ABSTRACT
With the progress of population aging, cerebral small vessel disease is increasingly becoming a common and frequent disease threatening human health, which is a common reason leaing to cognitive function decline.The changes of white matter, especially white matter hyperintensities, are the most common and typical imaging marker of small cerebral vascular disease.In recent years, a number of studies has found that white matter hyperintensities are associated with cognitive decline.These studies mainly focused on the relationship between white matter hyperintensities and cognitive frailty, and the correlation between the size, location and dynamic evolution of white matter hyperintensities and cognitive impairment of small cerebral vascular disease.Functional magnetic resonance imaging studies also revealed that patients with cognitive impairment of cerebral small vessel disease had abnormal white matter changes and structural network connectivity.Structural network can be used for quantitative analysis because of its good stability.Diffusion tensor imaging and quantitative measurement of multi-dimensional structural network were used qualitatively.It was found that the structural network integrity was damaged, the network connection efficiency was reduced, and the connection was interrupted within the white matter hyperintensity.Big data and artificial intelligence research can make early prediction of white matter hyperintensity and structural networks in patients with cerebral small vessel disease with cognitive impairment.These studies provide a reliable basis for the discovery of abnormal microstructure and network changes in the early stage of white matter hyperintensities in cerebral small vessel disease with cognitive impairment.The paper reviews the research progress of white matter hyperintensity and brain structural network in patients with cognitive impairment of cerebral small vessel disease in recent years, and in order to improve the early diagnosis of the disease and promote the early prevention and treatment.
ABSTRACT
Objective:To explore the structural brain network changes in healthy first-degree relatives of depressed patients and their relationship with depressive episodes.Methods:Prospectively, 200 healthy first-degree relatives of depressed patients admitted to Jiangsu University Hospital from May 2017 to June 2018 were collected. Meanwhile, 50 matched healthy controls without family history of depression (HC/FH-) were collected by questionnaire in the nearby community as study subjects. All study subjects underwent systemic magnetic resonance imaging scans and assessment of relevant scales after enrollment, followed by longitudinal follow-up (every 3 months) for up to 3 years. The diagnostic and statistical manual of mental disorders, 4th edition, structured interview was used to assess whether the subjects became depressed during the follow-up period. First-degree relatives who experienced depression during follow-up were included in the group of first-degree relatives who experienced depression (DD/FH+), whereas first-degree relatives who did not experience depression were included in the group of first-degree relatives who did not experience depression (HC/FH+). Subjects′ depression severity and whether they experienced major stressful life events were assessed by the 24-item Hamilton Depression Rating Scale (HDRS) and the Holmes and Rahe Social Readjustment Rating Scale, respectively. Correlations between subjects′ brain structural networks and HDRS scores were explored based on Pearson correlation analysis. Logistic regression models were constructed to investigate the predictive efficacy of brain structural network attributes on depression.Results:Significant group differences existed in the HC/FH- group (50 cases), HC/FH+ group (115 cases), and DD/FH+ group (21 cases) in feeder connectivity (17.62±1.34, 17.03±1.39, 15.82±1.12, F=13.63, P<0.001), global efficiency (0.24±0.03, 0.23±0.03, 0.22±0.03, F=4.73, P=0.010), right insula node efficiency (0.20±0.02, 0.21±0.01, 0.20±0.01, F=4.62, P=0.011), left hippocampal node efficiency (0.27±0.01, 0.27±0.01, 0.24±0.02, F=18.56, P<0.001), and left amygdala node efficiency (0.24±0.02, 0.24±0.02, 0.23±0.01, F=3.40, P=0.036). Logistic regression models showed feeder connectivity ( OR=0.55, 95% CI 0.38-0.78, P=0.001) and left hippocampal nodal efficiency ( OR=0.58, 95% CI 0.40-0.81, P<0.001) predicted the occurrence of final depression and had good predictive efficacy with an area under the curve of 0.75, 0.78, respectively. Correlation analysis showed that feeder connectivity ( r=-0.58, P=0.006) and left hippocampal node efficiency ( r=-0.60, P=0.004) at baseline in the DD/FH+ group correlated with their HDRS scores at the first follow-up. Conclusion:Among healthy first-degree relatives of depressed patients, those who exhibit decreased feeder connectivity and left hippocampal nodal efficiency are susceptible to developing this disease.
