Objective To explore the difference of white matter changes between bipolar affective disorder and schizophrenia using diffusion tensor imaging (DTI). Methods Patients with bipolar affective disorder and schizophrenia were selected from the Mental Health Center of West China Hospital of Sichuan University between October 2014 and January 2017. Volunteers were recruited from October 2014 to January 2017. The included patients were divided into bipolar affective disorder group and schizophrenia group according to their diagnosis. Volunteers were divided into normal control group. The bipolar affective disorder group was divided into two subgroups: manic episode and depressive episode. DTI was performed on the included patients and volunteers. Tract based spatial statistics (TBSS) was used to study the differences in fractional anisotropy (FA) of white matter between patients and normal controls, and FA values of two subgroups of bipolar affective disorder and schizophrenia were compared. Results A total of 99 patients and 40 normal controls were included in this study. Among them, there were 40 cases in schizophrenia group and 59 cases in bipolar affective disorder group (31 cases of manic episode and 28 cases of depressive episode). Compared with the normal control group, FA values decreased in corpus callosum, fornix, occipital forceps and left inferior longitudinal fasciculus with bipolar affective disorder group and schizophrenia group (P<0.05). There was no significant difference in FA values between bipolar affective disorder group and schizophrenia group (P>0.05), but the FA value in left posterior thalamic radiation decreased in depressive episode of bipolar affective disorder group compared with schizophrenia group (P=0.001). Conclusions There are similarities between white matter changes in bipolar affective disorder and schizophrenia. However, the white matter change in posterior thalamic radiation may be the characteristic change in depressive episode of bipolar affective disorder.
This study aims to determine the salient brain regions with abnormal changes in white matter structures from diffusion tensor imaging (DTI) images of the patients with temporal lobe epilepsy (TLE), and to discriminate the patients with TLE from normal controls (NCs). Firstly, the DTI images from 50 subjects (28 NCs and 22 TLE) were acquired. Secondly, the four measures including the fractional anisotropy (FA), the mean diffusivity (MD), the axial diffusivity (AD) and the radial diffusivity (RD) were calculated. Thirdly, the tract-based spatial statistics (TBSS) was adopted to extract the measures in brain regions with significant differences between the two compared groups. Fourthly, the obtained measures were used as input features of the support vector machine (SVM) for classification, and the support vector machine-recursive feature elimination (SVM-RFE) was compared with the support vector machine-tract-based spatial statistics (SVM-TBSS) method. Finally, the essential brain regions and their spatial distribution were analyzed and discussed. The experimental results showed that the FA measures of the TLE group decreased significantly in the corpus callosum, superior longitudinal fasciculus, corona radiata, external capsule, internal capsule, inferior fronto-occipital fasciculus, fasciculus uncinatus and sagittal stratum, which were nearly bilaterally distributed, while the MD and RD increased significantly in most of these brain regions of the TLE group. Although the AD also increased, the differences were not statistically significant. The SVM-TBSS classifier obtained accuracies of 82%, 76% and 76% using the FA, MD and RD for classification, respectively, and 80% using combined measures. The SVM-RFE classifier obtained accuracies of 90%, 90% and 92% using the FA, MD and RD respectively, while the highest accuracy was 100% using combined measures. These results demonstrated that the SVM-RFE outperformed the SVM-TBSS, and the dominant characteristic influencing classification in brain regions were in associative and commissural fibers. These results illustrated that the measures of DTI images could reveal the abnormal changes in white matter structure of patients with TLE, providing effective information to clarify its pathological mechanism, localize the focus and diagnose automatically.
In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.
This study aims to detect early changes of kidney in patients with primary hypertension by 3.0 T functional magnetic resonance imaging (fMRI). 26 patients with primary hypertension (hypertension group) and 33 healthy volunteers (control group) underwent conventional and functional magnetic resonance scans, which included blood oxygen level-dependent (BOLD) MRI, diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). We measured renal cortical thickness (CT), parenchymal thickness (PT), and functional values of renal cortex and medulla including R2* value, apparent diffusion coefficient (ADC) value and fractional anisotropy (FA) value in each group, and then calculated the cortical/parenchymal thickness ratio (CPR). Compared with those in the control group, CT and CPR in hypertension group were larger (P<0.01), cortical and medullar R2* values increased (P<0.01) whereas medullar FA values decreased (P<0.05). It could be well concluded that noninvasive 3.0 T functional MRI would have important clinical significance in identifying early abnormalities of kidney in hypertension patients.
