| Literature DB >> 32896599 |
Jing Du1, Hong Zhu2, Jie Zhou2, Peiwen Lu1, Yage Qiu3, Ling Yu4, Wenwei Cao4, Nan Zhi4, Jie Yang1, Qun Xu5, Junfeng Sun6, Yan Zhou7.
Abstract
Cerebral small vessel disease (CSVD) is a common disease among elderly individuals and recognized as a major cause of vascular cognitive impairment. Recent studies demonstrated that CSVD is a disconnection syndrome. However, due to the covert neurological symptoms and subtle changes in clinical performance, the connection alterations during the stage of preclinical cognitive impairment (PCI) and mild cognitive impairment (MCI) are usually neglected and still largely unknown. Using diffusion tensor imaging (DTI), we investigated the early structural network changes in PCI and MCI patients. The PCI group demonstrated well preserved rich-club organization, less nodal strength loss, and disruption of connections centered in the feeder and local connections. Nevertheless, the MCI group manifested a disruption in the rich-club organization, a worse nodal strength loss especially in hub nodes, and an overall disturbance in rich-club, feeder and local connections. Moreover, in all CSVD patients, the strength of the rich-club, feeder and local connections was significantly correlated with multiple cognitive scores, especially in attention, executive, and memory domains; while in MCI patients, only the strength of the rich-club connections was significantly correlated with cognition. Furthermore, based on the network-based statistic analysis, we also identified distinct network component disruption pattern between the PCI group and the MCI group, validating the results described above. These results suggest a disruption pattern from peripheral to central connections with the change of cognitive status, shedding light on the early identification and the underlying disruption of CSVD.Entities:
Keywords: cerebral small vessel disease (CSVD); diffusion tensor imaging (DTI); preclinical cognitive impairment (PCI); rich-club; structural brain network
Mesh:
Year: 2020 PMID: 32896599 DOI: 10.1016/j.neuroscience.2020.08.037
Source DB: PubMed Journal: Neuroscience ISSN: 0306-4522 Impact factor: 3.590