Abstract

An efficient multi-slice inversion–recovery EPI (MS-IR-EPI) sequence for fast, high spatial resolution, quantitative T1 mapping is presented, using a segmented simultaneous multi-slice acquisition, combined with slice order shifting across multiple acquisitions. The segmented acquisition minimises the effective TE and readout duration compared to a single-shot EPI scheme, reducing geometric distortions to provide high quality T1 maps with a narrow point-spread function. The precision and repeatability of MS-IR-EPI T1 measurements are assessed using both T1-calibrated and T2-calibrated ISMRM/NIST phantom spheres at 3 and 7 T and compared with single slice IR and MP2RAGE methods. Magnetization transfer (MT) effects of the spectrally-selective fat-suppression (FS) pulses required for in vivo imaging are shown to shorten the measured in-vivo T1 values. We model the effect of these fat suppression pulses on T1 measurements and show that the model can remove their MT contribution from the measured T1, thus providing accurate T1 quantification. High spatial resolution T1 maps of the human brain generated with MS-IR-EPI at 7 T are compared with those generated with the widely implemented MP2RAGE sequence. Our MS-IR-EPI sequence provides high SNR per unit time and sharper T1 maps than MP2RAGE, demonstrating the potential for ultra-high resolution T1 mapping and the improved discrimination of functionally relevant cortical areas in the human brain.

Highlights

  • Magnetic Resonance relaxometry techniques provide quantitative measures of the longitudinal (T1) relaxation time

  • A Monte Carlo simulation (Fig. 2A) showed that the accuracy of the fitted T1 is independent of the number of TIs used in the fit for greater than 4 TIs chosen, but that the standard deviation of the fitted T1 varies across slices

  • Pushing the spatial resolution of MS-inversion recovery (IR)‐echo-planar imaging (EPI) at 7 T To demonstrate the potential of MS-IR-EPI for high spatial resolution

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Summary

Introduction

Magnetic Resonance relaxometry techniques provide quantitative measures of the longitudinal (T1) relaxation time. Stüber et al (2014) reported that iron makes an average contribution of 10% to T1 in white matter and 36% to grey matter in fixed cadaver human brain at 7 T, and Callaghan et al (2015) showed that myelination is a better predictor of T1 than iron content. Quantitative T1-maps have been used as a marker of myelination during brain development (Eminian et al, 2018; Kupeli et al, 2020) as well as to characterize white matter demyelination in clinical conditions (e.g. multiple sclerosis (Al-Radaideh et al, 2015). The study of intracortical demyelination patterns is clinically relevant (Mougin et al, 2016; Beck et al, 2018) but still remains a challenge

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