Estimation of white matter hyperintensities with synthetic MRI myelin volume fraction in patients with multiple sclerosis and non-multiple-sclerosis white matter hyperintensities: A pilot study among the Indian population

Nisha Syed Nasser; Krish Sharma; Parv Mahendra Mehta; Vidur Mahajan; Harsh Mahajan; Vasantha Kumar Venugopal; Nisha Syed Nasser; Krish Sharma; Parv Mahendra Mehta; Vidur Mahajan; Harsh Mahajan; Vasantha Kumar Venugopal

doi:10.3934/Neuroscience.2023011

AIMS Neuroscience

2023, Volume 10, Issue 2: 144-153. doi: 10.3934/Neuroscience.2023011

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Research article

Estimation of white matter hyperintensities with synthetic MRI myelin volume fraction in patients with multiple sclerosis and non-multiple-sclerosis white matter hyperintensities: A pilot study among the Indian population

1.
Mahajan Imaging Private Limited, New Delhi, India
2.
CARPL.AI, New Delhi, India

Received: 26 December 2022 Revised: 03 May 2023 Accepted: 09 May 2023 Published: 24 May 2023

AIM
Synthetic MRI (SyMRI) works on the MDME sequence, which acquires the relaxation properties of the brain and helps to measure the accurate tissue properties in 6 minutes. The aim of this study was to evaluate the synthetic MRI (SyMRI)-generated myelin (MyC) to white matter (WM) ratio, the WM fraction (WMF), MyC partial maps performing normative brain volumetry to investigate MyC loss in multiple sclerosis (MS) patients with white-matter hyperintensites (WMHs) and non-MS patients with WMHs in a clinical setting.

MATERIALS and METHODS
Synthetic MRI images were acquired from 15 patients with MS, and from 15 non-MS patients on a 3T MRI scanner (Discovery MR750w; GE Healthcare; Milwaukee, USA) using MAGiC, a customized version of SyntheticMR's SyMRI® IMAGE software marketed by GE Healthcare under a license agreement. Fast multi-delay multi-echo acquisition was performed with a 2D axial pulse sequence with different combinations of echo time (TEs) and saturation delay times. The total image acquisition time was 6 minutes. SyMRI image analysis was done using SyMRI software (SyMRI Version: 11.3.6; Synthetic MR, Linköping, Sweden). SyMRI data were used to generate the MyC partial maps and WMFs to quantify the signal intensities of test group and control group, andcontrol group , and their mean values were recorded. All patients also underwent conventional diffusion-weighted imaging, i.e., T1w and T2w imaging.

RESULTS
The results showed that the WMF was significantly lower in the test group than in the control group (38.8% vs 33.2%, p < 0.001). The Mann-Whitney U nonparametric t-test revealed a significant difference in the mean myelin volume between the test group and the control group (158.66 ± 32.31 vs. 138.29 ± 29.28, p = 0.044). Also, there were no significant differences in the gray matter fraction and intracranial volume between the test group and the control group.

CONCLUSIONS
We observed MyC loss in test group using quantitative SyMRI. Thus, myelin loss in MS patients can be quantitatively evaluated using SyMRI.
- synthetic MRI,
- myelin loss,
- multiple sclerosis,
- MAGiC,
- white matter fraction
Citation: Nisha Syed Nasser, Krish Sharma, Parv Mahendra Mehta, Vidur Mahajan, Harsh Mahajan, Vasantha Kumar Venugopal. Estimation of white matter hyperintensities with synthetic MRI myelin volume fraction in patients with multiple sclerosis and non-multiple-sclerosis white matter hyperintensities: A pilot study among the Indian population[J]. AIMS Neuroscience, 2023, 10(2): 144-153. doi: 10.3934/Neuroscience.2023011

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Abstract

AIM

Synthetic MRI (SyMRI) works on the MDME sequence, which acquires the relaxation properties of the brain and helps to measure the accurate tissue properties in 6 minutes. The aim of this study was to evaluate the synthetic MRI (SyMRI)-generated myelin (MyC) to white matter (WM) ratio, the WM fraction (WMF), MyC partial maps performing normative brain volumetry to investigate MyC loss in multiple sclerosis (MS) patients with white-matter hyperintensites (WMHs) and non-MS patients with WMHs in a clinical setting.

