3D noise power spectrum applied on clinical mdct scanners: effects of reconstruction algorithms and reconstruction filters

The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

Typing less common ovarian tumors: A training tool based on a pattern-based algorithm applied to a set of 20 virtual slides.

Context: Ovarian tumors (OT) typing is a competency expected from pathologists, with significant clinical implications. OT however come in numerous different types, some rather rare, with the consequence of few opportunities for practice in some departments. Aim: Our aim was to design a tool for pathologists to train in less common OT typing. Method and Results: Representative slides of 20 less common OT were scanned (Nano Zoomer Digital Hamamatsu®) and the diagnostic algorithm proposed by Young and Scully applied to each case (Young RH and Scully RE, Seminars in Diagnostic Pathology 2001, 18: 161-235) to include: recognition of morphological pattern(s); shortlisting of differential diagnosis; proposition of relevant immunohistochemical markers. The next steps of this project will be: evaluation of the tool in several post-graduate training centers in Europe and Québec; improvement of its design based on evaluation results; diffusion to a larger public. Discussion: In clinical medicine, solving many cases is recognized as of utmost importance for a novice to become an expert. This project relies on the virtual slides technology to provide pathologists with a learning tool aimed at increasing their skills in OT typing. After due evaluation, this model might be extended to other uncommon tumors.

Mise au point concernantl'utilisation du dosagede l'antigène carcino-embryonnaire (CEA)en clinique

The carcinoembryonic antigen (CEA) is a tumor marker defined by specific heterologous antisera. Elevated levels of circulating CEA have been detected by radioimmunoassay in 20-90 per cent of cases of colorectal carcinomas depending on the degree of tumor spread. The fact that elevation of CEA level can also be observed in other types of carcinomas and in several non malignant conditions greatly limit the value of the CEA test for the early diagnosis of colorectal carcinoma. Thus, the CEA assay should not be used as a screening test for cancer. Repeatecl CEA mesurements, however, appear to be of importance for the evaluation of tumor resection and the detection of tumor recurrence. The only localized tumors known to produce elevation of CEA above the levels observed in non malignant diseases are carcinomas of the large bowel and the pancreas. In carcinomas derived from other organs a marked increase of CEA level is always associated with the presence of distant metastasis. Therefore at the present time the clinical applications of the CEA radioimmunoassay should be limited to the differentiai diagnosis of patients with suspicion of primary colorectal or pancreatic carcinoma, to the detection of distant metastasis in other types of carcinomas and to the post operative follow up of patients who had elevated levels of CEA before surgery. Well-controlled studies are still needed to determine if therapeutic decisions based on CEA results can lead to improved survival.

Oral flurbiprofen metabolic ratio assessment using a single-point dried blood spot.

We investigated whether a single blood measurement using the minimally invasive technique of a finger prick to draw a blood sample of 5 µl (to yield a dried blood spot (DBS)) is suitable for the assessment of flurbiprofen (FLB) metabolic ratio (MR). Ten healthy volunteers who had been genotyped for CYP2C9 were recruited as subjects. They received FLB alone in session 1 and FLB with fluconazole in session 2. In session 3, the subjects were pretreated for 4 days with rifampicin and received FLB with the last dose of rifampicin on day 5. Plasma and DBS samples were obtained between 0 and 8 h after FLB administration, and urine was collected during the 8 h after administration. The pharmacokinetic profiles of the drugs were comparable in DBS and plasma. FLB's apparent clearance values decreased by 35% in plasma and DBS during session 2 and increased by 75% in plasma and by 30% in DBS during session 3. Good correlations were observed between MRs calculated from urine, plasma, and DBS samples.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Study of OSEM with different subsets in grating-based X-ray differential phase-contrast imaging.

Impressive developments in X-ray imaging are associated with X-ray phase contrast computed tomography based on grating interferometry, a technique that provides increased contrast compared with conventional absorption-based imaging. A new "single-step" method capable of separating phase information from other contributions has been recently proposed. This approach not only simplifies data-acquisition procedures, but, compared with the existing phase step approach, significantly reduces the dose delivered to a sample. However, the image reconstruction procedure is more demanding than for traditional methods and new algorithms have to be developed to take advantage of the "single-step" method. In the work discussed in this paper, a fast iterative image reconstruction method named OSEM (ordered subsets expectation maximization) was applied to experimental data to evaluate its performance and range of applicability. The OSEM algorithm with different subsets was also characterized by comparison of reconstruction image quality and convergence speed. Computer simulations and experimental results confirm the reliability of this new algorithm for phase-contrast computed tomography applications. Compared with the traditional filtered back projection algorithm, in particular in the presence of a noisy acquisition, it furnishes better images at a higher spatial resolution and with lower noise. We emphasize that the method is highly compatible with future X-ray phase contrast imaging clinical applications.

Représentations sociales et représentations intimes de la maladie. Quelques réflexions d'un clinicien [Social and private representations of cancer. A clinician's point of view]

This paper discusses social representations in scientific communications and private ones that are linked to the individual imagination. Social representations, in a limited sense, are useful for the development of preventive messages, but of little benefit to clinical work. We highlight some non-explicit aspects of scientific discourse that impact on treatment: projected beliefs and values. We tackle the relationship between the concepts of representation, imagination, identity and temporality in the individual approach of the cancer patient.

Monsieur le Minotaure et son point de vue

Les visions hallucinées de Friedrich Dürrenmatt, l'un des plus importants écrivains suisses de l'après-guerre, au travers des dessins et des manuscrits consacrés aux mythes de la Pythie, du Minotaure et de Midas. L'itinéraire créatif de Friedrich Dürrenmatt, outre sa production littéraire bien connue, est constellé d'une intense activité de peintre, de dessinateur et de graveur sur cuivre, activité qui délimite un important terrain de confrontation des pensées et des thèmes caractérisant sa recherche. Ce volume, qui accompagne l'exposition organisée par le célèbre architecte tessinois Mario Botta, présente une sélection de dessins et de notes de voyage appartenant à la collection privée de Charlotte Kerr-Dürrenmatt. Ceux-ci ont trait aux mythes de la Pythie, du Minotaure et de Midas, auxquels Dürrenmatt a consacré tant de réflexions. Les thèmes de la mythologie grecque ont toujours été présents dans la recherche de l'auteur sur la condition humaine, au point qu'il en est parfois arrivé à se représenter, de manière autobiographique, comme le protagoniste des événements décrits. Ces oeuvres revêtent une importance fondamentale car elles mettent en valeur l'importance et la signification que l'écrivain attribue à cette activité, considérée comme " mineure " par la critique mais qu'il faut en revanche interpréter comme un complément important des métaphores écrites auxquelles renvoie toute sa pensée.

Endocardite infectieuse: mise au point [Infective endocarditis: update]

The pathogenesis of infective endocarditis (IE) is being dissected at the molecular level, which should help redefine new preventive and therapeutic strategies against IE. In spite of improving health care, the incidence of IE has not decreased over the last decades. While classical predisposing conditions such as rheumatic heart disease were being eradicated, new features of IE have emerged. These include IE in intravenous drug users, IE in elderly patients with sclerotic valve disease, prosthetic valve IE and nosocomial IE. The epidemiology, pathogenesis, diagnosis, prevention and treatment of IE are being reviewed in this article.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.