Investigating Sea-Level Brain Predictors for Acute Mountain Sickness: A Multimodal MRI Study before and after High-Altitude Exposure.

BACKGROUND AND PURPOSE: Acute mountain sickness is a series of brain-centered symptoms that occur when rapidly ascending to high altitude. Predicting acute mountain sickness before high-altitude exposure is crucial for protecting susceptible individuals. The present study aimed to evaluate the feasibility of predicting acute mountain sickness after high-altitude exposure by using multimodal brain MR imaging features measured at sea level. MATERIALS AND METHODS: We recruited 45 healthy sea-level residents who flew to the Qinghai-Tibet Plateau (3650 m). We conducted T1-weighted structural MR imaging, resting-state fMRI, and arterial spin-labeling perfusion MR imaging both at sea level and high altitude. Acute mountain sickness was diagnosed for 5 days using Lake Louise Scoring. Logistic regression with Least Absolute Shrinkage and Selection Operator logistic regression was performed for predicting acute mountain sickness using sea-level MR imaging features. We also validated the predictors by using MR images obtained at high altitude. RESULTS: The incidence rate of acute mountain sickness was 80.0%. The model achieved an area under the receiver operating characteristic curve of 86.4% (sensitivity = 77.8%, specificity = 100.0%, and P < .001) in predicting acute mountain sickness At sea level, valid predictors included fractional amplitude of low-frequency fluctuations (fALFF) and degree centrality from resting-state fMRI, mainly distributed in the somatomotor network. We further learned that the acute mountain sickness group had lower levels of fALFF in the somatomotor network at high altitude, associated with smaller changes in CSF volume and higher Lake Louise Scoring, specifically relating to fatigue and clinical function. CONCLUSIONS: Our study found that the somatomotor network function detected by sea-level resting-state fMRI was a crucial predictor for acute mountain sickness and further validated its pathophysiologic impact at high altitude. These findings show promise for pre-exposure prediction, particularly for individuals in need of rapid ascent, and they offer insight into the potential mechanism of acute mountain sickness.

Higher Blood-brain barrier permeability in patients with major depressive disorder identified by DCE-MRI imaging.

BACKGROUND: Studies from animal models and clinical trials of blood and cerebrospinal fluid have proposed that blood-brain barrier (BBB) dysfunction in depression (MDD). But there are no In vivo proves focused on BBB dysfunction in MDD patients. The present study aimed to identify whether there was abnormal BBB permeability, as well as the association with clinical status in MDD patients using dynamic contrast-enhanced magnetic resonance (DCE-MRI) imaging. METHODS: Patients with MDD and healthy adults were recruited and underwent DCE-MRI and structural MRI scans. The mean volume transfer constant (Ktrans) values were calculated for a quantitative assessment of BBB leakage. For each subject, the mean Ktrans values were calculated for the whole gray matter, white matter, and 90 brain regions of the anatomical automatic labeling template (AAL). The differences in Ktrans values between patients and controls and between treated and untreated patients were compared. RESULTS: 23 MDD patients (12 males and 11 females, mean age 28.09 years) and 18 healthy controls (HC, 8 males and 10 females, mean age 30.67 years) were recruited in the study. We found that the Ktrans values in the olfactory, caudate, and thalamus were higher in MDD patients compared to healthy controls (p<0.05). The Ktrans values in the orbital lobe, anterior cingulate gyrus, putamen, and thalamus in treated patients were lower than the patients never treated. There were positive correlations between HAMD total score with Ktrans values in whole brain WM, hippocampus and thalamus. The total HAMA score was positively correlated with the Ktrans of hippocampus. CONCLUSION: These findings supported a link between blood-brain barrier leakage and depression and symptom severity. The results also suggested a role for non-invasive DCE-MRI in detecting blood-brain barrier dysfunction in depression patients.

Harmonizing T1-Weighted Images to Improve Consistency of Brain Morphology Among Different Scanner Manufacturers in Alzheimer's disease.

