Alterations in Structural and Functional Connectivities in Patients with End-Stage Renal Disease

Persistent proteinuria is associated with the occurrence of cardiovascular disease: a nationwide population-based cohort study

Proteinuria is an important risk factor for cardiovascular disease (CVD) and acts as a surrogate marker of renal damage. This study aimed to determine the association between changes in proteinuria and the occurrence of CVD. In our study, 1,708,712 participants who consecutively underwent national health examinations from 2003-2004 (first period) to 2005-2006 (second period) were included. They were classified into four groups based on the presence of proteinuria at the two consecutive health examinations: (1) normal (0 → 0), (2) proteinuria-improved (participants who had improved proteinuria (+ 1 → 0, + 2 → ≤ +1 [0 or + 1], ≥ +3 → ≤ +2 [0, + 1 or + 2]), (3) proteinuria-progressed (0 → ≥ +1, + 1 → ≥ +2, + 2 → ≥ +3), and (4) proteinuria-persistent (+ 1 → +1, + 2 → +2, ≥ +3 → ≥ +3). We used a multivariate Cox proportional hazards model to assess the occurrence of CVD according to changes of presence and severity of proteinuria. During a median of 14.2 years of follow-up, 143,041 participants (event rate, 8.37%) with composite CVD were observed. Compared with the normal group, the risk of incident risk of CVD was increased according to the severity of proteinuria in each of the persistent, progressed, and improved groups (p for trend < 0.001). In a pairwise comparison, the risk of composite CVD in the improved (hazard ratio [HR]: 1.32, 95% confidence interval [CI]: 1.27-1.37), progressed (HR: 1.49, 95% CI: 1.44-1.54), and persistent groups (HR: 1.78, 95% CI: 1.64-1.94) were higher than that of the normal group. Furthermore, the improved group had a relatively lower risk of composite CVD compared to the persistent group (HR: 0.75, 95% CI: 0.69-0.83, p < 0.001). The incidence risk of composite CVD was associated with changes of presence and severity of proteinuria. Persistent proteinuria may be associated with increased risk of CVD, even compared with improved or progressed proteinuria status.

Alteration of multilayer network perspective on gray and white matter connectivity in obstructive sleep apnea

PURPOSE

The objective of this research was to examine changes in the neural networks of both gray and white matter in individuals with obstructive sleep apnea (OSA) in comparison to those without the condition, employing a comprehensive multilayer network analysis.

METHODS

Patients meeting the criteria for OSA were recruited through polysomnography, while a control group of healthy individuals matched for age and sex was also assembled. Utilizing T1-weighted imaging, a morphometric similarity network was crafted to represent gray matter, while diffusion tensor imaging provided structural connectivity for constructing a white matter network. A multilayer network analysis was then performed, employing graph theory methodologies.

RESULTS

We included 40 individuals diagnosed with OSA and 40 healthy participants in our study. Analysis revealed significant differences in various global network metrics between the two groups. Specifically, patients with OSA exhibited higher average degree overlap and average multilayer clustering coefficient (28.081 vs. 23.407, p < 0.001; 0.459 vs. 0.412, p = 0.004), but lower multilayer modularity (0.150 vs. 0.175, p = 0.001) compared to healthy controls. However, no significant differences were observed in average multiplex participation, average overlapping strength, or average weighted multiplex participation between the patients with OSA and healthy controls. Moreover, several brain regions displayed notable differences in degree overlap at the nodal level between patients with OSA and healthy controls.

CONCLUSION

Remarkable alterations in the multilayer network, indicating shifts in both gray and white matter, were detected in patients with OSA in contrast to their healthy counterparts. Further examination at the nodal level unveiled notable changes in regions associated with cognition, underscoring the effectiveness of multilayer network analysis in exploring interactions across brain layers.

Difference in functional connectivity between end-stage renal disease patients with and without restless legs syndrome: A prospective study

PURPOSE

The purpose of this study was to examine differences in functional connectivity between patients with end-stage renal disease (ESRD) with and without restless legs syndrome (RLS). In addition, the study aimed to identify any potential associations between RLS severity and functional connectivity.

