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Assessment of normal myelination in infants and young children using the T1w/T2w mapping technique

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Background White matter myelination is a crucial process of CNS maturation. The purpose of this study was to validate the T1w/T2w mapping technique for brain myelination assessment in infants and… Click to show full abstract

Background White matter myelination is a crucial process of CNS maturation. The purpose of this study was to validate the T1w/T2w mapping technique for brain myelination assessment in infants and young children. Methods Ninety-four patients (0–23 months of age) without structural abnormalities on brain MRI were evaluated by using the T1w/T2w mapping method. The T1w/T2w signal intensity ratio, which reflects white matter integrity and the degree of myelination, was calculated in various brain regions. We performed a Pearson correlation analysis, a LOESS regression analysis, and a 2nd order polynomial regression analysis to describe the relationships between the regional metrics and the age of the patients (in months). Results T1w/T2w ratio values rapidly increased in the first 6–9 months of life and then slowed thereafter. The T1w/T2w mapping technique emphasized the contrast between myelinated and less myelinated structures in all age groups, which resulted in better visualization. There were strong positive correlations between the T1w/T2w ratio values from the majority of white matter ROIs and the subjects’ age (R = 0.7–0.9, p < 0.001). Within all of the analyzed regions, there were non-linear relationships between age and T1/T2 ratio values that varied by anatomical and functional location. Regions such as the splenium and the genu of the corpus callosum showed the highest R2 values, thus indicating less scattering of data and a better fit to the model. Conclusion The T1w/T2w mapping technique may enhance our diagnostic ability to assess myelination patterns in the brains of infants and young children.

Keywords: myelination; t1w t2w; mapping technique; t2w mapping

Journal Title: Frontiers in Neuroscience
Year Published: 2023

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