Convolutional Neural Network With Graphical Lasso to Extract Sparse Topological Features for Brain Disease Classification

The functional connectivity provides new insights into the mechanisms of the human brain at network-level, which has been proved to be an effective biomarker for brain disease classification. Recently, machine learning methods have played an important role in functional connectivity classification, among which convolutional neural network (CNN) based methods become a new hot topic since they can extract topological features in the brain network. However, the conventional CNN-based methods haven't taken sparse connectivity patterns (SCPs) of the human brain into consideration, which may lead to redundancy of the topological features, and limit their performance and generalization. To solve it, we propose a novel CNN-based model with graphical Lasso (CNNGLasso) to extract sparse topological features for brain disease classification. First, we develop a novel graphical Lasso model for revealing the SCPs at group-level. Then, the SCPs are used to guide the topological feature extraction. Finally, the obtained sparse topological features are used to classify the patients from normal controls. The experiment results on the ABIDE dataset demonstrate that the CNNGLasso outperforms the others on various performances. Besides, the abnormal brain regions derived from the trained model are consistent with the previous investigations, which further proves the application prospect of the CNNGLasso.

A Novel Method for Differential Prognosis of Brain Degenerative Diseases Using Radiomics-Based Textural Analysis and Ensemble Learning Classifiers

We propose a novel approach to develop a computer-aided decision support system for radiologists to help them classify brain degeneration process as physiological or pathological, aiding in early prognosis of brain degenerative diseases. Our approach applies computational and mathematical formulations to extract quantitative information from biomedical images. Our study explores the longitudinal OASIS-3 dataset, which consists of 4096 brain MRI scans collected over a period of 15 years. We perform feature extraction using Pyradiomics python package that quantizes brain MRI images using different texture analysis methods. Studies indicate that Radiomics has rarely been used for analysis of brain cognition; hence, our study is also a novel effort to determine the efficiency of Radiomics features extracted from structural MRI scans for classification of brain degenerative diseases and to create awareness about Radiomics. For classification tasks, we explore various ensemble learning classification algorithms such as random forests, bagging-based ensemble classifiers, and gradient-boosted ensemble classifiers such as XGBoost and AdaBoost. Such ensemble learning classifiers have not been used for biomedical image classification. We also propose a novel texture analysis matrix, Decreasing Gray-Level Matrix or DGLM. The features extracted from this filter helped to further improve the accuracy of our decision support system. The proposed system based on XGBoost ensemble learning classifiers achieves an accuracy of 97.38%, with sensitivity 99.82% and specificity 97.01%.

A disease category feature database construction method of brain image based on deep convolutional neural network

BACKGROUND

Constructing a medical image feature database according to the category of disease can achieve a quick retrieval of images with similar pathological features. Therefore, this approach has important application values in the fields such as auxiliary diagnosis, teaching, research, and telemedicine.

METHODS

Based on the deep convolutional neural network, an image classifier applicable to brain disease was designed to distinguish between the image features of the different brain diseases with similar anatomical structures. Through the extraction and analysis of visual features, the images were labelled with the corresponding semantic features of a specific disease category, which can establish an association between the visual features of brain images and the semantic features of the category of disease which will permit to construct a disease category feature database of brain images.

RESULTS

Based on the similarity measurement and the matching strategy of high-dimensional visual feature, a high-precision retrieval of brain image with semantics category was achieved, and the constructed disease category feature database of brain image was tested and evaluated through large numbers of pathological image retrieval experiments, the accuracy and the effectiveness of the proposed approach was verified.

CONCLUSION

The disease category feature database of brain image constructed by the proposed approach achieved a quick and effective retrieval of images with similar pathological features, which is beneficial to the categorization and analysis of intractable brain diseases. This provides an effective application tool such as case-based image data management, evidence-based medicine and clinical decision support.

Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data

In this work, we study the potential of the deep residual neural network (ResNet) architecture to learn abstract neuroanatomical alterations in the structural MRI data by evaluating its diagnostic and prognostic classification performance on two large, independent multi-group (ADNI and BSNIP) neuroimaging datasets. We conduct several binary classification tasks to assess the diagnostic/prognostic performance of the ResNet architecture through a rigorous, repeated and stratified k-fold cross-validation procedure for each of the classification tasks independently. We obtained better than state of the art performance for the clinically most important task in the ADNI dataset analysis, and significantly higher classification accuracies over a standard machine learning method (linear SVM) in each of the ADNI and BSNIP classification tasks. Overall, our results indicate the high potential of this architecture to learn effectual feature representations from structural brain imaging data.

[Genetically determined epileptic encephalopathies]

Epileptic encephalopathies is a group of epileptic syndromes characterized by progressive cognitive impairment beyond the expected for the epilepsy activity. They are characterized by severe pharmaco-resistant epilepsy, severely abnormal electroencephalograms, early-age onset, neurocognitve impairment, variable phenotype and usually normal brain MRI. These syndromes are usually genetically determined. A correct and timely diagnosis could help and guide the medical counselling and the correct therapeutic approach improving the short, medium and long term outcomes. In this article we review the electroencephalographic and genetic findings along with the most recommended therapeutic options facilitating the clinical management. We include the following epileptic encephalopathy syndromes: Ohtahara, early myoclonic encephalopathy, epilepsy of infancy with migrating focal seizures, West, Dravet, non-progressive myoclonic status, Doose, Lennox-Gastaut, Landau-Kleffner and continuous spike-wave during sleep epilepsy.

Analysis of shared heritability in common disorders of the brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Consensus classification of posterior cortical atrophy

INTRODUCTION

A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings.

METHODS

Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA.

RESULTS

A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum.

DISCUSSION

There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead.

