Cortical thickness alterations and systemic inflammation define long-COVID patients with cognitive impairment.

As the heterogeneity of symptoms is increasingly recognized among long-COVID patients, it appears highly relevant to study potential pathophysiological differences along the different subtypes. Preliminary evidence suggests distinct alterations in brain structure and systemic inflammatory patterns in specific groups of long-COVID patients. To this end, we analyzed differences in cortical thickness and peripheral immune signature between clinical subgroups based on 3 T-MRI scans and signature inflammatory markers in n = 120 participants comprising healthy never-infected controls (n = 30), healthy COVID-19 survivors (n = 29), and subgroups of long-COVID patients with (n = 26) and without (n = 35) cognitive impairment according to screening with Montreal Cognitive Assessment. Whole-brain comparison of cortical thickness between the 4 groups was conducted by surface-based morphometry. We identified distinct cortical areas showing a progressive increase in cortical thickness across different groups, starting from healthy individuals who had never been infected with COVID-19, followed by healthy COVID-19 survivors, long-COVID patients without cognitive deficits (MoCA ≥ 26), and finally, long-COVID patients exhibiting significant cognitive deficits (MoCA < 26). These findings highlight the continuum of cortical thickness alterations associated with COVID-19, with more pronounced changes observed in individuals experiencing cognitive impairment (p < 0.05, FWE-corrected). Affected cortical regions covered prefrontal and temporal gyri, insula, posterior cingulate, parahippocampal gyrus, and parietal areas. Additionally, we discovered a distinct immunophenotype, with elevated levels of IL-10, IFNγ, and sTREM2 in long-COVID patients, especially in the group suffering from cognitive impairment. We demonstrate lingering cortical and immunological alterations in healthy and impaired subgroups of COVID-19 survivors. This implies a complex underlying pathomechanism in long-COVID and emphasizes the necessity to investigate the whole spectrum of post-COVID biology to determine targeted treatment strategies targeting specific sub-groups.

Understanding the concept of a novel tool requires interaction of the dorsal and ventral streams.

The left hemisphere tool-use network consists of the dorso-dorsal, ventro-dorsal, and ventral streams, each with distinct computational abilities. In the dual-loop model, the ventral pathway through the extreme capsule is associated with conceptual understanding. We performed a learning experiment with fMRI to investigate how these streams interact when confronted with novel tools. In session one, subjects observed pictures and video sequences in real world action of known and unknown tools and were asked whether they knew the tools and whether they understood their function. In session two, video sequences of unknown tools were presented again, followed again by the question of understanding their function. Different conditions were compared to each other and effective connectivity (EC) in the tool-use network was examined. During concept acquisition of an unknown tool, EC between dorsal and ventral streams was found posterior in fusiform gyrus and anterior in inferior frontal gyrus, with a functional interaction between BA44d and BA45. When previously unknown tools were presented for a second time, EC was prominent only between dorsal stream areas. Understanding the concept of a novel tool requires an interaction of the ventral stream with the dorsal streams. Once the concept is acquired, dorsal stream areas are sufficient.

Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis.

BACKGROUND AND PURPOSE: Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms. METHOD: A hundred and four patients with relapsing-remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables. RESULTS: Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC. CONCLUSION: Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks.

In vivo assessment of anisotropy of apparent magnetic susceptibility in white matter from a single orientation acquisition.

Multiple studies have reported a significant dependence of the effective transverse relaxation rate constant (R2*) and the phase of gradient-echo based (GRE) signal on the orientation of white matter fibres in the human brain. It has also been hypothesized that magnetic susceptibility, as obtained by single-orientation quantitative susceptibility mapping (QSM), exhibits such a dependence. In this study, we investigated this hypothesized relationship in a cohort of healthy volunteers. We show that R2* follows the predicted orientation dependence consistently across white matter regions, whereas the apparent magnetic susceptibility is related differently to fibre orientation across the brain and often in a complex non-monotonic manner. In addition, we explored the effect of fractional anisotropy measured by diffusion-weighted MRI on the strength of the orientation dependence and observed only a limited influence in many regions. However, with careful consideration of such an impact and the limitations imposed by the ill-posed nature of the dipole inversion process, it is possible to study magnetic susceptibility anisotropy in specific brain regions with a single orientation acquisition.

