本文選題：腦網(wǎng)絡(luò)　切入點(diǎn)：功能磁共振　出處：《天津醫(yī)科大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：目的： 采用獨(dú)立成分分析(independent component analysis, ICA)法,探索靜息態(tài)下運(yùn)動(dòng)功能恢復(fù)良好的慢性期皮層下腦梗死患者網(wǎng)絡(luò)內(nèi)和網(wǎng)絡(luò)間功能連接(functional connectivity, FC)改變。 材料與方法： 選擇運(yùn)動(dòng)功能恢復(fù)良好的慢性期單發(fā)腦梗死患者25例(7女,18男),病灶位于內(nèi)囊及其鄰近區(qū)域。另外,選擇22名(11女,11男)年齡相匹配的健康志愿者為對(duì)照組。采用GE Signa HD-X3.0T磁共振掃描儀進(jìn)行3D高分辨率T1WI解剖像和靜息態(tài)fMRI掃描。 1.采用基于Matlab的SPM8和DPARSF對(duì)靜息態(tài)fMRI數(shù)據(jù)進(jìn)行預(yù)處理,其過程包括：時(shí)間校正、頭動(dòng)校正、空間標(biāo)準(zhǔn)化、重采樣至3×3×3mm3的立方體素及空間平滑(6×6×6mm3)。 2.采用組ICA功能磁共振工具包來提取靜息態(tài)腦網(wǎng)絡(luò)(resting-state network, RSNs),得到11個(gè)RSNs�？刂颇挲g、性別后比較患者組與正常對(duì)照組之間每個(gè)RSN功能連接強(qiáng)度的差異。提取出網(wǎng)絡(luò)內(nèi)功能連接有顯著性差異的腦區(qū)作為感興趣區(qū)(region of interest, ROI),然后運(yùn)用一般線性模型(將年齡與性別作為協(xié)變量)進(jìn)行組間比較。同時(shí)運(yùn)用Monte Carlo模擬進(jìn)行多重比較校正。 3.對(duì)于網(wǎng)絡(luò)間功能連接的分析,其預(yù)處理過程在ICA預(yù)處理基礎(chǔ)上進(jìn)一步處理,包括濾波和去除協(xié)變量。首先,計(jì)算每一對(duì)RSNs個(gè)體平均時(shí)間序列的Pearson相關(guān)系數(shù),然后進(jìn)行Fisher's Z專換。最后將所有受試者的年齡、性別作為協(xié)變量,對(duì)具有統(tǒng)計(jì)學(xué)意義的網(wǎng)絡(luò)間功能連接進(jìn)行組間比較。 4.將患者組網(wǎng)絡(luò)內(nèi)和網(wǎng)絡(luò)間功能連接值分別與病灶體積大小做偏相關(guān),被試的年齡、性別為協(xié)變量,統(tǒng)計(jì)閾值為P0.05。 5.未翻轉(zhuǎn)數(shù)據(jù)組與翻轉(zhuǎn)數(shù)據(jù)組預(yù)處理及統(tǒng)計(jì)分析過程一樣,兩次ICA運(yùn)算得到兩套R(shí)SNs。 結(jié)果： 1.11個(gè)RSNs包括：腹側(cè)感覺運(yùn)動(dòng)網(wǎng)絡(luò)(vSMN)、背側(cè)感覺運(yùn)動(dòng)網(wǎng)絡(luò)(dSMN)、枕極視覺網(wǎng)絡(luò)(pVN)、內(nèi)側(cè)視覺網(wǎng)絡(luò)(mVN)、外側(cè)視覺網(wǎng)絡(luò)(1VN)、聽覺網(wǎng)絡(luò)(AN)、背側(cè)注意網(wǎng)絡(luò)(DAN)、前默認(rèn)網(wǎng)絡(luò)(aDMN)、后默認(rèn)網(wǎng)絡(luò)(pDMN)、左額頂網(wǎng)絡(luò)(1FPN)和右額頂網(wǎng)絡(luò)(rFPN)。 2.與正常對(duì)照組比較,腦梗死患者的感覺運(yùn)動(dòng)網(wǎng)絡(luò)、視覺網(wǎng)絡(luò)、聽覺網(wǎng)絡(luò)、背側(cè)注意網(wǎng)絡(luò)和默認(rèn)網(wǎng)絡(luò)功能連接增加。而且,還發(fā)現(xiàn)了患者功能連接減低的網(wǎng)絡(luò),包括額頂網(wǎng)絡(luò)和前默認(rèn)網(wǎng)絡(luò)。 3.腦梗死患者在VN-AN之間和VN-SMN之間從正常對(duì)照組的無功能連接轉(zhuǎn)變?yōu)轱@著的負(fù)功能連接。而且與正常對(duì)照組比較,腦梗死患者在pDMN-rFPN之間和aDMN-pDMN之間呈正功能連接減低的改變,在AN-rFPN之間、pDMN-dSMN之間呈負(fù)功能連接減低的改變。 4.偏相關(guān)分析結(jié)果顯示,病灶體積與腦梗死患者網(wǎng)絡(luò)內(nèi)、網(wǎng)絡(luò)間功能連接值之間均沒有顯著性相關(guān)(P0.05),表明病灶大小對(duì)本研究結(jié)果沒有顯著影響。 結(jié)論： 1.慢性期皮層下腦梗死患者存在多個(gè)腦功能網(wǎng)絡(luò)的改變,而且功能網(wǎng)絡(luò)重組與損傷共存； 2.慢性期皮層下腦梗死患者不僅網(wǎng)絡(luò)內(nèi)功能連接發(fā)生改變,網(wǎng)絡(luò)間功能連接也發(fā)生一定的改變； 3.從大尺度腦網(wǎng)絡(luò)的角度分析患者腦功能的改變,增加對(duì)皮層下腦梗死患者復(fù)雜臨床癥狀的理解。
