Van Damme L, Mauconduit F, Chambrion T, Boulant N, Gras V
Institut Elie Cartan, Université de Nancy, Nancy, France.
CEA, CNRS, BAOBAB, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France.
Magn Reson Med. 2021 Feb;85(2):678-693. doi: 10.1002/mrm.28441. Epub 2020 Aug 4.
In MRI at ultra-high field, the -point and spiral nonselective (SPINS) pulse design techniques can be advantageously combined with the parallel transmission (pTX) and universal pulse techniques to create uniform excitation in a calibration-free manner. However, in these approaches, pulse duration is typically increased as compared to standard hard pulses, and excitation quality in regions exhibiting large resonance frequency offsets often suffer. This limitation is inherent to structure of -point or SPINS pulse, and likely can be mitigated using parameterization-free pulse design approaches.
The Gradient Ascent Pulse Engineering (GRAPE) algorithm was used to design parameterization-free RF and magnetic field gradient (MFG) waveforms for creating excitation, up to scalable refocusing and inversion, nonselectively across the brain. Simulations were performed to provide flip angle normalized root-mean-squares error (FA-NRMSE) estimations for the and the -point, SPINS, and GRAPE pulses. GRAPE pulses were tested experimentally with anatomical head scans at 7T.
As compared to -points and SPINS, GRAPE provided substantial improvement of excitation, refocusing, and inversion quality at off-resonance while at least preserving the same global FA-NRMSE performance. As compared to -points, GRAPE allowed for a substantial reduction of the pulse duration for the excitation and the refocusing.
Parameterization-free universal nonselective pTX-pulses were successfully computed using GRAPE. Performance gains as compared to -points were validated numerically and experimentally for three imaging protocols. In its current implementation, the computational burden of GRAPE limits its use to applications where pulse computations are not subject to time constraints.
在超高场磁共振成像（MRI）中，γ点和螺旋非选择性（SPINS）脉冲设计技术可以与并行传输（pTX）和通用脉冲技术有效结合，以无校准方式实现均匀激发。然而，在这些方法中，与标准硬脉冲相比，脉冲持续时间通常会增加，并且在共振频率偏移较大的区域，激发质量往往较差。这种局限性是γ点或SPINS脉冲结构所固有的，可能可以通过无参数脉冲设计方法来缓解。
使用梯度上升脉冲工程（GRAPE）算法设计无参数的射频（RF）和磁场梯度（MFG）波形，以在整个大脑中无选择性地创建激发、高达可扩展的重聚焦和反转。进行模拟以提供γ点、SPINS和GRAPE脉冲的翻转角归一化均方根误差（FA-NRMSE）估计。在7T下对GRAPE脉冲进行了头部解剖扫描的实验测试。
与γ点和SPINS相比，GRAPE在失谐时显著提高了激发、重聚焦和反转质量，同时至少保持了相同的全局FA-NRMSE性能。与γ点相比，GRAPE在激发和重聚焦时可大幅缩短脉冲持续时间。
使用GRAPE成功计算出无参数的通用非选择性pTX脉冲。在三种成像协议中，与γ点相比的性能提升在数值和实验上得到了验证。在其当前实现中，GRAPE的计算负担限制了其在脉冲计算不受时间限制的应用中的使用。
