Unbiased Signal Equation for Quantitative Magnetization Transfer Mapping in Balanced Steady-State Free Precession MRI

TL;DR

This paper introduces an improved quantitative magnetization transfer (qMT) model for balanced steady-state free precession MRI that corrects biases in the original model, leading to more accurate brain tissue parameter estimates.

Contribution

The paper presents a new qMT bSSFP model that accounts for finite RF pulse effects and exchange-relaxation, reducing bias in parameter estimation compared to previous models.

Findings

Original model biased by 7-20% in simulations

New model reduces bias to less than 1%

Significant differences in qMT parameters in brain tissues, especially in MS lesions

Abstract

Purpose: Quantitative magnetization transfer (qMT) imaging can be used to quantify the proportion of protons in a voxel attached to macromolecules. Here, we show that the original qMT balanced steady-state free precession (bSSFP) model is biased due to over-simplistic assumptions made in its derivation. Theory and Methods: We present an improved model for qMT bSSFP, which incorporates finite radio-frequency (RF) pulse effects as well as simultaneous exchange and relaxation. Further, a correction to finite RF pulse effects for sinc-shaped excitations is derived. The new model is compared to the original one in numerical simulations of the Bloch-McConnell equations and in previously acquired in-vivo data. Results: Our numerical simulations show that the original signal equation is significantly biased in typical brain tissue structures (by 7-20 %) whereas the new signal equation outperforms the original one with minimal bias (< 1%). It is further shown that the bias of the original model strongly affects the acquired qMT parameters in human brain structures, with differences in the clinically relevant parameter of pool-size-ratio of up to 31 %. Particularly high biases of the original signal equation are expected in an MS lesion within diseased brain tissue (due to a low T2/T1-ratio), demanding a more accurate model for clinical applications. Conclusion: The improved model for qMT bSSFP is recommended for accurate qMT parameter mapping in healthy and diseased brain tissue structures.