Case definition and classification of leukodystrophies and leukoencephalopathies

OBJECTIVE

An approved definition of the term leukodystrophy does not currently exist. The lack of a precise case definition hampers efforts to study the epidemiology and the relevance of genetic white matter disorders to public health.

METHOD

Thirteen experts at multiple institutions participated in iterative consensus building surveys to achieve definition and classification of disorders as leukodystrophies using a modified Delphi approach.

RESULTS

A case definition for the leukodystrophies was achieved, and a total of 30 disorders were classified under this definition. In addition, a separate set of disorders with heritable white matter abnormalities but not meeting criteria for leukodystrophy, due to presumed primary neuronal involvement and prominent systemic manifestations, was classified as genetic leukoencephalopathies (gLE).

INTERPRETATION

A case definition of leukodystrophies and classification of heritable white matter disorders will permit more detailed epidemiologic studies of these disorders.

Clinicoradiological spectrum of reversible splenial lesion syndrome (RESLES) in adults: a retrospective study of a rare entity

The presence of reversible lesions that involve the splenium of the corpus callosum (SCC) has been reported in patients with a broad spectrum of diseases and conditions and is referred to as reversible splenial lesion syndrome (RESLES).To describe the clinicoradiological features and establish a clinical position for this disease, we retrospectively examined the clinicoradiological features of adult RESLES patients, as well as discuss the potential pathophysiological mechanisms of this disease.The clinical and MRI findings of patients who presented with RESLES accompanied by symptoms of neurological disorders were retrospectively reviewed. The patients were classified into 2 subgroups (favorable and poor outcome subgroups), which corresponded to the severity of the disability using the Modified Oxford Handicap Scale. In addition, we compared the clinical and neuroimaging features between the 2 outcome subgroups.Eight patients with RESLES associated with various diseases and conditions were included. The clinical presentation was nonspecific; however, MRI exhibited consistent lesions in the SCC with a hypointensity on apparent diffusion coefficient maps and a hyperintensity via diffusion-weighted imaging, which disappeared after a variable lapse. The number of patients with a severe disturbance of consciousness, extracallosal lesions, or diffuse slow waves in the poor outcome subgroup was significantly increased compared with the favorable outcome subgroup (P < 0.05). Thus, the clinicoradiological spectrum of RESLES could be classified into 2 principal categories according to differential outcomes.RESLES is a rare entity with a broad clinicoradiological spectrum because of the various diseases and conditions. Although the overall symptoms of RESLES patients tend to be alleviated, the prognosis of patients with a severe disturbance of consciousness, extracallosal lesions, or diffuse slow waves is likely unfavorable.

Seven challenges for neuroscience

Although twenty-first century neuroscience is a major scientific enterprise, advances in basic research have not yet translated into benefits for society. In this paper, I outline seven fundamental challenges that need to be overcome. First, neuroscience has to become "big science" - we need big teams with the resources and competences to tackle the big problems. Second, we need to create interlinked sets of data providing a complete picture of single areas of the brain at their different levels of organization with "rungs" linking the descriptions for humans and other species. Such "data ladders" will help us to meet the third challenge - the development of efficient predictive tools, enabling us to drastically increase the information we can extract from expensive experiments. The fourth challenge goes one step further: we have to develop novel hardware and software sufficiently powerful to simulate the brain. In the future, supercomputer-based brain simulation will enable us to make in silico manipulations and recordings, which are currently completely impossible in the lab. The fifth and sixth challenges are translational. On the one hand we need to develop new ways of classifying and simulating brain disease, leading to better diagnosis and more effective drug discovery. On the other, we have to exploit our knowledge to build new brain-inspired technologies, with potentially huge benefits for industry and for society. This leads to the seventh challenge. Neuroscience can indeed deliver huge benefits but we have to be aware of widespread social concern about our work. We need to recognize the fears that exist, lay them to rest, and actively build public support for neuroscience research. We have to set goals for ourselves that the public can recognize and share. And then we have to deliver on our promises. Only in this way, will we receive the support and funding we need.

The masks of identities: who's who? Delusional misidentification syndromes

Delusional misidentification syndromes (DMSs) are complex psychotic phenomena that may be present in a variety of ways within the context of several neurological and psychiatric disorders. Since the first case of Capgras syndrome was described in 1923, various other syndromes have been identified, including Fregoli syndrome, intermetamorphosis, subjective doubles, reduplicative paramnesia, mirrored self, delusional companions, and clonal pluralization of the self. In this article, we review each of the different syndromes in definition and presentation, as well as the field's attempts at classifying them. We then describe their role in forensic psychiatry, particularly in regard to their potential as a marker of a particular subpopulation or of illness severity and their consideration in risk assessments of violence. A review of the literature was conducted for this purpose, and, although it was extended to include publications from over four decades, it revealed a paucity of research on DMSs.

Exclusion of progressive brain disorders of childhood for a cerebral palsy monitoring system: a public health perspective

BACKGROUND

Cerebral palsy (CP) is defined by its nonprogressive features. Therefore, a standard definition and list of progressive disorders to exclude would be useful for CP monitoring and epidemiologic studies.

METHODS

We reviewed the literature on this topic to 1) develop selection criteria for progressive brain disorders of childhood for public health surveillance purposes, 2) identify categories of disorders likely to include individual conditions that are progressive, and 3) ascertain information about the relative frequency and natural history of candidate disorders.

RESULTS

Based on 19 criteria that we developed, we ascertained a total of 104 progressive brain disorders of childhood, almost all of which were Mendelian disorders.

DISCUSSION

Our list is meant for CP surveillance programs and does not represent a complete catalog of progressive genetic conditions, nor is the list meant to comprehensively characterize disorders that might be mistaken for cerebral palsy. The criteria for progressive disorders that we developed could be applied by public health investigators in the future, as more children with very rare conditions are followed and new candidate disorders are identified.

