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.
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.
ObjectiveTo explore the correlation between cognitive function and diffusion tensor imaging (DTI) in children with self-limited epilepsy with centrotemporal spikes (SelECTS). Methods A total of 28 children with SelECTS who visited our hospital from June 2020 to December 2022 were selected as the SelECTS group. An additional 28 healthy children of similar age and gender were selected as the control group. Cognitive function was assessed using the Wechsler Intelligence Scale for Children (WISC). The SelECTS group also underwent cranial DTI. The results of the WISC were then combined with DTI values for correlation analysis. Results Children in the SelECTS group exhibited varying degrees of cognitive deficits. Their full-scale IQ and verbal IQ were significantly lower than those of the control group (P<0.05). Specific cognitive domains, including classification, verbal comprehension, block design, knowledge, and comprehension, also showed significantly lower scores compared to the control group (P<0.05). DTI revealed significant microstructural changes in multiple regions of interest in the SelECTS group (P<0.05), and these changes were correlated with the results of several cognitive function tests. Conclusion Children with SelECTS have certain cognitive deficits. There is evidence of occult damage in brain white matter, and cognitive function is correlated with damage in specific brain regions.
Present study used diffusion tensor image and tractography to construct brain white matter networks of 15 cerebral palsy infants and 30 healthy infants that matched for age and gender. After white matter network analysis, we found that both cerebral palsy and healthy infants had a small-world topology in white matter network, but cerebral palsy infants exhibited abnormal topological organization: increased shortest path length but decreased normalize clustering coefficient, global efficiency and local efficiency. Furthermore, we also found that white matter network hub regions were located in the left cuneus, precuneus, and left posterior cingulate gyrus. However, some abnormal nodes existed in the frontal, temporal, occipital and parietal lobes of cerebral palsy infants. These results indicated that the white matter networks for cerebral palsy infants were disrupted, which was consistent with previous studies about the abnormal brain white matter areas. This work could help us further study the pathogenesis of cerebral palsy infants.
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.
The study aims to investigate whether there is difference in pre-treatment white matter parameters in treatment-resistant and treatment-responsive schizophrenia. Diffusion tensor imaging (DTI) was acquired from 60 first-episode drug-naïve schizophrenia (39 treatment-responsive and 21 treatment-resistant schizophrenia patients) and 69 age- and gender-matched healthy controls. Imaging data was preprocessed via FSL software, then diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted. Besides, structural network matrix was constructed based on deterministic fiber tracking. The differences of diffusion parameters and topology attributes between three groups were analyzed using analysis of variance (ANOVA). Compared with healthy controls, treatment-responsive schizophrenia showed altered white matter mainly in anterior thalamus radiation, splenium of corpus callosum, cingulum bundle as well as superior longitudinal fasciculus. While treatment-resistant schizophrenia patients showed white matter abnormalities in anterior thalamus radiation, cingulum bundle, fornix and pontine crossing tract relative to healthy controls. Treatment-resistant schizophrenia showed more severe white matter abnormalities in anterior thalamus radiation compared with treatment-responsive patients. There was no significant difference in white matter network topological attributes among the three groups. The performance of support vector machine (SVM) showed accuracy of 63.37% in separating the two patient subgroups (P = 0.04). In this study, we showed different patterns of white matter alterations in treatment-responsive and treatment-resistant schizophrenia compared with healthy controls before treatment, which may help guiding patient identification, targeted treatment and prognosis improvement at baseline drug-naïve state.
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.