METHODS

We enrolled patients with ESRD who had been undergoing hemodialysis. Patients with and without RLS were separated into two groups. Using functional near-infrared spectroscopy (fNIRS) and a graph theory approach, we determined the functional connectivity of patients with ESRD. The data were collected during a 300-s resting state evaluation performed in the dialysis room prior to dialysis.

RESULTS

Eighteen of 48 patients with ESRD were diagnosed with RLS, whereas 30 patients did not exhibit RLS symptoms. Notably, functional connectivity metrics differed significantly between patients with and without RLS. Specifically, patients with ESRD and RLS displayed higher values for mean clustering coefficient (0.474 vs. 0.352, p = 0.001), global efficiency (0.520 vs. 0.414, p = 0.001), strength (6.538 vs. 4.783, p = 0.001), and transitivity (0.714 vs. 0.521, p = 0.001), while values for diameter (5.451 vs. 7.338, p = 0.002), eccentricity (4.598 vs. 5.985, p = 0.004), and characteristic path length (2.520 vs. 3.271, p = 0.002) were lower in patients with ESRD and RLS compared to those without RLS. In addition, there were correlations between the RLS severity score and the assortative coefficient (r = 0.479, p = 0.044), the small-worldness index (r = -0.475, p = 0.046), and transitivity (r = 0.500, p = 0.034).

CONCLUSIONS

We demonstrated differences in functional connectivity between patients with ESRD with and without RLS, which may shed light on the pathophysiology of RLS. Notably, a number of functional connectivity metrics demonstrated strong associations with RLS severity. Our study also confirmed the applicability of fNIRS as a tool for investigating functional connectivity in patients with RLS.

Redefining the role of the cerebellum in restless legs syndrome

OBJECTIVES

We aimed to investigate alterations in cerebellar volume and the intrinsic cerebellar network in patients with restless legs syndrome (RLS).

METHODS

We recruited 69 patients with RLS and 50 healthy controls who underwent brain magnetic resonance imaging (MRI), including three-dimensional T1-weighted imaging. The total cerebellar volume and cerebellar volume subdivisions were analyzed through automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization program. The intrinsic cerebellar network was calculated through brain analysis using a graph theory program based on the cerebellar volume subdivisions. The cerebellar volumes and intrinsic cerebellar networks were compared between patients with RLS and healthy controls.

RESULTS

The cerebellar volume and subdivisions in patients with RLS did not show significant differences compared to those in healthy controls. However, significant alterations were observed in the intrinsic cerebellar network of patients with RLS. Increased mean clustering coefficient (0.185 vs. 0.114; p = 0.047) and small-worldness index (0.927 vs. 0.800; p = 0.047) were observed in patients with RLS. Additionally, total cerebellar volume was negatively correlated with the Pittsburgh Sleep Quality Index (r = -0.398; p = 0.020) and Insomnia Severity Index (ISI; r = -0.396; p = 0.011). Negative correlations were additionally observed between the right X lobule volume and the International Restless Legs Syndrome Severity Scale (r = -0.425; p = 0.008) and between the vermis VIII volume and ISI score (r = -0.399; p = 0.011).

CONCLUSION

We demonstrated alterations in the intrinsic cerebellar network in patients with RLS compared with healthy controls, showing increased connectivity with increased segregation in patients with RLS. This suggests a potential role of the cerebellum in RLS pathophysiology.

The effects of the dialysis on the white matter tracts in patients with end-stage renal disease using differential tractography study

