Structural Network In Patients Research Articles

Whole brain tractography in Malaysian patients using DMRI

Language processing involves multiple brain regions in a predominantly left lateralised cortical network. Language networks however are still very much elusive due to complexity of brain activity profiles that may vary considerably among different individuals particularly when there is a tumour present in the network. The ability to delineate fibres accurately is fundamental in the treatment planning of tumour patients. Tractography is useful in mapping white matter networks, however numerous methods like deterministic, probabilistic and global exist, each presenting with advantages and limitations. This study thus aims to investigate and map structural networks in patients with a left hemisphere primary brain tumour and healthy subjects using dMRI and tractography, with the intent of comparing these three methods. In this study, retrospective Hospital USM radiological 3T MRI treatment planning data between September 2012 and December 2017 of 6 left hemisphere tumour patients (3 gliomas, 3 meningiomas) and 3 radiologically normal brain patients is being used. Manual processing and packages DSI Studio, MRtrix3, ITK and FSL were used for pre-processing the data, setting up ROIs and running the different methods of tractography analysis. Fibre length and coefficient data were statistically compared using SPSS. The results indicated that probabilistic algorithms delineated the selected networks better than deterministic. Global tractography yielded slightly better results however in the case of tumour patients some false positives were indicated. Deterministic analysis terminated prematurely in line with previous research. Local probabilistic seems to yield more applicable as previous research has indicated in the case of other pathology.

Altered topological properties in white matter structural networks in patients with schizophrenia

Objective To explore the changes of whole brain white matter (WM) structural network topological property in patients with schizophrenia (SP) and the associations between WM networks topological efficiency and clinical variables in patients. Methods Deterministic tractography was used to construct the WM networks of 59 patients with SP (patients group) and 41 age-, handedness-, and gender-matched healthy controls (HCs), and graph theoretical methods were applied to investigate abnormalities in the global and nodal properties of the WM network in these patients.Partial correlation analysis was used to analyze the relationship between global and nodal properties of the WM network and clinical variables in patients with SP. Results Both the patients with SP and HCs showed small-world organization of the WM networks.However, compared with HCs, the patients with SP exhibited significant abnormal global topology, including increased shortest path length (t=7.95, P=0.0001) and decreased global efficiency (30.83±16.08, 8.25±6.13, t=-9.81, P=0.002), clustering coefficiency (0.03±0.01, 0.02±0.01, t=-4.48, P=0.0003), the average clustering coefficiency (t=-8.28, P=0.002), the small-worldness (3.92±0.79, 2.79±0.56, t=-7.82, P=0.001) of their WM structural networks(all P<0.005, FDR corrected). Further, the patients with SP showed a reduction in nodal efficiency predominately in the cingulate gyrus (t=-4.11, P=0.000), superior occipital gyrus (t=-6.05, P=0.002), superior temporal gyrus (t=-10.46, P=0.001), middle temporal gyrus (t=-10.38, P=0.000), thalamus (t=-6.10, P=0.000) and putamen (t=-8.38, P=0.000) (P<0.005, FDR corrected). Partial correlation results showed that there was no significant correlation between global topological properties, node efficiency and clinical symptoms in patients group(Eglob: r=-0.14, P=0.279; Eloc: r=-0.06, P=0.628; Lp: r=0.28, P=0.031; Cp: r=0.27, P=0.043; λ: r=-0.18, P=0.166; γ: r=-0.29, P=0.026; σ: r=0.26, P=0.048; nEglob: r=0.36, P=0.005; nEloc: r=0.02, P=0.901). Conclusions The patients with SP exhibit the abnormal of whole brain WM structural network topological property and the node efficiencies of cortico-striato-thalamo circuitry are significantly reduced. Key words: Schizophrenia; White matter; Topological properties; Graph theoretical

Large-scale network architecture and associated structural cortico-subcortical abnormalities in patients with sleep/awake-related seizures.

In this study, we aimed to estimate the alterations of brain networks and structural integrity linked to seizure occurrence during sleep and awake states. Using a graph theory approach to magnetic resonance imaging-derived volumes of cortical and subcortical regions, we investigated the topological organization of structural networks in patients with sleep seizures (n = 13), patients with awake seizures (n = 12), and age- and sex-matched healthy controls (n = 10). Abnormalities in regional structural substrates (cortical volume/surface area, subcortical volumes) associated with sleep seizures and awake seizures were further analyzed. Brain networks in patients with sleep seizures compared to patients with awake seizures displayed a more integrated structural organization coupled with greater networks' stability. When compared to healthy controls, networks in both patients with sleep and awake seizures were analogously compromised, exhibiting a less integrated and preserved organization. Patients with sleep seizures in contrast to awake seizures had larger volumes of bilateral insula, superior temporal, and orbitofrontal cortices but lower volumes of left postcentral and right middle temporal cortices in comparison to healthy controls. Patients with awake seizures compared to healthy controls displayed reduced volumes mainly in frontal, temporal, and parietal regions of right hemisphere. Volumes of hippocampus, amygdala, caudate, pallidum, and putamen were larger in patients with sleep seizures than in patients with awake seizures. Despite epileptogenesis, patients with sleep and awake seizures had distinct network and structural correlates across different epilepsy types. Identified regional cortical/subcortical abnormalities can endorse the pathophysiological alterations that induce seizures during the sleep or awake states.

