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Background/Objectives: Hypnosis shows great potential for managing patients suffering from fibromyalgia and chronic pain. Several studies have highlighted its efficacy in improving pain, quality of life, and reducing psychological distress. Despite its known feasibility and efficacy, the mechanisms of action remain poorly understood. Building on these insights, this innovative study aims to assess neural activity during hypnosis in fibromyalgia patients using high-density electroencephalography (EEG) and self-reported measures. Methods : Thirteen participants with fibromyalgia were included in this study. EEG recordings were done during resting state and hypnosis conditions. After both conditions, levels of pain, comfort, absorption, and dissociation were assessed using a numerical rating scale. Time perception was collected via an open-ended question. The study was prospectively registered in the ClinicalTrials.gov public registry (NCT04263324). Results : Neural oscillations showed increased theta power during hypnosis in the left parietal and occipital electrodes, increased beta power in the frontal and left temporal electrodes, and increased slow-gamma power in the frontal and left parietal electrodes. Functional connectivity using pairwise-phase consistency measures showed decreased connectivity in the frontal electrodes during hypnosis. Graph-based measures, the node strength, and the cluster coefficient were lower in frontal electrodes in the slow-gamma bands during hypnosis compared to resting state. Key findings indicate significant changes in neural oscillations and brain functional connectivity, suggesting potential electrophysiological markers of hypnosis in this patient population.

Purpose: To study the utility of T2-weighted MRI sequences in the identification of the inferior intercavernous sinus (IICS), a potential source of bleeding during transsphenoidal surgery of pituitary adenomas., Methods: Pituitary sagittal T1W and coronal T2W MRI sequences were analyzed in 237 consecutive patients, after the exclusion of postoperative MRIs and those revealing an empty sella or a pituitary macroadenoma. Sphenoid sinus pneumatization was defined as incomplete (group 1) if it did not reach the nadir of the sella turcica, as complete (group 2) if it extended beyond the nadir of the sella or asymmetric (group 3), when only one side of the sinus was completely pneumatized., Results: In Group 2 (70% of the patients), the IICS was rarely visualized on coronal T2W MRI (6/167 patients-3.6%), whereas in Group 1 it was identified in nearly all patients (55/57 patients - 96.5%, p < 0.001). In Group 3, the IICS was only visible above the non-pneumatized part of the sphenoid sinus., Conclusions: The IICS can be identified on coronal T2W images in patients with an incompletely pneumatized sphenoid sinus, but very rarely in patients with a totally pneumatized sinus. This information can help to increase awareness among pituitary surgeons of the need to potentially manage IICS bleeding during transsphenoidal surgery in patients with an incompletely pneumatized sphenoid sinus., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Pituitary MRI is essential in the diagnosis of ACTH-dependent Cushing's syndrome, but its results are inconsistent. The demonstration of a sellar image compatible with the diagnosis of corticotropinoma varies from 40% to 90%, depending on the centre where the imaging is performed. In fact, the expertise of the neuroradiologist, use of a Tesla 3.0 MRI and choice of sequences are fundamental. The T2 and 3D gradient echo sequences after gadolinium injection are the most informative and today allow the detection of macro- and microadenomas in almost all cases. The diagnosis of numerous picoadenomas (<3-4 mm) is more challenging. The 2D and 3D spin echo or delayed T1 SE or FLAIR sequences after gadolinium can be used as a complement or to confirm a suspicious image. Characterization of corticotropinomas remains problematic. However, the correct assessment of so-called incidentalomas by recognizing artifacts, anatomical variants and frequent Rathke's cleft cysts eliminates around 90% of the incidentalomas that mimic pituitary adenomas, as repetitively reported in the literature. For the time being, there is reason to believe that hybrid imaging combining PET and MRI such as 11C-methionine PET coregistered with volumetric MRI will solve the diagnosis of corticotropinomas in the near future., (© 2022 British Society for Neuroendocrinology.)