This study aimed to determine whether white matter tracts correlate with kidney function using correlation tractography, and to investigate the effects of dialysis on white matter tracts in patients with end-stage renal disease (ESRD) using differential tractography. Ten patients with ESRD, who had a glomerular filtration rate of < 15 mL/min/1.73 m2, were enrolled in this prospective study. Diffusion tensor imaging (DTI) was performed both before and after dialysis. We discovered that white matter tracts correlated with the estimated glomerular filtration rate based on pre- and post-dialysis DTI using correlation tractography and investigated the differences in the white matter tracts between pre- and post-dialysis DTI in patients with ESRD using differential tractography. Correlation tractography revealed no quantitative anisotropy of the white matter tracts that correlated with the estimated glomerular filtration rate in pre- and post-dialysis patients with ESRD. Differential tractography revealed significant differences in several white matter tracts, particularly the cingulum, thalamic radiation, corpus callosum, and superior longitudinal fasciculus, between pre- and post-dialysis DTI, which revealed increased diffusion density after dialysis. We demonstrated the significant effects of dialysis on several white matter tracts in patients with ESRD using differential tractography, which showed increased diffusion density after dialysis. In this study, we confirmed the effects of dialysis on brain structure, especially white matter tracts.

Changes in Cerebral Blood Flow in Patients Who Receive Different Durations of Hemodialysis: An Arterial Spin Labeling MRI Study

BACKGROUND AND PURPOSE

This study aimed to determine the changes in cerebral blood flow (CBF) in patients who received different durations of hemodialysis (HD) using arterial spin labeling magnetic resonance imaging.

METHODS

The study included 46 patients who received HD and 24 demographically similar healthy controls (HCs). Patients who received HD were divided into three subgroups based on its duration: HD-1 (n=15, dialysis duration ≤24 months), HD-2 (n=16, dialysis duration >24 and ≤72 months), and HD-3 (n=15, dialysis duration ≥73 months). All subjects completed the Mini Mental State Examination and Montreal Cognitive Assessment tests, and the patients who received HD underwent laboratory tests. Group-level differences in the global and regional CBFs between patients who received HD and HCs were assessed. Correlation analysis was performed to evaluate the associations among CBF, clinical variables, and cognitive function.

RESULTS

Compared with HCs, global and regional CBFs were significantly increased in the HD-1 and HD-2 groups (p<0.05), but there was no significant difference in the HD-3 group (p>0.05). However, compared with the HD-1 group, the HD-3 group had significantly decreased global and regional CBFs (p<0.05). The cognitive function was worse in patients who received long-term HD than in HCs. Increased dialysis duration and hemoglobin level were predictive risk factors for decreased CBF in patients who received long-term HD.

CONCLUSIONS

Patients who received long-term HD with normal CBF had worse cognitive function, which may be related to increased dialysis duration.

Differences in functional network between focal onset nonconvulsive status epilepticus and toxic metabolic encephalopathy: application to machine learning models for differential diagnosis

We aimed to compare network properties between focal-onset nonconvulsive status epilepticus (NCSE) and toxic/metabolic encephalopathy (TME) during periods of periodic discharge using graph theoretical analysis, and to evaluate the applicability of graph measures as markers for the differential diagnosis between focal-onset NCSE and TME, using machine learning algorithms. Electroencephalography (EEG) data from 50 focal-onset NCSE and 44 TMEs were analyzed. Epochs with nonictal periodic discharges were selected, and the coherence in each frequency band was analyzed. Graph theoretical analysis was performed to compare brain network properties between the groups. Eight different traditional machine learning methods were implemented to evaluate the utility of graph theoretical measures as input features to discriminate between the two conditions. The average degree (in delta, alpha, beta, and gamma bands), strength (in delta band), global efficiency (in delta and alpha bands), local efficiency (in delta band), clustering coefficient (in delta band), and transitivity (in delta band) were higher in TME than in NCSE. TME showed lower modularity (in delta band) and assortativity (in alpha, beta, and gamma bands) than NCSE. Machine learning algorithms based on EEG global graph measures classified NCSE and TME with high accuracy, and gradient boosting was the most accurate classification model with an area under the receiver operating characteristics curve of 0.904. Our findings on differences in network properties may provide novel insights that graph measures reflecting the network properties could be quantitative markers for the differential diagnosis between focal-onset NCSE and TME.