BACKGROUND: Brain MRI scanner variability can introduce bias in measurements. Harmonizing scanner variability is crucial. PURPOSE: To develop a harmonization method aimed at removing scanner variability, and to evaluate the consistency of results in multicenter studies. STUDY TYPE: Retrospective. POPULATION: Multicenter data from 170 healthy participants (males/females = 98/72; age = 73.8 ± 7.3) and 170 Alzheimer's disease patients (males/females = 98/72; age = 76.2 ± 8.5) were compared with reference data from another 340 participants. FIELD STRENGTH/SEQUENCE: 3-T, magnetization prepared rapid gradient echo and turbo field echo; 1.5-T, inversion recovery prepared fast spoiled gradient echo T1-weighted sequences. ASSESSMENT: Gray matter (GM) brain images, obtained through segmentation of T1-weighted images, were utilized to evaluate the performance of the harmonization method using common orthogonal basis extraction (HCOBE) and four other methods (removal of artificial voxel effect by linear regression, RAVEL; Z_score; general linear model, GLM; ComBat). Linear discriminant analysis (LDA) was used to access the effectiveness of different methods in reducing scanner variability. The performance of harmonization methods in preserving GM volumes heterogeneity was evaluated by the similarity of the relationship between GM proportion and age in the reference and multicenter data. Furthermore, the consistency of the harmonized multicenter data with the reference data were evaluated based on classification results (train/test = 7/3) and brain atrophy. STATISTICAL TESTS: Two-sample t-tests, area under the curve (AUC), and Dice coefficients were used to analyze the consistency of results from the reference and harmonized multicenter data. A P-value <0.01 was considered statistically significant. RESULTS: HCOBE reduced the scanner variability from 0.09 before harmonization to 0.003 (ideal: 0, RAVEL/Z_score/GLM/ComBat = 0.087/0.003/0.006/0.013). GM volumes showed no significant difference (P = 0.52) between the reference and HCOBE-harmonized multicenter data. Consistency evaluation showed that AUC values of 0.95 for both reference and HCOBE-harmonized multicenter data (RAVEL/Z_score/GLM/ComBat = 0.86/0.86/0.84/0.89), and the Dice coefficient increased from 0.73 before harmonization to 0.82 (ideal: 1, RAVEL/Z_score/GLM/ComBat = 0.39/0.64/0.59/0.74). DATA CONCLUSION: HCOBE may help to remove scanner variability and could improve the consistency of results in multicenter studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Typical metabolic pattern of 18F-FDG PET in Anti-NMDAR encephalitis in the acute and subacute phases and its correlation with T2 FLAIR-MRI features.

BACKGROUND/AIMS: Early diagnosis of Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis with non-invasive imaging modalities benefiting is crucial to guarantee prompt treatments decision-making and good prognosis for patients. The present study aimed to explore the correlation of MRI features with brain metabolism characteristics of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and to describe the metabolic patterns in Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis at acute and subacute phases. Twenty-four patients with anti-NMDAR encephalitis confirmed by serum and/or CSF tests at acute and subacute phases, 9 females and 15 males, with an age range of 6-80 years, were enrolled in this retrospective study as encephalitis group. 18F-FDG PET and MRI findings of all patients were investigated and interpreted with visual analysis. Chi-square test was performed to compare the diagnostic sensitivity between MRI and PET. Independent sample t-test was used to compare the standardized uptake value ratio (SUVR) of each ROI between the encephalitis group and control group, which consisted of 24 healthy volunteers of the same age and gender. RESULTS: There was no statistical difference in the diagnostic sensitivity between FDG PET (23/24, 95.83%) and MRI (18/24, 75.00%) in anti-NMDAR encephalitis patients (P > 0.05). Three categories of abnormalities shown on T2 FLAIR, including shallow of sulci and swelling of brain tissue, increased signal in the sulci, increased signal on brain gray matter or adjacent white matter presented hypermetabolism on PET, excepting increased signal in brain linear structure with hypometabolism of the basal ganglia on PET. We identified 19 brain regions with hypermetabolism and 16 brain regions with hypometabolism that exhibited statistically significant changes in SUVRs between anti-NMDAR encephalitis group and control group (FDR P < 0.05). CONCLUSION: Anteroposterior glucose metabolism gradient (frontal-temporal/parietal-occipital) is proved to be a typical pattern of anti-NMDAR encephalitis at the acute and subacute phases in both visual and statistical testing. Interestingly, the pattern is also commonly found in the anterior and posterior portions of the parietal lobe and cingular cortex, which may be a potential indicator for the diagnosis of this disorder. In addition, MRI is an important and reliable neuroimaging modality to assist in the correct evaluation of activity changes on individual 18F-FDG PET.

Dopaminergic damage pattern predicts phenoconversion time in isolated rapid eye movement sleep behavior disorder.

