Peterson Mallory, Warf Benjamin C, Schiff Steven J
1The Center for Neural Engineering and.
Departments of2Biomedical Engineering.
J Neurosurg Pediatr. 2018 May;21(5):478-485. doi: 10.3171/2017.10.PEDS17141. Epub 2018 Mar 2.
OBJECTIVE While there is a long history of interest in measuring brain growth, as of yet there is no definitive 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 fit. 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 fit 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 fit and the corresponding statistics were presented and analyzed. The Weibull fit 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 fit parameters for each model were provided to assure reproducibility. CONCLUSIONS The authors identified the Weibull model as the most effective growth curve fit 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.
目的 虽然测量脑生长已有很长的历史，但迄今为止，尚无确定的正常人类脑容量生长模型。本研究的目的是分析多种此类生长的候选模型，并选择统计适用性最佳的模型。作者试图优化临床适用的生长图表，以促进对脑积水等病症的治疗和预测管理的改善。方法 选择威布尔模型、二次幂律模型、韦斯特个体发育模型和冈珀茨模型作为潜在模型。从美国国立卫生研究院MRI数据库汇编正常脑容量数据，并使用非线性最小二乘回归算法对数据进行拟合。对每个模型分析适当的统计量，并通过预测边界曲线对最佳模型进行表征，以提供临床使用的百分位数估计。结果 展示并分析了每个模型曲线拟合及相应统计量。威布尔拟合对男性和女性均具有最佳统计结果，而二次幂律模型得分最差。提供每个模型的统计量和拟合优度参数以确保可重复性。结论 作者确定威布尔模型是男性和女性最有效的生长曲线拟合模型。开发并提供了临床可用的生长图表，以促进对脑积水等病症中脑容量生长的进一步临床研究。作者指出，汇编正常MRI数据所依据的同质人群限制了本研究。更好地了解儿童脑生长背后的动态过程将产生更具预测性的生长曲线，并改善脑积水的神经外科管理。
