论文标题
降低用于磁共振指纹的最佳实验设计的维度
Reducing the Dimensionality of Optimal Experiment Design for Magnetic Resonance Fingerprinting
论文作者
论文摘要
Bloch方程所描述的核磁共振信号动力学是高度复杂的，通常没有封闭式溶液。定量磁共振指纹（MRF）扫描尤其是这种情况，在该扫描中，采集参数的变化以有效探测参数空间。如前所述，相对于目标定量参数的方差，MRI采集参数的模式的优化可以改善实验设计。但是，这个过程依赖于大规模的非线性优化，数百至数千个未知数。因此，数值优化非常耗时，对猜测高度敏感，并且容易陷入本地最小值。在这里，我们描述了一种通过约束溶液跨越预定的低维基空间来降低最佳MRF实验设计复杂性的方法。与校准幻像实验中的标准翻转角模式相比，在不到一分钟的计算时间内优化了8个系数，可以提高T2中的精度。
Nuclear magnetic resonance signal dynamics as described by the Bloch equations are highly complex and often are without closed form solutions. This is especially the case for quantitative magnetic resonance fingerprinting (MRF) scans in which acquisition parameters are varied to efficiently probe the parameter space. As previously demonstrated, optimization of the pattern in which the MRI acquisition parameters are varied relative to the variance in the target quantitative parameters can improve experiment design. This process, however, relies on large scale non-linear optimizations with hundreds to thousands of unknowns. As such, the numerical optimization is extremely time consuming, highly sensitive to guesses, and prone to getting caught in local minima. Here, we describe a method to reduce the complexity of the optimal MRF experiment design by constraining the solutions to span a predetermined low-dimensional subspace. Compared with standard flip angle patterns in calibration phantom experiments, precision in T2 can be increased by optimizing as few as 8 coefficients in less than one minute of computation time.
