| Background and Objective: It is one of the most important methods for researching the human brain functions to combine the performances of neurology and anatomical damage. In the past decades, there have been many researchs to investigate the relationship between anatomy and advanced founction of brain and made many great progress and encouraging results. But, since the complexity structure of human brain, It had been stage exploration for researching the association between specific location of white matter and specific cognitive function. White matter hyperintensities(WMH) refers to abnormally high signal in magnetic resonance imaging T2-weighted imaging and fluid-attenuated inversion recovery(FLAIR) imaging. It is due to a variety of reason for white matter damage or degenerative changes associated with aging. It can help to reveal the basic functions of white matter and its participation in the neural network to assess on cognitive functions of specific WMH. According to the different anatomical site, WMH is divided into periventricular white matter hyperintensity, PVWMH, and deep white matter hyperintensity, DWMH. Frontal periventricular white matter hyperintensity, f PVWMH, refers to the periventricular white matter in the frontal lobe of hyperintensity often occurs in the early stages of PVWMH. Through reviewing documents, we have not yet found any research on the relationship of f PVWMH and special cognitive dysfunction. In this study, we assess neuropsychological scale on these subjects with isolated f PVWMH on MRI-FLAIR imaging. At the same time, we explore the effect on cognitive function f PVWMH nerves mechanism using diffusion magnetic resonance imaging, nerve fiber tracing and voxel-based morphometry, VBM.Methods: 1. Objects Observation group and control group were recruited from outpatient healthy population on a top three hospital. All the objects were told significance, content, purpose, and voluntary signed the consent to join the study. Observation group included 14 people with f PVWMH on MRI-FLAIR imaging, aged from 45 to 65 years old, male 8, female 6, and the level of education are more than nine years with right-handed. The control group included 14 people with normal FLAIR imaging was matched observation group with age, gender, education and handedness orientation. the selected population and the observation group were matched to eliminate factors with these maybe affect the results. Based on past history inquiry and health check for excluded psychiatric disorders, hypertension, diabetes, severe liver and kidney dysfunction, thyroid dysfunction, and traumatic brain injury and other diseases. These were excluded from the this study with a history of alcohol or other drug abuse history and claustrophobia, heart implant or pacemakers and orthopedic surgery and internal fixation surgery and other states can not complete the MRI examination. 2. neuropsychological assessment Using the mini-mental state examination(MMSE), Montreal cognitive assessment(Mo CA), trail making test A(TMT-A), center for epidemiological studies depression scale(CES-D) and directional memory(DM), associative learning(AL), graphic free recall(GFR), meaningless graphics recognition(MGR), portrait memory(PM) and other sets of neuropsychological scale assesses cognitive function. At the same time, the subjects underwent self-rating depression scale and neuropsychiatric assessment questionnaire, for exclusion recognize depression and mental disorders and other disturbances that may affect cognitive ability. 3. MRI examination [1] conventional brain MRI examination Conventional brain MRI examination includs MRI-T1, MRI-T2 scans and MRI-FLAIR. To decaded the exact location of white matter hyperintensities and to find other intracranial lesions. [2] Brain imaging MRI-DTI Single-shot spin-echo echo-planar(EPI) sequence acquisition DTI raw data. After calculation of the registration value and create whole brain fractional anisotropy(FA) color map imaging in inferior occipito-frontal fascicle(IOFF), genu of the corpus callosum(GCC), splenium of the corpus callosum(SCC), segment II of the superior longitudinal fascicle(SLFII), posterior segments of the cingulum bundle(PCB), middle segments of the cingulum bundle(MCB) and frontal white matter(f WM) etc. And then select a sets of rectangular regions of interest(ROI), ROI analysis of FA values. Nonparametric test of Mann- Whitney rank sum test to compare the observation group and the control group throughout the ROI of FA value differences. Using Spearman correlation analysis to calculate and analyze the relationship between FA value ROI and neuropsychological scores. [3] Based on brain MRI-DTI imaging bundle of nerve fibers Tracking Using multiple ROI methods to reconstruct Forceps minor(Fminor), uncinate fasciculus(UF), IFOF, anterior thalamic radiation(ATR), cingulum bundle(CB) and other nerve fibers in DTIStudio software. The observation group and the control group only one Fminor components, the individual fibers to distinguish between left and right, respectively. To recorde the number of nerve fibers of Fminor UF IFOF ATR and CB, using non-parametric tests of Mann- Whitney rank sum test. [4] voxel-based morphometry Using FFE gradient echo TFE fast imaging sequence acquisit the data of 3DT1 anatomical image on observation and control group. The 3DT1 image spatial normalization, brain tissue segmentation and gray image modulation and smoothed in SPM5 package MATLAB platform. Nonparametric test of Mann- Whitney rank sum test was used to compare brain gray matter, the white matter, and the cerebrospinal fluid between the observation group and the control group. The two-sample t-test in SPM was used for gray matter signal intensity between the two groups.Result: 1. results of neuropsychological evaluation The score of PM of the observation group is significantly lower than the control group, and the observation group score was 13.36 ± 3.39, PM score of control group was 17.29 ± 4.12, p = 0.017. There were no significant difference between the two groups on overall cognitive level, other measuring memory and TMT-A, CES-D. 2.based on brain imaging FA value analysis ROIs FA value on IFOF, GCC, SCC, SLFII, PCB, MCB of the observation group and control group were no significant difference in statistical test; FA value of f WM in the observation group decreased significantly than the control group(right: p = 0.015; left: p = 0.032). FA values were significantly associated with the right of f WM PM performance(r = 0.782, p = 0.01); 3. the nerve fiber bundles tracking results The average number of fibers of each nerve Fminor, UF, IFOF, ATR, CB in observe grounp were lower than the control group, Our study had showed that the left UF(p = 0.034), IFOF(p = 0.021), ATR(p = 0.046) and the number of nerve fibers in the right side of ATR(p = 0.011), CB(p = 0.011), IFOF(p = 0.047) were significantly different. By spearman correlation test, fibers number of bilateral ATR and left CB were positively correlated with Portrait memory score. 4. voxel-based morphometry studies of brain gray matter Gray matter between the observation group and the control group, white matter were no significant difference. Setting f PVWMH gray matter voxel intensity than the control group and test threshold p <0.05, after each comparison voxel-based, results without exceeding the threshold voxel. Similarly, there is no voxel which exceeding the threshold when setting f PVWMH gray matter voxel lower than the control group by comparing each voxel. which suggest that there were no significant difference between the brain’s gray matter of the two groups.Conclusion: This results had shown that PM of f PVWMH was significantly impaired, which may be due to the frontal white matter microstructural damage, especially bilateral ATR, resulting in the amount of connections, top, temporal, and occipital nerve portrait memory related network structure damage, resulting in the network depends on the structural and functional integrity of the portrait memory. |
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