Interrelations between dopamine and serotonin producing sites and regions of the default mode network.

Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level-dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5-HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top-down information flow in the resting-state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5-HT. We found that latencies range from milliseconds to seconds with high inter-subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.

Diffusion tensor imaging in borderline personality disorder showing prefrontal white matter alterations.

Borderline personality disorder (BPD) has repeatedly been linked to alterations in fronto-limbic dysfunction. In this study, we tested the hypothesis of disturbed structural connectivity in underlying fibre tracts and their relation to symptom profiles. We analysed diffusion tensor imaging (DTI) data from 18 female BPD patients and 38 female healthy controls. Group comparisons showed significant (p < .05, FDR adjusted) increase of radial diffusivity (RD) in the right frontal lobe, including the uncinate fasciculus, anterior thalamic radiation, and inferior fronto-occipital fasciculus, as well as overall apparent diffusion coefficient (ADC) increases in the anterior and posterior internal capsule. Symptom correlations, based on the BSL-95 questionnaires, within the BPD sample showed significant negative correlations of dysphoria with ADC the left and right anterior thalamic radiation, and positive correlations of fractional anisotropy with self-perception scores in the right superior corona radiata. While our findings add to the fronto-limbic dysfunction model of BPD, they provide additional evidence of links to its affective core pathology, particularly frontotemporal and fronto-thalamic systems.

Assessment of MR imaging during one-lung flooding in a large animal model.

OBJECTIVE: Magnetic resonance imaging (MRI) of the lung remains challenging due to the low tissue density, susceptibility artefacts, unfavourable relaxation times and motion. Previously, we demonstrated in vivo that one-lung flooding (OLF) with saline is a viable and safe approach. This study investigates the feasibility of OLF in an MRI environment and evaluates the flooding process on MR images. METHODS: OLF of the left lung was performed on five animals using a porcine model. Before, during and after OLF, standard T2w and T1w spin-echo (SE) and gradient-echo (GRE) sequences were applied at 3 T. RESULTS: The procedure was successfully performed in all animals. On T1w MRI, the flooded lung appeared homogenous and isointense with muscle tissue. On T2w images, vascular structures were highly hypointense, while the bronchi were clearly demarcated with hypointense wall and hyperintense lumen. The anatomical demarcation of the flooded lung from the surrounding organs was superior on T2w images. No outflow effects were seen, and no respiration triggering was required. DISCUSSION: OLF can be safely performed in an MR scanner with highly detailed visualization of the pulmonary structures on T2w images. The method provides new approaches to MRI-based image-guided pulmonary interventions using the presented experimental model.

Real-Time Clustered Multiple Signal Classification (RTC-MUSIC).

Magnetoencephalography (MEG) and electroencephalography provide a high temporal resolution, which allows estimation of the detailed time courses of neuronal activity. However, in real-time analysis of these data two major challenges must be handled: the low signal-to-noise ratio (SNR) and the limited time available for computations. In this work, we present real-time clustered multiple signal classification (RTC-MUSIC) a real-time source localization algorithm, which can handle low SNRs and can reduce the computational effort. It provides correlation information together with sparse source estimation results, which can, e.g., be used to identify evoked responses with high sensitivity. RTC-MUSIC clusters the forward solution based on an anatomical brain atlas and optimizes the scanning process inherent to MUSIC approaches. We evaluated RTC-MUSIC by analyzing MEG auditory and somatosensory data. The results demonstrate that the proposed method localizes sources reliably. For the auditory experiment the most dominant correlated source pair was located bilaterally in the superior temporal gyri. The highest activation in the somatosensory experiment was found in the contra-lateral primary somatosensory cortex.

