Normal childhood brain growth and a universal sex and anthropomorphic relationship to cerebrospinal fluid

Abstract

OBJECTIVE The study of brain size and growth has a long and contentious history, yet normal brain volume development has yet to be fully described. In particular, the normal brain growth and cerebrospinal fluid (CSF) accumulation relationship is critical to characterize because it is impacted in numerous conditions of early childhood in which brain growth and fluid accumulation are affected, such as infection, hemorrhage, hydrocephalus, and a broad range of congenital disorders. The authors of this study aim to describe normal brain volume growth, particularly in the setting of CSF accumulation. METHODS The authors analyzed 1067 magnetic resonance imaging scans from 505 healthy pediatric subjects from birth to age 18 years to quantify component and regional brain volumes. The volume trajectories were compared between the sexes and hemispheres using smoothing spline ANOVA. Population growth curves were developed using generalized additive models for location, scale, and shape. RESULTS Brain volume peaked at 10–12 years of age. Males exhibited larger age-adjusted total brain volumes than females, and body size normalization procedures did not eliminate this difference. The ratio of brain to CSF volume, however, revealed a universal age-dependent relationship independent of sex or body size. CONCLUSIONS These findings enable the application of normative growth curves in managing a broad range of childhood diseases in which cognitive development, brain growth, and fluid accumulation are interrelated.

Brain charts for the human lifespan

“…Harmonization of MRI data across primary studies to address these and other deficiencies in the extant literature is challenged by methodological and technical heterogeneity. Compared with relatively simple anthropometric measurements such as height or weight, brain morphometrics are known to be highly sensitive to variation in scanner platforms and sequences, data quality control, pre-processing and statistical analysis 18 , thus severely limiting the generalizability of trajectories estimated from any individual study 19 . Collaborative initiatives spurring collection of large-scale datasets 20 , 21 , recent advances in neuroimaging data processing 22 , 23 and proven statistical frameworks for modelling biological growth curves 2 , 24 , 25 provide the building blocks for a more comprehensive and generalizable approach to age-normed quantification of MRI phenotypes over the entire lifespan (see Supplementary Information 1 for details and consideration of previous work focused on the related but distinct objective of inferring brain age from MRI data).…”

“…We created brain charts for the human lifespan using generalized additive models for location, scale and shape 2 , 24 (GAMLSS), a robust and flexible framework for modelling non-linear growth trajectories recommended by the World Health Organization 24 . GAMLSS and related statistical frameworks have previously been applied to developmental modelling of brain structural and functional MRI phenotypes in open datasets 19 , 26 – 31 . Our approach to GAMLSS modelling leveraged the greater scale of data available to optimize model selection empirically, to estimate non-linear age-related trends (in median and variance) stratified by sex over the entire lifespan, and to account for site- or study-specific ‘batch effects’ on MRI phenotypes in terms of multiple random effect parameters.…”

Factors predicting regression of visual acuity following successful treatment of anisometropic amblyopia

“…If later studies replicate this finding, there are several possible explanations. Sex differences in childhood brain development are well established and involve differences in the rate and magnitude of brain structure changes (30)(31)(32). Amblyopia treatment, which relies critically on neuroplasticity within the brain, may interact with these developmental changes leading to sex-differences in the risk of treatment regression.…”

Cytomegalovirus infections in infants in Uganda: Newborn-mother pairs, neonates with sepsis, and infants with hydrocephalus

“…Infants with hydrocephalus have excess weight from their extra CSF; therefore, estimating the nutritional status based on unadjusted body weight is misleading. We overcame the limitation by calculating the volume of CSF in the head from CT scan data, and subtracting excess fluid weight (using 1 gm/mL CSF) for age based on normative curves ( Peterson et al, 2021 ).…”