Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic.
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
PLoS One. 2023 Apr 14;18(4):e0280892. doi: 10.1371/journal.pone.0280892. eCollection 2023.
Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.
尽管中风的全球负担不断增加，且对社会经济有影响，但人们对中风后认知障碍的神经影像学预测因素仍知之甚少。我们通过研究中风后 10 天内的白质完整性与患者发病 1 年后认知状态之间的关系来解决这一问题。我们使用弥散加权成像，采用基于束的空间统计学分析，并通过确定性束追踪来构建个体结构连接矩阵。我们进一步量化了个体网络的图论性质。基于束的空间统计确实确定了较低的各向异性分数作为认知状态的预测因子，但这种效应主要归因于与年龄相关的白质完整性下降。我们进一步观察到年龄的影响在其他分析水平上的传播。具体来说，在结构连接方法中，我们确定了与临床量表（即记忆、注意力和视空间功能）显著相关的区域对。然而，在进行年龄校正后，这些区域对与临床量表的相关性均不显著。最后，图论测量结果似乎对年龄的影响更稳健，但仍然不够敏感，无法捕捉到与临床量表的关系。总之，年龄的影响是一个主要的混杂因素，尤其是在年龄较大的队列中，如果不加以适当处理，可能会错误地驱动预测模型的结果。