[Neurocognitive disorders in DSM-5: a critical review]

BACKGROUND

The APA published the DSM-5 in May, 2013. When compared to dsm-iv, the latest edition incorporates many changes, some relating to neurocognitive disorders.

AIM

To review critically the new DSM-5 alterations and adjustments relating to neurocognitive disorders.

METHOD

We compared the relevant chapters in DSM-IV-TR and DSM-5 and we searched the literature for articles involving discussions about cognitive disorders in DSM-5.

RESULTS

With regard to differential diagnosis of neurocognitive disorders, DSM-5 has more in common with current clinical practice than does the DSM-IV. DSM-5 names ten etiological subtypes for which the diagnostic criteria are based on recent scientific research. However, some researchers and clinicians have reservations about using the term 'major neurocognitive disorder' instead of 'dementia', and are reluctant to make a distinction between 'mild' and 'major' cognitive disorders.

CONCLUSION

The alterations and adjustments that appear in DSM-5 in relation to neurocognitive disorders may well mean progress for clinicians and researchers but they will inevitably require greater investment.

[Mental disorders due to brain lesions in the DSM-5 in the light of the previous versions]

The DSM-5 introduces major modifications in the category of mental disorders due to brain lesions compared to the previous DSM versions, which are reviewed in this paper. The description of the category Major neurocognitive disorder, as a substitute for dementia, seems to fit better for patients and families, and more adapted to many neurodegenerative cognitive disorders for which memory impairment is not predominant. Similarly, the introduction of the category of Mild neurocognitive disorder appears to be an improvement although some difficulty still remains for distinguishing mild cognitive disorder from normal aging. The addition of new etiological categories such as fronto-temporal NCD or NCD with Lewy bodies should also to be considered as a significant improvement. Despite these advances, to circumscribe the mental disorders due to brain lesions to cognitive deficits and biological mechanisms remains highly questionable, and does not provide an adequate care for the patients and families if not complemented by a psychological and environmental approach.

Seven challenges for neuroscience

Although twenty-first century neuroscience is a major scientific enterprise, advances in basic research have not yet translated into benefits for society. In this paper, I outline seven fundamental challenges that need to be overcome. First, neuroscience has to become "big science" - we need big teams with the resources and competences to tackle the big problems. Second, we need to create interlinked sets of data providing a complete picture of single areas of the brain at their different levels of organization with "rungs" linking the descriptions for humans and other species. Such "data ladders" will help us to meet the third challenge - the development of efficient predictive tools, enabling us to drastically increase the information we can extract from expensive experiments. The fourth challenge goes one step further: we have to develop novel hardware and software sufficiently powerful to simulate the brain. In the future, supercomputer-based brain simulation will enable us to make in silico manipulations and recordings, which are currently completely impossible in the lab. The fifth and sixth challenges are translational. On the one hand we need to develop new ways of classifying and simulating brain disease, leading to better diagnosis and more effective drug discovery. On the other, we have to exploit our knowledge to build new brain-inspired technologies, with potentially huge benefits for industry and for society. This leads to the seventh challenge. Neuroscience can indeed deliver huge benefits but we have to be aware of widespread social concern about our work. We need to recognize the fears that exist, lay them to rest, and actively build public support for neuroscience research. We have to set goals for ourselves that the public can recognize and share. And then we have to deliver on our promises. Only in this way, will we receive the support and funding we need.

[Acquired brain injury: a proposal for its definition, diagnostic criteria and classification]

Acquired brain injury is a heterogeneous clinical concept that goes beyond the limits of the classical medical view, which tends to define processes and diseases on the grounds of a single causation. Although in the medical literature it appears fundamentally associated to traumatic brain injury, there are many other causes and management is similar in all of them, during the post-acute and chronic phases, as regards the measures to be taken concerning rehabilitation and attention to dependence. Yet, despite being an important health issue, today we do not have a set of diagnostic criteria or a classification for this condition. This is a serious handicap when it comes to carrying out epidemiological studies, designing specific care programmes and comparing results among different programmes and centres. Accordingly, the Extremadura Acquired Brain Injury Health Care Plan working group has drawn up these proposed diagnostic criteria, definition and classification. The proposal is intended to be essentially practical, its main purpose being to allow correct identification of the cases that must be attended to and to optimise the use of neurorehabilitation and attention to dependence resources, thereby ensuring attention is provided on a fair basis.

Neuropathologic measurements in focal cortical dysplasias: validation of the ILAE 2011 classification system and diagnostic implications for MRI

Focal cortical dysplasias (FCD) which represent a composite group of cortical malformations are increasingly recognized as morphological substrate for severe therapy-refractory epilepsy in children and young adults. However, presurgical evaluation remains challenging as not all FCD variants can be reliably detected by high-resolution magnetic resonance imaging (MRI). Here, we studied a cohort of 52 epilepsy patients with neuropathological evidence for FCD using the 2011 classification of the International League against Epilepsy (ILAE) and systematically analysed those histopathologic features applicable also for MRI diagnostics. Histopathologic parameters included quantitative measurements of cellular profiles, cortical thickness, heterotopic neurons in white matter, and myelination that were compared between FCD subtypes and age-/localization-matched controls (n = 36) using multivariate analysis. Dysmorphic neurons in both FCD Type II variants showed significantly increased diameter of their cell bodies and nuclei. Cortical thickness was also increased with a distinct loss of myelin content specifying FCD Type IIb from IIa. The data further suggested that myelination deficits in FCD Type IIb result from compromised oligodendroglial lineage differentiation and we concluded that the "transmantle sign" is a unique finding in FCD Type IIb. In contrast, FCD Type Ia was characterized by a smaller cortical ribbon and higher neuronal densities, but these parameters failed to reach statistical significance (considering age- and location-dependent variability in controls). All FCD variants showed abnormal grey-white matter boundaries with increased numbers of heterotopic neurons. Similar results were obtained also at deep white matter location. Thus, many FCD variants may indeed escape visual MRI inspection, but suspicious areas with increased or decreased cortical thickness as well as grey-white matter blurring may be uncovered using post-processing protocols of neuroimaging data. The systematic analysis of well-specified histopathological features could be helpful to improve sensitivity and specificity in MRI detection during pre-surgical work-up of patients with drug-resistant focal epilepsies.

