Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Assessment of a new MRI classification of spinal stenosis based on cross-sectional morphology of the dural sac : FM2

Introduction: Quantitative measures of degree of lumbar spinal stenosis (LSS) such as antero-posterior diameter of the canal or dural sac cross sectional area vary widely and do not correlate with clinical symptoms or results of surgical decompression. In an effort to improve quantification of stenosis we have developed a grading system based on the morphology of the dural sac and its contents as seen on T2 axial images. The grading comprises seven categories ranging form normal to the most severe stenosis and takes into account the ratio of rootlet/CSF content. Material and methods: Fifty T2 axial MRI images taken at disc level from twenty seven symptomatic lumbar spinal stenosis patients who underwent decompressive surgery were classified into seven categories by five observers and reclassified 2 weeks later by the same investigators. Intra- and inter-observer reliability of the classification were assessed using Cohen's and Fleiss' kappa statistics, respectively. Results: Generally, the morphology grading system itself was well adopted by the observers. Its success in application is strongly influenced by the identification of the dural sac. The average intraobserver Cohen's kappa was 0.53 ± 0.2. The inter-observer Fleiss' kappa was 0.38 ± 0.02 in the first rating and 0.3 ± 0.03 in the second rating repeated after two weeks. Discussion: In this attempt, the teaching of the observers was limited to an introduction to the general idea of the morphology grading system and one example MRI image per category. The identification of the dimension of the dural sac may be a difficult issue in absence of complete T1 T2 MRI image series as it was the case here. The similarity of the CSF to possibly present fat on T2 images was the main reason of mismatch in the assignment of the cases to a category. The Fleiss correlation factors of the five observers are fair and the proposed morphology grading system is promising.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Natural classification of knots

The principal objective of the knot theory is to provide a simple way of classifying and ordering all the knot types. Here, we propose a natural classification of knots based on their intrinsic position in the knot space that is defined by the set of knots to which a given knot can be converted by individual intersegmental passages. In addition, we characterize various knots using a set of simple quantum numbers that can be determined upon inspection of minimal crossing diagram of a knot. These numbers include: crossing number; average three-dimensional writhe; number of topological domains; and the average relaxation value

Une nouvelle Classification des néoptasies intraépithélates vulvaires [A new classification of vulvar intraepithelial neoplasia (VIN)]

Vulvar cancer is a rare disease and its screening is depending on the quality and the relevance of our clinical examination. Incidence of vulvar cancer and especially precancerous lesions, vulvar intraepithelial neoplasias (VIN), increased during these last years. The new terminology of vulvar intraepithelial neoplasia will help us to identify high risk groups which could develop a cancer: usual and differentiated VIN. An early diagnosis is essential to propose an adequate treatment. Management is a major point according to the rising incidence of these lesions in younger women. Until we can observe a benefit from the vaccination against human papillomavirus, we must increase the quality of screening by a careful examination of the vulva.

Why human islets die? analysis of death signaling pathways during isolation and following cytokine treatments