Context: Ectopic acromegaly is a consequence of rare neuroendocrine tumors (NETs) that secrete GHRH. This abnormal GHRH secretion drives GH and IGF-1 excess, with a clinical presentation similar to classical pituitary acromegaly. Identifying the underlying cause for the GH hypersecretion in the setting of ectopic GHRH excess is, however, essential for proper management both of acromegaly and the NET. Owing to the rarity of NETs, the imaging characteristics of the pituitary in ectopic acromegaly have not been analyzed in depth in a large series., Objective: Characterize pituitary magnetic resonance imaging (MRI) features at baseline and after NET treatment in patients with ectopic acromegaly., Design: Multicenter, international, retrospective., Setting: Tertiary referral pituitary centers., Patients: Thirty ectopic acromegaly patients having GHRH hypersecretion., Intervention: None., Main Outcome Measure: MRI characteristics of pituitary gland, particularly T2-weighted signal., Results: In 30 patients with ectopic GHRH-induced acromegaly, we found that most patients had hyperplastic pituitaries. Hyperplasia was usually moderate but was occasionally subtle, with only small volume increases compared with normal ranges for age and sex. T2-weighted signal was hypointense in most patients, especially in those with hyperplastic pituitaries. After treatment of the NET, pituitary size diminished and T2-weighted signal tended to normalize., Conclusions: This comprehensive study of pituitary MRI characteristics in ectopic acromegaly underlines the utility of performing T2-weighted sequences in the MRI evaluation of patients with acromegaly as an additional tool that can help to establish the correct diagnosis., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Glioblastoma (GBM) is the most aggressive primary brain tumor, characterized by a heterogeneous and abnormal vascularity. Subtypes of vascular habitats within the tumor and edema can be distinguished: high angiogenic tumor (HAT), low angiogenic tumor (LAT), infiltrated peripheral edema (IPE), and vasogenic peripheral edema (VPE)., Purpose: To validate the association between hemodynamic markers from vascular habitats and overall survival (OS) in glioblastoma patients, considering the intercenter variability of acquisition protocols., Study Type: Multicenter retrospective study., Population: In all, 184 glioblastoma patients from seven European centers participating in the NCT03439332 clinical study., Field Strength/sequence: 1.5T (for 54 patients) or 3.0T (for 130 patients). Pregadolinium and postgadolinium-based contrast agent-enhanced T 1 -weighted MRI, T 2 - and FLAIR T 2 -weighted, and dynamic susceptibility contrast (DSC) T 2 * perfusion., Assessment: We analyzed preoperative MRIs to establish the association between the maximum relative cerebral blood volume (rCBV max ) at each habitat with OS. Moreover, the stratification capabilities of the markers to divide patients into "vascular" groups were tested. The variability in the markers between individual centers was also assessed., Statistical Tests: Uniparametric Cox regression; Kaplan-Meier test; Mann-Whitney test., Results: The rCBV max derived from the HAT, LAT, and IPE habitats were significantly associated with patient OS (P < 0.05; hazard ratio [HR]: 1.05, 1.11, 1.28, respectively). Moreover, these markers can stratify patients into "moderate-" and "high-vascular" groups (P < 0.05). The Mann-Whitney test did not find significant differences among most of the centers in markers (HAT: P = 0.02-0.685; LAT: P = 0.010-0.769; IPE: P = 0.093-0.939; VPE: P = 0.016-1.000)., Data Conclusion: The rCBV max calculated in HAT, LAT, and IPE habitats have been validated as clinically relevant prognostic biomarkers for glioblastoma patients in the pretreatment stage. This study demonstrates the robustness of the hemodynamic tissue signature (HTS) habitats to assess the GBM vascular heterogeneity and their association with patient prognosis independently of intercenter variability., Level of Evidence: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1478-1486., (© 2019 International Society for Magnetic Resonance in Medicine.)

