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White matter microstructural abnormalities in primary insomnia: A systematic review of diffusion tensor imaging studies

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pnpbp.2020.110132

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Diffusion tensor imaging; Primary insomnia; White matter; Connectivity; Microstructural abnormality

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Primary insomnia (PI) is characterized by difficulties in initiating and maintaining sleep along with daytime functioning deficits. DTI studies have shown that patients with PI exhibit white matter disruptions, particularly in frontostriatal, frontothalamic, and corticocortical neural networks, shedding light on the potential etiology and pathology of the disorder. The findings suggest that future research should focus on the neural network alterations in PI patients to better understand the underlying mechanisms of the condition.
Primary insomnia (PI), the most common sleep disorder, is primarily characterized by difficulties in initiating and maintaining sleep and deficits in daytime functioning. Study of white matter (WM) connections of the brain might provide valuable information regarding the underlying neural mechanism of PI. Diffusion tensor imaging (DTI) provides non-invasive access to the microstructural and network properties of brain WM, and thus, a great opportunity to quantitatively and sensitively study the human brain. The current literature of PI does not provide a consistent explanation of the etiology and pathology of the disorder; thus, we searched PubMed, EMBASE, and SCOPUS for DTI studies that compared WM integrity or network organization between PI patients and healthy controls to integrate all existing literature as an insight for further studies, and, hopefully, effective prevention and management of the disorder. English peer-reviewed full-text publications that investigated the diffusion indices of PI patients or those with insomnia symptoms compared with a group of healthy controls were included. We included 11 studies and extracted the data for qualitative synthesis. Except for one study, all studies were rated as high-quality, based on quality assessment. In aggregation, a total of 541 patients with PI and 679 healthy controls were included in this study. Our review of DTI studies suggests that WM disruptions in PI are better characterized in the context of neural networks. Frontostriatal, frontothalamic, and corticocortiscal networks, as well as the limbic system, seem to be the main neural networks with microstructural and network alterations in patients with PI. To illustrate, different parts of corona radiate and internal capsule within the corticosubcortical networks and superior longitudinal fasciculus within the corticocortical networks showed altered microstructural properties in PI patients. In view of the fact that the findings from individual studies are heterogeneous, it is difficult to derive consistent findings from the results, and the divergence of the findings must not be disregarded. Thus, this study is a starting point for future studies, and its implications for etiology and pathogenesis of insomnia should be regarded cautiously.

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