阻塞性睡眠呼吸暫停低通氣綜合征的靜息態(tài)腦功能磁共振成像研究
[Abstract]:Part one resting state brain network study of obstructive sleep apnea hypopnea syndrome
Objective:
The resting state functional magnetic resonance imaging (resting-state functional magnetic resonance imaging, rs-fMRI) technique was used to obtain the rest of the obstructive sleep apnea hypopnea syndrome (obstructive sleep) (obstructive sleep) patients and the normal control group by the independent component analysis (independent component analysis, ICA). The state brain network studies the differences in the resting state brain network function connection between OSAHS patients and normal people and their relationship with the severity of OSAHS, and analyzes the structural basis of the functional connectivity differences between the two groups based on the voxel morphology (voxel-based morphometry, VBM), thus clarifying the brain network mechanism of cognitive and motor dysfunction in OSAHS patients.
Materials and methods:
24 cases of OSAHS patients, aged 31-59 years old, with an average of 44.6 + 7.4 years of age, were selected to conform to the standard of entry, 21 healthy volunteers, 30-60 years old and 40.6 + 11.4 years old. OSAHS patients and normal control groups were male, right hand, and age of two groups without statistical difference (P0.05), body mass index of OSAHS patients and apnea low The ventilation index (apnea-hypopnea index, AHI), (?) the proportion of oxygen saturation less than 90% (%TST90%), Epworth lethargy score (Epworth sleepiness score, ESS) were significantly higher than that of the normal control group (P0.001), but the MMSE score of OSAHS patients was lower than that of the normal control group. SPM8 and MICA software based on Matlab platform are used for preprocessing, independent component analysis and statistics. Preprocessing includes time correction, head motion correction, spatial standardization, spatial smoothing, de linear drift, low frequency filtering and removal of covariance. Three steps principal component analysis is used to decompose functional data into 30 components and be rebuilt into functional connections. Figure, the number of ICA operations is 100. according to visual observation, select seven components consistent with the common resting brain network reported in the literature. Statistical analysis uses a single sample t test to get the template of each component. On the basis of this template, two samples of t test are used to compare the differences in the functional connection of the brain network between the OSAHS patients and the normal control group. AphaSim correction was used. In order to analyze the effect of OSAHS severity on functional connectivity of the brain network, the correlation between OSAHS patients' AHI,%TST90%, ESS score and the functional connection of different brain regions was analyzed with age as the control variable. In order to clarify the structural basis of the functional connection changes of the OSAHS brain network, the functional connection between the two groups was poor. Different regions of interest (ROI) were used to compare the differences of grey matter volume (GMV) of ROI between the two groups by SPSS.
Result:
1. Except for visual and auditory networks, resting brain networks were significantly different between OSAHS patients and normal volunteers.
2. the functional connection and gray matter volume of the medial prefrontal lobes and the left dorsolateral prefrontal lobes decreased, indicating the functional and structural damage. The functional connection of the right dorsolateral prefrontal lobe and the left precentral gyrus was reduced and the volume of gray matter was normal, suggesting the function damage; the functional connection of the right posterior cingulate band was normal and the volume of gray matter was normal. Functional compensatory function;
3. there was a significant negative correlation between AHI and right frontal frontal network in OSAHS patients.
Conclusion:
1. the functional and structural changes of resting brain networks reflect memory, executive, attention and motor deficits in OSAHS patients.
2. the functional connectivity changes on the right front-end network can reflect the severity of OSAHS patients.
The second part of the whole brain regional coherence study of obstructive sleep apnea hypopnea syndrome
Objective:
Based on rs-fMRI data, using the local consistency (regional homogeneity, ReHo) algorithm to investigate the synchronization of low frequency oscillations in local brain region (ReHo), the relationship between ReHo and GMV changes in the whole brain of OSAHS patients and healthy volunteers was studied.
Materials and methods:
24 patients with OSAHS, 21 healthy volunteers, and 21 healthy volunteers, rs-fMRI examination by GE3.0T magnetic resonance scanner, pre processing and statistical analysis using SPM8 and REST software based on Matlab platform. The preprocessing includes time correction, head motion correction, spatial standardization, spatial smoothing, de linear drift, low-frequency filtering and removal. Covariant quantity. The pre processed data is calculated by REST software for each voxel's ReHo value, and each person's ReHo diagram is obtained by a voxel analysis. In order to eliminate the influence of individual differences, we calculate the standardized ReHo values and obtain the brain regions with significant differences in ReHo values between the two groups by the voxel based analysis. Multiple comparison uses AphaSim Correction. In order to clarify the structural basis of the changes in the ReHo value of the whole brain of OSAHS patients, the ReHo value difference between the two groups was taken as ROI, and the GMV difference between the two groups was compared with the SPSS two sample t test. The correlation between the score and the difference of ReHo and GMV in the brain region.