PURPOSE: The exact phenoconversion time from isolated rapid eye movement (REM) sleep behavior disorder (iRBD) to synucleinopathies remains unpredictable. This study investigated whole-brain dopaminergic damage pattern (DDP) with disease progression and predicted phenoconversion time in individual patients. METHODS: Age-matched 33 iRBD patients and 20 healthy controls with 11C-CFT-PET scans were enrolled. The patients were followed up 2-10 (6.7 ± 2.0) years. The phenoconversion year was defined as the base year, and every 2 years before conversion was defined as a stage. Support vector machine with leave-one-out cross-validation strategy was used to perform prediction. RESULTS: Dopaminergic degeneration of iRBD was found to occur about 6 years before conversion and then abnormal brain regions gradually expanded. Using DDP, area under curve (AUC) was 0.879 (90% sensitivity and 88.3% specificity) for predicting conversion in 0-2 years, 0.807 (72.7% sensitivity and 83.3% specificity) in 2-4 years, 0.940 (100% sensitivity and 84.6% specificity) in 4-6 years, and 0.879 (100% sensitivity and 80.7% specificity) over 6 years. In individual patients, predicted stages correlated with whole-brain dopaminergic levels (r = - 0.740, p < 0.001). CONCLUSION: Our findings suggest that DDP could accurately predict phenoconversion time of individual iRBD patients, which may help to screen patients for early intervention.

Metabolic Asymmetry Relates to Clinical Characteristics and Brain Network Abnormalities in Alzheimer's Disease.

BACKGROUND: Metabolic asymmetry has been observed in Alzheimer's disease (AD), but different studies have inconsistent viewpoints. OBJECTIVE: To analyze the asymmetry of cerebral glucose metabolism in AD and investigate its clinical significance and potential metabolic network abnormalities. METHODS: Standardized uptake value ratios (SUVRs) were obtained from 18F-FDG positron emission tomography (PET) images of all participants, and the asymmetry indices (AIs) were calculated according to the SUVRs. AD group was divided into left/right-dominant or bilateral symmetric hypometabolism (AD-L/AD-R or AD-BI) when more than half of the AIs of the 20 regions of interest (ROIs) were < -2SD, >2SD, or between±1SD. Differences in clinical features among the three AD groups were compared, and the abnormal network characteristics underlying metabolic asymmetry were explored. RESULTS: In AD group, the proportions of AD-L, AD-R, and AD-BI were 28.4%, 17.9%, and 18.5%, respectively. AD-L/AD-R groups had younger age of onset and faster rate of cognitive decline than AD-BI group (p < 0.05). The absolute values of AIs in half of the 20 ROIs became higher at follow-up than at baseline (p < 0.05). Compared with those in AD-BI group, metabolic connection strength of network, global efficiency, cluster coefficient, degree centrality and local efficiency were lower, but shortest path length was longer in AD-L and AD-R groups (p < 0.05). CONCLUSION: Asymmetric and symmetric hypometabolism may represent different clinical subtypes of AD, which may provide a clue for future studies on the heterogeneity of AD and help to optimize the design of clinical trials.

Microglia-dependent excessive synaptic pruning leads to cortical underconnectivity and behavioral abnormality following chronic social defeat stress in mice.

Synapse loss in medial prefrontal cortex (mPFC) has been implicated in stress-related mood disorders, such as depression. However, the exact effect of synapse elimination in the depression and how it is triggered are largely unknown. Through repeated longitudinal imaging of mPFC in the living brain, we found both presynaptic and postsynaptic components were declined, together with the impairment of synapse remodeling and cross-synaptic signal transmission in the mPFC during chronic stress. Meanwhile, chronic stress also induced excessive microglia phagocytosis, leading to engulfment of excitatory synapses. Further investigation revealed that the elevated complement C3 during the stress acted as the tag of synapses to be eliminated by microglia. Besides, chronic stress induced a reduction of the connectivity between the mPFC and neighbor regions. C3 knockout mice displayed significant reduction of synaptic pruning and alleviation of disrupted functional connectivity in mPFC, resulting in more resilience to chronic stress. These results indicate that complement-mediated excessive microglia phagocytosis in adulthood induces synaptic dysfunction and cortical hypo-connectivity, leading to stress-related behavioral abnormality.

Blood-brain barrier and brain structural changes in lung cancer patients with non-brain metastases.

