Cholinergic modulation supports dynamic switching of resting state networks through selective DMN suppression.

Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.

Longitudinal assessment of ventricular volume trajectories in early-stage schizophrenia: evidence of both enlargement and shrinkage.

BACKGROUND: Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. METHODS: We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. RESULTS: Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. CONCLUSION: Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.

Time is the enemy: Negative symptoms are related to even slight differences in the duration of untreated psychosis.

BACKGROUND: Negative symptoms (NS) represent a detrimental symptomatic domain in schizophrenia affecting social and occupational outcomes. AIMS: We aimed to identify factors from the baseline visit (V1) - with a mean illness duration of 0.47 years (SD = 0.45) - that predict the magnitude of NS at the follow-up visit (V3), occurring 4.4 years later (mean +/- 0.45). METHOD: Using longitudinal data from 77 first-episode schizophrenia spectrum patients, we analysed eight predictors of NS severity at V3: (1) the age at disease onset, (2) age at V1, (3) sex, (4) diagnosis, (5) NS severity at V1, (6) the dose of antipsychotic medication at V3, (7) hospitalisation days before V1 and; (8) the duration of untreated psychosis /DUP/). Secondly, using a multiple linear regression model, we studied the longitudinal relationship between such identified predictors and NS severity at V3 using a multiple linear regression model. RESULTS: DUP (Pearson's r = 0.37, p = 0.001) and NS severity at V1 (Pearson's r = 0.49, p < 0.001) survived correction for multiple comparisons. The logarithmic-like relationship between DUP and NS was responsible for the initial stunning incremental contribution of DUP to the severity of NS. For DUP < 6 months, with the sharpest DUP/NS correlation, prolonging DUP by five days resulted in a measurable one-point increase in the 6-item negative symptoms PANSS domain assessed 4.9 (+/- 0.6) years after the illness onset. Prolongation of DUP to 14.7 days doubled this NS gain, whereas 39 days longer DUP tripled NS increase. CONCLUSION: The results suggest the petrification of NS during the early stages of the schizophrenia spectrum and a crucial dependence of this symptom domain on DUP. These findings are clinically significant and highlight the need for primary preventive actions.

Obesity and brain structure in schizophrenia - ENIGMA study in 3021 individuals.

Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia.

Spectroscopic abnormalities in the pregenual anterior cingulate cortex in obsessive-compulsive disorder using proton magnetic resonance spectroscopy: a controlled study.

BACKGROUND: The main aim of the present study is to determine the role of metabolites observed using proton magnetic resonance spectroscopy (1H-MRS) in obsessive-compulsive disorder (OCD). As the literature describing biochemical changes in OCD yields conflicting results, we focused on accurate metabolite quantification of total N-acetyl aspartate (tNAA), total creatine (tCr), total choline-containing compounds (tCh), and myo-inositol (mI) in the anterior cingulate cortex (ACC) to capture the small metabolic changes between OCD patients and controls and between OCD patients with and without medication. METHODS: In total 46 patients with OCD and 46 healthy controls (HC) matched for age and sex were included in the study. The severity of symptoms in the OCD was evaluated on the day of magnetic resonance imaging (MRI) using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). Subjects underwent 1H-MRS from the pregenual ACC (pgACC) region to calculate concentrations of tNAA, tCr, tCho, and mI. Twenty-eight OCD and 28 HC subjects were included in the statistical analysis. We compared differences between groups for all selected metabolites and in OCD patients we analyzed the relationship between metabolite levels and symptom severity, medication status, age, and the duration of illness. RESULTS: Significant decreases in tCr (U = 253.00, p = 0.022) and mI (U = 197.00, p = 0.001) in the pgACC were observed in the OCD group. No statistically significant differences were found in tNAA and tCho levels; however, tCho revealed a trend towards lower concentrations in OCD patients (U = 278.00, p = 0.062). Metabolic concentrations showed no significant correlations with the age and duration of illness. The correlation statistics found a significant negative correlation between tCr levels and YBOCS compulsions subscale (cor = -0.380, p = 0.046). tCho and YBOCS compulsions subscale showed a trend towards a negative correlation (cor = -0.351, p = 0.067). Analysis of subgroups with or without medication showed no differences. CONCLUSIONS: Patients with OCD present metabolic disruption in the pgACC. The decrease in tCr shows an important relationship with OCD symptomatology. tCr as a marker of cerebral bioenergetics may also be considered as a biomarker of the severity of compulsions. The study failed to prove that metabolic changes correlate with the medication status or the duration of illness. It seems that a disruption in the balance between these metabolites and their transmission may play a role in the pathophysiology of OCD.

