. Author manuscript; available in PMC: 2009 Feb 2.

Published in final edited form as: Magn Reson Med. 2007 Feb;57(2):437–441. doi: 10.1002/mrm.21143

Table 1.

Results of Applying Eqs. [4] and [10] to Simulated SIR-FSE Data^*

	k_mf WM	p_m/p_f WM	k_mf GM	p_m/p_f GM	k_mf Mus.	p_m/p_f Mus.
Input parameters	15	0.155	28	0.059	46	0.108
Parameters determined using data created using Bloch equations	17.85	0.1364	30.15	0.0556	51.47	0.0972
Parameters determined using data created by nulling z- magnetization	17.85	0.1367	30.15	0.0558	51.47	0.0974

The data is created by either integrating the coupled Bloch equations (the more realistic method) or by setting the z-magnetization of both pools to zero at the end of the FSE pulse train. Other parameters are t_d = 2s, R_1m = 0.5 Hz, R_2m = 100000 Hz, andR_1f = 0.66 Hz, R_2f = 25 Hz for white matter (WM), R_1f = 0.52 Hz, R_2f = 22 Hz for gray matter (GM), and R_1f = 0.49 Hz, R_2f = 33 Hz for muscle (M). Sequence parameters are as in Fig. 1. Note that deviations from zero z-magnetization after the FSE pulse train have only a minor effect on p_m/p_f and no effect on k_mf. The difference between the fitted parameters and the input parameters is due nearly entirely to taking only a first order approximation in 1/k_mf in Eqs. [4] and [10].