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Updated: Aug 3, 2026
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Comparative Evaluation of 3D-QALAS Myelin Volume Fraction, Inhomogeneous Magnetization Transfer, and Myelin Water
Moto Nakaya1, Akifumi Hagiwara2, Yasunobu Hoshino1
1From the Department of Radiology (M.N., A.H., N.H., J.K., S.K., X.Z., S.M., C.F., Y.S., S.A., K.K.), Neurology (Y.H., Y.T., T.H.), Juntendo University School of Medicine, Tokyo, Japan; Department of Radiology (M.N., A.H., S.K.), Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan; Center for Medical Imaging Sciences and Visualization (CMIV) (M.W.), Linköping University Hospital, Sweden; Canon Medical Systems Corporation (M.A., H.K., R.Y., M.O.), Tochigi, Japan and Department of Radiology (M.H.), Toho University Omori Medical Center, Tokyo, Japan.
Background And Purpose:
Accurate in vivo quantification of myelin remains challenging despite advances in MRI. We evaluated three-dimensional synthetic MRI-derived myelin volume fraction from three-dimensional quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) by comparing it with inhomogeneous magnetization transfer ratio, myelin water fraction, and the T1-weighted/T2-weighted ratio in healthy volunteers and patients with multiple sclerosis.
Materials And Methods:
Thirty-one healthy volunteers and 33 consecutive patients with multiple sclerosis underwent 3T MRI including 3D-QALAS, 3D inhomogeneous magnetization transfer imaging, and 2D multi-echo spin-echo imaging for myelin water fraction. Synthetic T1-weighted/T2-weighted ratio maps were generated from quantitative R1, R2, and proton density data. Lesions were segmented using a deep learning-based method, and periplaque regions were defined by 2-voxel isotropic dilation. Atlas-based ROI analyses in normal-appearing brain tissue were performed using repeated-measures correlation. WM lesion-centered analyses were performed to compare metric differences relative to normal-appearing white matter using linear mixed-effects models.
Results:
In normal-appearing brain tissue pooled across patients and volunteers, myelin volume fraction demonstrated strong overall repeated-measures correlations with the inhomogeneous magnetization transfer ratio (r = 0.86; 95% CI, 0.85-0.87) and the T1-weighted/T2-weighted ratio (r = 0.89; 95% CI, 0.88-0.89), and more modest correlations with myelin water fraction (r = 0.63; 95% CI, 0.61-0.64). The inhomogeneous magnetization transfer ratio-myelin water fraction correlation was r = 0.60 (95% CI, 0.58-0.62). This overall ranking was preserved in volunteers and patients analyzed separately, and Spearman analyses showed a similar pattern. In WM lesion-centered analyses, values relative to normal-appearing WM were lowest for myelin volume fraction (44.2% in plaque, 75.4% in periplaque), followed by the T1-weighted/T2-weighted ratio (56.5%, 77.3%), the inhomogeneous magnetization transfer ratio (74.7%, 87.8%), and myelin water fraction (93.4%, 98.3%).
Conclusions:
3D-QALAS-derived myelin volume fraction demonstrated strong overall concordance with the inhomogeneous magnetization transfer ratio in normal-appearing brain tissue and greater lesion-associated deviation from normal-appearing white matter than the other myelin-sensitive metrics. These findings support 3D-QALAS-derived myelin volume fraction as a promising volumetric biomarker of myelin integrity with whole-brain coverage suitable for routine clinical application.
