Radiation-induced aberrant structural covariance networks in patients with nasopharyngeal carcinoma: a source-based morphometry study.

Multidimensional fatigue and its predictive factors in patients with radiation-induced brain injury after radiotherapy for nasopharyngeal carcinoma: A cross-sectional study.

Predicting cognitive aging through brain structural covariance networks: A decade of longitudinal insights using source-based morphometry.

Identifying Subgroups of Major Depressive Disorder Using Brain Structural Covariance Networks and Mapping of Associated Clinical and Cognitive Variables

BackgroundBrain structural alterations play an important role in patients with cervical spondylotic myelopathy (CSM). However, while there have been studies on regional brain structural alterations, only few studies have focused on the topological organization of the brain structural covariance network. This work aimed to describe the structural covariance network architecture alterations that are possibly linked to cortex reorganization in patients with CSM.MethodsHigh-resolution anatomical images of 31 CSM patients and 31 healthy controls (HCs) were included in the study. The images were acquired using a sagittal three-dimensional T1-weighted BRAVO sequence. Firstly, the gray matter volume of 90 brain regions of automated anatomical labeling atlas were computed using a VBM toolbox based on the DARTEL algorithm. Then, the brain structural covariance network was constructed by thresholding the gray matter volume correlation matrices. Subsequently, the network measures and nodal property were calculated based on graph theory. Finally, the differences in the network metrics and nodal property between groups were compared using a non-parametric test.ResultsPatients with CSM showed larger global efficiency and smaller local efficiency, clustering coefficient, characteristic path length, and sigma values than HCs. Patients with CSM had greater betweenness in the left superior parietal gyrus (SPG.L) and the left supplementary motor area (SMA.L) than HCs. Besides, patients with CSM had smaller betweenness in right middle occipital gyrus. The brain structural covariance networks of CSM patients exhibited equal resilience to random failure as those of HCs. However, the maximum relative size of giant connected components was approximately 10% larger in HCs than in CSM patients, upon removal of 44 nodes in targeted attack.ConclusionThese observed alternations in global network measures in CSM patients reflect that the brain structural covariance network in CSM exhibits the less optimal small-world model compared to that in HCs. Increased betweenness in SPG.L and SMA.L seems to be related to cortex reorganization to recover multiple sensory functions after spinal cord injury in CSM patients. The network resilience of patients with CSM exhibiting a relative mild vulnerability, compared to HCs, is probably attributable to the balance and interplay between cortex reorganization and ongoing degeneration.

PurposeTo evaluate factors affecting psychology, cognitive function and quality of life (QOL) of nasopharyngeal carcinoma (NPC) patients with radiation-induced brain injury (RI).Methods and Materials46 recurrence-free NPC patients with RI and 46 matched control patients without RI were recruited in our study. Subjective and objective symptoms of RI were evaluated with the LENT/SOMA systems. Psychological assessment was measured with Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS). Montreal Cognitive Assessment (MoCA) was carried out in these patients for assessing their cognitive function. QOL was evaluated by means of WHOQOL BREF.ResultsOf the patients with RI, 39(84.8%) had depression and 40(87.0%) had anxiety. The patients with RI got higher scores both in SDS and SAS than those without RI (SDS, 63.48±8.11vs. 58.67±7.52, p = 0.008; SAS, 67.36±10.41vs. 60.34±9.76, p = 0.005). Score in MoCA of patients with RI was significantly lower than that of patients without RI (21.32±2.45vs. 25.98±1.73, p<0.001). SAS was positive correlated with post-radiotherapy interval. Both SAS and SDS had a significantly positive correlation with the rank of SOMA, while MoCA had a significantly negative correlation with SOMA. Chemotherapy was a risk factor for cognitive dysfunction. In addition, patients with RI got significantly lower scores in physical health (16.50±11.05 vs. 35.02±10.43, p<0.001), psychological health (17.70±10.33 vs. 39.48±12.00, p<0.001) and social relationship (48.00±18.65 vs. 67.15±19.70, p<0.001) compared with those in patients without RI. Multiple linear regression analysis revealed that anxiety and cognitive impairment were significant predictors of global QOL.ConclusionsNPC patients with RI exhibit negative emotions, impaired cognitive function and QOL. The severity of clinical symptoms of RI plays an important role in both emotions and cognitive function. Anxiety and cognitive impairment are associated with decreased QOL.