RESUME Le diabète de type 1 se définit comme un désordre métabolique d'origine auto-immune qui aboutit à la destruction progressive et sélective de la cellule ß-pancréatique sécrétrice d'insuline. Cette maladie représente 10 % des cas de diabète enregistrés dans la population mondiale, et touche les jeunes de moins de 20 ans. Le traitement médical par insulinothérapie corrige le manque d'hormone mais ne prévient pas les nombreuses complications telles que les atteintes cardiaques, neurologiques, rénales, rétiniennes, et les amputations que la maladie provoque. Le remplacement de la cellule ß par transplantation d'îlots de Langerhans est une alternative prometteuse au traitement médical du diabète de type 1. Cependant la greffe d'îlots est encore un traitement expérimental et ne permet pas un contrôle efficace de la glycémie au long terme chez les patients transplantés, et les raisons de cet échec restent mal comprises. L'obstacle immédiat qui se pose est la purification d'un nombre suffisant d'îlots viables et la perte massive de ces îlots dans les premières heures suite à la greffe. Cette tendance presque systématique de la perte fonctionnelle du greffon immédiatement après la transplantation est connue sous le terme de « primary graft non-function » (PNF). En effet, la procédure d'isolement des îlots provoque la destruction des composantes cellulaires et non cellulaires du tissu pancréatique qui jouent un rôle déterminant dans le processus de survie de l'îlot. De plus, la transplantation elle-même expose les cellules à différents stress, notamment le stress par les cytokines inflammatoires qui encourage la mort cellulaire par apoptose et provoque par la suite le rejet de la greffe. L'ensemble de ces mécanismes aboutit a une perte de la masse d'îlot estimée a plus de 60%. Dans ce contexte, nous nous sommes intéressés à définir les voies majeures de stress qui régissent cette perte massive d'îlot par apoptose lors du processus d'isolement et suite à l'exposition immédiate aux cytokines. L'ensemble des résultats obtenus indique que plusieurs voies de signalisation intracellulaire sont recrutées qui s'activent de manière maximale très tôt lors des premières phases de l'isolement. La mise en culture des îlots deux jours permet aux voies activées de revenir aux taux de base. De ce fait nous proposons une stratégie dite de protection qui doit être 1) initiée aussitôt que possible lors de l'isolement des îlots pancréatiques, 2) devrait probablement bloquer l'activation de ces différentes voies de stress mis en évidence lors de notre étude et 3) devrait inclure la mise en culture des îlots purifiés deux jours après l'isolement et avant la transplantation. RESUME LARGE PUBLIC Le diabète est une maladie qui entraîne un taux anormalement élevé de sucre (glucose) dans le sang du à une insuffisance du pancréas endocrine à produire de l'insuline, une hormone qui régule la glycémie (taux de glucose dans le sang). On distingue deux types majeurs de diabètes; le diabète de type 1 ou juvénile ou encore appelé diabète maigre qui se manifeste souvent pendant l'enfance et qui se traduit par une déficience absolue en insuline. Le diabète de type 2 ou diabète gras est le plus fréquent, et touche les sujets de plus de 40 ans qui souffrent d'obésité et qui se traduit par une dysfonction de la cellule ß avec une incapacité à réguler la glycémie malgré la production d'insuline. Dans le diabète de type 1, la destruction de la cellule ß est programmée (apoptose) et est majoritairement provoquée par des médiateurs inflammatoires appelés cytokines qui sont produites localement par des cellules inflammatoires du système immunitaire qui envahissent la cellule ß-pancréatiques. Les cytokines activent différentes voies de signalisation parmi lesquelles on distingue celles des Mitogen-Activated Protein Kinase (MAPKs) composées de trois familles de MAPKs: ERK1/2, p38, et JNK, et la voie NF-κB. Le traitement médical par injections quotidiennes d'insuline permet de contrôler la glycémie mais ne prévient pas les nombreuses complications secondaires liées à cette maladie. La greffe d'îlots de Langerhans est une alternative possible au traitement médical, considérée avantageuse comparée a la greffe du pancréas entier. En effet l'embolisation d'îlots dans le foie par injection intraportale constitue une intervention simple sans complications majeures. Néanmoins la technique de préparation d'îlots altère la fonction endocrine et cause la perte massive d'îlots pancréatiques. De plus, la transplantation elle-même expose la cellule ß à différents stress, notamment le stress par les cytokines inflammatoires qui provoque le rejet de greffon cellulaire. Dans la perspective d'augmenter les rendements des îlots purifiés, nous nous sommes intéressés à définir les voies majeures de stress qui régissent cette perte massive d'îlot lors du processus d'isolement et suite à l'exposition immédiate aux cytokines après transplantation. L'ensemble de ces résultats indique que le stress induit lors de l'isolement des îlots et celui des cytokines recrute différentes voies de signalisation intracellulaire (JNK, p38 et NF-κB) qui s'additionnent entre-elles pour altérer la fonction et la viabilité de l'îlot. De ce fait une stratégie doit être mise en place pour bloquer toute action synergique entre ces différentes voies activées pour améliorer la viabilité et la fonction de la cellule ß lors du greffon cellulaire. SUMMARY Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by the progressive and selective destruction of the pancreatic ß-cells that secrete insulin, leading to absolute insulin deficiency. T1DM accounts for about 10% of all diabetes cases, affecting persons younger than 20 years of age. Medical treatment using daily exogenous insulin injection corrects hormone deficiency but does not prevent devastating complications such as heart attack, neuropathy, kidney failure, blindness, and amputation caused by the disease. Pancreatic islet transplantation (PIT) is one strategy that holds promise to cure patients with T1DM, but purified pancreatic islet grafts have failed to maintain long-term glucose homeostasis in human recipients, the reasons for this failure being still poorly understood. There is however a more immediate problem with islet grafting that is dependent upon poor islet recovery from donors and early islet loss following the first hours of grafting. This tendency of islet grafts to fail to function within a short period after transplantation is termed primary graft non-function (PNF). Indeed, the islet isolation procedure itself destroys cellular and non-cellular components of the pancreas that may play a role in supporting islet survival. Further, islet transplantation exposes cells to a variety of stressful stimuli, notably pro-inflammatory cytokines that encourage ß-cell death by apoptosis and lead to early graft failure. Altogether these mechanisms lead to an estimated loss of 60% of the total islet mass. Here, we have mapped the major intracellular stress signaling pathways that may mediate human islet loss by apoptosis during isolation and following cytokine attack. We found that several stress pathways are maximally activated from the earliest stages of the isolation procedure. Culturing islet for two days allow for the activated pathways to return to basal levels. We propose that protective strategies should 1) be initiated as early as possible during isolation of the islets, 2) should probably target the activated stress pathways that we uncovered during our studies and 3) should include culturing islets for two days post-isolation and prior transplantation.