Purpose: To explore the relationship between blood-brain barrier (BBB) leakage and brain structure in non-brain metastasis lung cancer (LC) by magnetic resonance imaging (MRI) as well as to indicate the possibility of brain metastasis (BM) occurrence. Patients and methods: MRI were performed in 75 LC patients and 29 counterpart healthy peoples (HCs). We used the Patlak pharmacokinetic model to calculate the average leakage in each brain region according to the automated anatomical labeling (AAL) atlas. The thickness of the cortex and the volumes of subcortical structures were calculated using the FreeSurfer base on Destrieux atlas. We compared the thickness of the cerebral cortex, the volumes of subcortical structures, and the leakage rates of BBB, and evaluated the relationships between these parameters. Results: Compared with HCs, the leakage rates of seven brain regions were higher in patients with advanced LC (aLC). In contrast to patients with early LC (eLC), the cortical thickness of two regions was decreased in aLCs. The volumes of twelve regions were also reduced in aLCs. Brain regions with increased BBB penetration showed negative correlations with thinner cortices and reduced subcortical structure volumes (P<0.05, R=-0.2 to -0.50). BBB penetration was positively correlated with tumor size and with levels of the tumor marker CYFRA21-1 (P<0.05, R=0.2-0.70). Conclusion: We found an increase in BBB permeability in non-BM aLCs that corresponded to a thinner cortical thickness and smaller subcortical structure volumes. With progression in LC staging, BBB shows higher permeability and may be more likely to develop into BM.

Neurometabolism and Ventricular Dyssynchrony in Patients With Heart Failure and Reduced Ejection Fraction.

BACKGROUND: The brain coordinates the heart through the autonomic nervous system (ANS). Numerous mediator signals along the brain-heart axis interact with the neuronal-metabolic system in heart failure (HF). Disturbances in cardio-neural interactions influence the disease progression in patients with HF. OBJECTIVES: The purpose of this study was to investigate the interactome between ANS-associated neurometabolism and ventricular dyssynchrony in patients with heart failure with reduced ejection fraction (HFrEF). Further, we studied the association of neurometabolism with major arrhythmic events (MAEs). METHODS: A total of 197 patients with HFrEF who underwent gated single-photon emission computed tomography myocardial perfusion imaging and the brain 18F-fluorodeoxyglucose positron emission tomography/computed tomography were prospectively enrolled. Relationships between the brain metabolism and MAEs were assessed using Cox models and mediation analyses. Finally, metabolic central autonomic networks were constructed and statistically compared between patients with and without MAEs. RESULTS: In total, 35 (17.8%) patients experienced MAEs during a median follow-up of 3.1 years. In patients with HFrEF (age 58 years [IQR: 50-64 years], left ventricular ejection fraction: 20.0% [IQR: 15.0%-25.0%]), glucose hypometabolism in the insula, hippocampus, amygdala, cingulate gyrus, and caudate nucleus were independent predictors for MAEs (all P < 0.05). Cerebral hypometabolism was related to ventricular dyssynchrony, which was the predominant risk factor of MAEs. Additionally, patients who experienced MAEs presented hypoconnectivity in the metabolic central autonomic network compared with those without MAEs (P < 0.05). CONCLUSIONS: We found an interaction of the neuronal metabolic-ventricular dyssynchronization axis in HF, which might be related to MAEs. This new brain-heart axis could expand our understanding of the distinct pathomechanisms of HFrEF.

Crossed cerebellar diaschisis-related supratentorial hemodynamic and metabolic status measured by PET/MR in assessing postoperative prognosis in chronic ischemic cerebrovascular disease patients with bypass surgery.

