Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth.

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.

Les hépatectomies majeures : mortalité, morbidité et facteurs de risque

RESUME L'objectif de ce travail est de rappeler l'historique des hépatectomies majeures, les bases anatomiques et les techniques opératoires de la chirurgie du foie. Puis, à partir de 212 cas d'exérèses majeures recencées entre 1992 et 2001 dans le service de Chirurgie Viscérale du CHUV, les facteurs de risques, la mortalité et la morbidité des hépatectomies majeures seront étudiés et comparés avec les données récentes de la littérature. L'anatomie hépatique peut être considérée de plusieurs façons morphologiquement (poids, faces, lobe droit, gauche et caudé...), fonctionnellement (segmentation en fonction de la distribution des pédicules portes et de la localisation des veines hépatiques) et chirurgicalement. La terminologie est rappelée (hépatectomies «typique », «atypique », «réglée », «majeure »...). A partir de ces données, les exérèses du foie sont ensuite classées. Les techniques d'hépatectomies sont expliquées, en rappelant les principes généraux, et les voies d'abord. Puis, les techniques de contrôle de l'hémostase, la reconstruction des voies biliaires, les méthodes utilisées par rapport à la tranche de section hépatique et à la loge d'hépatectomie sont discutées, Les acquisitions récentes sont abordées. Sur les 494 hépatecomies réalisées entre janvier 1992 et août 2001, 212 sont majeures. Elles sont reparties en 7 groupes selon l'exérèse (lobectomie G ou D, hépatecomie G ou D etc...). `Sur ces 212 résections, 177 cas concernaient des lésions malignes et 35 cas des lésions bénignes. Les indications ont été classées en 4 groupes : cancer primitif du foie, métastases hépatiques, maladies bénignes (par exemple l'échinococcose alvéolaire), et 8 cas classés dans le groupe «autres ». Une intervention en urgence a été réalisée dans 7 cas. Le bilan préopératoire comprend un bilan biologique et morphologique. Une embolisation de l'artère hépatique a été réalisées dans 6 cas, alors qu'une embolisation dans la veine porte a été faite dans 17 cas. Les modalités chirurgicales (voies d'abord, contrôle vasculaire, drainage biliaire post- opératoire, transfusions per- opératoires, et interventions extra- hépatiques) sont expliqués. En fin, les méthodes statistiques utilisées sont rappelées. Il n'y a pas eu de décès per- opératoire. La mortalité post- opératoire dans les 30 jours a été de 3,3 % (7 cas) et la mortalité globale hospitalière de 5,2 %. Dans cette série, 132 patients n'ont eu aucune complication. La morbidité est de 17% si on considère les complications majeures, ayant concerné 36 patients, mais de 37,75 si l'on considère toutes les complications. Les complications chirurgicales sont le faite d'hémorragie, de fuite biliaire et d'infection du foyer opératoire. Dans notre étude, 33 facteurs de risque ont été analysés. L'analyse statistique uni- variée met den évidence les facteurs de risque suivants : Le nombre de culots de sang transfusés, la présence d'une hépatite, celle d'une cirrhose, le tabagisme, la lobectomie droite, et la présence d'une hypertension artérielle. L'analyse multi variée réalisée a permis de faire ressortir une combinaison de facteur de risque avec une valeur statistique significative et de réaliser une échelle et un score de gravité en fonction des facteurs de risques obtenus dans l'analyse uni variée. Le taux de mortalité globale hospitalière obtenu dans notre série (5,2%) est comparable aux résultats reportés dans d'autres séries.

Dyssegmental dysplasia, Silverman-Handmaker type: prenatal ultrasound findings and molecular analysis.

