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
發(fā)布時間：2018-08-05 15:05
【摘要】：第一部分阻塞性睡眠呼吸暫停低通氣綜合征的靜息態(tài)腦網(wǎng)絡(luò)研究 目的： 運用靜息態(tài)功能磁共振成像(resting-state functional magnetic resonance imaging, rs-fMRI)技術(shù),采用獨立成分分析(independent component analysis,ICA)獲取阻塞性睡眠呼吸暫停低通氣綜合征(obstructive sleep apnea-hypopnea syndrome, OSAHS)患者和正常對照組的靜息態(tài)腦網(wǎng)絡(luò),研究OSAHS患者與正常人的靜息態(tài)腦網(wǎng)絡(luò)功能連接差異及其與OSAHS嚴重程度的關(guān)系,并運用基于體素形態(tài)學(voxel-based morphometry, VBM)分析兩組之間功能連接差異的結(jié)構(gòu)基礎(chǔ),從而闡明OSAHS患者認知及運動功能障礙的腦網(wǎng)絡(luò)機制。 材料與方法： 選擇符合入組標準的OSAHS患者24例,年齡：31-59歲,平均44.6±7.4歲；健康志愿者21例,年齡：30-60歲,平均40.6±11.4歲；OSAHS患者與正常對照組均為男性、右利手,且兩組之間年齡、教育年限無統(tǒng)計學差異(P0.05),OSAHS患者的體重指數(shù)、呼吸暫停低通氣指數(shù)(apnea-hypopnea index, AHI)、(?)氧飽和度低于90%的睡眠時間比例(%TST90%)、Epworth嗜睡評分(Epworth sleepiness score, ESS)均顯著高于正常對照組(P0.001),但是OSAHS患者MMSE評分低于正常對照組(P0.01)。采用GE3.0T磁共振掃描儀對所有受試者行rs-fMRI掃描。應(yīng)用基于Matlab平臺的SPM8及MICA軟件進行預(yù)處理、獨立成分分析和統(tǒng)計。預(yù)處理包括時間校正、頭動校正、空間標準化、空間平滑、去線性漂移、低頻濾波和去除協(xié)變量。運用三步主成分分析將功能數(shù)據(jù)分解為30個成分并重建為功能連接圖,ICA運算次數(shù)為100。根據(jù)視覺觀察,選擇與文獻報道的常見靜息態(tài)腦網(wǎng)絡(luò)一致的七個成分。統(tǒng)計分析采用單樣本t檢驗,分別得到每個成分的模板,在此模板基礎(chǔ)上采用兩樣本t檢驗比較OSAHS患者與正常對照組的腦網(wǎng)絡(luò)功能連接差異,多重比較采用AphaSim校正。為了分析OSAHS嚴重程度對腦網(wǎng)絡(luò)功能連接的影響,以年齡為控制變量,采用偏相關(guān)分析OSAHS患者AHI、%TST90%、ESS評分與差異腦區(qū)功能連接的相關(guān)性。為了闡明OSAHS腦網(wǎng)絡(luò)功能連接改變的結(jié)構(gòu)基礎(chǔ),以兩組之間功能連接差異區(qū)域作為感興趣區(qū)(region of interest, ROI),采用SPSS兩樣本檢驗比較兩組之間ROI的灰質(zhì)體積(grey matter volume, GMV)差異。 結(jié)果： 1.除視覺網(wǎng)絡(luò)和聽覺網(wǎng)絡(luò)以外,其他靜息態(tài)腦網(wǎng)絡(luò)在OSAHS患者和正常志愿者之間均存在顯著差異； 2. OSAHS患者的內(nèi)側(cè)前額葉和左側(cè)背外側(cè)前額葉的功能連接及灰質(zhì)體積均減小,提示功能和結(jié)構(gòu)損害；右側(cè)背外側(cè)前額葉和左側(cè)中央前回的功能連接減低而灰質(zhì)體積正常,提示功能損害；右側(cè)后扣帶的功能連接增強而灰質(zhì)體積正常,提示功能代償； 3. OSAHS患者AHI與右側(cè)額頂網(wǎng)絡(luò)的背外側(cè)前額葉功能連接存在顯著負相關(guān)。 結(jié)論： 1.靜息態(tài)腦網(wǎng)絡(luò)的功能與結(jié)構(gòu)改變反映了OSAHS患者的記憶、執(zhí)行、注意及運動功能缺陷。 2.右側(cè)額頂網(wǎng)絡(luò)功能連接改變能夠反映OSAHS患者的病情嚴重程度。 第二部分阻塞性睡眠呼吸暫停低通氣綜合征的全腦局部一致性研究 目的： 基于rs-fMRI數(shù)據(jù),利用考察局部腦區(qū)低頻振蕩信號同步性的局部一致性(regional homogeneity, ReHo)算法,研究OSAHS患者與健康志愿者的全腦ReHo值差異以及同GMV改變之間的關(guān)系。 材料與方法： 選擇符合入組標準的OSAHS患者24例、健康志愿者21例,采用GE3.0T磁共振掃描儀進行rs-fMRI檢查,應(yīng)用基于Matlab平臺的SPM8及REST軟件進行預(yù)處理和統(tǒng)計分析。預(yù)處理包括時間校正、頭動校正、空間標準化、空間平滑、去線性漂移、低頻濾波和去除協(xié)變量。預(yù)處理后數(shù)據(jù)用REST軟件計算每個體素的ReHo值,通過逐個體素的分析得到每個人的ReHo圖。