The effects of hemodialysis on the functional brain connectivity in patients with end-stage renal disease with functional near-infrared spectroscopy

This study aimed to investigate functional brain connectivity in patients with end-stage renal disease (ESRD) undergoing hemodialysis using functional near-infrared spectroscopy (fNIRS) and to analyze the effect of hemodialysis on functional brain connectivity. We prospectively enrolled patients with ESRD undergoing hemodialysis for > 6 months without any history of neurological or psychiatric disorders. fNIRS data were acquired using a NIRSIT Lite device. Measurements were performed thrice in the resting state for each patient: before the start of hemodialysis (pre-HD), 1 h after the start of hemodialysis (mid-HD), and after the end of hemodialysis (post-HD). We processed and exported all data, and created a weighted connectivity matrix using Pearson correlation analysis. We obtained functional connectivity measures from the connectivity matrix by applying a graph theoretical analysis. We then compared differences in functional connectivity measures according to hemodialysis status in patients with ESRD. We included 34 patients with ESRD. There were significant changes in the mean clustering coefficient, transitivity, and assortative coefficient between the pre- and post-HD periods (0.353 vs. 0.399, p = 0.047; 0.523 vs. 0.600, p = 0.042; and 0.043 vs. - 0.012, p = 0.044, respectively). However, there were no changes in the mean clustering coefficient, transitivity, and assortative coefficient between the pre- and mid-HD periods, or between the mid- and post-HD periods. In addition, there were no significant differences in the average strength, global efficiency, and local efficiency among the pre-, mid-, and post-HD periods. We demonstrated a significant effect of hemodialysis on functional brain connectivity in patients with ESRD. Functional brain connectivity changes more efficiently during hemodialysis.

Altered Resting-State Functional Networks in Nondialysis Patients with Stage 5 Chronic Kidney Disease: A Graph-Theoretical Analysis

This study aimed to investigate the topological characteristics of the resting-state functional network and the underlying pathological mechanism in nondialysis patients with stage 5 chronic kidney disease (CKD5 ND). Eighty-five subjects (21 patients with CKD5 ND, 32 patients with CKD on maintenance hemodialysis (HD), and 32 healthy controls (HCs)) underwent laboratory examinations, neuropsychological tests, and brain magnetic resonance imaging. The topological characteristics of networks were compared with a graph-theoretical approach, and correlations between neuropsychological scores and network properties were analyzed. All participants exhibited networks with small-world attributes, and global topological attributes were impaired in both groups of patients with CKD 5 (ND and HD) compared with HCs (p < 0.05); these impairments were more severe in the CKD5 ND group than in the HD group (p < 0.05). Compared with the HC group, the degree centrality of the CKD5 ND group decreased mainly in the basal ganglia and increased in the bilateral orbitofrontal gyrus, bilateral precuneus, and right cuneus. Correlation analysis showed that the degree of small-worldness, normalized clustering coefficients, and Montreal Cognitive Assessment (MoCA) scores were positively correlated and that characteristic path length was negatively correlated with these variables in patients with CKD5 ND. The nodal efficiency of the bilateral putamen (r = 0.53, p < 0.001 and r = 0.47, p < 0.001), left thalamus (r = 0.37, p < 0.001), and right caudate nucleus (r = 0.28, p = 0.01) was positively correlated with MoCA scores. In conclusion, all CKD5 ND patients exhibited changes in functional network topological properties and were closely associated with mild cognitive impairment. More interestingly, the topological property changes in CKD5 ND patients were dominated by basal ganglia areas, which may be more helpful to understand and possibly reveal the underlying pathological mechanisms of cognitive impairment in CKD5 ND.

Aberrant brain gray matter and functional networks topology in end stage renal disease patients undergoing maintenance hemodialysis with cognitive impairment

Purpose

To characterize the topological properties of gray matter (GM) and functional networks in end-stage renal disease (ESRD) patients undergoing maintenance hemodialysis to provide insights into the underlying mechanisms of cognitive impairment.

Materials and methods

In total, 45 patients and 37 healthy controls were prospectively enrolled in this study. All subjects completed resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) examinations and a Montreal cognitive assessment scale (MoCA) test. Differences in the properties of GM and functional networks were analyzed, and the relationship between brain properties and MoCA scores was assessed. Cognitive function was predicted based on functional networks by applying the least squares support vector regression machine (LSSVRM) and the whale optimization algorithm (WOA).

