Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods
Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods
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DOI：
10.1016/j.jmr.2015.03.003
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发表时间：
2015-05-01
影响因子：
2.2
通讯作者：
Shah, N. Jon
中科院分区：
文献类型：
--
作者：
Maximov, Ivan I.;Vinding, Mads S.;Shah, N. Jon
由于超高磁场系统、新的并行发射/接收线圈设计和可访问的强大计算设施的最新进展，越来越需要在现代磁共振成像（MRI）系统中开发先进的射频（RF）脉冲技术。2D空间选择性RF脉冲是具有许多临床相关应用的高级脉冲的示例，例如，2D空间选择性RF脉冲主要是利用可以处理大量控制和多个约束的数值方法来生成和优化的。通过这项研究，我们的目的是证明，数值，最优控制（OC）算法是有效的2D空间选择性MRI实验的设计，当对例如场不均匀性的鲁棒性是焦点。我们选择了三个流行的OC算法;两个是基于梯度的，并发的方法，分别使用一阶和二阶导数;和第三个属于顺序，单调收敛的家庭。我们使用了两个实验模型：一个水的幻影，在体内的人的头。考虑到具有挑战性的实验设置，我们的分析表明，使用顺序，单调的方法和二阶基于梯度的方法，计算速度，实验鲁棒性和图像质量是关键。在这项工作中使用的所有算法都在MATLAB环境中实现，并免费提供给MRI社区。(C)2015 Elsevier Inc. All rights reserved.
There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy.The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. (C) 2015 Elsevier Inc. All rights reserved.