Synopsis

Keywords: Quantitative Imaging, Neurodegeneration, MR Multitasking, Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative motor disorder that has a need for imaging methods for longitudinal studies. T1/T2/T1ρ MR multitasking is a multiparametric, quantitative, imaging method that shows promise in being a viable tool for this purpose. In this study, we tested the feasibility of a motion weighting modified T1/T2/T1ρ MR multitasking in the arm muscles, evaluating the accuracy and precision of quantitative measurements.

Introduction

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative motor disorder characterized by the dysfunction of both upper and lower motor neurons^{[1, 2]}. There is a need for imaging methods to monitor experimental ALS treatments as well as to elucidate the nature of ALS progression^{[1, 3]}. Muscle MRI is sensitive to changes in neuromuscular degenerative diseases^[4-6], revealing T1 hyperintensities, T1ρ-mapping changes in muscle, and diffuse T2-weighted changes^{[7, 8]}. Quantitative muscle tissue data obtained during diagnosis and treatment are better suited to longitudinal monitoring than weighted imaging^{[9, 10]}. However, multiparametric quantitative mapping suffers from long scan times and registration issues due to motion, which present challenges for their use^[11]. The multiparametric mapping framework MR Multitasking has shown promise in these areas^{[12, 13]} and has already been used to study T1/T2/T1ρ values in the brain^[12], making it a good candidate for use in ALS studies. Many imaging studies of neuromuscular disorders are done in the legs, but this study was done in the arms to evaluate new muscle groups. This study proposes to evaluate the viability of MR Multitasking in ALS patients by testing the sequence feasibility in n=5 healthy subjects.

Methods

Image Acquisition
All data were acquired on a 3T Siemens Biograph mMR scanner in n=5 healthy volunteers. The scan protocol consisted of the Multitasking sequence and its associated reference sequences. A MOLLI 5(3)3 sequence was used as the T1 reference, a T2-prep FLASH was used as the T2 reference, and a T1ρ-prepared FLASH sequence was used as the T1ρ reference. The MR Multitasking sequence used a pulse sequence configuration of four T2 preparatory blocks with four refocusing pulses and four T1ρ preparatory blocks with one refocusing pulse (Figure 1). After a preparatory block is finished, it is followed by a series of 3D FLASH^[14] readouts with 5° excitation pulses to measure the resulting magnetization throughout the entire recovery period^{[12, 15]}. The sequence parameters are shown in Figure 2.

Image Reconstruction
This study modified the standard MR Multitasking approach to image reconstruction^{[12, 13, 15]}, reducing the influence of motion-corrupted k-space lines via a weighting matrix reflecting the model error between acquired data and a motion-free physics model (Figure 3). Specifically, we first calculated the residual R between the auxiliary training data, D_tr, and its projection onto a Bloch dictionary–derived temporal basis, :
$$R=D_{tr}-D_{tr}\phi_{Bloch}^{+}\phi_{Bloch}$$
Because models contrast weighting changes but not motion, R is presumed to contain thermal noise and motion corruption. A diagonal weighting matrix is formed from R,
$$W_{jj}=(\sum_{i=1}^{N_{x}N_{c}}\left|{R_{ij}}\right|^{2})^{-1/2}$$
which is then normalized by the median weighting at each inversion time and incorporated into the tensor subspace estimation step^[15] to reduce the weight of motion-corrupted data.

Data Analysis
Fitted T1/T2/T1ρ maps were analyzed by calculating the mean value within an ROI of size 10x10 voxels taken from both the anterior and posterior of the arm and averaged together to create an average across the entire muscle tissue. The same calculations were done on the reference maps. The Multitasking and reference sequences were compared by way of Bland-Altman plots. Bias between mapping methods was determined by paired t-tests, regarding p<0.05 as significant.

Results

Figure 4 shows the impact of the weighting matrix to reduce motion artifacts in one volunteer. Bland-Altman plots showed a mean difference of +378ms (p<0.001) between the Multitasking T1 sequence values and the T1 reference, -7.0ms (p<0.001) for the T2 values and T2 reference and +0.2ms (p=0.88) for the T1ρ values and T1ρ reference (Figure 5).

Discussion

MR Multitasking values showed an overestimation of T1 values, an underestimation of T2 values, and similar estimation of T1ρ values compared to the reference sequences. T1 overestimation is expected versus T1 MOLLI, which is known to underestimate T1. T2 underestimation is consistent with previous Multitasking studies^{[16, 17]} compared to the T2-prep FLASH reference. T1 accuracy and precision are known to improve with B1+ mapping^[18]; T1ρ precision may also increase with improved homogeneity of the T1ρ preparation effects, which currently use only a single refocusing pulses. Performance may therefore improve with the addition of B1+ mapping and additional refocusing pulses^[19]. The MR Multitasking sequence also showed a marked improvement in scan time (5:36) compared to that of the T1ρ reference sequence (9:46) which was in line with other quantitative T1ρ and T2 sequences^[11].

Conclusion

MR Multitasking is feasible for imaging arm muscle and may find a role in the study of ALS. The proposed method showed slightly biased T1/T2 estimation and resembled T1ρ measurements compared to the reference method while maintaining the fast-imaging time benefit of MR Multitasking. In future work, B1+ mapping and more T1ρ preparatory refocusing pulses could be added to help deal with homogeneity issues affecting estimation of values.

Acknowledgements

This work was partially supported by NIH R01 EB028146.

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