Magnetic resonance markers of bilateral neuronal metabolic dysfunction in patients with unilateral internal carotid artery occlusion.

OBJECTIVES: To evaluate cerebral hemodynamic, metabolic and anatomic changes occurring in patients with unilateral occlusion of the internal carotid artery (ICA). MATERIALS AND METHODS: Twenty-two patients with unilateral occlusion of ICA and twenty age and sex matched healthy subjects were included in the study. Single voxel proton magnetic resonance spectroscopy (1H-MRS) of the centrum semiovale, semi-automated hippocampal volumetry in T1-weighted scans and transcranial Doppler examination (TCD) with calculation of Breath Holding Index (BHI) were performed in both groups. Metabolic, anatomic, and hemodynamic features were compared between the two groups. RESULTS: The N-acetylaspartate (NAA)/choline (Cho) ratio was significantly lower in both hemispheres of enrolled patients compared to controls (p = 0.005 for the side with occlusion, p = 0.04 for the side without occlusion). The hippocampus volume was significantly reduced bilaterally in patients compared to healthy subjects (p = 0.049). A statistically significant difference in BHI values was observed between the side with occlusion and without occlusion (p = 0.037) of the patients, as well as between BHI values of the side with occlusion and healthy volunteers (p = 0.014). DISCUSSION: Patients with unilateral ICA occlusion have reduced NAA/Cho ratio in the white matter of both hemispheres and have bilateral atrophy of hippocampus. The alteration of hemodynamics alone cannot explain these changes.

An overlapping pattern of cerebral cortical thinning is associated with both positive symptoms and aggression in schizophrenia via the ENIGMA consortium.

BACKGROUND: Positive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample. METHOD: To study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls. RESULTS: The result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression. CONCLUSION: These findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia.

FitzHugh-Nagumo oscillators on complex networks mimic epileptic-seizure-related synchronization phenomena.

We study patterns of partial synchronization in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in human subjects. We report the spontaneous occurrence of synchronization phenomena that closely resemble the ones seen during epileptic seizures in humans. In order to obtain deeper insights into the interplay between dynamics and network topology, we perform long-term simulations of oscillatory dynamics on different paradigmatic network structures: random networks, regular nonlocally coupled ring networks, ring networks with fractal connectivities, and small-world networks with various rewiring probability. Among these networks, a small-world network with intermediate rewiring probability best mimics the findings achieved with the simulations using the empirical structural connectivity. For the other network topologies, either no spontaneously occurring epileptic-seizure-related synchronization phenomena can be observed in the simulated dynamics, or the overall degree of synchronization remains high throughout the simulation. This indicates that a topology with some balance between regularity and randomness favors the self-initiation and self-termination of episodes of seizure-like strong synchronization.

Ultralong TE In Vivo 1 H MR Spectroscopy of Omega-3 Fatty Acids in Subcutaneous Adipose Tissue at 7 T.

BACKGROUND: Omega-3 (n-3) fatty acids (FA) play and important role in neural development and other metabolic diseases such as obesity and diabetes. The knowledge about the in vivo content and distribution of n-3 FA in human body tissues is not well established and the standard quantification of FA is invasive and costly. PURPOSE: To detect omega-3 (n-3 CH3 ) and non-omega-3 (CH3 ) methyl group resonance lines with echo times up to 1200 msec, in oils, for the assessment of n-3 FA content, and the n-3 FA fraction in adipose tissue in vivo. STUDY TYPE: Prospective technical development. POPULATION: Three oils with different n-3 FA content and 24 healthy subjects. FIELD STRENGTH/SEQUENCE: Single-voxel MR spectroscopy (SVS) with a point-resolved spectroscopy (PRESS) sequence with an echo time (TE) of 1000 msec at 7 T. ASSESSMENT: Knowledge about the J-coupling evolution of both CH3 resonances was used for the optimal detection of the n-3 CH3 resonance line at a TE of 1000 msec. The accuracy of the method in oils and in vivo was validated from a biopsy sample with gas chromatography analysis. STATISTICAL TESTS: SVS data were compared to gas chromatography with the Pearson correlation coefficient. RESULTS: T2 relaxation times in oils were assessed as follows: CH2 , 65 ± 22 msec; CH3 , 325 ± 7 msec; and n-3 CH3 , 628 ± 34 msec. The n-3 FA fractions from oil phantom experiments (n = 3) were in agreement with chromatography analysis and the comparison of in vivo obtained data with the results of chromatography analysis (n = 5) yielded a significant correlation (P = 0.029). DATA CONCLUSION: PRESS with ultralong-TE can detect and quantify the n-3 CH3 signal in vivo at 7 T. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:71-82.

Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.

BACKGROUND: Early diagnosis of schizophrenia could improve the outcome of the illness. Unlike classical between-group comparisons, machine learning can identify subtle disease patterns on a single subject level, which could help realize the potential of MRI in establishing a psychiatric diagnosis. Machine learning has previously been predominantly tested on gray-matter structural or functional MRI data. In this paper we used a machine learning classifier to differentiate patients with a first episode of schizophrenia-spectrum disorder (FES) from healthy controls using diffusion tensor imaging. METHODS: We applied linear support-vector machine (SVM) and traditional tract based spatial statistics between group analyses to brain fractional anisotropy (FA) data from 77 FES and 77 age and sex matched healthy controls. We also evaluated the effects of medication and symptoms on the SVM classification. RESULTS: The SVM distinguished between patients and controls with significant accuracy of 62.34% (p = 0.005). Participants with FES showed widespread FA reductions relative to controls in a large cluster (N = 56,647 voxels, corrected p = 0.002). The white matter regions, which contributed to the correct identification of participants with FES, overlapped with the regions, which showed lower FA in patients relative to controls. There was no association between the classification performance and medication or symptoms. CONCLUSIONS: Our results provide a proof of concept that SVM might help differentiate FES patients early in the course of illness from healthy controls using white-matter fractional anisotropy. As there was no effect of medications or symptoms, the SVM classification seemed to be based on trait rather than state markers and appeared to capture the lower FA in FES participants relative to controls.

The Effect of a Vegetarian vs Conventional Hypocaloric Diabetic Diet on Thigh Adipose Tissue Distribution in Subjects with Type 2 Diabetes: A Randomized Study.

OBJECTIVE: The aim of our study was to compare the effects of a vegetarian and a conventional diet on thigh adipose tissue distribution in subjects with type 2 diabetes (T2D). METHODS: Seventy-four subjects with T2D were randomly assigned to either follow a vegetarian diet (V, n = 37) or a control group who followed an isocaloric conventional anti-diabetic diet (C, n = 37). Both diets were calorie restricted (-500 kcal/day). To measure insulin sensitivity, the hyperinsulinemic (1 mU.kg-1.min-1) isoglycemic clamp was conducted. ß-Cell function was assessed using a mathematical model after a test meal. Magnetic resonance imaging of the thigh was performed. All subjects were examined at 0, 3, and 6 months. Statistical analyses were performed using repeated measures analysis of variance and a multivariate regression model. RESULTS: Greater reduction was observed in total leg area in V (-13.6 cm2 [95% confidence interval [CI], -14.2 to -12.9] in V vs -9.9 cm2 [95% CI, -10.6 to -9.2] in C; Gxt p < 0.001). The reduction in subcutaneous fat was comparable in response to both diets (Gxt, p = 0.64). Subfascial fat was reduced only in response to a vegetarian diet (-0.82 [95% CI, -1.13 to -0.55] cm2 in V vs -0.44 [95% CI, -0.78 to +0.02] cm2 in C; Gxt, p = 0.04). The reduction in intramuscular fat tended to be greater in response to a vegetarian diet (-1.78 [95% CI, -2.26 to -1.27] cm2 in V vs -0.57 [95% CI, -1.06 to -0.09] cm2 in C; Gxt, p = 0.12). Changes in subcutaneous and subfascial fat correlated with changes in glycated hemoglobin (HbA1c), fasting plasma glucose, and ß-cell insulin sensitivity. After adjustment for changes in body mass index (BMI), correlations remained significant for changes in fasting plasma glucose and ß-cell insulin sensitivity and with changes in triglycerides. CONCLUSIONS: Our data indicate the importance of both subcutaneous and subfascial fat in relationship to glucose and lipid metabolism. ABBREVIATIONS: BMI , body mass index; C , control group; FPG , fasting plasma glucose; Gxt , interaction between group and time; HbA1c , glycated hemoglobin; MCR , metabolic clearance rate of glucose; OPLS , orthogonal projections to latent structure; T2D , type 2 diabetes; V , vegetarian group.

