| Section I Resting-state brain networks of patients with obstructive sleep apnea-hypopnea syndromeObjective:To obtain common resting-state brain networks of patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) and healthy controls using independent component analysis. To investigate alterations in resting-state functional connectivity of the common brain networks in OSAHS patients and their correlations with disease severity of OSAHS, and their relationships with changes in grey matter volume (GMV) in the corresponding brain regions.Subjects and Methods:Twenty-four treatment-naive male patients with moderate to severe OSAHS (age ranges from31to59years) and21healthy controls matched for age, gender, years of education and handedness (age ranges from30to60years) were included in this study. Each participant was assessed by a detailed clinical interview and physical examination, and full nocturnal-polysomnography monitoring was performed on all patients with OSAHS and controls. The apnea-hypopnea index (AHI) is larger than15in patients with OSAHS but lower than5in control subjects. GE3.0T MR Scanner was used to obtain resting-state fMRI data and high resolution three-dimension (3D) T1-weighted images. The fMRI data were processed with the software of REST and SPM8. During the pre-processing steps, the rs-fMRI data were realigned, normalized, spatially smoothed, linear regressed, and band-pass filtered. A three-step principal component analysis was used to decompose the data set into30components. The GICA was run100times to obtain highly robust results. Seven meaningful components were identified via visual inspection and these components are well consistent with previous studies. For each brain network of interest, a two-sample t-test was used to identify group differences in the functional connectivity in a voxel-wise manner within the spatial mask. Multiple comparisons were corrected using Monte Carlo simulations (AlphaSim program in AFNI software, http://afni.nimh.nih.gov/). In the brain networks showing significant group differences in functional connectivity, voxel-based partial correlation analyses controlling for age were performed to identify brain regions whose functional connectivity was correlated with clinical variables. The mean GMV of each cluster with significant group differences in the functional connectivity was calculated and compared between the two groups using a two-sample t-test.Results:1. The OSAHS specifically affected the cognitive-and sensorimotor-related brain networks, but spared the visual and auditory networks.2. The medial prefrontal cortex and left dorsolateral prefrontal cortex (DLPFC) showed decreased functional connectivity and GMV in OSAHS patients, suggesting structural and functional deficits. The right DLPFC and left precentral gyrus showed decreased functional connectivity and unchanged GMV, indicating functional deficit. The right posterior cingulate cortex demonstrated increased functional connectivity and unchanged GMV, suggesting functional compensation.3. In OSAHS patients, the functional connectivity of right DLPFC was negatively correlated with the apnea-hypopnea index.Conclusion:1. OSAHS specifically affects functional connectivity in the cognitive-and sensorimotor-related brain networks which may be related to the impaired cognitive and motor functions in these patients.2. Altered functional connectivity of right frontoparietal network reflects disease severity of OSAHS. Section II Regional homogeneity in patients with obstructive sleep apnea-hypopnea syndromeObjective:To investigate alterations in regional homogeneity (ReHo) of the brain in OSAHS patients and their correlations with disease severity of OSAHS, and their relationships with changes in grey matter volume (GMV) in the corresponding brain regions.Subjects and Methods:Twenty-four treatment-naive male patients with moderate to severe OSAHS and21healthy controls matched for age, gender, years of education and handedness were included in this study. GE3.0T MR Scanner was used to obtain resting-state fMRI data and high resolution three-dimension (3D) T1-weighted images. The fMRI data were processed with the software of REST and SPM8. Individual ReHo maps were generated by calculating KCC within a gray matter mask in a voxel-wise way by the REST software. To reduce the effect of individual variance, we normalized the ReHo value of each voxel by dividing the mean ReHo of the whole brain for each subject. Brain areas with significant changes in ReHo values between the two groups were acquired by voxel-based analysis. Multiple comparisons were corrected using Monte Carlo simulations (AlphaSim program in AFNI software, http://afni.nimh.nih.gov/). In the brain areas showing significant group differences in ReHo values, voxel-based partial correlation analyses controlling for age were performed to identify brain regions whose ReHo value was correlated with clinical variables. The mean GMV of each cluster with significant group differences in the ReHo values was calculated and compared between the two groups using a two-sample t-test.Results:1. Compared to the control subjects, the patients with OSAHS showed significantly increased ReHo values in the right cerebellar hemisphere Ⅸ, right parahippocampal gyrus, right superior temporal gyrus, right putamen, bilateral precentral and postcentral gyri, and supplement motor areas.2. Compared to the control subjects, the patients with OSAHS showed significantly decreased ReHo values in the bilateral cerebellar hemisphere Ⅸ, left inferior temporal gyrus, bilateral prefrontal lobes, bilateral precuneus, bilateral angular gyri.3. Among the brain areas with increased ReHo values, the significant correlations were found between the ReHo value of right putamen and%TST<90%or ESS scores, and between the GMV of right parahippocampal gyrus and ESS score. Among the brain areas with decreased ReHo values, the significant correlations were found between the ReHo values of bilateral angular gyri and left precuneus and%TST<90%score, and between the ReHo value of right angular gyrus and AHI, and between the ReHo values and GMV of bilateral prefrontal lobes and ESS score.Conclusion:1. OSAHS specifically demonstrates increased ReHo values in the sensorimotor-related brain areas and decreased ReHo values in the cognitive-related brain areas.2. Altered ReHo values in OSAHS patients reflect the severity of excessive daytime sleepiness and nocturnal hypoxemia.Section III Amplitude of low frequency fluctuation in patients with obstructive sleep apnea-hypopnea syndromeObjective:To investigate alterations in amplitude of low frequency fluctuation (ALFF) of the brain in OSAHS patients and their correlations with disease severity of OSAHS, and their relationships with changes in grey matter volume (GMV) in the corresponding brain regions.Subjects and Methods:Twenty-four treatment-naive male patients with moderate to severe OSAHS and21healthy controls matched for age, gender, years of education and handedness were included in this study. GE3.0T MR Scanner was used to obtain resting-state fMRI data and high resolution three-dimension (3D) T1-weighted images. The fMRI data were processed with the software of REST and SPM8. The normalized ALFF values were calculated using specific algorithms, brain areas with significant changes in ALFF values between groups were acquired by a two-sample t test. Multiple comparisons were corrected using Monte Carlo simulations (AlphaSim program in AFNI software, http://afni.nimh.nih.gov/). In the brain areas showing significant group differences in ALFF values, voxel-based partial correlation analyses controlling for age were performed to identify brain regions whose ALFF value was correlated with clinical variables. The mean GMV of each cluster with significant group differences in the ALFF values was calculated and compared between the two groups using a two-sample t-test.Results:1. Compared to the control subjects, the patients with OSAHS showed significantly increased ALFF values in the right parahippocampal gyrus, fusiform gyrus and inferior temporal gyrus, right superior temporal gyrus, right postcentral gyrus and paracentral lobule, left middle cingulate cortex and supplement motor area, right superior parietal gyrus, left postcentral gyrus.2. Compared to the control subjects, the patients with OSAHS showed significantly decreased ALFF values in the bilateral prefrontal lobes, bilateral posterior cingulate cortices and precuneus.3. Among the brain areas with decreased ALFF values, the significant correlation was found between the ALFF values of bilateral precuneus and ESS score.Conclusion:1. OSAHS specifically demonstrates increased ALFF values in the sensorimotor-related brain areas and decreased ALFF values in the cognitive-related brain areas.2. Altered ALFF values in precuneus reflect the severity of excessive daytime sleepiness in OSAHS patients. |
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