Results

We observed disrupted topological organizations of both functional and GM networks in ESRD patients, as indicated by significantly decreased global measures. Specifically, ESRD patients had impaired nodal efficiency and degree centrality, predominantly within the default mode network, limbic system, frontal lobe, temporal lobe, and occipital lobe. Interestingly, the involved regions were distributed laterally. Furthermore, the MoCA scores significantly correlated with decreased standardized clustering coefficient (γ), standardized characteristic path length (λ), and nodal efficiency of the right insula and the right superior temporal gyrus. Finally, optimized LSSVRM could predict the cognitive scores of ESRD patients with great accuracy.

Conclusion

Disruption of brain networks may account for the progression of cognitive dysfunction in ESRD patients. Implementation of prediction models based on neuroimaging metrics may provide more objective information to promote early diagnosis and intervention.

Intravoxel incoherent motion to assess brain microstructure and perfusion in patients with end-stage renal disease

BACKGROUND AND PURPOSE

This study aimed to investigate the clinical value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in evaluating the brain microstructure and perfusion changes in end-stage renal disease (ESRD) patients.

METHODS

The routine head MRI sequences and IVIM were performed on 40 ESRD patients and 30 healthy subjects. The IVIM was executed with 10 b-values varying from 0 to 1000 seconds/mm² . All subjects were evaluated on neuropsychological test. Laboratory tests were conducted for ESRD patients.

RESULTS

Compared with the control group, increased slow apparent diffusion coefficient values (ADC_slow ) were found in the left frontal lobe, hippocampus, bilateral temporal lobe, and the right occipital lobe (p < .05), and increased fast ADC values (ADC_fast ) were found in all regions of interest (all p < .001) in ESRD patients. In ESRD patients, ADC_fast in right frontal lobe (p = .041) and insular lobe (p = .045) was negatively correlated with the Montreal Cognitive Assessment score (MoCA), and ADC_fast in the right parietal lobe (p = .009) and hippocampus (p = .041) had positive correlation with hemoglobin levels. Using receiver operating characteristics (ROC) analysis, ADC_fast in the right frontal lobe, insular lobe, hippocampus, and parietal lobe separately showed fair to good efficacy in differentiating ESRD patients from healthy subjects, with the area under the ROC ranging from .853 to .903.

CONCLUSIONS

The microstructure and perfusion of the brain were impaired in ESRD patients. ADC_fast of the right frontal lobe, insular lobe, hippocampus, and parietal lobe could be effective biomarker for evaluating cognitive impairment in ESRD patients.

K-Means Clustering Algorithm–Based Functional Magnetic Resonance for Evaluation of Regular Hemodialysis on Brain Function of Patients with End-Stage Renal Disease

This research was to evaluate the effects of regular hemodialysis (HD) on the brain function of patients with end-stage renal disease (ESRD). Resting-state functional magnetic resonance imaging (rs-fMRI) based on improved k-means clustering algorithm (k-means) was proposed to scan the brains of 30 regular dialysis patients with end-stage renal disease (ESRD) (experimental group) and 30 normal volunteers (control group). The proposed algorithm was compared with the traditional k-means algorithm and mean shift algorithm and applied to the magnetic resonance scan of patients with ESRD on long-term regular HD. The results showed that the neuropsychological cognitive function (NSCF) evaluation result of the test group was much better than that of the control group, and the difference was statistically obvious (P < 0.05). The results of blood biochemistry, Digit Symbol Substitution Test (DSST), and Montreal Cognitive Assessment Scale (MoCA) in the test group showed no statistical difference compared with those in the control group. The running time of the improved k-means algorithm was dramatically shorter than that of traditional k-means algorithm, showing statistical difference (P < 0.05). Comparison among the improved and traditional k-means algorithm and mean shift algorithm suggested that the improved k-means algorithm showed a lower error rate for image segmentation, and the differences were statistically remarkable (P < 0.05). In conclusion, the improved k-means algorithm showed better time efficiency and the lowest error rate in processing rs-fMRI images than the traditional k-means algorithm and mean shift algorithm, and the effects of regular HD on the brains of patients with ESRD were evaluated effectively.

