TY - JOUR
T1 - Normative human brain volume growth
AU - Peterson, Mallory
AU - Warf, Benjamin C.
AU - Schiff, Steven J.
N1 - Funding Information:
We gratefully acknowledge Dr. Jason Mandell for compilation of MRI NIH data, Dr. Paddy Ssentongo for advice on the manuscript, and Michael MacDonald for expertise in segmentation algorithms. This work was supported by the Penn State Schreyer Honors College, the Penn State Presidential Leadership Academy (M.P.), and NIH grant 1R01HD085853 (S.J.S. and B.C.W.).
Publisher Copyright:
© 2018 AANS.
PY - 2018/5
Y1 - 2018/5
N2 - OBJECTIVE While there is a long history of interest in measuring brain growth, as of yet there is no defnitive model for normative human brain volume growth. The goal of this study was to analyze a variety of candidate models for such growth and select the model that provides the most statistically applicable ft. The authors sought to optimize clinically applicable growth charts that would facilitate improved treatment and predictive management for conditions such as hydrocephalus. METHODS The Weibull, two-term power law, West ontogenic, and Gompertz models were chosen as potential models. Normative brain volume data were compiled from the NIH MRI repository, and the data were ft using a nonlinear least squares regression algorithm. Appropriate statistical measures were analyzed for each model, and the best model was characterized with prediction bound curves to provide percentile estimates for clinical use. RESULTS Each model curve ft and the corresponding statistics were presented and analyzed. The Weibull ft had the best statistical results for both males and females, while the two-term power law generated the worst scores. The statistical measures and goodness of ft parameters for each model were provided to assure reproducibility. CONCLUSIONS The authors identifed the Weibull model as the most effective growth curve ft for both males and females. Clinically usable growth charts were developed and provided to facilitate further clinical study of brain volume growth in conditions such as hydrocephalus. The authors note that the homogenous population from which the normative MRI data were compiled limits the study. Gaining a better understanding of the dynamics that underlie childhood brain growth would yield more predictive growth curves and improved neurosurgical management of hydrocephalus.
AB - OBJECTIVE While there is a long history of interest in measuring brain growth, as of yet there is no defnitive model for normative human brain volume growth. The goal of this study was to analyze a variety of candidate models for such growth and select the model that provides the most statistically applicable ft. The authors sought to optimize clinically applicable growth charts that would facilitate improved treatment and predictive management for conditions such as hydrocephalus. METHODS The Weibull, two-term power law, West ontogenic, and Gompertz models were chosen as potential models. Normative brain volume data were compiled from the NIH MRI repository, and the data were ft using a nonlinear least squares regression algorithm. Appropriate statistical measures were analyzed for each model, and the best model was characterized with prediction bound curves to provide percentile estimates for clinical use. RESULTS Each model curve ft and the corresponding statistics were presented and analyzed. The Weibull ft had the best statistical results for both males and females, while the two-term power law generated the worst scores. The statistical measures and goodness of ft parameters for each model were provided to assure reproducibility. CONCLUSIONS The authors identifed the Weibull model as the most effective growth curve ft for both males and females. Clinically usable growth charts were developed and provided to facilitate further clinical study of brain volume growth in conditions such as hydrocephalus. The authors note that the homogenous population from which the normative MRI data were compiled limits the study. Gaining a better understanding of the dynamics that underlie childhood brain growth would yield more predictive growth curves and improved neurosurgical management of hydrocephalus.
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U2 - 10.3171/2017.10.PEDS17141
DO - 10.3171/2017.10.PEDS17141
M3 - Article
C2 - 29498607
AN - SCOPUS:85048239434
VL - 21
SP - 478
EP - 485
JO - Journal of Neurosurgery: Pediatrics
JF - Journal of Neurosurgery: Pediatrics
SN - 1933-0707
IS - 5
ER -