Myelin Detection Using Rapid Quantitative MR Imaging Correlated to Macroscopically Registered Luxol Fast Blue-Stained Brain Specimens.

J B M Warntjes, A Persson, J Berge, W Zech

AJNR. American journal of neuroradiology 2017 Jun

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Myelin detection is of great value in monitoring diseases such as multiple sclerosis and dementia. However, most MR imaging methods to measure myelin are challenging for routine clinical use. Recently, a novel method was published, in which the presence of myelin is inferred by using its effect on the intra- and extracellular water relaxation rates and proton density, observable by rapid quantitative MR imaging. The purpose of this work was to validate this method further on the brains of 12 fresh, intact cadavers. The 12 brains were scanned with a quantification sequence to determine the longitudinal and transverse relaxation rates and proton density as input for the myelin estimations. Subsequently, the brains were excised at postmortem examination, and brain slices were stained with Luxol fast blue to verify the presence of myelin. The optical density values of photographs of the stained brain slices were registered with the MR images and correlated with the myelin estimation performed by quantitative MR imaging. A correlation was found between the 2 methods with a mean Spearman ρ for all subjects of 0.74 ± 0.11. Linear regression showed a mean intercept of 1.50% ± 2.84% and a mean slope of 4.37% ± 1.73%/%. A lower correlation was found for the separate longitudinal relaxation rates and proton density (ρ = 0.63 ± 0.12 and -0.73 ± 0.09, respectively). For transverse relaxation rates, the ρ was very low (0.11 ± 0.28). The observed correlation supports the validity of myelin measurement by using the MR imaging quantification method. © 2017 by American Journal of Neuroradiology.

Citation

J B M Warntjes, A Persson, J Berge, W Zech. Myelin Detection Using Rapid Quantitative MR Imaging Correlated to Macroscopically Registered Luxol Fast Blue-Stained Brain Specimens. AJNR. American journal of neuroradiology. 2017 Jun;38(6):1096-1102