The aging effect on prostate metabolite concentrations measured by 1H MR spectroscopy.

OBJECTIVE: The effects of aging, magnetic field and the voxel localization on measured concentrations of citrate (Cit), creatine (Cr), cholines (Cho) and polyamines (PA) in a healthy prostate were evaluated. MATERIALS AND METHODS: 36 examinations at both 1.5T and 3T imagers of 52 healthy subjects aged 19-71 years were performed with PRESS 3D-CSI sequences (TE = 120 and 145 ms). Concentrations in laboratory units and their ratios to citrate were calculated using the LCModel technique. Absolute concentrations were also obtained after the application of correction coefficients. Statistical analysis was performed using a robust linear mixed effects model. RESULTS: Significant effects of aging, the magnetic field strength and the voxel position in central (CZ) or peripheral (PZ) zones on all measured metabolites were found. The concentrations (mmol/kg wet tissue) including prediction intervals in a range of 20-70 years were found: Cit: 7.9-17.2; Cho: 1.4-1.7; Cr: 2.8-2.5; PA (as spermine): 0.6-2.1 at 3T in CZ. In PZ, the concentrations were higher by about 10 % as compared to CZ. CONCLUSION: Increasing citrate and spermine concentrations with age are significant and correlate well with a recently described increase of zinc in the prostate. These findings should be considered in decision-making if the values obtained from a subject are in the range of control values.

The in vivo J-difference editing MEGA-PRESS technique for the detection of n-3 fatty acids.

In this study, we present a method for the detection of n-3 fatty acid (n-3 FA) signals using MRS in adipose tissue in vivo. This method (called oMEGA-PRESS) is based on the selective detection of the CH3 signal of n-3 FA using the MEGA-PRESS (MEshcher-GArwood Point-RESolved Spectroscopy) J-difference editing technique. We optimized the envelope shape and frequency of spectral editing pulses to minimize the spurious co-editing and incomplete subtraction of the CH3 signal of other FAs, which normally obscure the n-3 FA CH3 signal in MR spectra acquired using standard PRESS techniques. The post-processing of the individual data scans with the phase and frequency correction before data subtraction and averaging was implemented to further improve the quality of in vivo spectra. The technique was optimized in vitro on lipid phantoms using various concentrations of n-3 FA and examined in vivo at 3 T on 15 healthy volunteers. The proportion of n-3 FA estimated by the oMEGA-PRESS method in phantoms showed a highly significant linear correlation with the n-3 FA content determined by gas chromatography. The signal attributed to n-3 FA was observed in all subjects. Comparisons with the standard PRESS technique revealed an enhanced identification of the n-3 FA signal using oMEGA-PRESS. The presented method may be useful for the non-invasive quantification of n-3 FA in adipose tissue, and could aid in obtaining a better understanding of various aspects of n-3 FA metabolism.

The effect of aging, hearing loss, and tinnitus on white matter in the human auditory system revealed with fixel-based analysis.