Adipsic diabetes insipidus is a rare complication of intracranial tumors in which impaired antidiuretic hormone secretion is associated with the loss of thirst sensation. Here, we present the case of a patient with bifocal intracranial germinoma, diagnosed due to symptoms mainly caused by adipsic diabetes insipidus. This is, to our knowledge, the first case of adipsic diabetes insipidus revealing an intracranial germinoma reported in the literature. We describe the diagnostic procedures and the three-year follow-up of this patient. Management of intracranial germ-cell tumors is made complex by the wide range of histological features. Although germinomas have a generally better prognosis than most nongerminomatous tumors, they can have severe or even life-threatening presentations. Adipsic diabetes insipidus is one such severe presentation and its rarity can make it difficult to recognize and manage. Awareness of this potential entity is therefore important for clinical practice., (Copyright © 2017 Elsevier Masson SAS. All rights reserved.)

Kidney transplantation (KTx) represents the best available treatment for patients with end-stage renal disease. Still, full benefits of KTx are undermined by acute rejection (AR). The diagnosis of AR ultimately relies on transplant needle biopsy. However, such an invasive procedure is associated with a significant risk of complications and is limited by sampling error and interobserver variability. In the present review, we summarize the current literature about non-invasive approaches for the diagnosis of AR in kidney transplant recipients (KTRs), including in vivo imaging, gene expression profiling and omics analyses of blood and urine samples. Most imaging techniques, like contrast-enhanced ultrasound and magnetic resonance, exploit the fact that blood flow is significantly lowered in case of AR-induced inflammation. In addition, AR-associated recruitment of activated leukocytes may be detectable by 18 F-fluoro-deoxy-glucose positron emission tomography. In parallel, urine biomarkers, including CXCL9/CXCL10 or a three-gene signature of CD3ε, IP-10 and 18S RNA levels, have been identified. None of these approaches has been adopted yet in the clinical follow-up of KTRs, but standardization of procedures may help assess reproducibility and compare diagnostic yields in large prospective multicentric trials.

Kidney transplantation (KTx) represents the best available treatment for patients with end-stage renal disease. Still, the full benefits of KTx are undermined by acute rejection (AR). The diagnosis of AR ultimately relies on transplant needle biopsy. However, such an invasive procedure is associated with a significant risk of complications and is limited by sampling error and interobserver variability. In the present review, we summarize the current literature about non-invasive approaches for the diagnosis of AR in kidney transplant recipients (KTRs), including in vivo imaging, gene-expression profiling and omics analyses of blood and urine samples. Most imaging techniques, such as contrast-enhanced ultrasound and magnetic resonance, exploit the fact that blood flow is significantly lowered in case of AR-induced inflammation. In addition, AR-associated recruitment of activated leucocytes may be detectable by 18F-fluorodeoxyglucose positron emission tomography. In parallel, urine biomarkers, including CXCL9/CXCL10 or a three-gene signature of CD3ε, CXCL10 and 18S RNA levels, have been identified. None of these approaches has yet been adopted in the clinical follow-up of KTRs, but standardization of analysis procedures may help assess reproducibility and comparative diagnostic yield in large, prospective, multicentre trials.

GH-secreting pituitary adenomas can be hypo-, iso- or hyper-intense on T2-weighted MRI sequences. We conducted the current multicenter study in a large population of patients with acromegaly to analyze the relationship between T2-weighted signal intensity on diagnostic MRI and hormonal and tumoral responses to somatostatin analogs (SSA) as primary monotherapy. Acromegaly patients receiving primary SSA for at least 3 months were included in the study. Hormonal, clinical and general MRI assessments were performed and assessed centrally. We included 120 patients with acromegaly. At diagnosis, 84, 17 and 19 tumors were T2-hypo-, iso- and hyper-intense, respectively. SSA treatment duration, cumulative and mean monthly doses were similar in the three groups. Patients with T2-hypo-intense adenomas had median SSA-induced decreases in GH and IGF-1 of 88% and 59% respectively, which were significantly greater than the decreases observed in the T2-iso- and hyper-intense groups (P < 0.001). Tumor shrinkage on SSA was also significantly greater in the T2-hypo-intense group (38%) compared with the T2-iso- and hyper-intense groups (8% and 3%, respectively; P < 0.0001). The response to SSA correlated with the calculated T2 intensity: the lower the T2-weighted intensity, the greater the decrease in random GH (P < 0.0001, r = 0.22), IGF-1 (P < 0.0001, r = 0.14) and adenoma volume (P < 0.0001, r = 0.33). The T2-weighted signal intensity of GH-secreting adenomas at diagnosis correlates with hormone reduction and tumor shrinkage in response to primary SSA treatment in acromegaly. This study supports its use as a generally available predictive tool at diagnosis that could help to guide subsequent treatment choices in acromegaly., (© 2016 Society for Endocrinology.)