White matter lesion (WML) of presumed vascular origin is one of the common imaging manifestations of cerebral small vessel diseases, which is the main reason of cognitive impairment and even vascular dementia in the elderly. However, there is a lack of early and effective diagnostic methods currently. In recent years, studies of diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) have shown that cognitive impairment in patients with WMLs is associated with disrupted white matter microstructural and brain network connectivity. Therefore, it’s speculated that DTI and rs-fMRI can be effective in early imaging diagnosis of WMLs-related cognitive impairment. This article reviews the role and significance of DTI and rs-fMRI in WMLs-related cognitive impairment.
This paper is aimed to analyze the topological properties of structural brain networks in depressive patients with and without anxiety and to explore the neuropath logical mechanisms of depression comorbid with anxiety. Diffusion tensor imaging and deterministic tractography were applied to map the white matter structural networks. We collected 20 depressive patients with anxiety (DPA), 18 depressive patients without anxiety (DP), and 28 normal controls (NC) as comparative groups. The global and nodal properties of the structural brain networks in the three groups were analyzed with graph theoretical methods.The result showed that ① the structural brain networks in three groups showed small-world properties and highly connected global hubs predominately from association cortices; ② DP group showed lower local efficiency and global efficiency compared to NC group, whereas DPA group showed higher local efficiency and global efficiency compared to NC group; ③ significant differences of network properties (clustering coefficient, characteristic path lengths, local efficiency, global efficiency) were found between DPA and DP groups; ④ DP group showed significant changes of nodal efficiency in the brain areas primarily in the temporal lobe and bilateral frontal gyrus, compared to DPA and NC groups. The analysis indicated that the DP and DPA groups showed nodal properties of the structural brain networks, compared to NC group. Moreover, the two diseased groups indicated an opposite trend in the network properties. The results of this study may provide a new imaging index for clinical diagnosis for depression comorbid with anxiety.
ObjectiveTo study the relationship between brain white matter fiber occult lesions and P100 wave latency of visual evoked potential (VEP) in neuromyelitis optica (NMO) patients by diffusion tensor imaging (DTI). MethodsTwenty patients with NMO who were treated between July 2008 and April 2009 were selected as the trial group. According to the VEP test, the latency of P100 wave was prolonged, the NMO patients were divided into VEP abnormal group (trial group 1) and VEP normal group (trial group 2). Twenty healthy adult volunteers served as the control group. The DTI examination in brain was done to measure the fractional anisotropy (FA) value of optic nerve (FAn), optic tract (FAt), and optic radiation (FAr);and the mean diffusivity (MD) value of optic nerve (MDn), optic tract (MDt), and optic radiation (MDr). The FA, MD, and P100 wave latency were compared between groups, and the correlation between MD, FA, and P100 wave latency of NMO were analyzed. ResultsIn the 20 NMO patients, 13 patients with VEP had prolonged bilateral P100 wave latency prolongation or no wave (trial group 1), and 7 patients had normal bilateral P100 wave latency (trial group 2). Compared with the trial group 2 and the control group, the FA values were significantly decreased, and the MD values were significantly increased in the trial group 1 (P<0.05). There was no significant difference in the FA and MD values between the trial group 2 and the control group (P>0.05). All FA (FAn, FAt, and FAr) values of each part of NMO patients were negatively correlated with the latency of P100 wave (P<0.05), all MD (MDn, MDt, and MDr) values were positively correlated with the latency of P100 wave (P<0.05). ConclusionDTI could show small pathylogical changes in the white matter fibers of visual pathway, and there is a correlation between DTI and VEP in NMO, suggesting that a more comprehensive assessment to the condition and prognosis can be made through the VEP in the clinical indicators.
ObjectiveChildhood absence epilepsy (CAE) is a common syndrome of idiopathic generalized epilepsy.However, little is known about the brain structural changes in this type of epilepsy, especially in the default mode network (DMN) regions.Diffusion tensor imaging (DTI) is a noninvasive techniques that can be used to quantitatively explore structural characteristics of brain.This study aims at using the DTI technique to quantify structural abnormalities of DMN nodes in CAE patients.MethodDTI data were obtained in 14 CAE patients and 13 age-and gender-matched healthy controls.The data were analyzed using voxel-based analysis (VBA) and statistically compared between patients and controls.For the regions with significant difference in group comparison, their DTI metrics were further analyzed with clinical symptoms using Pearson's correlation.ResultsPatients showed significant increase of apparent diffusion coefficient (ADC) in left medial prefrontal cortex (MPFC) (P=0.042), while fractional anisotropy (FA) value was significantly decreased in left precuneus (P=0.010).In correlation analysis, ADC value from left MPFC was positively associated with duration of epilepsy.Neither the disease duration nor the seizure frequency showed significant correlation with FA values.ConclusionThe findings indicate that structural impairments exist in DMN regions in children suffering from absence epilepsy.This may contribute to understanding the pathological mechanisms and chronic neurological deficits of this disorder.