Abnormal Dynamic Functional Connectivity in Patients With End-Stage Renal Disease

Dynamic functional connectivity (FC) analysis can capture time-varying properties of connectivity; however, studies focusing on dynamic FC in patients with end-stage renal disease (ESRD) are very limited. This is the first study to explore the dynamic aspects of whole-brain FC and topological properties in ESRD patients. Resting-state functional magnetic resonance imaging data were acquired from 100 ESRD patients [50 hemodialysis (HD) patients and 50 non-dialysis patients] and 64 healthy controls (HCs). Independent component analysis, a sliding-window approach and graph-theory methods were used to study the dynamic FC properties. The intrinsic brain FC were clustered into four configuration states. Compared with HCs, both patient groups spent longer time in State 3, in which decreased FC between subnetworks of the default mode network (DMN) and between the dorsal DMN and language network was observed in these patients, and a further reduction in FC between the DMN subnetworks was found in HD patients compared to non-dialysis patients. The number of transitions and the variability of global and local efficiency progressively decreased from that in HCs to that of non-dialysis patients to that of HD patients. The completion time of Trail Making Test A and Trail Making Test B positively correlated with the mean dwell time of State 3 and negatively correlated with the number of transitions in ESRD patients. Our findings suggest impaired functional flexibility of network connections and state-specific FC disruptions in patients with ESRD, which may underlie their cognitive deficits. HD may have an adverse effect on time-varying FC.

Brain networks in migraine with and without aura: An exploratory arterial spin labeling MRI study

OBJECTIVES

The aim of this exploratory study was to investigate the underlying pathomechanisms of migraine with aura (MA) and migraine without aura (MO) in the interictal phase using a connectivity analysis.

METHODS

We prospectively enrolled patients who were newly diagnosed with migraine. All patients underwent brain MRI, including diffusion tensor imaging and arterial spin labeling perfusion MRI. We analyzed the differences between patients with MA and those with MO in structural connectivity based on diffusion tensor imaging and functional connectivity based on arterial spin labeling perfusion MRI using a graph theoretical analysis.

RESULTS

We enrolled 58 patients with migraine (11 patients with MA and 47 patients with MO). There were no differences between patients with MA and those with MO in the network measures of global structural connectivity. However, differences in global functional connectivity were found between the two groups. The assortative coefficient was lower in patients with MA than in those with MO (-0.050 vs. -0.012, p = .017). There were no differences in local structural and functional connectivity between patients with MA and those with MO.

CONCLUSION

We found differences in global functional connectivity between patients with MO and those with MA. The study of MA and MO using a connectivity analysis may shed light on migraine pathophysiology. We suggest it is worthwhile to investigate if changes in functional connectivity may serve as novel biomarkers in MA. In this regard, ASL MRI appears to be valuable in the context of network analysis, but further studies are needed to confirm our findings.

Associations of the Disrupted Functional Brain Network and Cognitive Function in End-Stage Renal Disease Patients on Maintenance Hemodialysis: A Graph Theory-Based Study of Resting-State Functional Magnetic Resonance Imaging

