Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.
Brain Connect. 2024 Oct;14(8):418-429. doi: 10.1089/brain.2024.0007. Epub 2024 Jul 30.
Cerebral small vessel disease (CSVD) is a primary vascular disease of cognitive impairment. Previous studies have predominantly focused on brain linear features. However, the nonlinear measure, brain entropy (BEN), has not been elaborated. Thus, this study aims to investigate if BEN abnormalities could manifest in CSVD patients with cognitive impairment. Thirty-four CSVD patients with cognitive impairment and 37 healthy controls (HCs) were recruited. Analysis of gray matter approximate entropy (ApEn) and sample entropy (SampEn) which are two indices of BEN was calculated. To explore whether BEN can provide unique information, we further performed brain linear methods, namely, amplitude of low frequency fluctuation (ALFF) and regional homogeneity (ReHo), to observe their differences. The ratios of BEN/ALFF and BEN/ReHo which represent the coupling of nonlinear and linear features were introduced. Correlation analysis was conducted between imaging indices and cognition. Subsequently, the linear support vector machine (SVM) was used to assess their discriminative ability. CSVD patients exhibited lower ApEn and SamEn values in sensorimotor areas, which were correlated with worse memory and executive function. In addition, the results of BEN showed little overlap with ALFF and ReHo in brain regions. Correlation analysis also revealed a relationship between the two ratios and cognition. SVM analysis using BEN and its ratios as features achieved an accuracy of 74.64% (sensitivity: 86.49%, specificity: 61.76%, and AUC: 0.82439). Our study reveals that the reduction of sensorimotor system complexity is correlated with cognition. BEN exhibits distinctive characteristics in brain activity. Combining BEN and the ratios can be new biomarkers to diagnose CSVD with cognitive impairment. Impact Statement Cerebral small vessel disease (CSVD) is regarded as the most important vascular disease of cognitive impairment. However, conventional brain imaging fails to adequately elucidate the pathogenesis of cognitive disorder related to CSVD. In this regard, exploring brain entropy (BEN) based on resting-state functional magnetic resonance imaging (rs-fMRI) represents a relatively novel and unexplored approach in the context of CSVD. This approach provides novel insights into the pathogenesis, diagnosis, and rehabilitation of cognitive disorder associated with CSVD.
脑小血管病（CSVD）是认知障碍的主要血管性疾病。先前的研究主要集中在脑线性特征上。然而，脑熵（BEN）的非线性测量尚未得到详细阐述。因此，本研究旨在探讨认知障碍 CSVD 患者是否存在 BEN 异常。
研究纳入了 34 名认知障碍 CSVD 患者和 37 名健康对照者（HCs）。计算了两个 BEN 指标，即灰质近似熵（ApEn）和样本熵（SampEn）的分析。为了探讨 BEN 是否可以提供独特的信息，我们进一步进行了脑线性方法，即低频振幅（ALFF）和局部一致性（ReHo）的分析，以观察它们的差异。引入了代表非线性和线性特征耦合的 BEN/ALFF 和 BEN/ReHo 比值。对影像学指标与认知功能进行了相关性分析。随后，采用线性支持向量机（SVM）评估其判别能力。
CSVD 患者在感觉运动区表现出较低的 ApEn 和 SamEn 值，与记忆和执行功能下降有关。此外，BEN 的结果与大脑区域的 ALFF 和 ReHo 重叠较少。相关性分析还揭示了这两个比值与认知之间的关系。使用 BEN 及其比值作为特征的 SVM 分析达到了 74.64%的准确率（敏感性：86.49%，特异性：61.76%，AUC：0.82439）。
我们的研究表明，感觉运动系统复杂性的降低与认知有关。BEN 在脑活动中表现出独特的特征。结合 BEN 和比值可以成为诊断认知障碍 CSVD 的新生物标志物。