Background: Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in which patients regain the capacity for functional communication, object use, or both. We investigated neural correlates of consciousness in these patients compared with patients with disorders of consciousness and healthy controls, by multimodal imaging., Methods: In this cross-sectional, multimodal imaging study, patients with unresponsive wakefulness syndrome, patients in a minimally conscious state, and patients who had emerged from a minimally conscious state, diagnosed with the Coma Recovery Scale-Revised, were recruited from the neurology department of the Centre Hospitalier Universitaire de Liège, Belgium. Key exclusion criteria were neuroimaging examination in an acute state, sedation or anaesthesia during scanning, large focal brain damage, motion parameters of more than 3 mm in translation and 3° in rotation, and suboptimal segmentation and normalisation. We acquired resting state functional and structural MRI data and (18)F-fluorodeoxyglucose (FDG) PET data; we used seed-based functional MRI (fMRI) analysis to investigate positive default mode network connectivity (within-network correlations) and negative default mode network connectivity (between-network anticorrelations). We correlated FDG-PET brain metabolism with fMRI connectivity. We used voxel-based morphometry to test the effect of anatomical deformations on functional connectivity., Findings: We recruited a convenience sample of 58 patients (21 [36%] with unresponsive wakefulness syndrome, 24 [41%] in a minimally conscious state, and 13 [22%] who had emerged from a minimally conscious state) and 35 healthy controls between Oct 1, 2009, and Oct 31, 2014. We detected consciousness-level-dependent increases (from unresponsive wakefulness syndrome, minimally conscious state, emergence from minimally conscious state, to healthy controls) for positive and negative default mode network connectivity, brain metabolism, and grey matter volume (p<0·05 false discovery rate corrected for multiple comparisons). Positive default mode network connectivity differed between patients and controls but not among patient groups (F test p<0·0001). Negative default mode network connectivity was only detected in healthy controls and in those who had emerged from a minimally conscious state; patients with unresponsive wakefulness syndrome or in a minimally conscious state showed pathological between-network positive connectivity (hyperconnectivity; F test p<0·0001). Brain metabolism correlated with positive default mode network connectivity (Spearman's r=0·50 [95% CI 0·26 to 0·61]; p<0·0001) and negative default mode network connectivity (Spearman's r=-0·52 [-0·35 to -0·67); p<0·0001). Grey matter volume did not differ between the studied groups (F test p=0·06)., Interpretation: Partial preservation of between-network anticorrelations, which are seemingly of neuronal origin and cannot be solely explained by morphological deformations, characterise patients who have emerged from a minimally conscious state. Conversely, patients with disorders of consciousness show pathological between-network correlations. Apart from a deeper understanding of the neural correlates of consciousness, these findings have clinical implications and might be particularly relevant for outcome prediction and could inspire new therapeutic options., Funding: Belgian National Funds for Scientific Research (FNRS), European Commission, Natural Sciences and Engineering Research Council of Canada, James McDonnell Foundation, European Space Agency, Mind Science Foundation, French Speaking Community Concerted Research Action, Fondazione Europea di Ricerca Biomedica, University and University Hospital of Liège (Liège, Belgium), and University of Western Ontario (London, ON, Canada)., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Cardiac magnetic resonance (CMR) is increasingly used for the diagnosis and management of cardiac diseases. Recent studies have reported immediate post-CMR DNA double-strand breaks in T lymphocytes. We sought to evaluate CMR-induced DNA damage in lymphocytes, alterations of blood cells, and their temporal persistence., Methods and Results: In 20 prospectively enrolled healthy men (31.4±7.9 years), blood was drawn before and after (1-2 hours, 2 days, 1 month, and 1 year) unenhanced 1.5T CMR. Blood cell counts, cell death, and activation status of lymphocytes, monocytes, neutrophils, and platelets were evaluated. The first 2-hour post-CMR were characterized by a small increase of lymphocyte B and neutrophil counts and a transient drop of total lymphocytes because of a decrease in natural killer cells. Among blood cells, only neutrophils and monocytes displayed slight and transient activation. DNA double-strand breaks in lymphocytes were quantified through flow cytometric analysis of H2AX phosphorylation (γ-H2AX). γ-H2AX intensity in T lymphocytes did not change early after CMR but increased significantly at day 2 ≤1 month before returning to baseline levels of 1-year post-CMR., Conclusions: Unenhanced CMR is associated with minor but significant immediate blood cell alterations or activations figuring inflammatory response, as well as DNA damage in T lymphocytes observed from day 2 until the first month but disappearing at 1-year follow-up. Although further studies are required to definitely state whether CMR can be used safely, our findings already call for caution when it comes to repeat this examination within a month., (© 2015 American Heart Association, Inc.)