[Abstract]:Objective:
Independent component analysis (ICA) was used to explore the changes of functional connectivity (functional connectivity, FC) in patients with chronic subcortical cerebral infarction who had good motor function recovery in resting state.
Materials and methods:
Select the recovery of motor function in chronic period good single cerebral infarction 25 cases (7 female, 18 male), was located in the internal capsule and its adjacent areas. In addition, 22 patients (11 female, 11 male) and age-matched healthy volunteers as control group. Using GE Signa HD-X3.0T magnetic resonance scanner for high resolution 3D T1WI anatomy as a resting state fMRI scan.
1., we use Matlab based SPM8 and DPARSF to preprocess resting state fMRI data. The process includes: time correction, head correction, spatial standardization, resample to cube 3 and 3 x 3mm3, and spatial smoothing (6 * 6 * 6mm3).
The 2. group ICA with functional magnetic resonance imaging kit to extract restingstate networks (resting-state network, RSNs), 11 RSNs. after controlling for age, gender differences in each function were compared between RSN group and normal control group. The connection strength of the extracted network functional connectivity in brain regions has a significant difference of interest area (region of interest, ROI), and then using the general linear model (the age and gender as a covariate) were compared between the two groups. At the same time using the Monte Carlo simulation of correction for multiple comparisons.
3. for network functional connectivity analysis, the pretreatment process for further processing based on ICA pre processing, including filtering and removal of covariates. Firstly, the Pearson correlation coefficient to calculate the average time series of each individual RSNs, then Fisher's Z designed for. In the end, all the subjects were age, gender as co the statistically significant variables, the network connection between functional group were compared.
4. in the patient group, the value of the function connection between the network and the network is partial to the size of the lesion, the age of the subjects, the gender as the covariate, the statistical threshold is P0.05.
The 5. unflipped data group is the same as the preprocessing and statistical analysis of the overturned data group, and the two ICA operation gets two sets of RSNs.
Result錛，

本文編號(hào)：1617489