Triphasic waves

Triphasic waves (TWs) are a distinctive, although non-specific EEG pattern, which are quite frequently encountered and sometimes difficult to interpret. Although initially considered pathognomonic of hepatic encephalopathy, TWs have been described in association with a large number of conditions. TWs may occur in encephalopathies (metabolic or structural) or as an ictal pattern. Nonepileptic TWs with sharply contoured morphology may resemble epileptic patterns encountered in nonconvulsive status epilepticus (NCSE), thus leading to misinterpretation and overinterpretation of this pattern as ictal, if only the EEG is considered. An electroclinical response to benzodiazepines and the evaluation of consciousness impairment should be considered when interpreting TWs. Evaluating only the EEG without considering also clinical and laboratory findings is not only useless and meaningless, but may even lead to serious consequences.

[Pathogenesis of acute encephalitis and acute encephalopathy]

Many aspects of the pathogenesis of acute encephalitis and acute encephalopathy have been clarified in this decade, although many unknown mechanisms remain to be elucidated. According to progress of MRI and neuroimmunological analysis and the observation of clinical findings, many new syndromes were found, which enhanced our understanding of acute encephalitis and acute encephalopathy. The pathogenesis of encephalitis is divided into infection and immune mediated mechanisms. The antibodies to neuronal surface antigens(NSA) such as NMDA receptors, leucin-rich glioma inactivated 1 (LGI1) and aquaporin 4 were demonstrated in specific encephalitis, limbic encephalitis and neuromyelitis optica. Anti-NSA antibody encephalitis should be treated by immunotherapy such as corticosteroid and plasmapheresis. Acute encephalitis with refractory repetitive partial seizures (AERRPS) is a devastating postinfectious disease in children and adults, although the pathogenesis of AERRPS is poorly understood. Influenza associated encephalopathy(IAE) is characterized by it's high incidence in Japanese children between 1 year and 5 years of age, its onset in the first or the second day of illness and its high mortality (15-30%) and morbidity (25-40%). We proposed the classification of IAE with poor prognosis from the neuroradiological findings. Four types of encephalopathy seem to be differentiated from each other, acute necrotizing encephalopathy (ANE) type, hemorrhagic shock and encephalopathy syndrome (HSES) type, acute brain swelling (ABS) type, febrile convulsive status epilepticus (FCSE) type. The notable radiological features are thalamic lesions in ANE, diffuse cerebral cortical cytotoxic edema in HSES, reversible cerebral swelling in ABS which sometimes reaches lethal brain herniation, and in FCSE type, dendritic high signal in subcortical white matter by DWI ("bright tree appearance") appears simultaneously with the later onset of repetitive focal seizure. These four types are not specific to IAE but are noticed in another encephalopathies caused by HHV6, rotavirus, etc.

From the background to the spotlight: TASK channels in pathological conditions

TWIK-related acid-sensitive potassium channels (TASK1-3) belong to the family of two-pore domain (K(2P) ) potassium channels. Emerging knowledge about an involvement of TASK channels in cancer development, inflammation, ischemia and epilepsy puts the spotlight on a leading role of TASK channels under these conditions. TASK3 has been especially linked to cancer development. The pro-oncogenic potential of TASK3 could be shown in cell lines and in various tumor entities. Pathophysiological hallmarks in solid tumors (e.g. low pH and oxygen deprivation) regulate TASK3 channels. These conditions can also be found in (autoimmune) inflammation. Inhibition of TASK1,2,3 leads to a reduction of T cell effector function. It could be demonstrated that TASK1(-/-) mice are protected from experimental autoimmune inflammation while the same animals display increased infarct volumes after cerebral ischemia. Furthermore, TASK channels have both an anti-epileptic as well as a pro-epileptic potential. The relative contribution of these opposing influences depends on their cell type-specific expression and the conditions of the cellular environment. This indicates that TASK channels are per se neither protective nor detrimental but their functional impact depends on the "pathophysiological" scenario. Based on these findings TASK channels have evolved from "mere background" channels to key modulators in pathophysiological conditions.

[Clinical re-evaluation of pediatric inflammatory disorders of the central nervous system:a study based on the new classification criteria proposed by the International Pediatric MS Study Group]

A retrospective analysis of the clinical and MRI features in 20 Japanese children diagnosed with central nervous system inflammatory demyelinating disorders was performed. Using the new criteria proposed by International Pediatric MS Study Group, half of children were reclassified into clinical isolated demyelinating syndrome (CIS). Presence of seizures and a pattern of diffuse bilateral lesions on brain MRIs are more frequent in children with ADEM than in CIS. However we suggest these features and encephalopathy may be associated with the age of patients. Furthermore, though persistence of abnormal MRI lesions is significantly more likely in the group of CIS, none of these patients had a subsequent recurrence or developed MS during the follow-up period. The prediction of patient prognosis seems to be difficult even based on the new criteria, and the nationwide multicenter analysis may be necessary in Japan for acquiring the definite conclusion.