Despite advances in resting state functional magnetic resonance imaging investigations, clinicians remain with the challenge of how to implement this paradigm on an individualized basis. Here, we assessed the clinical relevance of resting state functional magnetic resonance imaging acquisitions in patients with disorders of consciousness by means of a systems-level approach. Three clinical centres collected data from 73 patients in minimally conscious state, vegetative state/unresponsive wakefulness syndrome and coma. The main analysis was performed on the data set coming from one centre (Liège) including 51 patients (26 minimally conscious state, 19 vegetative state/unresponsive wakefulness syndrome, six coma; 15 females; mean age 49 ± 18 years, range 11-87; 16 traumatic, 32 non-traumatic of which 13 anoxic, three mixed; 35 patients assessed >1 month post-insult) for whom the clinical diagnosis with the Coma Recovery Scale-Revised was congruent with positron emission tomography scanning. Group-level functional connectivity was investigated for the default mode, frontoparietal, salience, auditory, sensorimotor and visual networks using a multiple-seed correlation approach. Between-group inferential statistics and machine learning were used to identify each network's capacity to discriminate between patients in minimally conscious state and vegetative state/unresponsive wakefulness syndrome. Data collected from 22 patients scanned in two other centres (Salzburg: 10 minimally conscious state, five vegetative state/unresponsive wakefulness syndrome; New York: five minimally conscious state, one vegetative state/unresponsive wakefulness syndrome, one emerged from minimally conscious state) were used to validate the classification with the selected features. Coma Recovery Scale-Revised total scores correlated with key regions of each network reflecting their involvement in consciousness-related processes. All networks had a high discriminative capacity (>80%) for separating patients in a minimally conscious state and vegetative state/unresponsive wakefulness syndrome. Among them, the auditory network was ranked the most highly. The regions of the auditory network which were more functionally connected in patients in minimally conscious state compared to vegetative state/unresponsive wakefulness syndrome encompassed bilateral auditory and visual cortices. Connectivity values in these three regions discriminated congruently 20 of 22 independently assessed patients. Our findings point to the significance of preserved abilities for multisensory integration and top-down processing in minimal consciousness seemingly supported by auditory-visual crossmodal connectivity, and promote the clinical utility of the resting paradigm for single-patient diagnostics., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Introduction: Clinical presentations of prolactinomas are quite different between genders. In comparison with women's prolactinoma, those in men showed predominance of large tumors with high prolactin (PRL) levels. This preponderance could be attributed to a greater proliferative potential of the tumors. Differences in magnetic resonance imaging (MRI) signal at diagnosis have not been yet clearly evaluated., Methods: We conduct a retrospective study comparing MRI signal intensity (SI) on T2-weighted images (T2-WI) between 41 men and 41 women to investigate whether or not men prolactinoma present specific features., Results: In addition to the size of the adenoma and PRL levels (P < 0001), prolactinomas in men also exhibit differences from those in women in signal on T2-WI on MRI (P < 0001). Women's prolactinomas are mostly of high SI on T2-WI while men's prolactinomas exhibit a more heterogeneous pattern of SI on T2-WI. Prolactinomas presenting with low SI on T2-WI are almost exclusively encountered in men., Conclusions: Presence of T2-WI hypointensities in pituitary adenoma can be predictive of a different subtype of prolactinoma almost encountered in men and possibly translate the presence of spherical amyloid deposits, in agreement with the literature.