OBJECTIVES: The objective of this study is to describe the prenatal sonographic features and the results of DNA analysis on three fetuses with dyssegmental dysplasia, Silverman-Handmaker type (DD-SH). METHODS: A retrospective review of three fetuses with confirmed DD-SH was conducted. The fetal ultrasound findings, the radiological characteristics, and the results of the mutation analysis of the heparan sulphate perlecan gene 2 (HSPG2) were reviewed. RESULTS: There were three cases in two families with DD-SH diagnosed prenatally. The main prenatal ultrasound and the radiological features of DD-SH were severe limb shortening and vertebral segmentation and fusion defects (anisospondyly). The DNA analysis of the HSPG2 gene showed that the two affected fetuses in a nonconsanguineous family had a compound heterozygote for the c.646G > T transversion in exon 7 and a c.5788C > T transition in exon 46. The fetus born to the consanguineous couple had a homozygous mutation c.1356-27_1507 + 59del. CONCLUSION: DD-SH can be diagnosed prenatally using fetal ultrasound as early as 13 weeks. Xrays and DNA analysis of the HSPG2 gene are important for the confirmation of the diagnosis and for the preimplantation and prenatal diagnosis in pregnancies at risk. © 2013 John Wiley & Sons, Ltd.

Harmonic active contours.

We propose a segmentation method based on the geometric representation of images as 2-D manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set function and the objective functional corresponds to the surface of the image manifold. In this geometric framework, both data-fidelity and regularity terms of the segmentation are represented by a single functional that intrinsically aligns the gradients of the level set function with the gradients of the image and results in a segmentation criterion that exploits the directional information of image gradients to overcome image inhomogeneities and fragmented contours. The proposed formulation combines this robust alignment of gradients with attractive properties of previous methods developed in the same geometric framework: 1) the natural coupling of image channels proposed for anisotropic diffusion and 2) the ability of subjective surfaces to detect weak edges and close fragmented boundaries. The potential of such a geometric approach lies in the general definition of Riemannian manifolds, which naturally generalizes existing segmentation methods (the geodesic active contours, the active contours without edges, and the robust edge integrator) to higher dimensional spaces, non-flat images, and feature spaces. Our experiments show that the proposed technique improves the segmentation of multi-channel images, images subject to inhomogeneities, and images characterized by geometric structures like ridges or valleys.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Multi-parametric evaluation of sit-to-stand and stand-to-sit transitions in elderly people.

The aim of this study was to extract multi-parametric measures characterizing different features of sit-to-stand (Si-St) and stand-to-sit (St-Si) transitions in older persons, using a single inertial sensor attached to the chest. Investigated parameters were transition's duration, range of trunk tilt, smoothness of transition pattern assessed by its fractal dimension, and trunk movement's dynamic described by local wavelet energy. A measurement protocol with a Si-St followed by a St-Si postural transition was performed by two groups of participants: the first group (N=79) included Frail Elderly subjects admitted to a post-acute rehabilitation facility and the second group (N=27) were healthy community-dwelling elderly persons. Subjects were also evaluated with Tinetti's POMA scale. Compared to Healthy Elderly persons, frail group at baseline had significantly longer Si-St (3.85±1.04 vs. 2.60±0.32, p=0.001) and St-Si (4.08±1.21 vs. 2.81±0.36, p=0.001) transition's duration. Frail older persons also had significantly decreased smoothness of Si-St transition pattern (1.36±0.07 vs. 1.21±0.05, p=0.001) and dynamic of trunk movement. Measurements after three weeks of rehabilitation in frail older persons showed that smoothness of transition pattern had the highest improvement effect size (0.4) and discriminative performance. These results demonstrate the potential interest of such parameters to distinguish older subjects with different functional and health conditions.

A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis.

