Liu Wanqing, Cao Chuanlong, Hu Bing, Li Danyang, Sun Yumei, Wu Jianlin, Zhang Qing
Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian 116001, People's Republic of China.
Department of Radiology, Affiliated Xinhua Hospital of Dalian University, Dalian 116001, People's Republic of China.
Nat Sci Sleep. 2020 Jun 8;12:333-345. doi: 10.2147/NSS.S248643. eCollection 2020.
Patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) exhibit neurocognitive impairments; however, the neuroimaging mechanism of neurocognitive impairments remains unclear. The aim of this study was to understand the neuroimaging mechanism in adult patients with moderate-to-severe OSAHS, from the perspective of the connectome.
Thirty-one untreated patients with moderate-to-severe OSAHS (mean age: 41.23±8.22) were compared with 26 good sleepers (GS) (mean age: 39.50±7.92) matched according to age, gender, handedness, and education level. All subjects underwent thin-slice T1WI scanning of the skull using a 3.0T MRI. Then, a large-scale structural covariance network was constructed based on the gray matter volume extracted from the structural MRI. Graph theory was then used to determine the topological changes in the structural covariance network of OSAHS patients.
Although small-world networks were retained,the structural covariance network exhibited topological irregularities in regular architecture as evidenced by an increase in the clustering coefficient (=0.009), transfer coefficient (=0.029) and local efficiency (=0.031), and a local increase in the shortest path length (<0.05) compared with the GS group. Locally, OSAHS patients showed a decrease in nodal betweenness and degree in the left inferior parietal gyrus, left angular gyrus and right anterior cingulate cortex compared with the GS group (<0.05, uncorrected). In addition, the resistance of structural covariance networks in OSAHS patients to random fault is significantly lower than that of the GS group (=0.044).
Structural covariance networks are abnormal in terms of multiple network parameters, which provide network-level insight into the neuroimaging mechanism of cognitive impairments in adult OSAHS patients.
阻塞性睡眠呼吸暂停低通气综合征（OSAHS）患者存在神经认知障碍；然而，神经认知障碍的神经影像学机制仍不清楚。本研究的目的是从脑连接组的角度了解成年中重度OSAHS患者的神经影像学机制。
将31例未经治疗的中重度OSAHS患者（平均年龄：41.23±8.22）与26例根据年龄、性别、利手和教育水平匹配的睡眠良好者（GS）（平均年龄：39.50±7.92）进行比较。所有受试者均使用3.0T MRI对头骨进行薄层T1WI扫描。然后，基于从结构MRI中提取的灰质体积构建大规模结构协方差网络。随后使用图论确定OSAHS患者结构协方差网络的拓扑变化。
虽然保留了小世界网络，但结构协方差网络在规则结构中表现出拓扑不规则性，与GS组相比，聚类系数（=0.009）、传递系数（=0.029）和局部效率（=0.031）增加，最短路径长度局部增加（<0.05）。局部而言，与GS组相比，OSAHS患者左侧顶下小叶、左侧角回和右侧前扣带回皮质的节点中介中心性和度降低（<0.05，未校正）。此外，OSAHS患者结构协方差网络对随机故障的抵抗力明显低于GS组（=0.044）。
结构协方差网络在多个网络参数方面存在异常，这为成年OSAHS患者认知障碍的神经影像学机制提供了网络层面的见解。
