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使用多次自旋回波采集提高计算T1磁共振图像的精度。

Improved precision in calculated T1 MR images using multiple spin-echo acquisition.

作者信息

Riederer S J, Bobman S A, Lee J N, Farzaneh F, Wang H Z

出版信息

J Comput Assist Tomogr. 1986 Jan-Feb;10(1):103-10. doi: 10.1097/00004728-198601000-00022.

Abstract

Calculated T1 images require that magnetic resonance signals be detected at several inversion or repetition times (TR). Multiple spin-echo (SE) acquisitions provide several measurements of the magnetization at each TR, the signal size diminishing according to T2 decay. In this work we review one method (Case 1) for estimating T1 from single echoes and present four new methods (Cases 2-5) in which multiple acquired echoes are used. For Case 2 a fit is performed using the first echo at each TR, repeated using second echoes, etc., and the final T1 estimate is the simple average of the individual fits at each echo time (TE). For Case 3 the optimum weighted average is performed. For Cases 4 and 5 synthetic SE images are generated at each TR prior to the T1 fit, Case 4 using a synthetic TE of zero, and Case 5 using a TE providing maximum signal-to-noise ratio in the synthetic image. The relative precision in T1 provided by each method is calculated rigorously. It is proven that Cases 3 and 5 are optimum and equivalent and can theoretically reduce the noise in T1 images by as much as 40% over Case 1 with no increase in scanning time. Approximations are proposed that enable the optimum methods to be implemented in a practical fashion. Experimental images are presented that verify the relative predicted behavior.

摘要

计算得到的T1图像要求在多个反转时间或重复时间(TR)处检测磁共振信号。多次自旋回波(SE)采集在每个TR处提供了多次磁化强度测量,信号大小会根据T2衰减而减小。在这项工作中,我们回顾了一种从单回波估计T1的方法(案例1),并提出了四种新方法(案例2 - 5),这些方法使用了多个采集到的回波。对于案例2,在每个TR处使用第一个回波进行拟合,然后使用第二个回波重复进行,依此类推,最终的T1估计值是每个回波时间(TE)处各个拟合值的简单平均值。对于案例3,进行最优加权平均。对于案例4和案例5,在进行T1拟合之前,在每个TR处生成合成SE图像,案例4使用零合成TE,案例5使用在合成图像中提供最大信噪比的TE。严格计算了每种方法在T1方面提供的相对精度。结果表明,案例3和案例5是最优且等效的,理论上在不增加扫描时间的情况下,与案例1相比,可将T1图像中的噪声降低多达40%。提出了一些近似方法,使最优方法能够以实际可行的方式实现。展示了实验图像,验证了相对预测行为。

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