Glymphatic system impairment in sleep disruption: diffusion tensor image analysis along the perivascular space (DTI-ALPS)

• Published in: Japanese journal of radiology 2023-12, Vol.41 (12), p.1335-1343
• Main Authors: Saito, Yuya, Hayakawa, Yayoi, Kamagata, Koji, Kikuta, Junko, Mita, Takeshi, Andica, Christina, Taoka, Toshiaki, Uchida, Wataru, Takabayashi, Kaito, Tuerxun, Rukeye, Mahemuti, Zaimire, Yoshida, Seina, Kitagawa, Takafumi, Arai, Takashi, Suzuki, Akiyoshi, Sato, Kanako, Nishizawa, Mitsuo, Akashi, Toshiaki, Shimoji, Keigo, Wada, Akihiko, Aoki, Shigeki
• Format: Article
• Language: English
• Subjects: Correlation analysis; Disruption; Image analysis; Image processing; Imaging; Impairment; Latency; Magnetic resonance imaging; Mathematical analysis; Medicine; Medicine & Public Health; Nuclear Medicine; Original Article; Quality assessment; Radiology; Radiotherapy; Sleep; Tensors; Young adults
• ISSN: 1867-1071; 1867-108X
• DOI: 10.1007/s11604-023-01463-6

Purpose This study aimed to evaluate the relationship between sleep quality as assessed using the Pittsburgh Sleep Quality Index (PSQI) and the index of diffusivity along the perivascular space (ALPS index), a possible indirect indicator of glymphatic system activity. Materials and methods This study included the diffusion magnetic resonance imaging (MRI) data of 317 people with sleep disruption and 515 healthy controls (HCs) from the Human Connectome Project (WU-MINN HCP 1200). The ALPS index was calculated automatically based on diffusion tensor image analysis (DTI)-ALPS of diffusion MRI. The ALPS index of the sleep disruption and HC groups was compared using general linear model (GLM) analysis with covariates, such as age, sex, level of education, and intracranial volume. In addition, to confirm the relationship between sleep quality and the ALPS index in the sleep disruption group as well as evaluate the effect of each PSQI component on the ALPS index, correlation analyses between the ALPS indices and PSQI scores of all the components and between the ALPS index and each PSQI component was performed using GLM analysis with the abovementioned covariates, respectively. Results The ALPS index was significantly lower in the sleep disruption group than in the HC group ( p  = 0.001). Moreover, the ALPS indices showed significant negative correlations with the PSQI scores of all the components (false discovery rate [FDR]-corrected p