The altered topology of brain structural network in patients with acute stress response after traffic accident

Objective: To explore the changes of brain activities in traffic accident survivors with acute stress response (ASR) within a week by using complex networks analysis method based on graph-theory, and to find out the alteration of topological properties in structural brain network. Method: From January, 2013 to February, 2016, twenty traffic accidents survivors with acute stress disorders (Acute Stress Disorder Interview, ASDI>3)and twenty healthy controls underwent the 3T diffusion tensor imaging (DTI) magnetic resonance imaging scan in Nanjing General Hospital.The graph-theory analysis method was used to compare the structural brain network properties and nodal features between ASR survivors and controls.Statistical analyses were also performed by including anxiety and depression as covariates to evaluate their effect.In additional, Pearson correlation was performed between abnormal parametric values and clinical indices. Results: (1) The brain structural networks had small-world properties in both groups; (2) while compared with healthy controls, patients with ASR showed increased weighted connectivity strength (Si, 1.36±0.47 vs 0.92±0.38, P=0.008) and nodal betweenness centrality (BCi, 20±15 vs 7±6, P=0.002) in left triangular part of inferior frontal (IFG triang_L), increased Si in orbital part of inferior frontal gyrus (1.10±0.31 vs 0.77±0.30, P=0.004) and obviously decreased Si in left caudate (0.75±0.24 vs 1.04±0.35, P=0.004); (3) furthermore, the inclusion of anxiety and depression as covariates abolished nodal parameters differences in IFG triang_L, left caudate, thalamus and inferior temporal gyrus. Conclusions: The brain structure network in ASR patients has small world properties.But nodal parameters change obviously in some nodes compared with healthy controls and mainly locate in prefrontal lobe and striatum. High levels of anxiety and depression in ASR patients may partly account for these alterations.

Analysis of structure–function network decoupling in the brain systems of spastic diplegic cerebral palsy

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc.

Brain white matter structural networks in patients with non-neuropsychiatric systemic lupus erythematosus.

Previous neuroimaging studies have revealed cognitive dysfunction in patients with systemic lupus erythematosus (SLE) and suggested that it may be related to disrupted brain white matter (WM) connectivity. However, no study has examined the topological properties of brain WM structural networks in SLE patients, especially in patients with non-neuropsychiatric SLE (non-NPSLE). In this study, we acquired DTI datasets from 28 non-NPSLE patients and 24 healthy controls, constructed their brain WM structural networks by using a deterministic fiber tracking approach, estimated the topological parameters of their structural networks, and compared their group differences. We reached the following results: 1) At the global level, the non-NPSLE patients showed significantly increased characteristic path length, normalized clustering coefficient and small-worldness, but significantly decreased global efficiency and local efficiency compared to the controls; 2) At the nodal level, the non-NPSLE patients had significantly decreased nodal efficiency in regions related to movement control, executive control, and working memory (bilateral precentral gyri, bilateral middle frontal gyri, bilateral inferior parietal lobes, left median cingulate gyrus and paracingulate gyrus, and right middle temporal gyrus). In addition, to pinpointing the injured WM fiber tracts in the non-NPSLE patients, we reconstructed the major brain WM pathways connecting the abnormal regions at the nodal level with the corticospinal tract (CST), superior longitudinal fasciculus-parietal terminations (SLFP), and superior longitudinal fasciculus-temporal terminations (SLFT). By analyzing the diffusion parameters along these WM fiber pathways, we detected abnormal diffusion parameters in the bilateral CST and right SLFT in the non-NPSLE patients. These results seem to indicate that injured brain WM connectivity exists in SLE patients even in the absence of neuropsychiatric symptoms.

