Characterization of white matter microstructural abnormalities associated with cognitive dysfunction in cerebral small vessel disease with cerebral microbleeds

磁共振弥散成像 部分各向异性 白质 认知功能衰退 内科学 疾病 心理学 医学 病理 心脏病学 磁共振成像 放射科 痴呆
作者
Chaofan Sui,Hongwei Wen,Shengpei Wang,Mengmeng Feng,Haotian Xin,Yian Gao,Jing Li,Lingfei Guo,Changhu Liang
出处
期刊:Journal of Affective Disorders [Elsevier BV]
卷期号:324: 259-269 被引量:2
标识
DOI:10.1016/j.jad.2022.12.070
摘要

Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore white matter (WM) microstructural alterations. Cerebral small vessel disease (CSVD) may be accompanied by extensive WM microstructural deterioration, while cerebral microbleeds (CMBs) are an important factor affecting CSVD.Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 49 CSVD patients with CMBs (CSVD-c), 114 CSVD patients without CMBs (CSVD-n), and 83 controls were analyzed using DTI-derived tract-based spatial statistics to detect WM diffusion changes among groups.Compared with the CSVD-n and control groups, the CSVD-c group showed a significant FA decrease and AD, RD and MD increases mainly in the cognitive and sensorimotor-related WM tracts. There was no significant difference in any diffusion metric between the CSVD-n and control groups. Furthermore, the widespread regional diffusion alterations among groups were significantly correlated with cognitive parameters in both the CSVD-c and CSVD-n groups. Notably, we applied the multiple kernel learning technique in multivariate pattern analysis to combine multiregion and multiparameter diffusion features, yielding an average accuracy >77 % for three binary classifications, which showed a considerable improvement over the single modality approach.We only grouped the study according to the presence or absence of CMBs.CSVD patients with CMBs have extensive WM microstructural deterioration. Combining DTI-derived diffusivity and anisotropy metrics can provide complementary information for assessing WM alterations associated with cognitive dysfunction and serve as a potential discriminative pattern to detect CSVD at the individual level.
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