Structural MRI Research In Patients With Type 2 Diabetes Mellitus

Part One:The Microstructure Characteristics of Patients with Type 2 Diabetes Mellitus:a DTI-TBSS StudyObjective:To noninvasively investigate white matter (WM) microstructural dynamic changes by using diffusion tensor imaging (DTI) and tract based spatial statistic (TBSS) in type 2 diabetes mellitus(T2DM) patients. Also observe the relationship between levels of Hemoglobin A1c(HbA1C) and the parameters of DTI respectively. Materials and methods:96 subjects from outpatient and inpatient of Nanfang Hospital were recruited, with 48 T2DM patients and 48 healthy persons.Before MR scans, all subjects had completed the neuropsychological, electrocardiogram(ECG), chest X-ray, blood pressure and blood biochemical examinations, the latter one included Fasting Blood-glucose (FDG), Hemoglobin A1c(HbA1c), Total Cholesterol(TC), Triglyceride(TG), High Density Lipoprotein(HDL), Low Density Lipoprotein(LDL), and we also obtained a detailed medical histoiy and demographic data. The diagnosis of all the T2DM patients met the 2010 American Diabetes Association(ADA) diagnostic criteria and classification standards, including 1. HbA1c≥6.5%; 2. FDG≥7.0mmol/L(126mg/dL); 3. OGTT test 2h postprandial blood glucos≥1.1 mmol/L (200mg/dL); 4. Symptoms of hyperglycemia or hyperglycemic crises and random blood glucos≥11.1mmol/L (200mg/dL), without symptoms of hyperglycemia, the standard should be reviewed of 1 to 3 items. All T2DM patients should be with MRI examinations, and without clinical cognitive dysfiinction, patients who had other endocrinic diseases, psychic diseases, physical signs of impairment of cognitive function, severe liver, kidney disease, coronary heart disease, ahistory of TIA attack in past two years, smokingaddiction, alcoholism and other psychotropic substance abusers should be excluded. Moreover, T2DM patients should be without impaired glucose tolerance or impaired fasting glucose, acute metabolic complications of diabetes, severe hypoglycemia, ketoacidosis history and without hypertension and hyperlipemia. Last but not least, there should be no specific abnormalities of conventional MR scans in T2DM patients, any changes found in the white matter on T2-weighted fluid attenuated inversion recovery(FLAIR) and T2WI, ARWMC Wahlund (1) scoring rules was used. About the normal control group:Normal mental development, age, gender, education level was matched to healthy people, no history of diabetes and other potential systemic diseases which would affect the central nervous system, no hypertension and hyperlipidemia, no history of dependence on tobacco, alcohol and drugs, no clear neurological and psychiatric history that impacted cognitive function, no positive findings of routine brain MR scans, no clear positive signs of neurological examination. All subjects were informed prior of the contents related to this research project, and signed informed consent.All MR imaging data were acquired using a 3.0 T GE clinical scanner (SIGNA EXCITE GE Medical Systems, Milwaukee, WI, USA) with an eight-channel head coil. Before DTI scans, the routine MRI brain protocol including axial T1-weighted images, T2-weighted images, and FLAIR was obtained for every subject to detect intracranial lesions. DTI scans were performed employing a single-shot echo-planar imaging (SS-EPI) sequence and arrayed spatial sensitivity encoding technique with the following parameters:25 non-collinear difiusion gradient directions with a b-value of 1000 sec/mm2, flip angle(FA)=90°, NEX=1, repetition time (TR)=12000ms, echo time(TE)=75.5ms, field of view (FOV)=24*24cm, matrixsize=128*128, slice thickness=3mm, no slice gap. The scan time was 5 minutes and 36 seconds.DTI data was analyzed by using FSL (FMRIB Software Library, www.firirib.ox.ac.uk/fsl, version 4.19) tools. Before that, we should change the form of all the original data from DICOM to NIFTI as preprocessing. The procedure of DTI data processing included:First, correction for head movement and eddy current distortion by using FDT tool of the FSL software. Second, mask image for each brain was created by using each subject’s BO image with BET tool of the FSL software. Third, the diffusion