Linear least-squares method for unbiased estimation of T1 from SPGR signals
Linear least-squares method for unbiased estimation of T1 from SPGR signals
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DOI：
10.1002/mrm.21669
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发表时间：
2008-08-01
影响因子：
3.3
通讯作者：
Pierpaoli, Carlo
中科院分区：
文献类型：
--
作者：
Chang, Lin-Ching;Koay, Cheng Guan;Pierpaoli, Carlo
纵向弛豫时间 T-1 可以根据用不同翻转角和/或重复时间 (TR) 采集的两个或多个损坏的梯度回忆回波图像 (SPGR) 来估计。信号强度与翻转角和TR相关的函数是非线性的；然而，30年前提出的线性形式目前被广泛使用。在这里，我们表明，这种线性方法提供的 T-1 估计与非线性方法获得的估计具有相似的精度，但精度较低。我们还表明，由于拟合中噪声的考虑不当，线性方法估计的 T-1 存在偏差。这种偏差对于临床 SPGR 图像可能很重要；例如，脑组织中估计的 T-1 (800 ms < T-1 < 1600 ms) 可能会被高估 10% 到 20%。我们提出了一种加权方案，可以正确考虑拟合过程中的噪声贡献。 SPGR 实验的蒙特卡罗模拟用于评估广泛使用的线性方法、提出的加权不确定性线性方法和非线性方法估计的 T-1 的准确性。我们表明，具有加权不确定性的线性方法减少了线性方法的偏差，提供与非线性方法的精度和准确度相当的 T-1 估计，同时显着减少计算时间。
The longitudinal relaxation time, T-1, can be estimated from two or more spoiled gradient recalled echo images (SPGR) acquired with different flip angles and/or repetition times (TRs). The function relating signal intensity to flip angle and TR is nonlinear; however, a linear form proposed 30 years ago is currently widely used. Here we show that this linear method provides T-1 estimates that have similar precision but lower accuracy than those obtained with a nonlinear method. We also show that T-1 estimated by the linear method is biased due to improper accounting for noise in the fitting. This bias can be significant for clinical SPGR images; for example, T-1 estimated in brain tissue (800 ms < T-1 < 1600 ms) can be overestimated by 10% to 20%. We propose a weighting scheme that correctly accounts for the noise contribution in the fitting procedure. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy of the estimated T-1 from the widely-used linear, the proposed weighted-uncertainty linear, and the nonlinear methods. We show that the linear method with weighted uncertainties reduces the bias of the linear method, providing T-1 estimates comparable in precision and accuracy to those of the nonlinear method while reducing computation time significantly.