bloch image simulations of the numerical phantoms.

Results

Figure 2A shows the 280th image of the relaxation-time phantom acquired with the one-shot MRF sequence and reconstructed from three consecutive signals. The temporal changes of the pixel values at the center of the cylindrical samples are shown in Figure 2B. The abrupt changes were caused by reconstruction noise. The simulation time for the one-shot MRF sequence was 137 seconds.

Figure 3 shows images selected from the image series of the dictionary phantom acquired with the full MRF sequences. The simulation times for the dictionaries were 5.89 and 2.75 h. No noticeable artifacts were seen in the image by Cartesian sampling, whereas remarkable reconstruction noise appeared in that by the spiral sampling. However, reconstruction noise was almost removed by the LPF. Therefore, we used the image dataset obtained from the Cartesian-sampling and the low-pass filtered image dataset obtained from the spiral sampling for the dictionary matching.

Figure 4 shows temporal changes in the image intensity of the MRF dictionaries. Although two dictionary datasets presented almost the same changes, remarkable intensity decrease in shorter T₂ entries for the spiral sampling dictionary was observed.

Figures 5 show matching results for the relaxation-time phantom datasets and the two dictionaries, deviation maps from true values, and correlation plots for T₁ and T₂. The Cartesian dictionary was used in A and C and the spiral dictionary was used in B and D. The Cartesian sampling MRF image dataset and the full spiral-sampling MRF image dataset were used in A and B. The one-shot spiral-sampling MRF image dataset was used in C and D. Figure 5A clearly shows that the deviation in T₁ and T₂ was caused by the lack of resolution of the dictionary entries. Figure 5B shows that the deviation in T₁ and T₂ was caused by reconstruction noise as well as the lack of the resolution. In Figures 5C-5D, the deviation in T₁ and T₂ were mostly caused by the reconstruction noise but the matching result for 5D was better than that for 5C, which demonstrated the shorter T₂ effect on the spiral trajectory.

Discussion and Conclusion

Bloch image simulation for a FISP-based MRF sequence clarified a difference between trajectories used for the data-acquisition.

In conclusion, Bloch image simulations successfully reproduced the MRF process and the proposed method is a simple and accurate method for dictionary generation in MRF.

Acknowledgements

References

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