tensor was calculated on a voxel-by-voxel basis by using dtifit, including fractional anisotropy (FA), mean dififusivity (MD) and axial diffusivity(AD). Last, DTI match with high resolution MRI, and follow the tract based spatial statistic (TBSS) processes, then threshold-free cluster enhancement (TFCE) in randomise was used to perform the multisubject analysis of FA, MD and AD respectively, P value less than 0.05 was considered as significant correlation.Statistical analysis was performed using SPSS version 20.0 software. All data were subjected to 1-Sample Kolmogorov-Smirnov and Levene test for normality and homogeneity of variance. When our data met normal distribution and homogeneity of variance, we used parametric test, when didn’t, nonparametric test would be used. A Independent-Sample T Test was used to compare the age, blood pressure and body mass index (BMI) between the T2DM group and the healthy control group. A chi-square test was used to compare gender between the two groups. Spearmen correlation analysis was used to examine the correlation between HbA1c levels and the DTI data. ResultThe FA values of vermis cerebella, corpus callosum, bilateral thalami, right frontal lobe, bilateral cingule gyri and parietal lobes in T2DM patients had significantly decreased comparing with the controls. The MD values of bilateral thalami and right temporal lobe had significantly increased.Moreover the AD values of bilateral thalami and left cingule gyri also had significantly increased. The areas of the damaged white matter was simulate with Ads’. There was no correlation between HbA1c levels and the DTI data, but the curve showed that the higher HbA1c levels, the trend of the damage of the white matter would be more significant. ConclusionsCompared with the ROI analysis, TBSS coulde find more abnormal brain areas, and the position will be shown more accurate. The areaslevels of HbA1c had the negative correlation of the degree of damage of the fibers. Moreover, hippocampus, temporal lobes, frontal lobes, gyri callosus and the corpus callosum were influenced the worst, affecting the memory and mood. Though there was no correlation between HbA1c levels and the DTI data, there still was seen a trend that the higher HbA1c levels, the more significant damaging about the white matter in T2DM patients.Part two:To Explore the Cortex Thickness Abnormalities in Patients with Type 2 Diabetes MellitusObjective:To explore the cortex thickness abnormalities in type 2 diabetes mellitus by using high resolution MRI and DARTEL-VBM. Also observe the relationship between levels of Hemoglobin A1C (HbA1c) and cortex thickness by making correlation curve.Materials and methods:96 subjects from outpatient and inpatient of Nanfang Hospital were recruited, with 48 T2DM patients and 48 healthy persons. Before MR scans, all subjects had completed the neuropsychological, electrocardiogram(ECG), chest X-ray, blood pressure and blood biochemical examinations, the latter one included Fasting Blood-glucose (FDG), Hemoglobin A1c (HbA1c), Total Cholesterol(TC), Triglyceride(TG), High Density Lipoprotein(HDL), Low Density Lipoprotein(LDL), and we also obtained a detailed medical histoiy and demographic data. The diagnosis of all the T2DM patients met the 2010 American Diabetes Association(ADA) diagnostic criteria and classification standards, including 1. HbA1c≥6.5%; 2. FDG≥7.0mmol/L (126mg/dL); 3. OGTT test 2h postprandial blood glucos≥1.1 mmol/L (200mg/dL); 4. Symptoms of hyperglycemia or hyperglycemic crises and random blood glucos≥11.1mmol/L (200mg/dL), without symptoms of hyperglycemia, the standard should be reviewed of 1 to 3 items. All T2DM patients should be with MRI examinations, and without clinical cognitive dysfiinction, patients who had other endocrinic diseases, psychic diseases, physical signs of impairment of cognitive function, severe liver, kidney disease, coronary heart disease, a history of TIA attack in past two years, smokingaddiction, alcoholism and other psychotropic substance abusers should be excluded. Moreover, T2DM patients should be without impaired glucose tolerance or impaired fasting glucose, acute metabolic complications of diabetes, severe hypoglycemia, ketoacidosis