Objective: Cognitive impairment (CI) is a common neurological complication in patients with end-stage renal disease undergoing maintenance hemodialysis (MHD). Brain network analysis based on graph theory is a promising tool for studying CI. Therefore, the purpose of this study was to analyze the changes of functional brain networks in patients on MHD with and without CI by using graph theory and further explore the underlying neuropathological mechanism of CI in these patients. Methods: A total of 39 patients on MHD (19 cases with CI and 20 without) and 25 healthy controls (HCs) matched for age, sex, and years of education were enrolled in the study. Resting-state functional magnetic resonance imaging (rs-fMRI) and T1-weighted high-resolution anatomical data were obtained, and functional brain networks for each subject were constructed. The brain network parameters at the global and regional levels were calculated, and a one-way analysis of covariance was used to compare the differences across the three groups. The associations between the changed graph-theory parameters and cognitive function scores in patients on MHD were evaluated using Spearman correlation analysis. Results: Compared with HCs, the global parameters [sigma, gamma, and local efficiency (Eloc)] in both patient groups decreased significantly (p < 0.05, Bonferroni corrected). The clustering coefficient (Cp) in patients with CI was significantly lower than that in the other two groups (p < 0.05, Bonferroni corrected). The regional parameters were significantly lower in the right superior frontal gyrus, dorsolateral (SFGdor) and gyrus rectus (REC) of patients with CI than those of patients without CI; however the nodal local efficiency in the left amygdala was significantly increased (all p < 0.05, Bonferroni corrected). The global Cp and regional parameters in the three brain regions (right SFGdor, REC, and left amygdala) were significantly correlated with the cognitive function scores (all FDR q < 0.05). Conclusion: This study confirmed that the topology of the functional brain network was disrupted in patients on MHD with and without CI and the disruption of brain network was more severe in patients with CI. The abnormal brain network parameters are closely related to cognitive function in patients on MHD.

Decreased Neural Connectivity in the Default Mode Network Among Youth and Young Adults With Chronic Kidney Disease

An increasing amount of literature has indicated that chronic kidney disease (CKD) is associated with cognitive deficits that increase with worsening disease severity. Although abnormalities in brain structure have been widely documented, few studies to date have examined the functioning of brain areas associated with the specific cognitive domains affected by CKD (namely, attention and executive functions). Furthermore, few studies have examined functional connectivity among CKD youth who are relatively early in the course of the disease. The present study used functional magnetic resonance imaging to examine the resting state connectivity in 67 youth with CKD (mean age, 17 y) and 58 age-matched healthy controls. Using seed-based multiple regression, decreased connectivity was observed within the anterior cingulate portion of the default mode network. In addition, decreased connectivity within the dorsolateral prefrontal cortex, paracingulate gyrus, and frontal pole were correlated significantly with disease severity. These data indicate that connectivity deficits in circuits implementing attentional processes may represent an early marker for cognitive decline in CKD.

Diffusion Tensor Imaging Features of Watershed Segmentation Algorithm for Analysis of the Relationship between Depression and Brain Nerve Function of Patients with End-Stage Renal Disease

The aim of this research was to explore the relationship between depression and brain nerve function in patients with end-stage renal disease (ESRD) and long-term maintenance hemodialysis (MHD) based on watershed segmentation algorithm using diffusion tensor imaging (DTI) technology. A total of 29 ESRD patients with depression who received MHD treatment in the hemodialysis center of hospital were included as the research subjects (case group). A total of 29 healthy volunteers were recruited as the control group, and a total of 29 ESRD patients with depression and brain lesions were recruited as the control group (HC group). Within 24 h after hemodialysis, the blood biochemical indexes were collected before this DTI examination. All participants completed the neuropsychological scale (MoCA, TMT A, DST, SAS, and SDS) test. The original DTI data of all subjects were collected and processed based on watershed segmentation algorithm, and the results of automatic segmentation according to the image were evaluated as DSC = 0.9446, MPA = 0.9352, and IOU = 0.8911. Finally, the average value of imaging brain neuropathy in patients with depression in the department of nephrology was obtained. The differences in neuropsychological scale scores (PSQI, MoCA, TMTA, DST, SAS, and SDS) between the two groups were statistically significant (P < 0.05). The differences of FA values in all the white matter partitions of Fu organs, except the cingulum of hippocampus (CgH) between the two groups, were statistically significant (P < 0.05). ESRD and DTI quantitative detection under the guidance of watershed segmentation algorithm in MHD patients showed that ESRD patients can be early identified, so as to carry out psychological nursing as soon as possible to reduce the occurrence of depression, and then protect the brain nerve to reduce brain neuropathy.

Network differences based on arterial spin labeling related to anti-seizure medication response in focal epilepsy

PURPOSE

The aim of this study was to determine whether anti-seizure medication (ASM) response is associated with structural connectivity in diffusion tensor imaging (DTI) or functional co-variance network in arterial spin labeling (ASL) magnetic resonance imaging (MRI) in patients with focal epilepsy.