Objective: What mechanisms underlie the loss and recovery of consciousness after severe brain injury? We sought to establish, in the largest cohort of patients with disorders of consciousness (DOC) to date, the link between gold standard clinical measures of awareness and wakefulness, and specific patterns of local brain pathology-thereby possibly providing a mechanistic framework for patient diagnosis, prognosis, and treatment development., Methods: Structural T1-weighted magnetic resonance images were collected, in a continuous sample of 143 severely brain-injured patients with DOC (and 96 volunteers), across 2 tertiary expert centers. Brain atrophy in subcortical regions (bilateral thalamus, basal ganglia, hippocampus, basal forebrain, and brainstem) was assessed across (1) healthy volunteers and patients, (2) clinical entities (eg, vegetative state, minimally conscious state), (3) clinical measures of consciousness (Coma Recovery Scale-Revised), and (4) injury etiology., Results: Compared to volunteers, patients exhibited significant atrophy across all structures (p < 0.05, corrected). Strikingly, we found almost no significant differences across clinical entities. Nonetheless, the clinical measures of awareness and wakefulness upon which differential diagnosis rely were systematically associated with tissue atrophy within thalamic and basal ganglia nuclei, respectively; the basal forebrain was atrophied in proportion to patients' response to sensory stimulation. In addition, nontraumatic injuries exhibited more extensive thalamic atrophy., Interpretation: These findings provide, for the first time, a grounding in pathology for gold standard behavior-based clinical measures of consciousness, and reframe our current models of DOC by stressing the different links tying thalamic mechanisms to willful behavior and extrathalamic mechanisms to behavioral (and electrocortical) arousal., (© 2015 American Neurological Association.)

Background: Zolpidem, a short-acting non-benzodiazepine GABA agonist hypnotic, has been shown to induce paradoxical responses in some patients with disorders of consciousness (DOC), leading to recovery of arousal and cognitive abilities. We here assessed zolpidem-induced changes in regional brain metabolism in three patients with known zolpidem response in chronic post-anoxic minimally conscious state (MCS)., Methods: [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) and standardized clinical assessments using the Coma Recovery Scale-Revised were performed after administration of 10 mg zolpidem or placebo in a randomized double blind 2-day protocol. PET data preprocessing and comparison with a healthy age-matched control group were performed using statistical parametric mapping (SPM8)., Results: Behaviorally, all patients recovered functional communication after administration of zolpidem (i.e., emergence from the MCS). FDG-PET showed increased metabolism in dorsolateral prefrontal and mesiofrontal cortices after zolpidem but not after placebo administration., Conclusion: Our data show a metabolic activation of prefrontal areas, corroborating the proposed mesocircuit hypothesis to explain the paradoxical effect of zolpidem observed in some patients with DOC. It also suggests the key role of the prefrontal cortices in the recovery of functional communication and object use in hypoxic patients with chronic MCS.

Introduction: In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects., Methods: 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy., Results: Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects., Conclusions: FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Medical imaging plays a crucial role in the diagnosis, staging and therapeutic strategy of oncologic patients. The development of medical imaging over the last decade has allowed significant progresses in radiotherapy. Indeed, medical imaging is now considered the corner stone of radiotherapy. The main challenge for the radiation oncologist consists in the tumour identification with a view to irradiate the tumour at a curative dose while avoiding healthy tissues. To achieve these goals, the radiotherapist daily uses anatomical imaging such as computed tomography (CT) or magnetic resonance imaging (MRI). Since several years now, the development of functional imaging such as positron emission tomography (PET) combined with CT or functional MRI has opened new perspectives in the management of oncologic diseases. Indeed, these imaging techniques offer new information on tumour metabolism that may be taken into account to plan the radiotherapy treatment. This article illustrates the different imaging techniques used in radiotherapy and the role of functional imaging for establishing new therapeutic strategies in radiation oncology.