The Characteristics of Brain Structural Network in Patients with Low Grade Glioma Revealed by Diffusion Tensor Imaging

Purpose: At present, few studies have investigated the functional performance in patients with low grade glioma (LGG) from the perspective of brain structural characteristics. This study aimed to analyze the topological properties of brain structural networks in LGG patients and investigate the influence of operation and lesion location on whole-brain and hemisphere networks. On this basis, the structural plasticity and function compensatory mechanism of LGG patient were discussed. Method : We constructed whole-brain and hemisphere anatomical networks for 20 LGG patients and 20 normal controls (NC). The structural connections were established by selecting an appropriate connectivity threshold. Brain hub nodes and random nodes between LGG and NC were compared. Statistical analyses were performed to reveal the significant differences of various network characteristics between LGG patients and NC as well as between LGG patients before and after operation. The two-factor variance analysis was used to investigate the influence of operation and lesion location on whole-brain and hemisphere networks. Results: From the graph-based topological metrics of the constructed network, various global parameters changed significantly in LGG patients. Meanwhile, altered regions in the LGG patients was obtained and various nodal parameters were further calculated in each region. Most of hub nodes were identical between LGG and NC groups, while the betweenness centrality values of those hub nodes and some random nodes were higher in the LGG patients. By comparing LGG patients pre- and post- operation, more significantly altered network metrics were obtained from hemisphere network analysis than that from whole-brain network analysis, and network features of dominant hemisphere changed more drastically when the lesion is located in the same hemisphere. Conclusion: To conclude, the present study indicates the existence of compensatory mechanism in LGG patients to adapt to cognitive requirements. Function reorganization and the rewiring of neuronal circuits allow signal transmission bypassing the lesion area or surgical trauma. It also suggests that graph-based topological metrics analysis could become a useful method to provide valuable indices of brain function in the evaluation of the LGG.

Radiation-Induced Changes in Structural Network in Patients with Nasopharyngeal Carcinoma

Radiation therapy (RT) is the standard radical treatment for nasopharyngeal carcinoma (NPC), and has produced excellent effects in terms of survival rate [1, 2]. However, one of the serious complications gave rise by the RT is brain injury. Previous studies have found that RT could cause brain structural abnormalities on gray matter and white matter. Nevertheless, the RT effects on the network level should be further investigated. Herein, we explored changes on the structural network for patients with NPC induced by RT. The structural magnetic resonance data (sMRI) were used to investigate the structural network in 20 NPC patients after and before radiotherapy. After constructing the structural network, we examined the radiation-induced changes in topology properties of small world network using graph theoretical analysis. Our results found that both the before and after radiotherapy groups showed small world properties. Compared with the before radiotherapy (pre-RT) group, the after radiotherapy (post-RT) group had lower global and local efficiency, longer shortest path length, and less clustering coefficient. In addition, the hub regions in the post-RT group were significantly different from the pre-RT group. Our findings exhibited the architecture of network topology and information transfer efficiency became poor in post-RT group. We speculated radiation therapy might induce the differences. The results can provide a new perspective to explore and diagnose radiation-induced brain injury and evaluate the effect of radiotherapy.

Alterations of white matter structural networks in patients with non-neuropsychiatric systemic lupus erythematosus identified by probabilistic tractography and connectivity-based analyses.

PurposeSystemic lupus erythematosus (SLE) is a chronic inflammatory female-predominant autoimmune disease that can affect the central nervous system and exhibit neuropsychiatric symptoms. In SLE patients without neuropsychiatric symptoms (non-NPSLE), recent diffusion tensor imaging studies showed white matter abnormalities in their brains. The present study investigated the entire brain white matter structural connectivity in non-NPSLE patients by using probabilistic tractography and connectivity-based analyses.MethodsWhole-brain structural networks of 29 non-NPSLE patients and 29 healthy controls (HCs) were examined. The structural networks were constructed with interregional probabilistic connectivity. Graph theory analysis was performed to investigate the topological properties, and network-based statistic was employed to assess the alterations of the interregional connections among non-NPSLE patients and controls.ResultsCompared with HCs, non-NPSLE patients demonstrated significantly decreased global and local network efficiencies and showed increased characteristic path length. This finding suggests that the global integration and local specialization were impaired. Moreover, the regional properties (nodal efficiency and degree) in the frontal, occipital, and cingulum regions of the non-NPSLE patients were significantly changed and negatively correlated with the disease activity index. The distribution pattern of the hubs measured by nodal degree was altered in the patient group. Finally, the non-NPSLE group exhibited decreased structural connectivity in the left median cingulate-centered component and increased connectivity in the left precuneus-centered component and right middle temporal lobe-centered component.ConclusionThis study reveals an altered topological organization of white matter networks in non-NPSLE patients. Furthermore, this research provides new insights into the structural disruptions underlying the functional and neurocognitive deficits in non-NPSLE patients.

Anomalous gray matter structural networks in patients with hepatitis B virus-related cirrhosis without overt hepatic encephalopathy.