OBJECTIVE: Cerebral ischemic status is an indicator of bypass surgery. Both hemodynamics and glucose metabolism are significant factors for evaluating cerebral ischemic status. The occurrence of crossed cerebellar diaschisis (CCD) is influenced by the degree of supra-tentorial perfusion and glucose metabolism reduction. This study aimed to investigate the relationship between the CCD-related supra-tentorial blood flow and metabolic status before bypass surgery in patients with chronic and symptomatic ischemic cerebrovascular disease and the prognosis of surgery. METHODS: Twenty-four participants with chronic ischemic cerebrovascular disease who underwent hybrid positron emission tomography (PET)/magnetic resonance (MR) before bypass surgery were included. Arterial spin labeling (ASL)-MR and FDG-PET were used to measure blood flow and metabolism, respectively. The PET images were able to distinguish CCD. The supratentorial asymmetry index (AI) and volume in the decreased blood flow region, decreased metabolism region and co-decreased region on the affected side, except for the infarct area, were respectively obtained before bypass surgery. The neurological status was determined using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) scores. Differences between CCD-positive (CCD +) and CCD-negative (CCD-) groups were investigated. RESULTS: Fourteen (58%) of the 24 patients were diagnosed as CCD +. Before surgery, the NIHSS and mRS scores of the CCD + were significantly higher than those of the CCD- (1.0(1.0) vs. 0.0(1.0), P = 0.013; 1.0(1.5) vs. 0.0(1.5), P = 0.048). After the surgery, the NIHSS and mRS scores of the CCD + showed a significant decrease (0.0(1.0) to 0.0(0.0), P = 0.011; 0.0(0.5) to 0.0(0.0), P = 0.008). Significant differences were observed in the supra-tentorial decreased metabolism region (all Ps ≤ 0.05) between the CCD + and CCD- groups, but no differences were observed in the preprocedural decreased supratentorial blood flow region (P > 0.05). The preprocedural NIHSS score was strongly correlated with the metabolism AI value in the decreased metabolism region (r = 0.621, P = 0.001) and the co-decreased region (r = 0.571, P = 0.004). CONCLUSIONS: Supratentorial blood flow and metabolism are important indicators of CCD. This study showed that CCD + patients benefited more from bypass surgery than CCD- patients. Staging based on CCD-related supra-tentorial blood flow and metabolic status by hybrid PET/MR may help to personalize treatment.

Increased Blood-Brain Barrier Permeability of the Thalamus Correlated With Symptom Severity and Brain Volume Alterations in Patients With Schizophrenia.

BACKGROUND: While direct in vivo data from patients is insufficient, cumulative evidence of microvascular dysfunction has shown that the blood-brain barrier (BBB) is disrupted in schizophrenia. In this study, we attempted to test the hypothesis that greater BBB permeability in patients with schizophrenia was associated with clinical characteristics and brain volumetric alterations using dynamic contrast-enhanced magnetic resonance imaging techniques. METHODS: Structural magnetic resonance imaging and dynamic contrast-enhanced magnetic resonance imaging data from 29 patients with schizophrenia and 18 age- and sex-matched control subjects were obtained. We calculated the volume transfer constant (Ktrans) value and compared the difference between the 2 groups. The regions with an abnormal Ktrans value were extracted as regions of interest (thalamus), and the correlations with clinical characteristics and gray matter volume were analyzed. RESULTS: The results revealed that Ktrans value of the bilateral thalamus was higher in the schizophrenia group as compared to the healthy control group (p < .001). There were significant positive correlations between thalamic mean Ktrans value with disease duration (p < .05) and symptom severity (p < .001). Analysis of the thalamic subregions revealed that BBB disruption was significant in the pulvinar, especially the medial pulvinar nucleus and lateral pulvinar nucleus (p < .001). The correlation between the Ktrans values and the corresponding volumes was negative for the whole brain, the thalamus, and the thalamic subregions. CONCLUSIONS: These results provide the first in vivo evidence of BBB disruption of thalamus in patients with schizophrenia and suggest that BBB dysfunction might contribute to the pathological brain structural alterations in schizophrenia.

Modulation effect of substantia nigra iron deposition and functional connectivity on putamen glucose metabolism in Parkinson's disease.

Neurodegeneration of the substantia nigra affects putamen activity in Parkinson's disease (PD), yet in vivo evidence of how the substantia nigra modulates putamen glucose metabolism in humans is missing. We aimed to investigate how substantia nigra modulates the putamen glucose metabolism using a cross-sectional design. Resting-state fMRI, susceptibility-weighted imaging, and [18 F]-fluorodeoxyglucose-PET (FDG-PET) data were acquired. Forty-two PD patients and 25 healthy controls (HCs) were recruited for simultaneous PET/MRI scanning. The main measurements of the current study were R2* images representing iron deposition (28 PD and 25 HCs), standardized uptake value ratio (SUVr) images representing FDG-uptake (33 PD and 25 HCs), and resting state functional connectivity maps from resting state fMRI (34 PD and 25 HCs). An interaction term based on the general linear model was used to investigate the joint modulation effect of nigral iron deposition and nigral-putamen functional connectivity on putamen FDG-uptake. Compared with HCs, we found increased iron deposition in the substantia nigra (p = .007), increased FDG-uptake in the putamen (left: PFWE < 0.001; right: PFWE < 0.001), and decreased functional connectivity between the substantia nigra and the anterior putamen (left PFWE < 0.001, right: PFWE  = 0.007). We then identified significant interaction effect of nigral iron deposition and nigral-putamen connectivity on FDG-uptake in the putamen (p = .004). The current study demonstrated joint modulation effect of the substantia nigra iron deposition and nigral-putamen functional connectivity on putamen glucose metabolic distribution, thereby revealing in vivo pathological mechanism of nigrostriatal neurodegeneration of PD.

