脑小血管病(cSVD)是血管性混合性认知障碍(CI)的主要病因之一,它是相关联的,特别是,大脑老化了解cSVD中完整脑白质的结构组织变化可能会使人们开发出敏感的生物标志物,以进行早期诊断和监测疾病进展。
目的:使用扩散MRI(D-MRI)方法评估不同程度CI的cSVD患者call体(CC)的微观结构变化,并揭示扩散指标与CI的最敏感相关性。
方法:该研究包括166名cSVD患者(51.8%女性;60.4±7.6岁)和44名健康志愿者(65.9%女性;59.6±6.8岁)。所有受试者均接受D-MRI(3T)信号(弥散张量和峰度)和生物物理(神经突方向弥散和密度成像,NODDI,白质道完整性,WMTI,多室球形平均技术,MC-SMT)在三个CC部分进行建模以及神经心理学评估。
结果:在cSVD患者中,在已经处于主观CI阶段的所有CC段中发现了微观结构变化,被发现恶化为mildCI和痴呆症。在小镊子中观察到更明显的变化。在信号模型FA中,MD,MK,RD,还有RK,以及在生物物理模型中,MC-SMT(EMD,ETR)和WMTI(AWF)指标表现出最大的曲线下面积(>0.85),表征微结构完整性的损失,潜在脱髓鞘的严重程度,以及轴突内水的比例,分别。结论:该研究揭示了先进的D-MRI方法对评估cSVD脑组织变化的相关性。鉴定的扩散生物标志物可用于CI进展的澄清和观察。
The cerebral small vessel disease (cSVD) is one of the main causes of vascular and mixed cognitive impairment (CI), and it is associated, in particular, with brain ageing. An understanding of structural tissue changes in an intact cerebral white matter in cSVD might allow one to develop the sensitive biomarkers for early diagnosis and monitoring of disease progression.
OBJECTIVE: to evaluate microstructural changes in the corpus callosum (CC) using diffusion MRI (D-MRI) approaches in cSVD patients with different severity of CI and reveal the most sensitive correlations of diffusion metrics with CI.
METHODS: the study included 166 cSVD patients (51.8% women; 60.4 ± 7.6 years) and 44 healthy volunteers (65.9% women; 59.6 ± 6.8 years). All subjects underwent D-MRI (3T) with signal (diffusion tensor and kurtosis) and biophysical (neurite orientation dispersion and density imaging, NODDI, white matter tract integrity, WMTI, multicompartment spherical mean technique, MC-SMT) modeling in three CC segments as well as a neuropsychological assessment.
RESULTS: in cSVD patients, microstructural changes were found in all CC segments already at the subjective CI stage, which was found to worsen into mild CI and dementia. More pronounced changes were observed in the forceps minor. Among the signal models FA, MD, MK, RD, and RK, as well as among the biophysical models, MC-SMT (EMD, ETR) and WMTI (AWF) metrics exhibited the largest area under the curve (>0.85), characterizing the loss of microstructural integrity, the severity of potential demyelination, and the proportion of intra-axonal water, respectively. Conclusion: the study reveals the relevance of advanced D-MRI approaches for the assessment of brain tissue changes in cSVD. The identified diffusion biomarkers could be used for the clarification and observation of CI progression.