ABSTRACT
Objective: To construct brain structural network based on DTI data,so as to investigate whether the brain structural network of with mild cognitive impairment (MCI) patients has small-world property,also to observe the changes of relevant characteristic parameters. Methods: Brain DTI data of 26 MCI patients (MCI group) and 27 healthy elders (NC group) were collected. The images were preprocessed with PANDA software, and the cerebral cortex was divided into 90 regions using automated anatomical labeling (AAL) template. Diffusion tensor tractography was implemented using deterministic fiber tracing algorithm, and the white matter fiber connection network was constructed with the fiber number (FN) between 2 brain regions as the threshold T value. T value was set in the range of 1-5, step length was 1, then the characteristic parameters of the brain network at different T value were calculated, including average path length (Lp), aggregation coefficient (CP), global efficiency (Eglobal) and local efficiency (Elocal). The network was considered to be a small-world network if γ=C/Crand>1 and λ=L/Lrand≈1 (rand representing relative random networks) or δ=γ/λ>1 were satisfied. The differences of brain structural network characteristic parameters were compared between 2 groups. Results: When 1≤T≤5, MCI group and NC group both met the criteria of γ>1 and λ≈1; LP of MCI group were all higher than those of NC group (all P0.05). When 1≤T≤4, Eglobal of MCI group were all lower than those of NC group (all P<0.05), when T=2, Elocal of MCI group was lower than that of NC group (P<0.05). Conclusion: The brain structural network of MCI patients has small-world property, but its small-world characteristics are impaired.
ABSTRACT
Objective@#To explore the changes in brain structure network connection in children with attention deficit hyperactivity disorder(ADHD), and to provide novel markers for early identification of ADHD in clinical practice.@*Methods@#Deterministic diffusion-tensor tractography and graph theory approaches were used to investigate the topologic organization of the brain structural connectome in 25 children with ADHD and 23 healthy control children from May 2017 to May 2018, at Children′s Hospital of Xuzhou Medical University.Individual white matter networks were constructed for each participant, then the global properties, nodal properties and edge-wise distributions were compared between the two groups.@*Results@#(1)The global efficiency of the ADHD group (0.30±0.13) was significantly lower than that of the healthy control group (0.38±0.11), but the clustering coefficient (0.35±0.28) and the characteristic path length (2.94±0.38) were significantly higher than those of the healthy control group (0.28±0.10, 2.65±0.37), and the differences were statistically significant (t=-2.41, 2.31, 2.62, all P<0.05). (2)In the ADHD group, the nodal efficiency of the left inferior frontal gyrus, triangular part (0.13±0.06), left supramarginal gyrus (0.30±0.10), left inferior parietal, angular gyri (0.29±0.10), left precuneus (0.26±0.12)were significantly lower than the healthy control group(0.17±0.07, 0.38±0.10, 0.40±0.12, 0.35±0.12), while the nodal efficiency of the right superior frontal gyrus, orbital part and right paracentral lobule were significantly higher than the healthy control group(0.49±0.17, 0.43±0.14), and the differences were statistically significant[t=-2.52, -2.62, -3.11, -2.77, 2.34, 2.79, all P<0.05, false discovery rate(FDR) corrected]. (3)A disrupted subnetwork was observed that consisted of left frontoparietal areas, basal ganglia, thalamus and insular network (P<0.05, FDR corrected), which has the potential to discriminate individuals with ADHD from healthy control children(area under receiver operating characteristic curve was 0.78). (4)Diminished strength of the subnet work connections was correlated with the attention defect in patients with ADHD(r=-0.607, P=0.003).@*Conclusions@#Using magnetic resonance diffusion tensor imaging, with the help of graph theory analysis technology, ADHD children can be observed changes in brain structure network at multiple levels.The distribution pattern of brain network structure connection changes is expected to become a new marker for identifying ADHD.
ABSTRACT
Objective To explore the differences of the global efficiency of the brain structural networks between the male paranoid schizophrenia and male healthy and its relationship with the psychotic symptoms of the schizophrenia.Methods The diffusion tensor imaging data were obtained from 27 male paranoid schizophrenia patients and 28 male healthy controls.The whole cerebral cortex was parcellated into 90 regions by the anatomical label map.Tractography was performed in the whole cerebral cortex of each subject to reconstruct white matter tracts of the brain using fiber assignment by continuous tracking(FACT) algorithm.And then the brain structural binary networks were constructed using the complex network theory.The average global efficiency of the brain network and the global efficiency of the nodes of both groups were examined by two sample t-test and its relationship with the psychotic symptoms in the male paranoid schizophrenia was explored by the correlation analysis.Results Compared with control group,the average global efficiency of the brain network of the patients decreased significantly (7.87±0.56,8.17±0.56,P=0.005),and the global efficiency of the nodes in the brain network of the patient decreased significantly in the left superior frontal gyrus (orbital part) (P=0.00025),the left superior parietal gyrus (P=0.00011),the left cuneus (P=0.00012) and the left putamen (P=0.00032),all survived FDR correction.Significant negative correlation was found between the global efficiency of the left putamen and the total scores (r=-0.43,P=0.03),the positive scores (r=-0.41,P=0.03) and the cognitive scores (r=-0.40,P=0.04) of PANSS.Conclusion The decreased global efficiency of the left frontal,parietal and occipital lobes and the subcortical structures lead to the occurrence of schizophrenia.And the reduced efficiency of the subcortical structures is associated with the positive symptoms and the abnormal cognitive function of the patients.