[Trigeminal autonomic cephalgias. After initial diagnosis, consider secondary causes]

Trigeminal autonomic cephalgias (TAC) are classified as primary headache syndromes. The use of instrumental procedures including neuroimaging in the diagnostic workup of the TACs is controversially discussed in the literature. Several case reports have been previously published, reporting trigeminal autonomic cephalgias related to structural lesions. We contribute two of our own cases of symptomatic TACs and demonstrate that a "classic" clinical presentation does not preclude a symptomatic etiology. Thus, we advocate a systematic diagnostic evaluation including neuroimaging in every patient presenting with symptoms indicative of TAC for the first time.

Development of the Korean Academy of Medical Sciences Guideline for rating the impairment in the brain injured and brain diseased persons with motor dysfunction

To develop an objective and scientific method to evaluate the brain injured and brain diseased persons with motor dysfunction, American Medical Association's Guides to the Evaluation of Permanent Impairment was used as an exemplar. After the motor dysfunction due to brain injury or brain disease was confirmed, active range of motion and muscle strength of affected extremities were measured. Also, the total function of extremities was evaluated through the assessment of activities of daily living, fine coordination of hand, balance and gait. Then, the total score of manual muscle test and functional assessment of impaired upper and lower extremity were added, respectively. Spasticity of upper and lower extremity was used as minus factors. Patients with movement disorder such as Parkinson's disease were assessed based on the degree of dysfunction in response to medication. We develop a new rating system based on the concept of total score.

Lesion mapping of cognitive abilities linked to intelligence

The Wechsler Adult Intelligence Scale (WAIS) assesses a wide range of cognitive abilities and impairments. Factor analyses have documented four underlying indices that jointly comprise intelligence as assessed with the WAIS: verbal comprehension (VCI), perceptual organization (POI), working memory (WMI), and processing speed (PSI). We used nonparametric voxel-based lesion-symptom mapping in 241 patients with focal brain damage to investigate their neural underpinnings. Statistically significant lesion-deficit relationships were found in left inferior frontal cortex for VCI, in left frontal and parietal cortex for WMI, and in right parietal cortex for POI. There was no reliable single localization for PSI. Statistical power maps and cross-validation analyses quantified specificity and sensitivity of the index scores in predicting lesion locations. Our findings provide comprehensive lesion maps of intelligence factors, and make specific recommendations for interpretation and application of the WAIS to the study of intelligence in health and disease.

Complications during the Wada test

OBJECTIVE

The intracarotid amobarbital procedure (IAP) is routinely used in the preoperative workup of patients with epilepsy. We previously reported dissections and seizures as complications of this procedure and now have reviewed our cohort for additional complications associated with the IAP.

METHODS

Charts of 677 consecutive patients were reviewed for complications during the IAP.

RESULTS

Complications were observed in 74 patients (10.9%) and included encephalopathy (7.2%), seizures (1.2%), strokes (0.6%), transient ischemic attacks (0.6%), localized hemorrhage at the catheter insertion site (0.6%), carotid artery dissections (0.4%), allergic reaction to contrast (0.3%), bleeding from the catheter insertion site (0.1%), and infection (0.1%). Older patients were more prone to strokes and dissections, whereas younger patients more frequently experienced seizures. Use of amobarbital was associated with encephalopathy, whereas methohexital was related to seizures.

CONCLUSION

The IAP bears the risk of minor and major complications in up to 11% of patients. Risks, benefits, and possible alternative options have to be considered when a patient is to undergo the IAP.

[PET/CT-based classification of delayed radiation encephalopathy following radiotherapy for nasopharyngeal carcinoma]

OBJECTIVE

To investigate positron-emission tomography-computed tomography (PET/CT) findings of radiation encephalopathy (RE) following radiotherapy for nasopharyngeal carcinoma (NPC), observe the metabolic changes of the compromised brain tissues, and postulate the clinical classification of RE to provide reference for its diagnosis.

METHODS

This study included 53 pathologically confirmed NPC patients who received previous radical radiotherapy, and the diagnosis of RE was established according to the clinical manifestations and CT/PET findings. All the patients underwent PET/CT whole-body and head scans, and the image data were evaluated along with the clinical data of the patients.

RESULTS

RE most frequently involved the lateral or bilateral inferior temporal lobes. PET identified hypometabolic changes in the bilateral temporal lobes of 35 patients (70 lobes) and in the lateral temporal lobe of 18 patients (18 lobes). According to the PET/CT findings, the lesions were classified into 3 types, namely the oedema type (56 temporal lobes), liquefactive necrosis type (10 temporal lobes), and atrophic calcification type (22 temporal lobes). One patient with oedema type lesion received neurotrophic treatment and recovered completely with normal brain tissue density and metabolism, but the oedema type lesions in 2 patients progressed into to atrophic calcification type; the liquefactive necrotic lesions in another 2 patients also progressed into atrophic calcification type.

CONCLUSION

RE patients exhibit significant hypometabolic changes in the inferior temporal lobe on PET. According to the findings by PET/CT, RE can be classified into the oedema type, liquefactive necrosis type, and atrophic calcification type, and lesions of the former two types may progress into the third type.

Diagnosis of brain abnormality using both structural and functional MR images

A number of neurological diseases are associated with structural and functional alterations in the brain. This paper presents a method of using both structural and functional MR images for brain disease diagnosis, by machine learning and high-dimensional template warping. First, a high-dimensional template warping technique is used to complete morphological and functional representation for each individual brain in a template space, within a mass preserving framework. Then, statistical regional features are extracted to reduce the dimensionality of morphological and functional representation , as well as to achieve the robustness to registration errors and inter-subject variations. Finally, the most discriminative regional features are selected by a hybrid feature method for brain classification, using a nonlinear support vector machine. The proposed method has been applied to classifying the brain images of prenatally cocaine-exposed young adults from those of socioeconomically matched controls, resulting in 91.8% correct classification rate using a leave-one-out cross-validation. Comparison results show the effectiveness of our method and also the importance of simultaneously using both structural and functional images for brain classification.

