This analysis identifies changes in frontal lobe morphometry in healthy children, highlighting age-related variations and implications for cognitive development.
Background: Magnetic resonance imaging-based morphometry is a highly informative, noninvasive method for early diagnosis of structural brain changes, which facilitates their quantitative and qualitative evaluation. The frontal lobes increase significantly in size during brain development, which is associated with their important role in cognitive functions and environmental adaptations. Frontal lobe morphometry in pediatric patients can be used to identify abnormalities and understand normal developmental processes in early childhood. AIM: To identify any changes in the morphometry of the frontal lobes in neurologically healthy children and to analyze how these changes may vary across sex and age groups. METHODS: The study included 49 children aged 6 months to 18 years. The observations were categorized into two age groups: from 0 to 7 years (17 children) and from 7 to 18 years (32 children). Automatic magnetic resonance imaging-based morphometry was performed with FreeSurfer software used to determine morphometric parameters, including frontal lobe volume, surface area, and cortical thickness. RESULTS: The findings showed age-related variations in the frontal lobe volume, area, and thickness. There were no significant sex-specific differences in the morphometric parameters between the age groups. However, relative values of the morphometric parameters calculated as a percentage of intracranial volume were higher in boys than in girls. The obtained results demonstrate both symmetrical and asymmetrical changes, thereby underscoring the multidirectional nature of the frontal lobe development during human growth. CONCLUSION: Magnetic resonance imaging-based morphometry is a highly effective method for identifying the developmental patterns of the frontal lobes in neurologically healthy children. The morphometric parameters outlined in this study may serve as reference values in the assessment of pediatric populations diagnosed with neurodegenerative diseases.
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Semibratov et al. (2025) studied this question.
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