Simultaneous Multislice Brain MRI T1 Mapping with Improved Low-Rank Modeling.

Sugil Kim,Suhyung Park

doi:10.3390/tomography7040047

Sugil Kim, Suhyung Park

Open Access

https://doi.org/10.3390/tomography7040047

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Abstract

To accelerate data acquisition speed in magnetic resonance imaging (MRI), multiple slices are simultaneously acquired using multiband pulses. Simultaneous multislice (SMS) imaging typically unfolds slice aliasing from the acquired collapsed slices. In this study, we extended the SMS framework to accelerated MR parameter quantification such as T1 mapping. Assuming that the slice-specific null space and signal subspace are invariant along the parameter dimension, we formulated the SMS framework as a constrained optimization problem under a joint reconstruction framework such that the noise and signal subspaces are used for slice separation and recovery, respectively. The proposed method was validated on 3T MR human brain scans. We successfully demonstrated that the proposed method outperforms competing methods in suppressing aliasing artifacts and noise at high SMS accelerations, thus leading to accurate T1 maps.

Highlights

As parameter mapping in magnetic resonance imaging (MRI) requires that several repeated measurements with varying imaging parameters, it may result in prohibitively long imaging times, compromising imaging efficiency and possibly limiting a range of clinical applications
In accelerated MR parameter mapping, simultaneous multislice (SMS) imaging has gained attention owing to its ability to provide the signal-to-noise ratio (SNR) benefit of volumetric signal averaging by simultaneously exciting multiple imaging slices [5,6,7]
Case does not display strong artifacts, close inspection does reveal that some noise is still present

Summary

Introduction

In magnetic resonance imaging (MRI), quantitative parameter mapping, which includes voxelwise delineation of tissue-specific relaxation times, has been widely used in characterizing inherent tissue properties and evaluating various pathological diseases, thereby providing valuable insight into disease processes. These voxels serve as imaging markers for clinical applications such as acute stroke, epilepsy, and multiple sclerosis [1,2,3,4]. In accelerated MR parameter mapping, simultaneous multislice (SMS) imaging has gained attention owing to its ability to provide the signal-to-noise ratio (SNR) benefit of volumetric signal averaging by simultaneously exciting multiple imaging slices [5,6,7]. To obtain better noise suppression and artifact mitigation over conventional data acquisition, a controlled aliasing (CAIPI) technique was introduced to SMS acquisition by applying phase-modulated

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Conclusion