[Prevalence of dementia or other form of organic brain disorder on a geriatric psychiatry ward]

INTRODUCTION

The prevalence of dementia in various geriatric psychiatry settings has previously been investigated and been found to lie between 15.2% and 61%. The present study investigated the percentage of patients with "organic brain disorder" [OBD] (dementia, acquired brain injury or other brain disease) in one geriatric psychiatric department in Copenhagen, Denmark.

MATERIALS AND METHODS

The journals of all patients admitted to the geriatric psychiatric department (locked ward, open ward, and day hospital) in 2002 were studied in order to find evidence of (a) psychiatric discharge diagnosis of OBD in 2002 (b) previous diagnosis of OBD (c) the basis of these diagnoses.

RESULTS

130 patients were admitted at least once in 2002. 33.1% had an OBD diagnosis at discharge, whilst a further 18.4% had documented evidence of previously diagnosed OBD and/or assessments supporting the presence of OBD. Effects of gender and age at first admission were found on discharge diagnosis.

CONCLUSION

There is evidence that over half of the patients admitted to the geriatric psychiatry department in this study had an OBD, which is higher than the percentage of patients who were discharged with this diagnosis. The possible consequences of findings and the drawbacks of the study are discussed.

Neonatal Encephalopathy and Socioeconomic Status

OBJECTIVE

To investigate the association between maternal socioeconomic status and the risk of encephalopathy in full-term newborns.

DESIGN

Population-based case-control study.

SETTING

Washington State births from 1994 through 2002 recorded in the linked Washington State Birth Registry and Comprehensive Hospital Abstract Reporting System.

PARTICIPANTS

Cases (n = 1060) were singleton full-term newborns with Comprehensive Hospital Abstract Reporting System International Classification of Diseases, Ninth Revision diagnoses of seizures, birth asphyxia, central nervous system dysfunction, or cerebral irritability. Control cases (n = 5330) were singleton full-term newborns selected from the same database. Main Exposures Socioeconomic status was defined by median income of the census tract of the mother's residence, number of years of maternal educational achievement, or maternal insurance status.

MAIN OUTCOME MEASURES

Odds ratios estimating the risk of encephalopathy associated with disadvantaged socioeconomic status were calculated in 3 separate analyses using multivariate adjusted logistic regression.

RESULTS

Newborns of mothers living in neighborhoods in which residents have a low median income were at increased risk of encephalopathy compared with newborns in neighborhoods in which residents have a median income more than 3 times the poverty level (adjusted odds ratio, 1.9; 95% confidence interval, 1.5-2.3). There was also a trend for increasing risk of encephalopathy associated with decreasing neighborhood income (P<.001). Newborns of mothers with less than 12 years of educational achievement had a higher risk of encephalopathy compared with newborns of mothers with more than 16 years of educational achievement (adjusted odds ratio, 1.7; 95% confidence interval, 1.3-2.3). Newborns of mothers receiving public insurance also had a higher risk of encephalopathy compared with newborns of mothers who have commercial insurance (adjusted odds ratio, 1.4; 95% confidence interval, 1.2-1.7).

CONCLUSION

Disadvantaged socioeconomic status was independently associated with an increased risk of encephalopathy in full-term newborns. These findings suggest that a mother's socioeconomic status may influence the risk of encephalopathy for her full-term newborn.

Diagnosis of dementia in primary care: a representative survey of family physicians and neuropsychiatrists in Germany

AIM

To measure the diagnostic competence of family physicians (FP) and neuropsychiatrists (NP) for moderate dementia.

METHODS

Written case vignettes describing moderate dementia either of Alzheimer type or vascular type were randomized to a representative sample of 122 FP and 68 NP, corresponding to response rates of 71.8 and 67.3%, respectively. They served as the basis for a structured face-to-face interview.

RESULTS

NP and FP did not differ with regard to their diagnostic considerations, however, concerning diagnostic workup. Vascular dementia was much better recognized than dementia of Alzheimer type. Neuropsychological tests and brain imaging would be done by 14.8 and 32.8% of the FP in the case of vascular dementia. In Alzheimer dementia they would apply these methods in 24.6 and 19.7%, respectively. The corresponding numbers for NP were about 60% in both cases for testing and more than 80% for brain imaging.

CONCLUSIONS

There is still a wide gap between guidelines and practice in primary care. The apparent overdiagnosis of vascular dementia may be one reason for the low drug treatment rates.

Trinucleotide repeat disorders

DNA trinucleotide repeat expansion diseases represent an interesting group of disorders that include a common cause of mental retardation and autism as well as neurodegenerative and other diseases. Many of these disorders have expression in the pediatric age group. The varied molecular mechanisms of these disorders make them model diseases for the study of mitochondrial dysfunction induced apoptosis, abnormal axonal transport induced apoptosis and disrupted transcription of neighboring genes. Clinical variation in the pathogenesis, severity, onset and inheritance of these disorders make them models for clinical study and research.

Atypical patterns of inheritance

The incomplete prediction of clinical phenotype from genotype in monogenic disorders assumes other complex mechanisms are responsible. Recent examples derived from well-known human diseases will be discussed in this review in the context of the roles of modifier genes, digenic and triallelic inheritance, and the consequence of imprinting and opposite transcripts in known human genetic disorders. Specifically, this review will focus on cystic fibrosis, Huntington's disease, sensory neural deafness due to Connexin gene mutations, Bardet-Biedl syndrome, and the Beckwith-Wiedemann syndrome as there is evidence that complex inheritance is responsible for at least part of the phenotypic variability that is not explainable by the genotype alone. This review is meant to extend and complement the other topics in this issue as the concept of atypical inheritance is explored in more detail.