history and without hypertension and hyperlipemia. Last but not least, there should be no specific abnormalities of conventional MR scans in T2DM patients, any changes found in the white matter on T2-weighted fluid attenuated inversion recovery(FLAIR) and T2WI, ARWMC Wahlund (1) scoring rules was used. About the normal control group:Normal mental development, age, gender, education level was matched to healthy people, no history of diabetes and other potential systemic diseases which would affect the central nervous system, no hypertension and hyperlipidemia, no history of dependence on tobacco, alcohol and drugs, no clear neurological and psychiatric history that impacted cognitive function, no positive findings of routine brain MR scans, no clear positive signs of neurological examination. All subjects were informed prior of the contents related to this research project, and signed informed consent.All MR imaging data were acquired using a 3.0 T GE clinical scanner (SIGNA EXCITE GE Medical Systems, Milwaukee, WI, USA) with an eight-channel head coil, obtaining 3D-T1 images.3D-T1 imaging was performed using a three-dimensional fast field echo (FFE) pulse sequence, parallel to the AC-PC line, with the following imaging parameters:TR=6.9 ms, TE=1.5 ms, field of view=240*240mm2, matrix=256*256, slice thickness=1 mm, slice gap=0 mm, NEX=1,the scan time was 4 minutes and 30 seconds.The processing of the images was used DARTEL-VBM tool. The DARTEL tool, a extention tool of SPM, was used to perform anatomical images analysis, the main procedures include:1. The original images of all the subjects were segmented; 2.O btain the *seg.sn.mat profile, which was then imported to DARTEL for calculateing and getting gray matter(GM) image for each participant; 3.Create GM template using DARTEL; 4.Use the GM template to normalize each participant’s GM with; 5.Modulate the resulting GM images with a Jacobian determinant, then the voxel’s values indicate the absolute volume of the local GM; 6. Use a 12-mm full width at half maximum (FWHM) isotropic Gaussian kernel to smooth resulting images; 7. The GM was transformed to the MNI coordinate for SPM analysis. And then these preprocessed GM data was analysised by using SPM8 through GLM and random field theory. The differences between two group was determined by a voxel based comparison, a cluster-level threshold of p<0.05 were set to produce statistical maps, which was corrected for multiple comparisons using false discovery rate (FDR). P value less than 0.05 was considered as significant correlation. Pearson correlation analysis was used to examine the correlation between HbA1c levels and the thickness of the cortex. The statistical analysis was performed using SPSS version 20.0 software.ResultThe averaged cortex of T2DM patients were thicker than the controls, but they were no statistical differences. We found T2DM patients would show thicker cortex earlier after dividing the subjects into 3 groups by decades(as the population under 40 and above 70 was too small, so we excluded them). Comparing with the DTI-TBSS test, we think patients with shorter disease duration may have more serious damages in white matter than gray matter, therefore it maybe a hint for the clinic to pay more antention for the white matter espically the patients with no lesion in the conventional MRI scans. The damages may refer to the cognitive disorder. Moreover, there was no correlation between the averaged whole brain gray matter in T2DM and HbA1c levels, but the trend that the higher HbA1c level, the thicker the averaged cortex in T2DM.ConclusionThe averaged cortex of T2DM patients were thicker than the controls, but they were no statistical differences, it might refer to the shorter disease duration comparing with the previous study. We think patients with shorter disease duration may have more serious damages in white matter than gray matter, therefore it maybe a hint for the clinic to pay more antention for the white matter espically the patients with no lesion in the conventional MRI scans.We found T2DM patients would show less gray matter volumes earlier. Moreover, the trend showed that the higher HbA1c level, the thicker the averaged cortex in T2DM.