To explore the evaluation of white matter structural network analysis in the differentiation of Alzheimer’s disease (AD) and subcortical ischemic vascular dementia (SIVD), 67 participants [31 AD patients, 19 SIVD patients, and 19 normal control (NC)] were enrolled in this study. Each participant underwent 3.0T MRI scanning. Diffusion tensor imaging (DTI) data were analyzed by graph theory (GRETNA toolbox). Statistical analyses of global parameters [gamma, sigma, lambda, global shortest path length (Lp), global efficiency (Eg), and local efficiency (Eloc)] and nodal parameters [betweenness centrality (BC)] were obtained. Network-based statistical analysis (NBS) was employed to analyze the group differences of structural connections. The diagnosis efficiency of nodal BC in identifying different types of dementia was assessed by receiver operating characteristic (ROC) analysis. There were no significant differences of gender and years of education among the groups. There were no significant differences of sigma and gamma in AD vs. NC and SIVD vs. NC, whereas the Eg values of AD and SIVD were statistically decreased, and the lambda values were increased. The BC of the frontal cortex, left superior parietal gyrus, and left precuneus in AD patients were obviously reduced, while the BC of the prefrontal and subcortical regions were decreased in SIVD patients, compared with NC. SIVD patients had decreased structural connections in the frontal, prefrontal, and subcortical regions, while AD patients had decreased structural connections in the temporal and occipital regions and increased structural connections in the frontal and prefrontal regions. The highest area under curve (AUC) of BC was 0.946 in the right putamen for AD vs. SIVD. White matter structural network analysis may be a potential and promising method, and the topological changes of the network, especially the BC change in the right putamen, were valuable in differentiating AD and SIVD patients.

BackgroundHow brain neural activity changes at multiple time points throughout the day and the neural mechanisms underlying time‐dependent modulation of vigilance are less clear.PurposeTo explore the effect of circadian rhythms and homeostasis on brain neural activity and the potential neural basis of time‐dependent modulation of vigilance.Study TypeProspective.SubjectsA total of 30 healthy participants (22–27 years old).Field Strength/SequenceA 3.0 T, T1‐weighted imaging, echo‐planar functional MRI (fMRI).AssessmentSix resting‐state fMRI (rs‐fMRI) scanning sessions were performed at fixed times (9:00 h, 13:00 h, 17:00 h, 21:00 h, 1:00 h, and 5:00 h) to investigate fractional amplitude of low‐frequency fluctuation (fALFF) and regional homogeneity (ReHo) diurnal variation. The fALFF/ReHo and the result of the psychomotor vigilance task were used to assess local neural activity and vigilance.Statistical TestsOne‐way repeated measures analysis of variance (ANOVA) was used to assess changes in vigilance (P < 0.05) and neural activity in the whole brain (P < 0.001 at the voxel level and P < 0.01 at the cluster level, Gaussian random field [GRF] corrected). Correlation analysis was used to examine the relationship between neural activity and vigilance at all‐time points of the day.ResultsThe fALFF/ReHo in the thalamus and some perceptual cortices tended to increase from 9:00 h to 13:00 h and from 21:00 h to 5:00 h, whereas the key nodes of the default mode network (DMN) tended to decrease from 21:00 h to 5:00 h. The vigilance tended to decrease from 21:00 h to 5:00 h. The fALFF/ReHo in the thalamus and some perceptual cortices was negatively correlated with vigilance at all‐time points of the day, whereas the fALFF/ReHo in the key nodes of the DMN was positively correlated with vigilance.Data ConclusionNeural activities in the thalamus and some perceptual cortices show similar trends throughout the day, whereas the key nodes of the DMN show roughly opposite trends. Notably, diurnal variation of the neural activity in these brain regions may be an adaptive or compensatory response to changes in vigilance.Evidence Level1.Technical Efficacy1.

No abstract

Purpose: To evaluate the early bilirubin-induced neurologic dysfunction (BIND) by T1 weighted imaging (T1WI), diffusion tensor imaging (DTI), and arterial spin labeling (ASL).Methods: Forty newborns: hyperbilirubinemia with BIND (BIND group, n=13), hyperbilirubinemia without BIND (non-BIND group, n=17), and healthy newborns (HC group, n=10). The MRI parameters of globus pallidus were measured, including the T1WI signal values from conventional MRI, apparent diffusion coefficient (ADC), the fractional anisotropy (FA), relative anisotropy (RA) and volume ratio (VR) value from DTI, and the relative cerebral blood flow (rCBF) value from ASL. The group differences were analyzed by ANOVA with Bonferroni correction. The diagnosis efficiencies were assessed by the receiver operating characteristic curve (ROC). The correlation between those parameters and serum bilirubin level was evaluated by Pearson’s correlation coefficient.Results: 1）The mean signal values of globus pallidus on T1WI and DTI parameters were significantly different among the groups (p < 0.05). The difference in T1WI between the non-BIND group and the BIND group was not significant (p >0.05). The rCBF of globus pallidus was not significantly different among the three groups (p > 0.05). 2) The T1WI, FA, and RA values were positively while the VR value was negatively correlated with serum bilirubin level (r =0.763, 0.585, 0.586, -0.544 respectively, p < 0.05). The ADC value and rCBF were not correlated with serum bilirubin (r = -0.050, -0.275 respectively, p > 0.05). 3) The area under curve (AUC) of T1WI, FA, RA, VR was 0.953, 0.897, 0.897, 0.860 respectively. And the AUC of the diagnosis method, combined T1WI, FA, RA and VR, was 0.987.Conclusion: The index, combined T1WI and DTI parameters, was important for diagnosing early hyperbilirubinemia brain injury. ASL might not have function on diagnosing early hyperbilirubinemia brain injure.