Unified spatial normalization method of brain PET images using adaptive probabilistic brain atlas.

PURPOSE: A unique advantage of the brain positron emission tomography (PET) imaging is the ability to image different biological processes with different radiotracers. However, the diversity of the brain PET image patterns also makes their spatial normalization challenging. Since structural MR images are not always available in the clinical practice, this study proposed a PET-only spatial normalization method based on adaptive probabilistic brain atlas. METHODS: The proposed method (atlas-based method) consists of two parts, an adaptive probabilistic brain atlas generation algorithm, and a probabilistic framework for registering PET image to the generated atlas. To validate this method, the results of MRI-based method and template-based method (a widely used PET-only method) were treated as the gold standard and control, respectively. A total of 286 brain PET images, including seven radiotracers (FDG, PIB, FBB, AV-45, AV-1451, AV-133, [18F]altanserin) and four groups of subjects (Alzheimer disease, Parkinson disease, frontotemporal dementia, and healthy control), were spatially normalized using the three methods. The results were then quantitatively compared by using correlation analysis, meta region of interest (meta-ROI) standardized uptake value ratio (SUVR) analysis, and statistical parametric mapping (SPM) analysis. RESULTS: The Pearson correlation coefficient between the images computed by atlas-based method and the gold standard was 0.908 ± 0.005. The relative error of meta-ROI SUVR computed by atlas-based method was 2.12 ± 0.18%. Compared with template-based method, atlas-based method was also more consistent with the gold standard in SPM analysis. CONCLUSION: The proposed method provides a unified approach to spatially normalize brain PET images of different radiotracers accurately without MR images. A free MATLAB toolbox for this method has been provided.

Effects of MRI protocols on brain FDG uptake in simultaneous PET/MR imaging.

PURPOSE: To investigate the potential effects of MRI protocols on brain FDG uptake in simultaneous PET/MR imaging. METHODS: Seventy healthy subjects and ten patients with temporal lobe epilepsy were enrolled. Healthy subjects were divided to three groups to undergo different PET/MR scan protocols: "continuous MRI" with MRI stimulation presented during the whole scan, "late MRI" with MRI stimulation started after 40 min glucose uptake, and "no MRI" without MRI stimulation at all. Region-wise and voxel-wise differences in FDG uptake among the three protocols were compared. All epilepsy patients were scanned with the "continuous MRI" scan protocol. The effects of MRI protocol stimulation on pathological interpretation were evaluated. RESULTS: Highest global averaged metabolism was found in the normal dataset with continuous MRI scan protocol (P < 0.05). Specifically, we observed higher FDG uptake in the primary auditory cortex, putamen, and lower FDG uptake in the occipital lobe and cerebellum during the "continuous MRI" scan protocol. However, MRI protocol stimulation after 40 min glucose uptake did not cause any significant differences in FDG uptake. Respectively compared to the normal dataset, patients with epilepsy showed consistent hypometabolism in the temporal lobe. Besides, significant metabolism changes in the primary auditory cortex, vermis, and occipital lobe were found in the "late MRI" protocol. CONCLUSION: The effects of MRI protocol on brain FDG uptake were varied. The effects, including from other practical setting, were conspicuous for scans where MRI protocol started immediately after glucose uptake, but would dramatically decrease to negligible 40 min later. Hence, it would be necessary for pathology studies to collect data from a normal control group using the same scan protocol for unbiased evaluation.

Assessment of cerebral glucose metabolism in patients with heart failure by 18F-FDG PET/CT imaging.