High levels of neuroticism are associated with decreased cortical folding of the dorsolateral prefrontal cortex.

The personality trait neuroticism has been identified as a vulnerability factor for common psychiatric diseases and defining potential neuroanatomical markers for early recognition and prevention strategies is mandatory. Because both personality traits and cortical folding patterns are early imprinted and timely stable there is reason to hypothesize an association between neuroticism and cortical folding. Thus, to identify a putative linkage, we tested whether the degree of neuroticism is associated with local cortical folding in a sample of 109 healthy individuals using a surface-based MRI approach. Based on previous findings we additionally tested for a potential association with cortical thickness. We found a highly significant negative correlation between the degree of neuroticism and local cortical folding of the left dorsolateral prefrontal cortex (DLPFC), i.e., high levels of neuroticism were associated with low cortical folding of the left DLPFC. No association was found with cortical thickness. The present study is the first to describe a linkage between the extent of local cortical folding and the individual degree of neuroticism in healthy subjects. Because neuroticism is a vulnerability factor for common psychiatric diseases such as depression our finding indicates that alterations of DLPFC might constitute a neurobiological marker elevating risk for psychiatric burden.

Real-Time MEG Source Localization Using Regional Clustering.

With its millisecond temporal resolution, Magnetoencephalography (MEG) is well suited for real-time monitoring of brain activity. Real-time feedback allows the adaption of the experiment to the subject's reaction and increases time efficiency by shortening acquisition and off-line analysis. Two formidable challenges exist in real-time analysis: the low signal-to-noise ratio (SNR) and the limited time available for computations. Since the low SNR reduces the number of distinguishable sources, we propose an approach which downsizes the source space based on a cortical atlas and allows to discern the sources in the presence of noise. Each cortical region is represented by a small set of dipoles, which is obtained by a clustering algorithm. Using this approach, we adapted dynamic statistical parametric mapping for real-time source localization. In terms of point spread and crosstalk between regions the proposed clustering technique performs better than selecting spatially evenly distributed dipoles. We conducted real-time source localization on MEG data from an auditory experiment. The results demonstrate that the proposed real-time method localizes sources reliably in the superior temporal gyrus. We conclude that real-time source estimation based on MEG is a feasible, useful addition to the standard on-line processing methods, and enables feedback based on neural activity during the measurements.

Association between white matter fiber structure and reward-related reactivity of the ventral striatum.

Individual responsiveness to rewards or rewarding stimuli may affect various domains of normal as well as pathological behavior. The ventral striatum/nucleus accumbens (NAcc) constitutes a key brain structure in the regulation of reward-appetitive behavior. It remains unclear, however, to which extent individual reward-related BOLD response in the NAcc is dependent on individual characteristics of connecting white matter fiber tracts. Using tract-based spatial statistics (TBSS) and statistical parametric mapping (SPM) this combined DTI - fMRI study investigated this question by correlating NAcc BOLD signal upon receipt of a monetary reward with different white matter characteristics (FA, axial diffusivity, radial diffusivity). The results show that increased integrity of white matter as assessed by FA in the cingulate and corpus callosum, the inferior fronto-occipital fasciculus, the anterior thalamic radiation and the anterior limb of the internal capsule was positively correlated with reward-related activation in the NAcc. There were no negative correlations as well as no significant results regarding axial and radial diffusivity. These findings indicate that microstructural properties of fiber tracts connecting, amongst others, the cortex with the striatum may influence intensity of reward-related responsiveness of the ventral striatum by constraining or increasing efficiency in information transfer within relevant circuitries involved in processing of reward.

Fast low-angle shot diffusion tensor imaging with stimulated echo encoding in the muscle of rabbit shank.

