OBJECTIVES To investigate whether longitudinal structural network efficiency is associated with cognitive decline and whether baseline network efficiency predicts mortality in cerebral small vessel disease (SVD). METHODS A prospective, single-centre cohort consisting of 277 non-demented individuals with SVD was conducted. In 2011 and 2015, all participants were scanned with MRI and underwent neuropsychological assessment. We computed network properties using graph theory from probabilistic tractography and calculated changes in psychomotor speed and overall cognitive index. Multiple linear regressions were performed, while adjusting for potential confounders. We divided the group into mild-to-moderate white matter hyperintensities (WMH) and severe WMH group based on median split on WMH volume. RESULTS The decline in global efficiency was significantly associated with a decline in psychomotor speed in the group with severe WMH (β=0.18, p=0.03) and a trend with change in cognitive index (β=0.14, p=0.068), which diminished after adjusting for imaging markers for SVD. Baseline global efficiency was associated with all-cause mortality (HR per decrease of 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76). CONCLUSION Disruption of the network efficiency, a metric assessing the efficiency of network information transfer, plays an important role in explaining cognitive decline in SVD, which was however not independent of imaging markers of SVD. Furthermore, baseline network efficiency predicts risk of mortality in SVD that may reflect the global health status of the brain in SVD. This emphasises the importance of structural network analysis in the context of SVD research and the use of network measures as surrogate markers in research setting.

中文翻译：

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脑小血管疾病的结构网络变化。

目的研究纵向结构网络效率是否与认知能力下降有关，以及基线网络效率是否可预测脑小血管疾病（SVD）的死亡率。方法进行了一项前瞻性单中心队列研究，该队列由277名SVD非痴呆症患者组成。在2011年和2015年，所有参与者均接受了MRI扫描，并接受了神经心理学评估。我们使用概率论中的图论来计算网络属性，并计算精神运动速度和整体认知指数的变化。进行了多元线性回归，同时对潜在的混杂因素进行了调整。根据WMH量的中位数划分，我们将该组分为轻度至中度白质高血压（WMH）和重度WMH组。结果在重度WMH组（β= 0.18，p = 0.03）和认知指数变化趋势（β= 0.14，p = 0.068）方面，整体效率的下降与精神运动速度的下降显着相关（β= 0.14，p = 0.068）调整SVD的成像标记后。基线整体效率与全因死亡率相关（HR下降1 SD 0.43，95％CI 0.23至0.80，p = 0.008，C统计0.76）。结论网络效率的破坏是一种评估网络信息传输效率的指标，在​​解释SVD的认知能力下降中起着重要作用，但是它并不独立于SVD的成像标记。此外，基线网络效率可预测SVD的死亡风险，这可能反映了SVD中大脑的整体健康状况。