Glioblastoma is a primary brain tumor that occurs most often in elderly patients. Despite improved management, the prognosis of this cancer remains poor. This review describes the multidisciplinary management of the patient with glioblastoma. It includes surgery, radiation therapy and chemotherapy.

In this paper, we present a novel approach for functional network connectivity in fMRI resting activity using distance correlation. The proposed method accounts for nonlinear relationships between the resting state networks and can be used for both single subject and group level analyses. We showed that the new strategy improves the capacity of characterization of pathological populations, such as, patients with disorder of consciousness, when compared to related approaches.

Cerebrotendinous xanthomatosis (CTX) is a rare and treatable autosomal recessive disease. The diagnosis should be suspected in the presence of a suggestive clinical triad characterized by early-onset cataract, tendinous xanthomata and neurological symptoms and signs, notably cerebellar ataxia, mental retardation and pyramidal syndrome.The diagnosis is confirmed by demonstrating an increased blood level of cholestanol, or/and by molecular genetic analysis.In typical cases, brain MRI shows bilateral hyperintensity of the cerebellar nucleus dentatus together with cerebral atrophy and leukoencephalopathy. The treatment is based on the administration of chenodeoxycholic acid. The aim is to restore the negative feedback on the enzymatic cascade altered by mutation in the gene CYP27 which induces a 27-hydroxylase deficiency

Background: Existing methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging (DTI)., Methods: In a multicenter study, the authors prospectively enrolled 105 patients who remained comatose at least 7 days after traumatic brain injury. Patients underwent brain magnetic resonance imaging, including DTI in 20 preselected white matter tracts. Patients were evaluated at 1 yr with a modified Glasgow Outcome Scale. A composite DTI score was constructed for outcome prognostication on this training database and then validated on an independent database (n=38). DTI score was compared with the International Mission for Prognosis and Analysis of Clinical Trials Score., Results: Using the DTI score for prediction of unfavorable outcome on the training database, the area under the receiver operating characteristic curve was 0.84 (95% CI: 0.75-0.91). The DTI score had a sensitivity of 64% and a specificity of 95% for the prediction of unfavorable outcome. On the validation-independent database, the area under the receiver operating characteristic curve was 0.80 (95% CI: 0.54-0.94). On the training database, reclassification methods showed significant improvement of classification accuracy (P < 0.05) compared with the International Mission for Prognosis and Analysis of Clinical Trials score. Similar results were observed on the validation database., Conclusions: White matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score.

MRI Diffusion Tensor Imaging (DTI) has been recently proposed as a highly discriminative measurement to detect structural damages in Disorders of Consciousness patients (Vegetative State/Unresponsive Wakefulness Syndrome-(VS/UWS) and Minimally Consciousness State-MCS). In the DTI analysis, certain tensor features are often used as simplified scalar indices to represent these alterations. Those characteristics are mathematically and statistically more tractable than the full tensors. Nevertheless, most of these quantities are based on a tensor diffusivity estimation, the arithmetic average among the different strengths of the tensor orthogonal directions, which is supported on a symmetric linear relationship among the three directions, an unrealistic assumption for severely damaged brains. In this paper, we propose a new family of scalar quantities based on Generalized Ordered Weighted Aggregations (GOWA) to characterize morphological damages. The main idea is to compute a tensor diffusitivity estimation that captures the deviations in the water diffusivity associated to damaged tissue. This estimation is performed by weighting and combining differently each tensor orthogonal strength. Using these new scalar quantities we construct an affine invariant DTI tensor feature using regional tissue histograms. An evaluation of these new scalar quantities on 48 patients (23 VS/UWS and 25 MCS) was conducted. Our experiments demonstrate that this new representation outperforms state-of-the-art tensor based scalar representations for characterization and classification problems.