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Published on: July 30, 2009
Brain Maturation Patterns on Normalized FLAIR MR Imaging in Children and Adolescents
K Chan1,2, A Ghazvanchahi3,2, D Rabba3,2
1From the Department of Electrical, Computer and Biomedical Engineering (K.C., A.G., D.R., A.K.), Toronto Metropolitan University, Toronto, Ontario, Canada karissa.chan@torontomu.ca.
Background And Purpose:
Signal analysis of FLAIR sequences is gaining momentum for studying neurodevelopment and brain maturation, but FLAIR intensity varies across scanners and needs to be normalized. This study aimed to establish normative values for standardized FLAIR intensity in the pediatric brain.
Materials And Methods:
A new automated algorithm for signal normalization was used to standardize FLAIR intensity across scanners and subjects. Mean intensity was extracted from GM, WM, deep GM, and cortical GM regions. Regression curves were fitted across the pediatric age range, and ANOVA was used to investigate intensity differences across age groups. Correlations between intensity and regional volume were also examined.
Results:
We analyzed 429 pediatric FLAIR sequences in children 2-19 years of age with a median age of 11.2 years, including 199 males and 230 females. WM intensity had a parabolic relationship with age, with significant differences between various age groups (P < .05). GM and cortical GM intensity increased over the pediatric age range, with significant differences between early childhood and adolescence (P < .05). There were no significant relationships between volume and intensity in early childhood, while there were significant positive and negative correlations (P < .05) in WM and GM, respectively, for increasing age groups. Only the oldest age group showed significant differences between males and females (P < .05).
Conclusions:
This work presents a FLAIR intensity standardization algorithm to normalize intensity across large data sets, which allows FLAIR intensity to be used to compare regions and individuals as a surrogate measure of the developing pediatric brain.