BACKGROUND: The yeast Schizosaccharomyces pombe is frequently used as a model for studying the cell cycle. The cells are rod-shaped and divide by medial fission. The process of cell division, or cytokinesis, is controlled by a network of signaling proteins called the Septation Initiation Network (SIN); SIN proteins associate with the SPBs during nuclear division (mitosis). Some SIN proteins associate with both SPBs early in mitosis, and then display strongly asymmetric signal intensity at the SPBs in late mitosis, just before cytokinesis. This asymmetry is thought to be important for correct regulation of SIN signaling, and coordination of cytokinesis and mitosis. In order to study the dynamics of organelles or large protein complexes such as the spindle pole body (SPB), which have been labeled with a fluorescent protein tag in living cells, a number of the image analysis problems must be solved; the cell outline must be detected automatically, and the position and signal intensity associated with the structures of interest within the cell must be determined. RESULTS: We present a new 2D and 3D image analysis system that permits versatile and robust analysis of motile, fluorescently labeled structures in rod-shaped cells. We have designed an image analysis system that we have implemented as a user-friendly software package allowing the fast and robust image-analysis of large numbers of rod-shaped cells. We have developed new robust algorithms, which we combined with existing methodologies to facilitate fast and accurate analysis. Our software permits the detection and segmentation of rod-shaped cells in either static or dynamic (i.e. time lapse) multi-channel images. It enables tracking of two structures (for example SPBs) in two different image channels. For 2D or 3D static images, the locations of the structures are identified, and then intensity values are extracted together with several quantitative parameters, such as length, width, cell orientation, background fluorescence and the distance between the structures of interest. Furthermore, two kinds of kymographs of the tracked structures can be established, one representing the migration with respect to their relative position, the other representing their individual trajectories inside the cell. This software package, called "RodCellJ", allowed us to analyze a large number of S. pombe cells to understand the rules that govern SIN protein asymmetry. CONCLUSIONS: "RodCell" is freely available to the community as a package of several ImageJ plugins to simultaneously analyze the behavior of a large number of rod-shaped cells in an extensive manner. The integration of different image-processing techniques in a single package, as well as the development of novel algorithms does not only allow to speed up the analysis with respect to the usage of existing tools, but also accounts for higher accuracy. Its utility was demonstrated on both 2D and 3D static and dynamic images to study the septation initiation network of the yeast Schizosaccharomyces pombe. More generally, it can be used in any kind of biological context where fluorescent-protein labeled structures need to be analyzed in rod-shaped cells. AVAILABILITY: RodCellJ is freely available under http://bigwww.epfl.ch/algorithms.html, (after acceptance of the publication).

Temporal SNR characteristics in segmented 3D-EPI at 7T.

Three-dimensional segmented echo planar imaging (3D-EPI) is a promising approach for high-resolution functional magnetic resonance imaging, as it provides an increased signal-to-noise ratio (SNR) at similar temporal resolution to traditional multislice 2D-EPI readouts. Recently, the 3D-EPI technique has become more frequently used and it is important to better understand its implications for fMRI. In this study, the temporal SNR characteristics of 3D-EPI with varying numbers of segments are studied. It is shown that, in humans, the temporal variance increases with the number of segments used to form the EPI acquisition and that for segmented acquisitions, the maximum available temporal SNR is reduced compared to single shot acquisitions. This reduction with increased segmentation is not found in phantom data and thus likely due to physiological processes. When operating in the thermal noise dominated regime, fMRI experiments with a motor task revealed that the 3D variant outperforms the 2D-EPI in terms of temporal SNR and sensitivity to detect activated brain regions. Thus, the theoretical SNR advantage of a segmented 3D-EPI sequence for fMRI only exists in a low SNR situation. However, other advantages of 3D-EPI, such as the application of parallel imaging techniques in two dimensions and the low specific absorption rate requirements, may encourage the use of the 3D-EPI sequence for fMRI in situations with higher SNR.

Right coronary artery flow velocity and volume assessment with spiral K-space sampled breathhold velocity-encoded MRI at 3 tesla: accuracy and reproducibility.