In the past, spin-echo (SE) echo planar imaging(EPI)-based diffusion tensor imaging (DTI) has been widely used to study the fiber structure of skeletal muscles in vivo. However, this sequence has several shortcomings when measuring restricted diffusion in small animals, such as its sensitivity to susceptibility-related distortions and a relatively short applicable diffusion time. To address these limitations, in the current work, a stimulated echo acquisition mode (STEAM) MRI technique, in combination with fast low-angle shot (FLASH) readout (turbo-STEAM MRI), was implemented and adjusted for DTI in skeletal muscles. Signal preparation using stimulated echoes enables longer effective diffusion times, and thus the detection of restricted diffusion within muscular tissue with intracellular distances up to 100 µm. Furthermore, it has a reduced penalty for fast T2 muscle signal decay, but at the expense of 50% signal loss compared with a SE preparation. Turbo-STEAM MRI facilitates high-resolution DTI of skeletal muscle without introducing susceptibility-related distortions. To demonstrate its applicability, we carried out rabbit in vivo measurements on a human whole-body 3 T scanner. DTI parameters of the shank muscles were extracted, including the apparent diffusion coefficient, fractional anisotropy, eigenvalues and eigenvectors. Eigenvectors were used to calculate maps of structural parameters, such as the planar index and the polar coordinates θ and ϕ of the largest eigenvector. These parameters were compared between three muscles. θ and ϕ showed clear differences between the three muscles, reflecting different pennation angles of the underlying fiber structures. Fiber tractography was performed to visualize and analyze the architecture of skeletal pennate muscles. Optimization of tracking parameters and utilization of T2 -weighted images for improved muscle boundary detection enabled the determination of additional parameters, such as the mean fiber length. The presented results support the applicability of turbo-STEAM MRI as a promising method for quantitative DTI analysis and fiber tractography in skeletal muscles.

Predicting disease-related MRI patterns of multiple sclerosis through GAN-based image editing.

INTRODUCTION: Multiple sclerosis (MS) is a complex neurodegenerative disorder that affects the brain and spinal cord. In this study, we applied a deep learning-based approach using the StyleGAN model to explore patterns related to MS and predict disease progression in magnetic resonance images (MRI). METHODS: We trained the StyleGAN model unsupervised using T1-weighted GRE MR images and diffusion-based ADC maps of MS patients and healthy controls. We then used the trained model to resample MR images from real input data and modified them by manipulations in the latent space to simulate MS progression. We analyzed the resulting simulation-related patterns mimicking disease progression by comparing the intensity profiles of the original and manipulated images and determined the brain parenchymal fraction (BPF). RESULTS: Our results show that MS progression can be simulated by manipulating MR images in the latent space, as evidenced by brain volume loss on both T1-weighted and ADC maps and increasing lesion extent on ADC maps. CONCLUSION: Overall, this study demonstrates the potential of the StyleGAN model in medical imaging to study image markers and to shed more light on the relationship between brain atrophy and MS progression through corresponding manipulations in the latent space.

Normative connectome-based analysis of sensorimotor deficits in acute subcortical stroke.

The interrelation between acute ischemic stroke, persistent disability, and uncertain prognosis underscores the need for improved methods to predict clinical outcomes. Traditional approaches have largely focused on analysis of clinical metrics, lesion characteristics, and network connectivity, using techniques such as resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). However, these methods are not routinely used in acute stroke diagnostics. This study introduces an innovative approach that not only considers the lesion size in relation to the National Institutes of Health Stroke Scale (NIHSS score), but also evaluates the impact of disrupted fibers and their connections to cortical regions by introducing a disconnection value. By identifying fibers traversing the lesion and estimating their number within predefined regions of interest (ROIs) using a normative connectome atlas, our method bypasses the need for individual DTI scans. In our analysis of MRI data (T1 and T2) from 51 patients with acute or subacute subcortical stroke presenting with motor or sensory deficits, we used simple linear regression to assess the explanatory power of lesion size and disconnection value on NIHSS score. Subsequent hierarchical multiple linear regression analysis determined the incremental value of disconnection metrics over lesion size alone in relation to NIHSS score. Our results showed that models incorporating the disconnection value accounted for more variance than those based solely on lesion size (lesion size explained 44% variance, disconnection value 60%). Furthermore, hierarchical regression revealed a significant improvement (p < 0.001) in model fit when adding the disconnection value, confirming its critical role in stroke assessment. Our approach, which integrates a normative connectome to quantify disconnections to cortical regions, provides a significant improvement in assessing the current state of stroke impact compared to traditional measures that focus on lesion size. This is achieved by taking into account the lesion's location and the connectivity of the affected white matter tracts, providing a more comprehensive assessment of stroke severity as reflected in the NIHSS score. Future research should extend the validation of this approach to larger and more diverse populations, with a focus on refining its applicability to clinical assessment and long-term outcome prediction.