ABSTRACT
Objective To investigate the small-worldness and the betweenness centrality of the nodes in the brain structural networks and its relationship with the course and the central role of the brain regions in the transmission of information across the whole brain in depression.Methods The diffusion tensor imaging data were obtained from 27 depression patients and 33 healthy controls.The brain structural networks were constructed using the complex network theory.Results The brain structural networks had small-world properties in both groups.When compared with the healthy,the betweenness centrality of the nodes of the networks in depression significantly decreased in right superior frontal gyms (orbital part) (P=0.00035,region survived critical FDR threshold for multiple comparisons),and left putamen (P=0.00054,region survived critical FDR threshold for multiple comparisons).Significant negative correlation was found between the betweenness centrality of left hippocampus and the course in the depression(r=0.50,P=0.016).Conclusion Both of the brain structural networks in depression patients and normal people have the property of small-worldness.But the central role of orbit frontal cortex and putamen in the transmission of information across the whole brain is declined,and the betweenness centrality of hippocampus is negatively related with the course in the depression.
ABSTRACT
Objective To explore the differences of the degree and distribution of hub regions of the brain structural networks between the schizophrenia and healthy and then analysis the importance of brain regions in the information transmission in across the whole brain.Methods The diffusion tensor imaging data were obtained from 22 schizophrenia patients and 24 healthy controls.The whole cerebral cortex was parcellated into 90 regions by the anatonical label map.Tractography was performed in the whole cerebral cortex of each subject to reconstruct white matter tracts of the brain using the fiber assignment by continuous tracking (FACT) algorithm.And then the brain structural binary networks were constructed using the complex network theory.The average degree of the network and the degree of the nodes in the network between the brain structural networks of both groups were examined by two sample t-tests.Results The average degree of the brain structural network in the patient group (7.82±0.56) decreased significantly when compared with the control group (8.17 ±0.56; P=0.04).The degree of the nodes in the brain structural network of the patient group (the left hippocampus:11.41 ± 1.84; the left parahippocampal gyrus:6.41± 1.33 ; the left calcarine fissure:11.50±2.97 ; the left fusiform gyrus:8.27± 1.83) decreased significantly when compared with the control group (14.43±2.26; 8.54±2.15; 14.79±2.80; 10.25± 1.36; all P＜0.01,survived critical FDR threshold for multiple comparisons).And the distribution of the hub regions in the temporal and occipital lobes of the patient group was difference from that of the control group.Conclusion The importance of the hippocampus and the brain regions in the occipital lobe is decrease for the information transmission across the whole brain.The damage of the topological properties of these brain regions maybe related to the disorder of the transmission and integration of information in the brain of the schizophrenia.
ABSTRACT
Objective To explore the differences of the connectivity strength,the clustering coefficient and the local efficiency of the nodes in the brain structural networks in the depression and healthy subjects and then analyze the mode of the local connections of the brain regions and their local efficiency of the transmission of information and their relationship with the severity of the disease in the depression.Methods The Diffusion Tensor Imaging data were obtained from 24 depression patients and 25 healthy controls.The whole cerebral cortex was parcellated into 90 regions by the anatomical label map.Tractography was performed in the whole cerebral cortex of each subject to reconstruct white matter tracts of the brain using the fiber assignment by continuous tracking (FACT) algorithm.And then the brain structural networks were constructed using the complex network theory.The local topological properties of the brain structural networks of the depression and healthy were examined by two sample t-test.Results The local efficiency of the nodes of the networks in depression decreased significantly (the left middle frontal gyrus (orbital part):0.64±0.30,the left hippocampus:0.57±0.07,the right parahippocampal gyrus:0.50±0.15) compared with the healthy (0.88±0.10,0.64±0.06,0.66±0.13 respectively,P=0.00098,0.00039,0.00017,survived critical FDR threshold for multiple comparisons) ; and the clustering coefficient of the nodes of the networks in depression (the left middle frontal gyrus (orbital part):0.14±0.07) decreased significantly when compared with the healthy (0.22±0.06,P=0.000030,survived critical FDR threshold for multiple comparisons).Significant negative correlation was found between the local efficiency of the left middle frontal gyrus (orbital part) and the total scores of HAMD-17 in the depression (r=-0.48,P=0.02).Conclusion The degree of the localization and the local efficiency of the information transmission of the frontal lobe are decreased.The local efficiency in the information transmission in the hippocampal is also decreased.And the local efficiency of the frontal lobe is negatively related with the severity of the disease in the depression.