利用弥散张量成像技术观察小血管病所致非痴呆型血管性认知障碍患者白质结构损害与认知下降的关系

doi:10.3969/j.issn.1006-7795.2021.03.006

首都医科大学学报 ›› 2021, Vol. 42 ›› Issue (3): 373-384.doi: 10.3969/j.issn.1006-7795.2021.03.006

利用弥散张量成像技术观察小血管病所致非痴呆型血管性认知障碍患者白质结构损害与认知下降的关系

秦琪¹, 唐毅^1*, 曲怡达², 周爱红¹, 丁建平¹, 尹筠思¹, 刘勇^2,3, 贾建平^1,4*

1.首都医科大学宣武医院神经疾病高创中心国家老年疾病临床医学研究中心北京市老年病医疗研究中心,北京 100053;
2.中国科学院自动化研究所模式识别国家重点实验室/脑网络组研究中心,北京 100190;
3.中国科学院大学人工智能学院北京邮电大学人工智能学院,北京 100876;
4.老年认知障碍疾病北京市重点实验室首都医科大学神经变性病与记忆障碍疾病临床诊疗与研究中心北京脑重大疾病研究院阿尔茨海默病研究所,北京 100053

收稿日期:2020-03-17 出版日期:2021-06-21 发布日期:2021-06-16
通讯作者: *E-mail:tangyixw@163.com;jjp@ccmu.edu.cn
基金资助:
国家重点研发计划(2016YFC1306305),首都卫生发展科研专项青年优才项目(首发2020-4-1033)。

Study on the association between white matter connectivity changes and cognitive deficits in vascular cognitive impairment no dementia using diffusion tensor imaging

Qin Qi¹, Tang Yi^1*, Qu Yida², Zhou Aihong¹, Ding Jianping¹, Yin Yunsi¹, Liu Yong^2,3, Jia Jianping^1,4*

1. Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases,Beijing Municipal Geriatric Medical Research Center, Beijing 100053,China;
2. Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190,China;
3. School of Artificial Intelligence, University of Chinese Academy of Sciences; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876,China;
4. Beijing Key Laboratory of Geriatric Cognitive Disorders; Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University; Center of Alzheimer's Disease, Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053,China

Received:2020-03-17 Online:2021-06-21 Published:2021-06-16
Contact: *E-mail:tangyixw@163.com;jjp@ccmu.edu.cn
Supported by:
National key R&D Program (2016YFC1306305), Capital's Funds for Health Improvement and Research (CFH 2020-4-1033).

摘要/Abstract

摘要： 目的非痴呆型血管性认知障碍(vascular cognitive impairment, no dementia, VCIND)是血管性认知障碍最常见亚型,早期诊断是改善预后的关键。神经影像为VCIND早期诊断、严重程度及疗效评价提供依据,但传统结构磁共振(magnetic resonance imaging, MRI)不能较好阐明结构改变与认知损害的关系。本项目利用弥散张量成像技术(diffusion tensor imaging, DTI)探讨VCIND患者脑白质结构改变及其和认知障碍的关系。方法利用DTI对31名VCIND患者和22名正常对照者进行全脑246个脑区的白质连接完整性检测,并对所有受试者进行认知评估。然后分析患者各脑区DTI各向异性程度值(fractional anisotropy, FA)和平均弥散率(mean diffusivity, MD),并与认知评分进行相关性分析及中介分析。结果 VCIND患者全脑246个脑区中的部分关键区域发生了显著的白质连接改变,尤其额叶脑区显著。FA值与总体认知评估及记忆、执行功能评分正相关,MD值与总体认知评估及记忆、执行功能评分负相关。中介分析发现VCIND患者白质结构连接的改变介导了神经心理量表评分的改变。结论本研究显示DTI可以为VCIND的早期诊断及认知严重程度的评估提供客观影像学指标。

关键词: 弥散张量成像技术, 非痴呆型血管性认知障碍, 白质结构损害, 认知评估

Abstract: Objective To explore the relationship between vascular cognitive impairment, no dementia (VCIND) and white matter microstructural changes to confirm a diagnosis of dementia. VCIND is the most common subtype of mild cognitive dysfunction. Neuroimaging provides the basis for the early diagnosis, severity and efficacy evaluation of VCIND.However, traditional magnetic resonance imaging (MRI) cannot clarify the relationship between structural changes and cognitive impairment. Methods Diffusion tensor imaging (DTI) was carried out to investigate white matter microstructural changes in 246 brain areas in 31 VCIND patients and 22 normal controls. All patients underwent neuropsychological assessments and DTI examination. Voxel-based analyses were performed to extract fractional anisotropy (FA) and mean diffusivity (MD) measures. Correlation analysis and mediation analysis were performed with cognitive dysfunction. Results Compared with the healthy elderly subjects, subcortical VCIND patients presented with abnormal white matter connectivity changes in several key hubs, especially in frontal lobes. The severity of damage significantly correlated with cognitive dysfunction. FA significantly correlated with general cognitive impairment,memory function and executive function. We also found a significant negative correlation between MD and general cognitive function,memory function and executive function. Mediation analyses demonstrated that the disrupted white matter connectivity could explain the cognitive dysfunction. Conclusions The results indicate that the brain white matter connectivity changes of DTI may be a neuroimaging marker for VCIND early diagnosis and cognitive severity measurement.

Key words: diffusion tensor imaging, vascular cognitive impairment, no dementia, white matter connectivity changes, cognitive function

中图分类号:

R445

秦琪, 唐毅, 曲怡达, 周爱红, 丁建平, 尹筠思, 刘勇, 贾建平. 利用弥散张量成像技术观察小血管病所致非痴呆型血管性认知障碍患者白质结构损害与认知下降的关系[J]. 首都医科大学学报, 2021, 42(3): 373-384.

Qin Qi, Tang Yi, Qu Yida, Zhou Aihong, Ding Jianping, Yin Yunsi, Liu Yong, Jia Jianping. Study on the association between white matter connectivity changes and cognitive deficits in vascular cognitive impairment no dementia using diffusion tensor imaging[J]. Journal of Capital Medical University, 2021, 42(3): 373-384.

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利用弥散张量成像技术观察小血管病所致非痴呆型血管性认知障碍患者白质结构损害与认知下降的关系

Study on the association between white matter connectivity changes and cognitive deficits in vascular cognitive impairment no dementia using diffusion tensor imaging

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