Introduction: Aging negatively influences the structure of the human brain including the white matter. The objective of our study was to identify, using fixel-based morphometry, the age induced changes in the pathways connecting several regions of the central auditory system (inferior colliculus, Heschl's gyrus, planum temporale) and the pathways connecting these structures with parts of the limbic system (anterior insula, hippocampus and amygdala). In addition, we were interested in the extent to which the integrity of these pathways is influenced by hearing loss and tinnitus. Methods: Tractographic data were acquired using a 3 T MRI in 79 volunteers. The participants were categorized into multiple groups in accordance with their age, auditory thresholds and tinnitus status. Fixel-based analysis was utilized to identify alterations in the subsequent three parameters: logarithm of fiber cross-section, fiber density, fiber density and cross-section. Two modes of analysis were used: whole brain analysis and targeted analysis using fixel mask, corresponding to the pathways connecting the aforementioned structures. Results: A significantly negative effect of aging was present for all fixel-based metrics, namely the logarithm of the fiber cross-section, (7 % fixels in whole-brain, 14% fixels in fixel mask), fiber density (5 % fixels in whole-brain, 15% fixels in fixel mask), fiber density and cross section (7 % fixels in whole-brain, 19% fixels in fixel mask). Expressed age-related losses, exceeding 30% fixels, were particularly present in pathways connecting the auditory structures with limbic structures. The effect of hearing loss and/or tinnitus did not reach significance. Conclusions: Our results show that although an age-related reduction of fibers is present in pathways connecting several auditory regions, the connections of these structures with limbic structures are even more reduced. To what extent this fact influences the symptoms of presbycusis, such as decreased speech comprehension, especially in noise conditions, remains to be elucidated.

Multimodal-neuroimaging machine-learning analysis of motor disability in multiple sclerosis.

Motor disability is a dominant and restricting symptom in multiple sclerosis, yet its neuroimaging correlates are not fully understood. We apply statistical and machine learning techniques on multimodal neuroimaging data to discriminate between multiple sclerosis patients and healthy controls and to predict motor disability scores in the patients. We examine the data of sixty-four multiple sclerosis patients and sixty-five controls, who underwent the MRI examination and the evaluation of motor disability scales. The modalities used comprised regional fractional anisotropy, regional grey matter volumes, and functional connectivity. For analysis, we employ two approaches: high-dimensional support vector machines run on features selected by Fisher Score (aiming for maximal classification accuracy), and low-dimensional logistic regression on the principal components of data (aiming for increased interpretability). We apply analogous regression methods to predict symptom severity. While fractional anisotropy provides the classification accuracy of 96.1% and 89.9% with both approaches respectively, including other modalities did not bring further improvement. Concerning the prediction of motor impairment, the low-dimensional approach performed more reliably. The first grey matter volume component was significantly correlated (R = 0.28-0.46, p < 0.05) with most clinical scales. In summary, we identified the relationship between both white and grey matter changes and motor impairment in multiple sclerosis. Furthermore, we were able to achieve the highest classification accuracy based on quantitative MRI measures of tissue integrity between patients and controls yet reported, while also providing a low-dimensional classification approach with comparable results, paving the way to interpretable machine learning models of brain changes in multiple sclerosis.

Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging.

Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.

Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study.

Objective: Schizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. Methods: This meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. Results: We found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. Conclusions: Higher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

Quantitative MR imaging and spectroscopy of brain tumours: a step forward?

OBJECTIVES: A prospective quantitative MR study of brain tumours was performed to show the potential of combining different MR techniques to distinguish various disease processes in routine clinical practice. METHODS: Twenty-three patients with various intracranial tumours before treatment (diagnosis confirmed by a biopsy) and 59 healthy subjects were examined on a 3-T system by conventional MR imaging, 1H spectroscopic imaging, diffusion tensor imaging and T2 relaxometry. Metabolic concentrations and their ratios, T2 relaxation times and mean diffusivities were calculated and correlated on a pixel-by-pixel basis and compared to control data. RESULTS: Different tumour types and different localisations revealed specific patterns of correlations between metabolic concentrations and mean diffusivity or T2 relaxation times. The patterns distinguish given tissue states in the examined area: healthy tissue, tissue infiltrated by tumour, active tumour, oedema infiltrated by tumour, oedema, etc. This method is able to describe the complexity of a highly heterogeneous tissue in the tumour and its vicinity, and determines crucial parameters for tissue differentiation. CONCLUSIONS: A combination of different MR parameters on a pixel-by-pixel basis in individual patients enables better identification of the tumour type, direction of proliferation and assessment of the tumour extension. KEY POINTS : • Magnetic resonance offers many different methods of examining the brain. • A combination of quantitative MR parameters helps distinguish different brain lesions • Different tumour types revealed specific correlation patterns amongst different MR parameters • The correlation patterns reflect highly heterogeneous complex tissue within tumours.