We investigated the changes in structural connectivity (using diffusion tensor imaging [DTI]) and the structural covariance network based on structural volume using graph theory in patients with neurofibromatosis type 1 (NF1) compared to a healthy control group. We included 14 patients with NF1, according to international consensus recommendations, and 16 healthy individuals formed the control group. This was retrospectively observational study followed STROBE guideline. Both groups underwent brain magnetic resonance imaging including DTI and 3-dimensional T1-weighted imaging. We analyzed structural connectivity using DTI and Diffusion Spectrum Imaging Studio software and evaluated the structural covariance network based on the structural volumes using FreeSurfer and Brain Analysis Using Graph Theory software. There were no differences in the global structural connectivity between the 2 groups, but several brain regions showed significant differences in local structural connectivity. Additionally, there were differences between the global structural covariance networks. The characteristic path length was longer and the small-worldness index was lower in patients with NF1. Furthermore, several regions showed significant differences in the local structural covariance networks. We observed changes in structural connectivity and covariance networks in patients with NF1 compared to a healthy control group. We found that global structural efficiency is decreased in the brains of patients with NF1, and widespread changes in the local structural network were found. These results suggest that NF1 is a brain network disease, and our study provides direction for further research to elucidate the biological processes of NF1.

The current study is to characterize the alterations of peripheral cytokines and anatomical brain changes, and their relationships in untreated nasopharyngeal carcinoma (NPC) patients with depressive symptoms. Twenty-nine newly diagnosed NPC patients without any treatment and 46 matched healthy comparisons were recruited, scanned with high-resolution T1 images and assessed psychologically using Hamilton Rating Scale for Depression (HAMD). Serum levels of interleukin-1 beta (IL-1β), IL-2, IL-6, IL-8, IL-10, interferon-gamma (IFN-γ) and transforming growth factor-beta (TGF-β) were measured by quantitative chemiluminescence assay. Inter-group comparisons of anatomical brain measures were performed, and regions with significant inter-group differences were correlated to HAMD scores and cytokines in NPC patients. A subgroup analysis especially within NPC patients with depression was conducted to precisely characterize the associations among serum cytokines, brain changes and depressive symptoms. Relative to healthy subjects, NPC patients showed significantly decreased cortical thickness in the left parahippocampal gyrus, increased surface area in the right superior parietal lobule and precentral gyrus, and increased gray matter volume in the right postcentral gyrus, bilateral caudate nucleus and right thalamus, as well as significantly elevated IL-1β, IL-2 and IL-10. The elevated IL-2 and IL-10 were negatively correlated with surface area in right superior parietal lobule, whilst IL-1β level was positively correlated to HAMD scores. In patients with depression, specific brain changes and evaluated IL-1β were identified, and the IL-1β interacted with right precentral gyrus to significantly affect the depressive symptoms. Our findings provide novel evidence indicating potential effects of inflammation on brain structure and behavior in NPC patients.

Abnormal structural covariance network in major depressive disorder: Evidence from the REST-meta-MDD project

Decision letter: Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer’s disease continuum

BackgroundThe aim of this study was to investigate alterations in structural connectivity and structural co-variance network in patients with focal cortical dysplasia (FCD).MethodsWe enrolled 37 patients with FCD and 35 healthy controls. All subjects underwent brain MRI with the same scanner and with the same protocol, which included diffusion tensor imaging (DTI) and T1-weighted imaging. We analyzed the structural connectivity based on DTI, and structural co-variance network based on the structural volume with T1-weighted imaging. We created a connectivity matrix and obtained network measures from the matrix using the graph theory. We tested the difference in network measure between patients with FCD and healthy controls.ResultsIn the structural connectivity analysis, we found that the local efficiency in patients with FCD was significantly lower than in healthy controls (2.390 vs. 2.578, p = 0.031). Structural co-variance network analysis revealed that the mean clustering coefficient, global efficiency, local efficiency, and transitivity were significantly decreased in patients with FCD compared to those in healthy controls (0.527 vs. 0.635, p = 0.036; 0.545 vs. 0.648, p = 0.026; 2.699 vs. 3.801, p = 0.019; 0.791 vs. 0.954, p = 0.026, respectively).ConclusionsWe demonstrate that there are significant alterations in structural connectivity, based on DTI, and structural co-variance network, based on the structural volume, in patients with FCD compared to healthy controls. These findings suggest that focal lesions with FCD could affect the whole-brain network and that FCD is a network disease.