Planning adaptive treatment by longitudinal response assessment implementing MR imaging, liquid biopsy and analysis of microenvironment during neoadjuvant treatment of rectal cancer (PRIMO).

INTRODUCTION: Conducting neoadjuvant chemoradiotherapy (CRT) and additional preoperative consolidating chemotherapy (CTx), that is, total neoadjuvant therapy (TNT), improves local control and complete response (CR) rates in locally advanced rectal cancer (LARC), putting the focus on organ preservation concepts. Therefore, assessing response before surgery is crucial. Some LARC patients would either not benefit from intensification by TNT or may reach CR, making resection not mandatory. Treatment of LARC should therefore be based on patient individual risk and response to avoid overtreatment.The "PRIMO" pilot study aims to determine early response assessment to form a basis for development and validation of a noninvasive response prediction model by a subsequent prospective multicenter trial, which is highly needed for individual, response-driven therapy adaptions. METHODS: PRIMO is a prospective observational cohort study including adult patients with LARC receiving neoadjuvant CRT. At least 4 multiparametric magnetic resonance imaging (MRI) scans (diffusion-weighted imaging [DWI] and hypoxia-sensitive sequences) as well as repeated blood samples in order to analyze circulating tumor cells (CTC) and cell-free tumor DNA (ctDNA) are scheduled. Pelvic radiotherapy (RT, 50.4 Gy) will be performed in combination with a 5-fluorouracil/oxaliplatin regimen in all patients (planned: N = 50), succeeded by consolidation CTx (FOLFOX4) if feasible. Additional (immuno)histochemical markers, such as tumor-infiltrating lymphocytes (TIL) and programmed death ligand 1 (PD-L1) status will be analyzed before and after CRT. Routine resection is scheduled subsequently, nonoperative management is offered alternatively in case of clinical CR (cCR).The primary endpoint is pathological response; secondary endpoints comprise longitudinal changes in MRI as well as in CTCs and TIL. These are evaluated for early response prediction during neoadjuvant therapy, in order to develop a noninvasive response prediction model for subsequent analyses. DISCUSSION: Early response assessment is the key in differentiating "good" and "bad" responders during neoadjuvant CRT, allowing adaption of subsequent therapies (additional consolidating CTx, organ preservation). This study will contribute in this regard, by advancing MR imaging and substantiating new surrogate markers. Adaptive treatment strategies might build on these results in further studies.

Perceiving age and gender in unfamiliar faces: an fMRI study on face categorization.

Efficient processing of unfamiliar faces typically involves their categorization (e.g., into old vs. young or male vs. female). However, age and gender categorization may pose different perceptual demands. In the present study, we employed functional magnetic resonance imaging (fMRI) to compare the activity evoked during age vs. gender categorization of unfamiliar faces. In different blocks, participants performed age and gender classifications for old or young unfamiliar faces (50% female respectively). Both tasks elicited activations in the bilateral fusiform gyri (fusiform face area, FFA) and bilateral inferior occipital gyri (occipital face area, OFA). Importantly, the same stimuli elicited enhanced activation during gender as compared to age categorization. This enhancement was significant in the right FFA and the left OFA, and may be related to increased configural processing. Our findings replicate and extend recent work, and shows that the activation of core components of the face processing network is strongly dependent on task demands.

Investigation of biases in convolutional neural networks for semantic segmentation using performance sensitivity analysis.

