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通过模拟退火优化复杂脉冲序列的参数值:应用于脑部三维MP-RAGE成像

Optimization of parameter values for complex pulse sequences by simulated annealing: application to 3D MP-RAGE imaging of the brain.

作者信息

Epstein F H, Mugler J P, Brookeman J R

机构信息

Department of Radiology, University of Virginia Health Sciences Center, Charlottesville 22908.

出版信息

Magn Reson Med. 1994 Feb;31(2):164-77. doi: 10.1002/mrm.1910310210.

Abstract

A number of pulse sequence techniques, including magnetization-prepared gradient echo (MP-GRE), segmented GRE, and hybrid RARE, employ a relatively large number of variable pulse sequence parameters and acquire the image data during a transient signal evolution. These sequences have recently been proposed and/or used for clinical applications in the brain, spine, liver, and coronary arteries. Thus, the need for a method of deriving optimal pulse sequence parameter values for this class of sequences now exists. Due to the complexity of these sequences, conventional optimization approaches, such as applying differential calculus to signal difference equations, are inadequate. We have developed a general framework for adapting the simulated annealing algorithm to pulse sequence parameter value optimization, and applied this framework to the specific case of optimizing the white matter-gray matter signal difference for a T1-weighted variable flip angle 3D MP-RAGE sequence. Using our algorithm, the values of 35 sequence parameters, including the magnetization-preparation RF pulse flip angle and delay time, 32 flip angles in the variable flip angle gradient-echo acquisition sequence, and the magnetization recovery time, were derived. Optimized 3D MP-RAGE achieved up to a 130% increase in white matter-gray matter signal difference compared with optimized 3D RF-spoiled FLASH with the same total acquisition time. The simulated annealing approach was effective at deriving optimal parameter values for a specific 3D MP-RAGE imaging objective, and may be useful for other imaging objectives and sequences in this general class.

摘要

许多脉冲序列技术,包括磁化准备梯度回波(MP-GRE)、分段GRE和混合RARE,采用了相对大量的可变脉冲序列参数,并在瞬态信号演变过程中采集图像数据。这些序列最近已被提出和/或用于脑部、脊柱、肝脏和冠状动脉的临床应用。因此,现在需要一种为这类序列推导最佳脉冲序列参数值的方法。由于这些序列的复杂性,传统的优化方法,如将微分学应用于信号差分方程,是不够的。我们已经开发了一个通用框架,用于使模拟退火算法适应脉冲序列参数值优化,并将该框架应用于优化T1加权可变翻转角3D MP-RAGE序列的白质-灰质信号差异的具体情况。使用我们的算法,得出了35个序列参数的值,包括磁化准备射频脉冲翻转角和延迟时间、可变翻转角梯度回波采集序列中的32个翻转角以及磁化恢复时间。与在相同总采集时间下优化的3D射频扰相FLASH相比,优化后的3D MP-RAGE的白质-灰质信号差异提高了130%。模拟退火方法有效地为特定的3D MP-RAGE成像目标推导了最佳参数值,并且可能对这类一般的其他成像目标和序列有用。

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