BACKGROUND: To evaluate the cerebral metabolism in patients with heart failure (HF). METHODS: One hundred and two HF patients were prospectively enrolled, who underwent gated 99mTc-sestamibi single photon emission computed tomography (SPECT)/CT, cardiac and cerebral 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT. Fifteen healthy volunteers served as controls. Patients were stratified by extent of hibernating myocardium (HM) and left ventricular ejection fraction (LVEF) into 4 groups where Group1: HM < 10% (n = 33); Group2: HM ≥ 10%, LVEF < 25% (n = 34); Group3: HM ≥ 10%, 25% ≤ LVEF ≤ 40% (n = 16) and Group 4: LVEF > 40% (n = 19). The standardized uptake value (SUV) in the whole brain (SUVwhole-brain) and the SUV ratios (SUVR) in 24 cognition-related brain regions were determined. SUVwhole-brain and SUVRs were compared between the 4 patient groups and the healthy controls. RESULTS: SUVwhole-brain (r = 0.245, P = 0.013) and SUVRs in frontal areas, hippocampus, and para-hippocampus (r: 0.213 to 0.308, all P < 0.05) were correlated with HM. SUVwhole-brain differed between four patient groups and the healthy volunteers (P = 0.016) and SUVwhole-brain in Group 1 was lower than that in healthy volunteers (P < 0.05). SUVRs of Group 3 in frontal areas were the highest among four patient subgroups (P < 0.05). CONCLUSIONS: Cerebral metabolism in the whole brain was reduced but maintained in cognition-related frontal areas in HF patients with HM and moderately impaired global left ventricular function.

A Comparative Study of Structural and Metabolic Brain Networks in Patients With Mild Cognitive Impairment.

Background: Changes in the metabolic and structural brain networks in mild cognitive impairment (MCI) have been widely researched. However, few studies have compared the differences in the topological properties of the metabolic and structural brain networks in patients with MCI. Methods: We analyzedmagnetic resonance imaging (MRI) and fluoro-deoxyglucose positron emission tomography (FDG-PET) data of 137 patients with MCI and 80 healthy controls (HCs). The HC group data comes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The permutation test was used to compare the network parameters (characteristic path length, clustering coefficient, local efficiency, and global efficiency) between the two groups. Partial Pearson's correlation analysis was used to calculate the correlations of the changes in gray matter volume and glucose intake in the key brain regions in MCI with the Alzheimer's Disease Assessment Scale-Cognitive (ADAS-cog) sub-item scores. Results: Significant changes in the brain network parameters (longer characteristic path length, larger clustering coefficient, and lower local efficiency and global efficiency) were greater in the structural network than in the metabolic network (longer characteristic path length) in MCI patients than in HCs. We obtained the key brain regions (left globus pallidus, right calcarine fissure and its surrounding cortex, left lingual gyrus) by scanning the hubs. The volume of gray matter atrophy in the left globus pallidus was significantly positively correlated with comprehension of spoken language (p = 0.024) and word-finding difficulty in spontaneous speech item scores (p = 0.007) in the ADAS-cog. Glucose intake in the three key brain regions was significantly negatively correlated with remembering test instructions items in ADAS-cog (p = 0.020, p = 0.014, and p = 0.008, respectively). Conclusion: Structural brain networks showed more changes than metabolic brain networks in patients with MCI. Some brain regions with significant changes in betweenness centrality in both structural and metabolic networks were associated with MCI.

Variations of Brain Functional Connectivity in Alcohol-Preferring and Non-Preferring Rats with Consecutive Alcohol Training or Acute Alcohol Administration.

Alcohol addiction is regarded as a series of dynamic changes to neural circuitries. A comparison of the global network during different stages of alcohol addiction could provide an efficient way to understand the neurobiological basis of addiction. Two animal models (P-rats screened from an alcohol preference family, and NP-rats screened from an alcohol non-preference family) were trained for alcohol preference with a two-bottle free choice method for 4 weeks. To examine the changes in the neural response to alcohol during the development of alcohol preference and acute stimulation, different trials were studied with resting-state fMRI methods during different periods of alcohol preference. The correlation coefficients of 28 regions in the whole brain were calculated, and the results were compared for alcohol preference related to the genetic background/training association. The variety of coherence patterns was highly related to the state and development of alcohol preference. We observed significant special brain connectivity changes during alcohol preference in P-rats. The comparison between the P- and NP-rats highlighted the role of genetic background in alcohol preference. The results of this study support the alterations of the neural network connection during the formation of alcohol preference and confirm that alcohol preference is highly related to the genetic background. This study could provide an effective approach for understanding the neurobiological basis of alcohol addiction.

Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout.

Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout. Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness. Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients. Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network. Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.