# Magnetization Transfer in Magnetic Resonance Fingerprinting

## TL;DR

This study investigates how magnetization transfer (MT) affects magnetic resonance fingerprinting (MRF) signals and demonstrates that incorporating MT models improves the accuracy of T1, T2, and pool size estimations in brain tissue.

## Contribution

The paper introduces an MRF sequence with off-resonance MT pulses and a two-pool model to account for MT effects, enhancing parameter estimation accuracy.

## Key findings

- MT influences MRF signals in tissue.
- Using an MT-inclusive dictionary improves signal matching accuracy.
- Accounting for MT reveals differences in T1, T2, and pool size between tissue types.

## Abstract

Purpose: To study the effects of magnetization transfer (MT, in which a semisolid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF). Methods: Simulations and phantom experiments were performed to study the impact of MT on the MRF signal and its potential influence on T1 and T2 estimation. Subsequently, an MRF sequence implementing off-resonance MT pulses and a dictionary with an MT dimension by incorporating a two-pool model were used to estimate the fractional pool size in addition to the B1+, T1, and T2 values. The proposed method was evaluated in the human brain. Results: Simulations and phantom experiments showed that an MRF signal obtained from a cross-linked bovine serum sample is influenced by MT. Using a dictionary based on an MT model, a better match between simulations and acquired MR signals can be obtained (NRMSE 1.3% versus 4.7%). Adding off-resonance MT pulses can improve the differentiation of MT from T1 and T2. In-vivo results showed that MT affects the MRF signals from white matter (fractional pool-size ~16%) and gray matter (fractional pool-size ~10%). Furthermore, longer T1 (~1060 ms versus ~860 ms) and T2 values (~47 ms versus ~35 ms) can be observed in white matter if MT is accounted for. Conclusion: Our experiments demonstrated a potential influence of MT on the quantification of T1 and T2 with MRF. A model that encompasses MT effects can improve the accuracy of estimated relaxation parameters and allows quantification of the fractional pool size.