The application of deep neural networks for segmentation in medical imaging has gained substantial interest in recent years. In many cases, this variant of machine learning has been shown to outperform other conventional segmentation approaches. However, little is known about its general applicability. Especially the robustness against image modifications (e.g., intensity variations, contrast variations, spatial alignment) has hardly been investigated. Data augmentation is often used to compensate for sensitivity to such changes, although its effectiveness has not yet been studied. Therefore, the goal of this study was to systematically investigate the sensitivity to variations in input data with respect to segmentation of medical images using deep learning. This approach was tested with two publicly available segmentation frameworks (DeepMedic and TractSeg). In the case of DeepMedic, the performance was tested using ground truth data, while in the case of TractSeg, the STAPLE technique was employed. In both cases, sensitivity analysis revealed significant dependence of the segmentation performance on input variations. The effects of different data augmentation strategies were also shown, making this type of analysis a useful tool for selecting the right parameters for augmentation. The proposed analysis should be applied to any deep learning image segmentation approach, unless the assessment of sensitivity to input variations can be directly derived from the network.

Magnetic susceptibility anisotropy in normal appearing white matter in multiple sclerosis from single-orientation acquisition.

Quantitative susceptibility mapping (QSM) has been successfully applied to study changes in deep grey matter nuclei as well as in lesional tissue, but its application to white matter has been complicated by the observed orientation dependence of gradient echo signal. The anisotropic susceptibility tensor is thought to be at the origin of this orientation dependence, and magnetic susceptibility anisotropy (MSA) derived from this tensor has been proposed as a marker of the state and integrity of the myelin sheath and may therefore be of particular interest for the study of demyelinating pathologies such as multiple sclerosis (MS). Reconstruction of the susceptibility tensor, however, requires repeated measurements with multiple head orientations, rendering the approach impractical for clinical applications. In this study, we combined single-orientation QSM with fibre orientation information to assess apparent MSA in three white matter tracts, i.e., optic radiation (OR), splenium of the corpus callosum (SCC), and superior longitudinal fascicle (SLF), in two cohorts of 64 healthy controls and 89 MS patients. The apparent MSA showed a significant decrease in optic radiation in the MS cohort compared with healthy controls. It decreased in the MS cohort with increasing lesion load in OR and with disease duration in the splenium. All of this suggests demyelination in normal appearing white matter. However, the apparent MSA observed in the SLF pointed to potential systematic issues that require further exploration to realize the full potential of the presented approach. Despite the limitations of such single-orientation ROI-specific estimation, we believe that our clinically feasible approach to study degenerative changes in WM is worthy of further investigation.

1H-MR spectroscopic detection of metabolic changes in pain processing brain regions in the presence of non-specific chronic low back pain.

Reliable detection of metabolic changes in the brain in vivo induced by chronic low back pain may provide improved understanding of neurophysiological mechanisms underlying the manifestation of chronic pain. In the present study, absolute concentrations of N-acetyl-aspartate (NAA), creatine (Cr), total choline (tCho), myo-inositol (mI), glutamate (Glu) and glutamine (Gln) were measured in three different pain processing cortical regions (anterior insula, anterior cingulate cortex, and thalamus) of ten patients with non-specific chronic low back pain by means of proton MR spectroscopy ((1)H-MRS) and compared to matched healthy controls. Significant decrease of Glu was observed in the anterior cingulate cortex of patients. Patients also revealed a trend of decreasing Gln concentrations in all investigated brain areas. Reductions of NAA were observed in the patient group in anterior insula and in anterior cingulated cortex, whereas mI was reduced in anterior cingulated cortex and in thalamus of patients. Reduced concentrations of Glu and Gln may indicate disordered glutamatergic neurotransmission due to prolonged pain perception, whereas decrease of NAA and mI may be ascribed to neuron and glial cell loss. No significant changes were found for Cr. The morphological evaluation of anatomic brain data revealed a significantly decreased WM volume of 17% (p<0.05) as well as a non significant trend for GM volume increase in the anterior insula of patients.