Purpose:To model and correct the dephasing effects in the gradient-echo signal for arbitrary RF excitation pulses with large flip angles in the presence of macroscopic field variations. Methods: The dephasing of the spoiled 2D gradient-echo signal was modeled using a numerical solution of the Bloch equations to calculate the magnitude and phase of the transverse magnetization across the slice profile. Additionally, regional variations of the transmit RF field and slice profile scaling due to macroscopic field gradients were included. Simulations, phantom, and in vivo measurements at 3 T were conducted for R * 2 and myelin water fraction (MWF) mapping. Results: The influence of macroscopic field gradients on R * 2 and myelin water fraction estimation can be substantially reduced by applying the proposed model. Moreover, it was shown that the dephasing over time for flip angles of 60° or greater also depends on the polarity of the slice-selection gradient because of phase variation along the slice profile. Conclusion: Substantial improvements in R * 2 accuracy and myelin water fraction mapping coverage can be achieved using the proposed model if higher flip angles are required. In this context, we demonstrated that the phase along the slice profile and the polarity of the slice-selection gradient are essential for proper modeling of the gradient-echo signal in the presence of macroscopic field variations.
K E Y W O R D Sfield inhomogeneities, myelin water fraction, R * 2 , relaxometry, slice profile, T * 2
Non-selective inversion pulses find widespread use in MRI applications, where requirements on them are increasingly demanding. With the use of high and ultrahigh field strength systems, robustness to ΔB 0 and B þ 1 inhomogeneities, while tackling SAR and hardware limitations, has rapidly become important. In this work, we propose a time-optimal control framework for the optimization of ΔB 0 -and1 -robust inversion pulses. Robustness is addressed by means of ensemble formulations, while allowing inclusion of hardware and energy limitations. The framework is flexible and performs excellently for various optimization goals. The optimization results are analyzed extensively in numerical experiments. Furthermore, they are validated, and compared with adiabatic RF pulses, in various phantom and in vivo measurements on a 3 T MRI system.
We optimized CEST saturation pulse train using an optimal control framework and validated the simulation results on a preclinical scanner that allowed also Gold Standard continuous wave saturation. The optimized pulses almost reached the same saturation as the continuous wave pulse while addressing the allowed duty cycle and SAR limitations of clinical scanners. In measurements, the optimized pulses outperform state-of-the-art Gaussian pulses by over $$$47\%$$$.
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