MC BTS: Simultaneously Resolving Magnetization Transfer Effect and Relaxation for Multiple Components

TL;DR

This paper introduces a new MRI framework that accurately measures tissue properties while accounting for magnetic field and magnetization transfer effects.

Contribution

A novel signal modeling framework that simultaneously resolves magnetization transfer and relaxation effects in multi-component tissues.

Findings

Simulation results matched the analytical signal equation across various flip angles and echo times.

Monte Carlo simulations confirmed robust parameter estimation under different noise conditions.

In vivo results in brain and knee tissues aligned with previous literature.

Abstract

To propose a signal acquisition and modeling framework for multi‐component tissue quantification that encompasses transmit field inhomogeneity, multi‐component relaxation and magnetization transfer (MT) effects.

By applying off‐resonance irradiation between excitation and acquisition within an RF‐spoiled gradient‐echo scheme, in combination with multiple echo‐time acquisitions, both Bloch‐Siegert shift and magnetization transfer effects are simultaneously induced while relaxation and spin exchange processes occur concurrently. The spin dynamics are modeled using a three‐pool framework, from which an analytical signal equation is derived and validated through numerical Bloch simulations. Monte Carlo simulations were further performed to analyze and compare the model's performance. Finally, the feasibility of this novel approach was investigated in vivo in human brain and knee tissues.

Simulation results showed excellent agreement with the derived analytical signal equation across a wide range of flip angles and echo times. Monte Carlo analyses further validated that the three‐pool parameter estimation pipeline performed robustly over various signal‐to‐noise ratio conditions. Multi‐parameter fitting results from in vivo brain and knee studies yielded values consistent with previously reported literature. Collectively, these findings confirm that the proposed method can reliably characterize multi‐component tissue parameters in macromolecule‐rich environments while effectively compensating for B1+ inhomogeneity.

A signal acquisition and modeling framework for multi‐component tissue quantification that accounts for magnetization transfer effects and B1+ inhomogeneity has been developed and validated. Both simulation and experimental results confirmed the robustness of this method and its applicability to various tissue types in the brain and knee.

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