1 Michael E. DeBakey Veterans Affairs Medical Center , Houston, Texas.
2 Department of Neuroscience, Baylor College of Medicine , Houston, Texas.
J Neurotrauma. 2017 Nov 15;34(22):3107-3116. doi: 10.1089/neu.2017.5022. Epub 2017 Aug 4.
Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.
寻找轻度创伤性脑损伤(TBI)的客观和可量化的影像学标志物一直具有挑战性,尤其是在军事人群中。动物和人类报告了损伤后皮质厚度的变化,但尚不清楚这些改变在慢性期如何表现,并且难以通过影像学进行准确描述。我们使用源自高级归一化工具(ANTs)的皮质厚度测量值来预测连续的人口统计学变量:年龄。我们训练了四个不同的回归模型(线性回归、支持向量回归、高斯过程回归和随机森林),从公开可用的数据集(n=762)中的健康对照组大脑中预测年龄。然后,我们使用这些模型来预测患有 TBI(n=92)和没有 TBI(n=34)的军事人员的大脑年龄。我们的结果表明,所有四个模型都高估了患有 TBI 的军人的年龄,并且与军人对照组相比,预测的年龄差异明显更大。这些数据扩展了以前的平民研究结果,并表明皮质厚度测量值可能揭示了与军事 TBI 随时间加速变化的关联。