為了消除個體差異的影響,我們計算出標準化的ReHo值,通過基于體素的分析,獲得兩組之間ReHo值存在顯著差異的腦區(qū),多重比較采用AphaSim校正。為了闡明OSAHS患者全腦ReHo值改變的結(jié)構(gòu)基礎(chǔ),將兩組之間ReHo值差異腦區(qū)作為ROI,采用SPSS兩樣本t檢驗比較兩組之間ROI的GMV差異。為了分析OSAHS嚴重程度對全腦ReHo改變的影響,以年齡為控制變量,采用偏相關(guān)分析OSAHS患者AHI、%TST90%、ESS評分與差異腦區(qū)ReHo值及GMV的相關(guān)性。 結(jié)果： 1. OSAHS患者ReHo值升高區(qū)域包括右側(cè)小腦半球、海馬旁回、顳上回、殼核、雙側(cè)中央前回、中央后回及輔助運動區(qū),主要位于感覺運動相關(guān)腦區(qū),提示OSAHS患者的腦功能代償； 2. OSAHS患者ReHo值減低區(qū)域包括左側(cè)顳下回、雙側(cè)小腦半球、前額葉、楔前葉及角回,主要位于認知相關(guān)腦區(qū),提示OSAHS患者的認知功能損害； 3.在DSAHS患者ReHo升高腦區(qū)中,右側(cè)殼核ReHo值與患者的%TST90%、ESS呈顯著正相關(guān),右側(cè)海馬旁回GMV與患者的ESS呈顯著負相關(guān)；在OSAHS患者ReHo減低腦區(qū)中,雙側(cè)角回ReHo值與患者的%TST90%呈顯著負相關(guān),左側(cè)楔前葉ReHo值與患者的%TST90%呈顯著負相關(guān),內(nèi)側(cè)前額葉ReHo值、GMV均與患者的ESS呈顯著負相關(guān),提示以上腦區(qū)的功能和結(jié)構(gòu)改變能夠反映OSAHS嚴重程度。 結(jié)論： 1. OSAHS患者與正常對照組的全腦ReHo值存在顯著性差異,其中患者ReHo值升高主要位于運動感覺相關(guān)腦區(qū),ReHo值減低主要位于認知相關(guān)腦區(qū)； 2. OSAHS患者ReHo值改變與日間嗜睡及夜間缺氧程度具有顯著相關(guān)性。 第三部分阻塞性睡眠呼吸暫停低通氣綜合征的全腦低頻振幅研究 目的： 基于rs-fMRI數(shù)據(jù),利用考察靜息狀態(tài)下腦自發(fā)性神經(jīng)元活動的低頻振幅(amplitude of low frequency fluctuations, ALFF)算法,研究OSAHS患者與健康志愿者的全腦ALFF值差異以及同GMV改變之間的關(guān)系。 材料與方法： 選擇符合入組標準的OSAHS患者24例、健康志愿者21例,采用GE3.0T磁共振掃描儀進行靜息態(tài)fMRI檢查,應(yīng)用基于Matlab平臺的SPM8及REST軟件進行預(yù)處理和統(tǒng)計分析。預(yù)處理包括時間校正、頭動校正、空間標準化、空間平滑、去線性漂移、低頻濾波和去除協(xié)變量。預(yù)處理后數(shù)據(jù)用REST軟件計算每個體素的ALFF值,通過逐個體素的分析得到每個人的ALFF圖。為了消除個體差異的影響,我們計算出標準化的ALFF值,通過基于體素的分析,獲得兩組之間ALFF值存在顯著差異的腦區(qū),多重比較采用AphaSim校正。為了闡明OSAHS患者全腦ALFF值改變的結(jié)構(gòu)基礎(chǔ),將兩組之間ALFF值差異腦區(qū)作為ROI,采用SPSS兩樣本t-檢驗比較兩組之間ROI的GMV差異。為了分析OSAHS嚴重程度對全腦ALFF改變的影響,以年齡為控制變量,采用偏相關(guān)分析OSAHS患者AHI、%TST90%、ESS評分與差異腦區(qū)ALFF值及GMV的相關(guān)性。 結(jié)果： 1. OSAHS患者ALFF值升高區(qū)域包括右側(cè)海馬旁回、梭狀回及顳下回,顳上回、頂上回、右側(cè)中央前后回、左側(cè)中央旁小葉、中扣帶和輔助運動區(qū)、中央后回,主要位于感覺運動相關(guān)腦區(qū),提示OSAHS患者的腦功能代償機制； 2. OSAHS患者ALFF值減低區(qū)域包括雙側(cè)前額葉、后扣帶及楔前葉,主要位于認知相關(guān)腦區(qū),代表OSAHS患者的認知功能損害； 3. OSAHS患者雙側(cè)楔前葉ALFF值與ESS評分呈負相關(guān),提示患者楔前葉功能損害與日間嗜睡程度有關(guān)。 結(jié)論： 1. OSAHS患者與正常對照組的全腦ALFF值存在顯著性差異,其中患者ALFF值升高主要位于感覺運動相關(guān)腦區(qū),ALFF值減低主要位于認知相關(guān)腦區(qū)； 2. OSAHS患者日間嗜睡與雙側(cè)楔前葉ALFF值改變具有顯著相關(guān)性。
[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.
【學位授予單位】：天津醫(yī)科大學
【學位級別】：博士
【學位授予年份】：2012
【分類號】：R766;R445.2
本文編號：2166159
[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.
【學位授予單位】：天津醫(yī)科大學
【學位級別】：博士
【學位授予年份】：2012
【分類號】：R766;R445.2
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