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.

Classification of cell death: recommendations of the Nomenclature Committee on Cell Death 2009

Different types of cell death are often defined by morphological criteria, without a clear reference to precise biochemical mechanisms. The Nomenclature Committee on Cell Death (NCCD) proposes unified criteria for the definition of cell death and of its different morphologies, while formulating several caveats against the misuse of words and concepts that slow down progress in the area of cell death research. Authors, reviewers and editors of scientific periodicals are invited to abandon expressions like 'percentage apoptosis' and to replace them with more accurate descriptions of the biochemical and cellular parameters that are actually measured. Moreover, at the present stage, it should be accepted that caspase-independent mechanisms can cooperate with (or substitute for) caspases in the execution of lethal signaling pathways and that 'autophagic cell death' is a type of cell death occurring together with (but not necessarily by) autophagic vacuolization. This study details the 2009 recommendations of the NCCD on the use of cell death-related terminology including 'entosis', 'mitotic catastrophe', 'necrosis', 'necroptosis' and 'pyroptosis'.

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

Venous cannula performance assessment in a realistic caval tree model.

OBJECTIVES: A new caval tree system was designed for realistic in vitro simulation. The objective of our study was to assess cannula performance for virtually wall-less versus standard percutaneous thin-walled venous cannulas in a setting of venous collapse in case of negative pressure. METHODS: For a collapsible caval model, a very flexible plastic material was selected, and a model with nine afferent veins was designed according to the anatomy of the vena cava. A flow bench was built including a lower reservoir holding the caval tree, built by taking into account the main afferent vessels and their flow provided by a reservoir 6 cm above. A cannula was inserted in this caval tree and connected to a centrifugal pump that, in turn, was connected to a reservoir positioned 83 cm above the second lower reservoir (after-load = 60 mmHg). Using the same pre-load, the simulated venous drainage for cardiopulmonary bypass was realized using a 24 F wall-less cannula (Smartcanula) and 25 F percutaneous cannula (Biomedicus), and stepwise increased augmentation (1500 RPM, 2000 and 2500 RPM) of venous drainage. RESULTS: For the thin wall and the wall-less cannulas, 36 pairs of flow and pressure measurements were realized for three different RPM values. The mean Q-values at 1500, 2000 and 2500 RPM were: 3.98 ± 0.01, 6.27 ± 0.02 and 9.81 ± 0.02 l/min for the wall-less cannula (P <0.0001), versus 2.74 ± 0.02, 3.06 ± 0.05, 6.78 ± 0.02 l/min for the thin-wall cannula (P <0.0001). The corresponding inlet pressure values were: -8.88 ± 0.01, -23.69 ± 0.81 and -70.22 ± 0.18 mmHg for the wall-less cannula (P <0.0001), versus -36.69 ± 1.88, -80.85 ± 1.71 and -101.83 ± 0.45 mmHg for the thin-wall cannula (P <0.0001). The thin-wall cannula showed mean Q-values 37% less and mean P values 26% more when compared with the wall-less cannula (P <0.0001). CONCLUSIONS: Our in vitro water test was able to mimic a negative pressure situation, where the wall-less cannula design performs better compared with the traditional thin-wall cannula.

AWSum-Combining Classification with Knowledge Aquisition

Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.

Multiscale determinants of tree frog (Hyla arborea L.) calling ponds in western Switzerland

A tree frog (Hyla arborea L., 1758) metapopulation in western Switzerland was studied during spring 2001. All potential calling ponds in an area of 350 km(2) were searched for tree frog calling males. Twenty-nine out of 111 ponds sheltered between 1 and 250 callers. Most ponds were occupied by less than 12 males. Pond parameters were measured at three different levels using field analysis and a Geographical Information System (GIS). The first level was water chemistry and pond-associated measures. The second level was the surrounding land use in a 30 m buffer around the pond. The third level consisted of landscape indices on a broader scale (up to 2 km). Logistic regression was applied to identify parameters that can predict the presence of calling males in a pond. Response variable was the presence or absence of callers. Four significant parameters allowed us to explain about 40% of the total deviance of the observed occupational pattern. Urbanization around the pond had a highly negative impact on the probability of presence of calling males. Hours of direct sunlight on the pond was positively correlated with callers. Higher water conductivity was associated with a lesser probability of species presence. Finally, the further the closest two-lane road, the higher the probability of callers presence. Our results show that presence or absence of callers is influenced by factors acting at various geographical scales.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Minimal data requirements for a continuous monitoring of the quality of care using the DRG classification.

The DRG classification provides a useful tool for the evaluation of hospital care. Indicators such as readmissions and mortality rates adjusted for the hospital Casemix could be adopted in Switzerland at the price of minor additions to the hospital discharge record. The additional information required to build patients histories and to identify the deaths occurring after hospital discharge is detailed.

Intrinsically photosensitive retinal ganglion cells: classification, function and clinical implications.

PURPOSE OF REVIEW: The discovery of a new class of intrinsically photosensitive retinal ganglion cells (ipRGCs) revealed their superior role for various nonvisual biological functions, including the pupil light reflex, and circadian photoentrainment. RECENT FINDINGS: Recent works have identified and characterized several anatomically and functionally distinct ipRGC subtypes and have added strong new evidence for the accessory role of ipRGCs in the visual system in humans. SUMMARY: This review summarizes current concepts related to ipRGC morphology, central connections and behavioural functions and highlights recent studies having clinical relevance to ipRGCs. Clinical implications of the melanopsin system are widespread, particularly as related to chronobiology.

A sex-specific marker reveals male heterogamety in European tree frogs.

Most amphibians examined so far show undifferentiated sex chromosomes. The heterogametic sex's identity, usually revealed through indirect means, often varies among closely related species or even populations (as do sex-linkage groups), suggesting great evolutionary instability of the sex-determining genes. Here we take advantage of a sex-specific marker that amplifies in several related species of European tree frogs (Hyla arborea group) to disclose a homogeneous pattern of male heterogamety. Besides relevance for evolutionary studies of sex determination in amphibians, our results have potential for addressing practical issues in conservation biology because sex reversal by anthropogenic endocrine disruptors is considered one possible cause of amphibian decline.