METHODS

In this retrospective study conducted at a tertiary hospital, we enrolled 105 patients with focal epilepsy, of which 64 patients were good ASM responders, and 41 patients were poor ASM responders. All patients showed normal MRI findings on visual inspection and underwent DTI and ASL MRI from August 2018 to July 2020, with regular follow-up for at least 12 months after epilepsy diagnosis while taking ASMs. We calculated the structural connectivity based on DTI and functional co-variance network based on ASL MRI by using graph theory and analyzed their differences in relation to the ASM response.

RESULTS

No differences were observed in structural connectivity between the good and poor ASM responders. However, significant differences were observed in functional co-variance network between the good and poor ASM responders. In comparison with good ASM responders, poor ASM responders showed a significantly greater characteristic path length (2.557 vs. 1.753, p = 0.034) and a lower local efficiency (2.311 vs. 3.927, p = 0.048).

CONCLUSION

Significant differences were observed in functional co-variance network based on ASL MRI between the good and poor ASM responders. These findings suggest that functional co-variance network could serve as a new biomarker of ASM response in focal epilepsy.

Temporal lobe epilepsy with or without hippocampal sclerosis: Structural and functional connectivity using advanced MRI techniques

BACKGROUND AND PURPOSE

The aim of this study was to investigate the differences in structural connectivity based on diffusion tensor imaging (DTI) and functional connectivity based on arterial spin labeling (ASL) MRI between temporal lobe epilepsy (TLE) patients with and without hippocampal sclerosis (HS).

METHODS

We enrolled 50 patients with TLE, including 25 patients with HS and 25 patients without HS, who underwent brain MRI, including DTI and ASL. We calculated the network parameters of structural connectivity based on DTI and functional connectivity based on ASL using a graph theoretical analysis. The parameters included global network measures (radius, diameter, characteristic path length, global efficiency, local efficiency, mean clustering coefficient, transitivity, assortative coefficient, and small-worldness index) and a local network measure (betweenness centrality).

RESULTS

The global and local network measures of structural connectivity were not different between TLE patients with and without HS. However, significant differences in functional connectivity existed between the two groups. The radius and diameter of the global network measures in the TLE patients with HS were significantly increased compared with those without HS (4.140 vs. 3.140, p = 0.045; 6.812 vs. 5.132, p = 0.049; respectively). No differences were detected between other global network measures of functional connectivity and local network measure.

CONCLUSIONS

Significant differences in global network measures of functional connectivity based on ASL existed between TLE patients with and without HS. These findings suggest that TLE patients with HS exhibit a more disconnected functional brain network than those without HS.

Abnormal brain functional networks in end-stage renal disease patients with cognitive impairment

INTRODUCTION

Cognitive impairment (CI) is common in patients with end-stage renal disease (ESRD). Neuroimaging studies have demonstrated structural and functional brain alterations underlying CI in patients with ESRD. However, the patterns of change in whole-brain functional networks in ESRD patients with CI remain poorly understood.

METHODS

We enrolled 66 patients with ESRD (36 patients with CI and 30 patients without CI) and 48 healthy control subjects (HCs). We calculated the topological properties using a graph theoretical analysis. An analysis of covariance (ANCOVA) was used to compare network metrics among the three groups. Moreover, we analyzed the relationships between altered network measures and clinical variables in ESRD patients with CI.

RESULTS

Compared with HCs, both patient groups showed lower local efficiency and small-worldness. ESRD patients had decreased nodal centralities in the default mode regions and right amygdala. Comparison of the two patient groups showed significantly decreased global (small-worldness) and nodal (nodal centralities in the default mode regions) properties in the CI group. Altered nodal centralities in the bilateral medial part of the superior frontal gyrus, left posterior cingulate gyrus, and right precuneus were associated with cognitive performance in the CI group.

CONCLUSION

Disrupted brain functional networks were demonstrated in patients with ESRD, which were more severe in those with CI. Moreover, impaired nodal centralities in the default mode regions might underlie CI in patients with ESRD.