PURPOSE: To evaluate accuracy and reproducibility of flow velocity and volume measurements in a phantom and in human coronary arteries using breathhold velocity-encoded (VE) MRI with spiral k-space sampling at 3 Tesla. MATERIALS AND METHODS: Flow velocity assessment was performed using VE MRI with spiral k-space sampling. Accuracy of VE MRI was tested in vitro at five constant flow rates. Reproducibility was investigated in 19 healthy subjects (mean age 25.4 +/- 1.2 years, 11 men) by repeated acquisition in the right coronary artery (RCA). RESULTS: MRI-measured flow rates correlated strongly with volumetric collection (Pearson correlation r = 0.99; P < 0.01). Due to limited sample resolution, VE MRI overestimated the flow rate by 47% on average when nonconstricted region-of-interest segmentation was used. Using constricted region-of-interest segmentation with lumen size equal to ground-truth luminal size, less than 13% error in flow rate was found. In vivo RCA flow velocity assessment was successful in 82% of the applied studies. High interscan, intra- and inter-observer agreement was found for almost all indices describing coronary flow velocity. Reproducibility for repeated acquisitions varied by less than 16% for peak velocity values and by less than 24% for flow volumes. CONCLUSION: 3T breathhold VE MRI with spiral k-space sampling enables accurate and reproducible assessment of RCA flow velocity.

Magnetization transfer-based 3D visualization of foot peripheral nerves.

PURPOSE: To investigate magnetization transfer (MT) effects as a new source of contrast for imaging and tracking of peripheral foot nerves. MATERIALS AND METHODS: Two sets of 3D spoiled gradient-echo images acquired with and without a saturation pulse were used to generate MT ratio (MTR) maps of 260 μm in-plane resolution for eight volunteers at 3T. Scan parameters were adjusted to minimize signal loss due to T2 dephasing, and a dedicated coil was used to improve the inherently low signal-to-noise ratio of small voxels. Resulting MTR values in foot nerves were compared with those in surrounding muscle tissue. RESULTS: Average MTR values for muscle (45.5 ± 1.4%) and nerve (21.4 ± 3.1%) were significantly different (P < 0.0001). In general, the difference in MTR values was sufficiently large to allow for intensity-based segmentation and tracking of foot nerves in individual subjects. This procedure was termed MT-based 3D visualization. CONCLUSION: The MTR serves as a new source of contrast for imaging of peripheral foot nerves and provides a means for high spatial resolution tracking of these structures. The proposed methodology is directly applicable on standard clinical MR scanners and could be applied to systemic pathologies, such as diabetes.

Predicting clinical scores from magnetic resonance scans in Alzheimer's disease.

Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.

Variations publicitaires sur le genre : une analyse linguistique des représentations publicitaires du féminin et du masculin

Résumé:¦Sur le plan économique, le système de genre est une pierre angulaire du discours publicitaire. Il intervient dans la segmentation des marchés, la sélection des médias et des supports, l'apparence extérieure des produits, le ton des campagnes, le choix des arguments de vente et, bien sûr, les scripts des annonces. En contrepartie, sur le plan symbolique, le discours publicitaire est un dépositaire privilégié des imaginaires de genre qui circulent dans son contexte de diffusion. En cette qualité, confronté à un marché toujours plus concurrentiel, à l'instabilité croissante des consommateurs ainsi qu'à une critique médiatique, académique et publique à l'affût des stéréotypes, le discours publicitaire est amené à proposer des représentations des hommes et des femmes de plus en plus diversifiées. Le présent ouvrage, qui relève de l'analyse linguistique des discours, rentre dans la complexité de ces variations publicitaires sur le féminin et le masculin et déchiffre les imaginaires de genre dont elles relèvent. Il soulève par ailleurs la question de la dimension politique des recherches académiques.

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE.

PURPOSE: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images. MATERIALS AND METHODS: 8 healthy subjects (29.0±4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. RESULTS: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈6.6% to ≈2.4% for the uniform image and robust T1w image respectively. CONCLUSIONS: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.