Optimized T(1)-weighted MP-RAGE MRI of the brain at 0.55 T using variable flip angle coherent gradient echo imaging and deep learning reconstruction

利用可变翻转角相干梯度回波成像和深度学习重建技术,在0.55T磁场下对脑部进行优化的T(1)加权MP-RAGE MRI成像

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Abstract

PURPOSE: To propose and evaluate an optimized MP-RAGE protocol for rapid T(1)-weighted imaging of the brain at 0.55 T. METHODS: Incoherent and coherent steady state free precession (SSFP) RAGE kernels with constant and variable excitation angles were investigated in terms of the white matter SNR and the white matter-gray matter signal difference. Potential edge smearing from the transient signal readout was assessed based on a differential point spread function analysis. Finally, the prospects of a deep-learning reconstruction (DLR) method for accelerated MP-RAGE MRI of undersampled data were evaluated for the best performing variant. RESULTS: MP-RAGE imaging with a variable flip angle (vFA) SSFP-FID kernel outperformed all other investigated variants. As compared to the standard MPRAGE sequence using a spoiled gradient echo kernel with constant flip angle, vFA SSFP-FID offered an average gain in the white matter SNR of 21% ± 2% and an average improvement for the white matter-gray matter signal difference for cortical gray matter of 47% ± 7%. The differential point spread function was narrowest for the spoiled gradient echo but slightly increased by 8% for vFA SSFP-FID. For vFA SSFP-FID, DLR offered a considerable decrease in the overall scan time from 5:17 min down to 2:46 min without noticeable image artifacts and degradations. CONCLUSIONS: At 0.55 T, a vFA MP-RAGE variant using an SSFP-FID kernel combined with a DLR method offers excellent prospects for rapid T(1)-weighted whole brain imaging in less than 3 min with nearly 1 mm (1.12 × 1.17 × 1.25 mm(3)) isotropic resolution.

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