AIMS White matter hyperintensity (WMH) is the most common neuroimaging manifestation of cerebral small vessel disease and is related to cognitive dysfunction or dementia. This study aimed to investigate the mechanism and effective indicators to predict WMH-related cognitive impairment. METHODS We recruited 22 healthy controls (HC), 25 cases of WMH with normal cognition (WMH-NC), and 23 cases of WMH with mild cognitive impairment (WMH-MCI). All individuals underwent diffusion tensor imaging (DTI) and a standardized neuropsychological assessment. Automated Fiber Quantification was used to extract altered DTI metrics between groups, and partial correlation was performed to assess the associations between WM integrity and cognitive performance. Furthermore, machine learning analyses were performed to determine underlying imaging markers of WMH-related cognitive impairment. RESULTS Our study found that mean diffusivity (MD) values of several fiber bundles including the bilateral anterior thalamic radiation (ATR), the left inferior fronto-occipital fasciculus (IFOF), the right inferior longitudinal fasciculus (ILF), and the right superior longitudinal fasciculus (SLF) were negatively correlated with memory function, while that of the anterior component of the right IFOF and the posterior and intermediate component of the right ILF showed significant negative correlation with MMSE and episodic memory, respectively. Furthermore, machine learning analyses showed that the accuracy of recognizing WMH-MCI patients from the WMH populations was up to 80.5% and the intermediate and posterior components of the right ILF and the anterior component of the right IFOF contribute the most. CONCLUSIONS Changes in the properties of DTI may be the potential mechanism of WMH-related MCI, especially the right IFOF and the right ILF, which may become imaging markers for predicting WMH-related cognitive dysfunction.

中文翻译：

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右下额枕叶和下纵束的微观结构破坏会导致 WMH 相关的认知障碍。

AIMS 白质高信号 (WMH) 是脑小血管疾病最常见的神经影像学表现，与认知功能障碍或痴呆有关。本研究旨在探讨预测 WMH 相关认知障碍的机制和有效指标。方法 我们招募了 22 名健康对照 (HC)、25 例认知正常的 WMH (WMH-NC) 和 23 例轻度认知障碍 (WMH-MCI) 的 WMH。所有个体都接受了弥散张量成像 (DTI) 和标准化的神经心理学评估。自动纤维量化用于提取组间改变的 DTI 指标，并执行部分相关以评估 WM 完整性与认知性能之间的关联。此外，进行机器学习分析以确定 WMH 相关认知障碍的潜在成像标志物。结果 我们的研究发现，包括双侧前丘脑辐射 (ATR)、左侧额枕下束 (IFOF)、右侧下纵束 (ILF) 和右侧上纵束在内的几种纤维束的平均扩散率 (MD) 值束（SLF）与记忆功能呈负相关，而右侧 IFOF 的前部成分和右侧 ILF 的后部和中间成分分别与 MMSE 和情景记忆呈显着负相关。此外，机器学习分析表明，从 WMH 人群中识别 WMH-MCI 患者的准确率高达 80。5%，右侧 ILF 的中间和后部成分以及右侧 IFOF 的前部成分贡献最大。结论 DTI特性的改变可能是WMH相关MCI的潜在机制，尤其是右侧IFOF和右侧ILF，可能成为预测WMH相关认知功能障碍的影像学标志物。