Inbar Seroussi^{1}, Nir Sochen^{1,2}, Noam Ben-Eliezer^{2,3,4}, and Ofer Pasternak ^{5}

Quantifying the effect of self-diffusion on multi-parametric sequences, such as those used for Magnetic Resonance Fingerprinting (MRF) is important to increase the accuracy of dictionary based parameter estimation. To quantify diffusion, we propose a signal simulation approach, which replaces the Bloch equation with the Bloch-Torrey equation, and accounts for protocol and scan dependent parameters. We apply this framework on a Multi Spin Echo (MSE) protocol and quantify the diffusion encoding introduced by the spoiler gradients in this sequence. We further show that increasing the spoiler strength would allow detecting diffusion by including the diffusion effect in the dictionary.

**Discussion: **

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Fig. 1. $$$T_2$$$ weighted image of the nine-tube
phantom used in this study. Tubes were doped with varying concentrations of
manganese chloride (MnCl2) imparting each tube a different $$$T_2$$$ relaxation time.

Fig. 2. Estimated $$$T_2$$$ values: The estimated $$$T_2$$$ from MSE with weak spoiler gradient shows an agreement between the values estimated using
Bloch simulation (blue), Bloch-Torrey simulation (green), and values estimated
from a single spin echo (red).

Fig. 3. Weak versus strong spoilers. Looking at a
single tube, following the application of a strong spoiler the diffusion effect
is visible as the difference in the signal between the Bloch simulation (green)
and the Bloch-Torrey simulation (magenta). The signal of the strong spoiler
deviates from that of the weak spoiler which shows no difference between the
Bloch (black) and Bloch-Torrey (blue) simulations, and agrees with the measured
single spin echo signal (red).