Background and PurposeIncreasing evidence suggests that cirrhosis may affect the connectivity among different brain regions in patients before overt hepatic encephalopathy (OHE) occurs. However, there has been no study investigating the structural reorganization of these altered connections at the network level. The primary focus of this study was to investigate the abnormal topological organization of the structural network in patients with hepatitis B virus-related cirrhosis (HBV-RC) without OHE using structural MRI.MethodsUsing graph theoretical analysis, we compared the global and regional topological properties of gray matter structural networks between 28 patients with HBV-RC without OHE and 30 age-, sex- and education-matched healthy controls. The structural correlation networks were constructed for the two groups based on measures of gray matter volume.ResultsThe brain network of the HBV-RC group exhibited a significant decrease in the clustering coefficient and reduced small-worldness at the global level across a range of network densities. Regionally, brain areas with altered nodal degree/betweenness centrality were observed predominantly in association cortices (frontal and temporal regions) (p < 0.05, uncorrected), including a significantly decreased nodal degree in the inferior temporal gyrus (p < 0.001, uncorrected). Furthermore, the HBV-RC group exhibited a loss of association hubs and the emergence of an increased number of non-association hubs compared with the healthy controls.ConclusionThe results of this large-scale gray matter structural network study suggest reduced topological organization efficiency in patients with HBV-RC without OHE. Our findings provide new insight concerning the mechanisms of neurobiological reorganization in the HBV-RC brain from a network perspective.

Altered cortical network in female with adolescent idiopathic scoliosis

Objective The aim of the study was to investigate abnormalities in the organization of the brain cortical network in patients with AIS based on MR data. Adolescent idiopathic scoliosis (AIS) is a three dimensional spinal deformity that affects teenagers especially girls between the ages of 10-16 at prevalence of 1-4%. The etiopathogenesis remains uncertain but scientific studies have suggested it is a multifactorial disease included different intrinsic and extrinsic factors. A recent study has demonstrated the abnormal cortical thickness between patients with AIS and healthy controls. Cortical thickness is strongly correlated between regions that are axonally connected. Hence, the hypothesis of altered organization pattern of large-scale structural network in patients with AIS has been tested in this study.

Altered Topological Organization of White Matter Structural Networks in Patients with Neuromyelitis Optica

ObjectiveTo investigate the topological alterations of the whole-brain white-matter (WM) structural networks in patients with neuromyelitis optica (NMO).MethodsThe present study involved 26 NMO patients and 26 age- and sex-matched healthy controls. WM structural connectivity in each participant was imaged with diffusion-weighted MRI and represented in terms of a connectivity matrix using deterministic tractography method. Graph theory-based analyses were then performed for the characterization of brain network properties. A multiple linear regression analysis was performed on each network metric between the NMO and control groups.ResultsThe NMO patients exhibited abnormal small-world network properties, as indicated by increased normalized characteristic path length, increased normalized clustering and increased small-worldness. Furthermore, largely similar hub distributions of the WM structural networks were observed between NMO patients and healthy controls. However, regional efficiency in several brain areas of NMO patients was significantly reduced, which were mainly distributed in the default-mode, sensorimotor and visual systems. Furthermore, we have observed increased regional efficiency in a few brain regions such as the orbital parts of the superior and middle frontal and fusiform gyri.ConclusionAlthough the NMO patients in this study had no discernible white matter T2 lesions in the brain, we hypothesize that the disrupted topological organization of WM networks provides additional evidence for subtle, widespread cerebral WM pathology in NMO.

Diffusion Tensor Tractography Reveals Disrupted Topological Efficiency in White Matter Structural Networks in Multiple Sclerosis

Little is currently known about the alterations in the topological organization of the white matter (WM) structural networks in patients with multiple sclerosis (MS). In the present study, we used diffusion tensor imaging and deterministic tractography to map the WM structural networks in 39 MS patients and 39 age- and gender-matched healthy controls. Graph theoretical methods were applied to investigate alterations in the network efficiency in these patients. The MS patients and the controls exhibited efficient small-world properties in their WM structural networks. However, the global and local network efficiencies were significantly decreased in the MS patients compared with the controls, with the most pronounced changes observed in the sensorimotor, visual, default-mode, and language areas. Furthermore, the decreased network efficiencies were significantly correlated with the expanded disability status scale scores, the disease durations, and the total WM lesion loads. Together, the results suggest a disrupted integrity in the large-scale brain systems in MS, thus providing new insights into the understanding of MS connectome. Our data also suggest that a topology-based brain network analysis can provide potential biomarkers for disease diagnosis and for monitoring the progression and treatment effects for patients with MS.