# Inversion Efficiency Model Yields Improved Accuracy in MP2RAGE‐Based T 1 Mapping in the Human Brain at 7.0T

## TL;DR

A new model improves the accuracy of T1 mapping in the brain using MP2RAGE by accounting for magnetization transfer effects.

## Contribution

An empirical model for apparent inversion efficiency is introduced to correct systematic T1 underestimation in MP2RAGE.

## Key findings

- The apparent inversion efficiency is lower in white matter compared to gray matter.
- Using the new model reduces T1 underestimation in white matter by over 200 ms.
- The model retains B1+ compensation and enables accurate T1 quantification without extra parameters.

## Abstract

Estimation of the longitudinal relaxation time T
1 from the MP2RAGE pulse sequence is based on a monoexponential signal evolution model. However, magnetization transfer (MT) caused by the inversion pulse induces a fast relaxation component, which appears as a reduction in the efficiency of the inversion. This may explain the underestimation of T
1 derived from MP2RAGE. To address this systematic bias, an “apparent” inversion efficiency (f
inv) was introduced, which comprises all mechanisms that affect the inversion in the monoexponential MP2RAGE signal model. The model was then extended by calibrating an empirical linear dependence of f
inv on R
1 = 1/T
1, resulting in increased accuracy of the estimated T
1. The apparent inversion efficiency f
inv and the apparent T
1* (yielding T
1 by auxiliary B
1
+ mapping) were mapped at 7T in healthy adults using phase‐sensitive inversion recovery (IR) with four consecutive RAGE trains (PS‐MP4RAGE) in conjunction with adiabatic inversion using time‐resampled (TR)–FOCI and hyperbolic secant pulses. Upon validation by conventional IR‐EPI, PS‐MP4RAGE was used to calibrate the linear f
inv model for the human brain. These 3D T
1 maps also served as a reference to assess the improvement of the MP2RAGE‐based T
1 estimates. The apparent inversion efficiency f
inv was consistently smaller in white matter (WM) than in gray matter (~0.73 vs. ~0.84). The difference in WM T
1 between MP2RAGE and the reference PS‐MP4RAGE technique was reduced by more than 200 ms when using the suggested f
inv model. MT effects after spin inversion in MP2RAGE can be accounted for by calibrating the apparent inversion efficiency f
inv without introducing additional parameters. The proposed empirical model retains the B
1
+ compensation inherent to MP2RAGE and facilitates accurate T
1 quantification in brain tissue.

Quantification of the longitudinal relaxation time using the MP2RAGE pulse sequence and a monoexponential forward signal model may be underestimated because of MT effects introduced by the radiofrequency inversion pulse. We address this bias by identifying an empirical relationship between the “apparent inversion efficiency” and the longitudinal relaxation rate.