ITMIG consensus statement on the use of the WHO histological classification of thymoma and thymic carcinoma: refined definitions, histological criteria, and reporting.

INTRODUCTION: The 2004 version of the World Health Organization classification subdivides thymic epithelial tumors into A, AB, B1, B2, and B3 (and rare other) thymomas and thymic carcinomas (TC). Due to a morphological continuum between some thymoma subtypes and some morphological overlap between thymomas and TC, a variable proportion of cases may pose problems in classification, contributing to the poor interobserver reproducibility in some studies. METHODS: To overcome this problem, hematoxylin-eosin-stained and immunohistochemically processed sections of prototypic, "borderland," and "combined" thymomas and TC (n = 72) were studied by 18 pathologists at an international consensus slide workshop supported by the International Thymic Malignancy Interest Group. RESULTS: Consensus was achieved on refined criteria for decision making at the A/AB borderland, the distinction between B1, B2, and B3 thymomas and the separation of B3 thymomas from TCs. "Atypical type A thymoma" is tentatively proposed as a new type A thymoma variant. New reporting strategies for tumors with more than one histological pattern are proposed. CONCLUSION: These guidelines can set the stage for reproducibility studies and the design of a clinically meaningful grading system for thymic epithelial tumors.

Perforation cardiaque d'un ulcère gastrique: une cause inhabituelle de décès, après résection oesogastrique pour carcinome épidermoïde de l'oesophage [Cardiac perforation by a gastric ulcer: an unusual cause of death, after an esophageal and gastric resection of an epidermoid esophageal carcinoma]

We report here the case of a 55 year old female that underwent surgery for a well differentiated squamous cell carcinoma of the esophagus (middle third). Four months after surgery, she complains of neck pain, for which she is prescribed non steroidal antiinflammatory drugs (NSAID). A CT-scan and a Barium swallow are then normal. After three weeks of treatment, the patient is admitted on emergency to the Intensive Care Unit for a resuscitation hematemesis and atrial fibrillation with a fast ventricular response. The symptoms are stabilized after the transfusion of a few packed red blood cells. A few hours later, however, a massive hematemesis recurs and the patient dies despite intense resuscitation measures. Autopsy reveals three gastric ulcers, one of which had perforated through the cardiac left ventricular wall

CD34/QBEND10 immunostaining in bone marrow biopsies: an additional parameter for the diagnosis and classification of myelodysplastic syndromes.

CD34/QBEND10 immunostaining has been assessed in 150 bone marrow biopsies (BMB) including 91 myelodysplastic syndromes (MDS), 16 MDS-related AML, 25 reactive BMB, and 18 cases where RA could neither be established nor ruled out. All cases were reviewed and classified according to the clinical and morphological FAB criteria. The percentage of CD34-positive (CD34 +) hematopoietic cells and the number of clusters of CD34+ cells in 10 HPF were determined. In most cases the CD34+ cell count was similar to the blast percentage determined morphologically. In RA, however, not only typical blasts but also less immature hemopoietic cells lying morphologically between blasts and promyelocytes were stained with CD34. The CD34+ cell count and cluster values were significantly higher in RA than in BMB with reactive changes (p<0.0001 for both), in RAEB than in RA (p=0.0006 and p=0.0189, respectively), in RAEBt than in RAEB (p=0.0001 and p=0.0038), and in MDS-AML than in RAEBt (p<0.0001 and p=0.0007). Presence of CD34+ cell clusters in RA correlated with increased risk of progression of the disease. We conclude that CD34 immunostaining in BMB is a useful tool for distinguishing RA from other anemias, assessing blast percentage in MDS cases, classifying them according to FAB, and following their evolution.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.