Cole James H, Leech Robert, Sharp David J
Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom.
Ann Neurol. 2015 Apr;77(4):571-81. doi: 10.1002/ana.24367.
OBJECTIVE: The long-term effects of traumatic brain injury (TBI) can resemble observed in normal ageing, suggesting that TBI may accelerate the ageing process. We investigate this using a neuroimaging model that predicts brain age in healthy individuals and then apply it to TBI patients. We define individuals' differences in chronological and predicted structural "brain age," and test whether TBI produces progressive atrophy and how this relates to cognitive function. METHODS: A predictive model of normal ageing was defined using machine learning in 1,537 healthy individuals, based on magnetic resonance imaging-derived estimates of gray matter (GM) and white matter (WM). This ageing model was then applied to test 99 TBI patients and 113 healthy controls to estimate brain age. RESULTS: The initial model accurately predicted age in healthy individuals (r = 0.92). TBI brains were estimated to be "older," with a mean predicted age difference (PAD) between chronological and estimated brain age of 4.66 years (±10.8) for GM and 5.97 years (±11.22) for WM. This PAD predicted cognitive impairment and correlated strongly with the time since TBI, indicating that brain tissue loss increases throughout the chronic postinjury phase. INTERPRETATION: TBI patients' brains were estimated to be older than their chronological age. This discrepancy increases with time since injury, suggesting that TBI accelerates the rate of brain atrophy. This may be an important factor in the increased susceptibility in TBI patients for dementia and other age-associated conditions, motivating further research into the age-like effects of brain injury and other neurological diseases.
目的:创伤性脑损伤(TBI)的长期影响可能类似于正常衰老过程中观察到的情况,这表明TBI可能加速衰老进程。我们使用一种神经影像学模型来研究这一现象,该模型可预测健康个体的脑龄,然后将其应用于TBI患者。我们定义个体在实际年龄和预测的结构“脑龄”上的差异,并测试TBI是否会导致进行性萎缩以及这与认知功能的关系。 方法:基于磁共振成像得出的灰质(GM)和白质(WM)估计值,通过机器学习在1537名健康个体中定义了正常衰老的预测模型。然后将该衰老模型应用于99名TBI患者和113名健康对照,以估计脑龄。 结果:初始模型能够准确预测健康个体的年龄(r = 0.92)。TBI患者的大脑被估计“年龄更大”,GM的实际年龄与估计脑龄之间的平均预测年龄差(PAD)为4.66岁(±10.8),WM为5.97岁(±11.22)。这个PAD可预测认知障碍,并且与TBI后的时间密切相关,表明在慢性损伤后阶段脑组织损失会增加。 解读:TBI患者的大脑被估计比其实际年龄更大。这种差异随受伤时间的增加而增大,表明TBI加速了脑萎缩的速度。这可能是TBI患者患痴呆症和其他与年龄相关疾病易感性增加的一个重要因素,促使进一步研究脑损伤和其他神经系统疾病的类似衰老效应。
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