MATERIALS and METHODS

Synthetic MRI images were acquired from 15 patients with MS, and from 15 non-MS patients on a 3T MRI scanner (Discovery MR750w; GE Healthcare; Milwaukee, USA) using MAGiC, a customized version of SyntheticMR's SyMRI® IMAGE software marketed by GE Healthcare under a license agreement. Fast multi-delay multi-echo acquisition was performed with a 2D axial pulse sequence with different combinations of echo time (TEs) and saturation delay times. The total image acquisition time was 6 minutes. SyMRI image analysis was done using SyMRI software (SyMRI Version: 11.3.6; Synthetic MR, Linköping, Sweden). SyMRI data were used to generate the MyC partial maps and WMFs to quantify the signal intensities of test group and control group, andcontrol group , and their mean values were recorded. All patients also underwent conventional diffusion-weighted imaging, i.e., T1w and T2w imaging.

RESULTS

The results showed that the WMF was significantly lower in the test group than in the control group (38.8% vs 33.2%, p < 0.001). The Mann-Whitney U nonparametric t-test revealed a significant difference in the mean myelin volume between the test group and the control group (158.66 ± 32.31 vs. 138.29 ± 29.28, p = 0.044). Also, there were no significant differences in the gray matter fraction and intracranial volume between the test group and the control group.

CONCLUSIONS

We observed MyC loss in test group using quantitative SyMRI. Thus, myelin loss in MS patients can be quantitatively evaluated using SyMRI.

Acknowledgments

None.

Conflict of interest

The authors declare that there are no conflicts of interest.

Author contributions

Conceptual framework and study design was done by HM and VKV; Literature search was done by PMM and KS; Data collection, data analysis and data interpretation were performed by NSN; Manuscript drafting was done by NSN, KS and PMM; Verification of analytical methods and supervision of the study was done by NSN, HM and VM.

References

[1]	Ghasemi N, Razavi S, Nikzad E (2017) Multiple Sclerosis: Pathogenesis, Symptoms, Diagnoses and Cell-Based Therapy. Cell J (Yakhteh) 19: 1. https://doi.org/10.22074/cellj.2016.4867
[2]	McKinley R, Wepfer R, Grunder L, et al. (2020) Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence. NeuroImage-Clin 25: 102104. https://doi.org/10.1016/j.nicl.2019.102104
[3]	Hagiwara A, Hori M, Yokoyama K, et al. (2017) Synthetic MRI in the Detection of Multiple Sclerosis Plaques. Am J Neuroradiol 38: 257-263. https://doi.org/10.3174/ajnr.A5012
[4]	Hagiwara A, Warntjes M, Hori M, et al. (2017) SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement. Invest Radiol 52: 647-657. https://doi.org/10.1097/RLI.0000000000000365
[5]	Fujita S, Yokoyama K, Hagiwara A, et al. (2021) 3D Quantitative Synthetic MRI in the Evaluation of Multiple Sclerosis Lesions. Am J Neuroradiol 42: 471-478. https://doi.org/10.3174/ajnr.A6930
[6]	Tanenbaum LN, Tsiouris AJ, Johnson AN, et al. (2017) Synthetic MRI for Clinical Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) Prospective, Multicenter, Multireader Trial. Am J Neuroradiol 38: 1103-1110. https://doi.org/10.3174/ajnr.A5227
[7]	Geurts JJ, Barkhof F (2008) Grey matter pathology in multiple sclerosis. Lancet Neurol 7: 841-851. https://doi.org/10.1016/S1474-4422(08)70191-1
[8]	Klaver R, De Vries HE, Schenk GJ, et al. (2013) Grey matter damage in multiple sclerosis: A pathology perspective. Prion 7: 66-75. https://doi.org/10.4161/pri.23499

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