Validity of the Children's Category Test-Level 1 in a clinical sample with heterogeneous forms of brain dysfunction

Validity of the Children's Category Test-Level 1 (CCT-1) was evaluated in 123 children with various forms of brain dysfunction. Confirmatory factor analyses indicated that the CCT-1 is composed of two factors. The first factor was composed of subtests II and III, and was named "Conceptual Discrimination", while the second was composed of subtests IV and V, and was named "Conceptual Memory". Both factors were more highly correlated with mathematical achievement than with reading or writing achievement. Comparisons between traumatic brain injury (TBI) and Attention-Deficit/Hyperactivity Disorder (ADHD) groups indicated that the Conceptual Discrimination factor was more sensitive to TBI than the Conceptual Memory factor. Also, the total error composite T-score was not particularly sensitive to ADHD. Findings indicate that the composite T-score should be interpreted with caution because it does not appear sensitive to milder forms of brain dysfunction and because the CCT-1 is a multidimensional procedure.

Prefrontal modulation of working memory performance in brain injury and disease

The inter-related cognitive constructs of working memory (WM) and processing speed are fundamental components to general intellectual functioning in humans. Importantly, both WM and processing speed are highly susceptible to disruption in cases of brain injury, neurologic illness, and even in normal aging. A goal of this article is to summarize and critique the functional imaging studies of speeded working memory in neurologically impaired populations. This review focuses specifically on the role of the lateral prefrontal cortex in mediating WM performance and integrates the relevant WM literature in healthy adults with the current findings in the clinical literature. One important finding emerging from a summary of this literature is the dissociable contributions made by ventrolateral and dorsolateral prefrontal cortex (VLPFC and DLPFC) in guiding performance on tasks of WM. Throughout this review, it is shown that when cerebral resources are challenged, it is DLPFC, and often right DLPFC specifically, that plays a critical role in modulating WM functioning. In addition, this article will examine the relationship between task performance and brain activation across studies to clarify the role of increased DLPFC activity in clinical samples. Finally, explanations are offered for the observed increased DLPFC activation and the potentially unique role of right DLPFC in mediating WM performance during periods of cerebral challenge.

Cost estimates of brain disorders in Belgium

This article presents the data on cost of the major brain disorders in Belgium which were retrieved from "Cost of Disorders of the Brain in Europe" study sponsored by the European Brain Council and performed by Stockholm Health Economics. The disorders selected were: addiction, depression, anxiety disorders, brain tumours, dementia, epilepsy, migraine and other headaches, multiple sclerosis, Parkinson's disease, psychotic disorders, stroke and trauma. Figures for prevalence of disorders and direct medical, direct non-medical and indirect costs are based on data coming from available electronic data bases, or when missing for Belgium, best possible estimates or extrapolated data were used. All economic data were transformed to Euro's for 2004 and adjusted for purchasing power parity (PPP). The results show that the total number of people with any brain disorder in Belgium amounts to 2.9 million in 2004, the most prevalent being anxiety disorders 1.1 million, migraine 860000, addiction (any) 800,000 and depression 500,000 cases. The total cost of all included brain disorders in Belgium was estimated at 10.6 billion Euros. Most costly per case are brain tumours, multiple sclerosis, stroke and dementia. Because of their higher prevalence, however depression, dementia, addiction, anxiety disorders and migraine have the highest total costs. Taken together brain disorders consume 4% of the gross national product and cost each citizen of Belgium 1029 Euros per year. The drug costs for brain disorders constitute only 10% of the total drug market in Belgium, and only 4% of the total cost of brain disorders in Belgium. This should be compared to the cost estimates and to a previous study which showed that brain disorders are responsible for 35% of the total burden of all disorders in Europe. This study suggests therefore that the direct healthcare resources, including expenses for drug therapies, allocated to brain disorders in Belgium are not leveled to the indirect costs and burden of these disorders. A comparison with data available from a direct prospective study in demented Belgian patients suggests that the mathematical estimates presented here reflect quite accurately the real average cost for dementia, although there are large variations depending on disease severity. As, in addition, subjects with brain disorders face collateral costs which have not been taken into associations, a complementary survey in the Belgian ecosystem to establish the cost profile of representative patients for the major brain disorders. Such a survey is being organized by a task force of the Belgian Brain Council.

Clinical characteristics of acute encephalopathy of obscure origin: a biphasic clinical course is a common feature

OBJECTIVE

To evaluate the clinical characteristics of acute encephalopathy of obscure origin (AE).

STUDY DESIGN

We examined clinical, imaging, and laboratory findings in children with AE. Specific subtypes of AE such as Reye's syndrome (RS), acute necrotizing encephalopathy (ANE), hemorrhagic shock and encephalopathy (HSE), acute encephalitis with refractory, repetitive partial seizures (AERRPS), and hemiconvulsion-hemiplegia syndrome (HH) were diagnosed. Other AE patients were regarded as non-specific subtype.

RESULTS

Nineteen patients were identified; specific AEs in 14 and non-specific AE in 5. Patients with RS, ANE, HSE frequently showed neuroimaging abnormalities (9/9) and significant elevation of liver enzymes (7/9) within 2 days after onset. Prognoses were extremely poor; early death in 6 and severe neurological sequelae in 3. Two of the 3 HH patients and 4 of the 5 non-specific AE patients showed biphasic clinical courses (AEBC); consciousness levels transiently improved following initial seizures and were exacerbated at the fourth to sixth days. In AEBC, neuroimaging abnormalities were rarely observed during the acute phase (1/5) but were detectable at clinical exacerbation. They rarely showed severely abnormal elevation in liver enzymes (1/6) and resulted in mild to moderate neurological sequelae (6/6).