Result:
1. the elevation of ReHo value in 1. OSAHS patients included right cerebellar hemisphere, parahippocampal gyrus, upper temporal gyrus, putamen, bilateral central anterior gyrus, posterior central gyrus and auxiliary motor area, which were mainly located in the related brain regions of sensory movement, suggesting the compensatory brain function of OSAHS patients.
2. OSAHS patients with decreased ReHo value included left temporal gyrus, bilateral cerebellar hemisphere, prefrontal lobe, prefrontal lobe, and angular gyrus, mainly in cognitive related brain regions, suggesting cognitive impairment in OSAHS patients.
3. in the ReHo elevation of the DSAHS patients, the ReHo value of the right putamen was significantly positively correlated with the patient's%TST90% and ESS, and the right parahippocampal gyrus GMV was negatively correlated with the patient's ESS, and the bilateral angular gyrus ReHo value was negatively correlated with the patient's%TST90% in the ReHo reduced brain area of OSAHS patients. The left anterior lobe ReHo value was significantly negative to the patient. ReHo and GMV in medial prefrontal lobe were negatively correlated with ESS, suggesting that functional and structural changes in the above brain regions could reflect the severity of OSAHS.
Conclusion:
There was a significant difference in the ReHo value of the whole brain between 1. OSAHS patients and the normal control group. The increase of the ReHo value in the patients was mainly located in the motor related brain region, and the decrease of the ReHo value was mainly in the cognitive related brain area.
2. the change of ReHo in OSAHS patients was significantly correlated with daytime sleepiness and nocturnal hypoxia.
The third part of the whole brain low frequency amplitude study of obstructive sleep apnea hypopnea syndrome
Objective:
Based on rs-fMRI data, the amplitude of low frequency fluctuations (ALFF) algorithm was used to study the low frequency amplitude (ALFF) of spontaneous neuron activity in resting state (ALFF). The relationship between the whole brain ALFF difference and the GMV changes in OSAHS patients and healthy volunteers was studied.
Materials and methods:
24 OSAHS patients and 21 healthy volunteers were selected in accordance with the standard of the group. The GE3.0T magnetic resonance scanner was used for resting state fMRI examination. The SPM8 and REST software based on the Matlab platform were used for preprocessing and statistical analysis. The preprocessing includes time correction, head motion correction, space standardization, spatial smoothing, de linear drift, low-frequency filtering, and The ALFF value of each voxel is calculated by REST software and the ALFF diagram of each person is obtained by the analysis of the voxel. In order to eliminate the influence of individual differences, we calculate the standardized ALFF values and obtain the brain regions with significant differences in ALFF values between the two groups by the analysis of voxels, and the multiple comparison uses Ap. HaSim correction. In order to clarify the structural basis of the changes in the ALFF value of the whole brain of OSAHS patients, the difference of the brain region between the two groups was taken as ROI, and the GMV difference between the two groups was compared with the SPSS two sample t- test. In order to analyze the effect of OSAHS severity on the ALFF changes in the whole brain, the age was used as the controlled variable, and the partial correlation analysis was used. 0%, the correlation between ESS score and ALFF value and GMV in different brain regions.
Result:
1. the elevation of ALFF value in 1. OSAHS patients included right parahippocampal gyrus, fusiform gyrus and inferior temporal gyrus, upper temporal gyrus, upper parietal gyrus, right central posterior gyrus, left paracentral lobule, cingulate belt and auxiliary motor area, central posterior gyrus, mainly located in the related brain area of sensory movement, suggesting the compensatory mechanism of brain function in OSAHS patients.
2. The decreased ALFF values in OSAHS patients include bilateral prefrontal lobes, posterior cingulate and anterior cuneate lobes, mainly located in the cognitive-related brain regions, representing cognitive impairment in OSAHS patients.
3. The ALFF value of bilateral anterior wedge lobe in OSAHS patients was negatively correlated with ESS score, suggesting that the impairment of anterior wedge lobe function was related to daytime sleepiness.
Conclusion:
There was a significant difference in the ALFF value of the whole brain between 1. OSAHS patients and the normal control group. The increase of the ALFF value in the patients was mainly located in the sensory motor related brain region, and the decrease of the ALFF value was mainly located in the cognitive related brain area.
2. the daytime sleepiness of OSAHS patients was significantly correlated with the change of ALFF value in bilateral anterior wedge.
【學(xué)位授予單位】:天津醫(yī)科大學(xué)
【學(xué)位級(jí)別】:博士
【學(xué)位授予年份】:2012
【分類號(hào)】:R766;R445.2
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