Neuroimaging studies have found significant structural alterations of the cerebral cortex in patients with nasopharyngeal carcinoma (NPC) following radiotherapy (RT) or concomitant chemoradiotherapy (CCRT), while their effects on the shape of subcortical structures remain largely unknown. In this study, we investigated the subcortical shape alterations between three groups: 56 untreated NPC patients (pre-RT group), 37 RT-treated NPC patients (post-RT group), and 108 CCRT-treated NPC patients (post-CCRT group). Using FSL-FIRST, we found that, compared with the pre-RT group, the post-CCRT group exhibited significant inward atrophy in the bilateral thalamus, bilateral putamen, left pallidum, and left caudate and outward inflation in the left caudate, while the post-RT group only exhibited inward atrophy in the bilateral thalamus. In addition, greater maximum dosage of RT for temporal lobes was associated with more severe inward atrophy of the bilateral thalamus in treated NPC patients. These results indicated that there may be an interaction between RT and CT that can cause subcortical damage.

The structural covariance network (SCN) alterations in patients with temporal lobe epilepsy and comorbid sleep disorder (PWSD) remain poorly understood. This study aimed to investigate changes in SCNs using structural magnetic resonance imaging. Thirty-four PWSD patients, thirty-three patients with temporal lobe epilepsy without sleep disorder (PWoSD), and seventeen healthy controls underwent high-resolution structural MRI imaging. Subsequently, SCNs were constructed based on gray matter volume and analyzed via graph-theoretical approaches. PWSD exhibited significantly increased clustering coefficients, shortest path lengths, transitivity, and local efficiency. In addition, various distributions and numbers of SCN hubs were identified in PWSD. Furthermore, PWSD networks were less robust to random and target attacks than those of healthy controls and PWoSD patients. This study identifies aberrant SCN changes in PWSD that may be related to the susceptibility of patients with epilepsy to sleep disorders.

Objective To explore the correlation between microdamage in white matter and radiotherapy dose at early stage after radiotherapy (RT) in patients with nasopharyngeal carcinoma (NPC). Methods Thirty-three patients who were initially diagnosed with NPC were recruited and received diffusion tensor imaging (DTI) scan and neuro-cognitive scale test within 1 week before RT and the first day after RT. DTI-related characteristic parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ‖), and radial diffusivity (λ⊥) were calculated based on whole-brain voxel analysis method. Paired t-test was conducted to evaluate statistical significance between pre-RT and post-RT groups. In the subgroup analysis, all the subjects were divided into 3 groups according to the average dose of temporal lobe, and each group was set with an equal dose interval range. The DTI-related parameters of whole brain pre-RT and post-RT in each group were statistically compared. All the statistical results were corrected by FDR with a threshold of P 100. Results FA, MD, λ‖ and λ⊥in the post-RT group significantly differed compared with those in the pre-RT group (P<0.05). The values of FA, MD, λ‖ and λ⊥were 0.455±0.016, (9.893±0.403)×10-4, (13.441±0.412)×10-4 and (8.231±0.429)×10-4, respectively. Subgroup analysis showed that the extent and degree of λ‖ and λ⊥ changes were exacerbated with the increase of the average dose of temporal lobe after RT. Particularly in high-dose group, the average dose range was 25-35 Gy and the extent of regions with significant changes was significantly larger than those in the medium-dose (15-25 Gy) and low-dose groups (5-15 Gy)(P<0.05). Conclusions DTI can be utilized to detect brain tissue microdamage in NPC patients at early stage after RT. The average radiation dose of temporal lobe may be one of the reasons for the severity of cerebral microdamage. In the future, DTI technique may be useful for guiding exposure dose of organs at risk during RT planning and to evaluate the cohort with a high risk of cerebral microdamage at early stage after RT, thereby protecting normal cerebral tissues to the maximum extent. Key words: Diffusion tensor imaging; Nasopharyngeal neoplasm/radiotherapy; Radiation-induced brain injury; Dosimetry

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development.