CONCLUSION

A biphasic clinical course is a common feature in HH and non-specific AE.

Test performance and classification statistics for the Rey Auditory Verbal Learning Test in selected clinical samples

The Rey Auditory Verbal Learning Test [RAVLT; Rey, A. (1941). L'examen psychologique dans les cas d'encéphalopathie traumatique. Archives de Psychologie, 28, 21] is a commonly used neuropsychological measure that assesses verbal learning and memory. Normative data have been compiled [Schmidt, M. (1996). Rey Auditory and Verbal Learning Test: A handbook. Los Angeles, CA: Western Psychological Services]. When assessing an individual suspected of neurological dysfunction, useful comparisons include the extent that the patient deviates from healthy peers and also how closely the subject's performance matches those with known brain injury. This study provides the means and S.D.'s of 392 individuals with documented neurological dysfunction [closed head TBI (n=68), neoplasms (n=57), stroke (n=47), Dementia of the Alzheimer's type (n=158), and presurgical epilepsy left seizure focus (n=28), presurgical epilepsy right seizure focus (n=34)] and 122 patients with no known neurological dysfunction and psychiatric complaints. Patients were stratified into three age groups, 16-35, 36-59, and 60-88. Data were provided for trials I-V, List B, immediate recall, 30-min delayed recall, and recognition. Classification characteristics of the RAVLT using [Schmidt, M. (1996). Rey Auditory and Verbal Learning Test: A handbook. Los Angeles, CA: Western Psychological Services] meta-norms found the RAVLT to best distinguish patients suspected of Alzheimer's disease from the psychiatric comparison group.

Evolution of stimulus-induced rhythmic EEG discharges in three patients with encephalopathy

Stimulus-induced rhythmic EEG discharges (SIRDs) is a recently reported phenomenon in critically ill patients and little is known about their evolution. We found SIRDs in three patients with encephalopathy and followed them with serial EEGs. SIRDs appeared between 4 and 13 days after the onset of illness and persisted for 2-3 days. The discharges were elicited by tactile or nociceptive stimuli and lasted for 20-120 s. They were detected in 2/6, 1/3 and 2/11 EEGs performed between 9 and 32, 2 and 4 and 3 and 15 days, respectively, after the onset of illness. Their morphology varied: blunt triphasic waves, rhythmic delta activity and rhythmic sharp wave complexes. The background EEG activity was slowed or suppressed in all. One patient had acute disseminated encephalomyelitis (ADEM) with good recovery and the other two had fatal hypoxic ischemic encephalopathy. SIRDs appear to be a transient phenomena occurring in patients with encephalopathy, appearing hours to few days after the onset of illness. This is the first report of SIRDs in ADEM. Serial EEGs and repeated testing of EEG response to tactile and nociceptive stimuli is required for their detection. Larger number of patients with SIRDs need to be studied to assess their prognostic significance.

PRES: posterior or potentially reversible encephalopathy syndrome?

Posterior reversible encephalopathy syndrome (PRES) is an acronym that identifies a new clinico-neuroradiologic entity occurring in association with different conditions. We report a patient with eclamptic encephalopathy whose clinico-radiological picture normalised after prompt treatment. We suggest defining this condition as potentially RES, to emphasise that reversibility is not spontaneous but is usually related to an adequate treatment, and that the posterior localisation of the lesions, even if constant, may not represent the most relevant finding in some patients.

An online database for brain disease research

Background

The Stanley Medical Research Institute online genomics database (SMRIDB) is a comprehensive web-based system for understanding the genetic effects of human brain disease (i.e. bipolar, schizophrenia, and depression). This database contains fully annotated clinical metadata and gene expression patterns generated within 12 controlled studies across 6 different microarray platforms.

Description

A thorough collection of gene expression summaries are provided, inclusive of patient demographics, disease subclasses, regulated biological pathways, and functional classifications.

Conclusion

The combination of database content, structure, and query speed offers researchers an efficient tool for data mining of brain disease complete with information such as: cross-platform comparisons, biomarkers elucidation for target discovery, and lifestyle/demographic associations to brain diseases.

Pathogenesis of migration disorders

PURPOSE OF REVIEW

Neocortical neurons have to migrate from their site of production in the periventricular germinative zone or in the ganglionic eminence towards the cortical plate. Our understanding of the underlying molecular mechanisms has advanced considerably in recent years due to the identification of genes involved in human migration disorders and experimental studies. This review will highlight some of the most recent findings in the deciphering of the molecular machinery controlling neuronal migration.

RECENT FINDINGS

Neuronal migration is a complex process which involves cytoskeletal molecules controlling the initiation of migration, leading edge extension and nucleokinesis; signalling molecules (the reelin pathway playing a central role) integrating external signals and linking them to the cytoskeleton; stop signals; and other molecular players including neurotrophins, glutamate receptors and peroxisome-derived factors. Emerging evidence supports the existence of cross-talk between these pathways.

SUMMARY

Identifying these mechanisms has shed light on typical human neuronal migration disorders such as periventricular heterotopias (disorder of migration initiation linked to filamin), type I lissencephaly (cytoskeletal abnormality linked to Lis1, a microtubule-associated protein), double cortex syndrome (cytoskeletal abnormality linked to doublecortin, a microtubule-associated protein), or lissencephaly plus cerebellar hypoplasia (reelin defect).