Computer Aided Detection and measurement of peripheral artery disease.

Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

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.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Management of Pharyngeal Fistulas After Anterior Cervical Spine Surgery: A Treatment Algorithm for Severe Complications.

STUDY DESIGN:: Retrospective database- query to identify all anterior spinal approaches. OBJECTIVES:: To assess all patients with pharyngo-cutaneous fistulas after anterior cervical spine surgery. SUMMARY OF BACKGROUND DATA:: Patients treated in University of Heidelberg Spine Medical Center, Spinal Cord Injury Unit and Department of Otolaryngology (Germany), between 2005 and 2011 with the diagnosis of pharyngo-cutaneous fistulas. METHODS:: We conducted a retrospective study on 5 patients between 2005 and 2011 with PCF after ACSS, their therapy management and outcome according to radiologic data and patient charts. RESULTS:: Upon presentation 4 patients were paraplegic. 2 had PCF arising from one piriform sinus, two patients from the posterior pharyngeal wall and piriform sinus combined and one patient only from the posterior pharyngeal wall. 2 had previous unsuccessful surgical repair elsewhere and 1 had prior radiation therapy. In 3 patients speech and swallowing could be completely restored, 2 patients died. Both were paraplegic. The patients needed an average of 2-3 procedures for complete functional recovery consisting of primary closure with various vascularised regional flaps and refining laser procedures supplemented with negative pressure wound therapy where needed. CONCLUSION:: Based on our experience we are able to provide a treatment algorithm that indicates that chronic as opposed to acute fistulas require a primary surgical closure combined with a vascularised flap that should be accompanied by the immediate application of a negative pressure wound therapy. We also conclude that particularly in paraplegic patients suffering this complication the risk for a fatal outcome is substantial.

Chaotic systems with a null conditional Lyapunov exponent under nonlinear driving.

Control of a chaotic system by homogeneous nonlinear driving, when a conditional Lyapunov exponent is zero, may give rise to special and interesting synchronizationlike behaviors in which the response evolves in perfect correlation with the drive. Among them, there are the amplification of the drive attractor and the shift of it to a different region of phase space. In this paper, these synchronizationlike behaviors are discussed, and demonstrated by computer simulation of the Lorentz model [E. N. Lorenz, J. Atmos. Sci. 20 130 (1963)] and the double scroll [T. Matsumoto, L. O. Chua, and M. Komuro, IEEE Trans. CAS CAS-32, 798 (1985)].

Safety of a new algorithm for the management of childhood illness (Almanach) to improve quality of care and rational use of drugs

Introduction New evidence from randomized controlled and etiology of fever studies, the availability of reliable RDT for malaria, and novel technologies call for revision of the IMCI strategy. We developed a new algorithm based on (i) a systematic review of published studies assessing the safety and appropriateness of RDT and antibiotic prescription, (ii) results from a clinical and microbiological investigation of febrile children aged <5 years, (iii) international expert IMCI opinions. The aim of this study was to assess the safety of the new algorithm among patients in urban and rural areas of Tanzania.Materials and Methods The design was a controlled noninferiority study. Enrolled children aged 2-59 months with any illness were managed either by a study clinician using the new Almanach algorithm (two intervention health facilities), or clinicians using standard practice, including RDT (two control HF). At day 7 and day 14, all patients were reassessed. Patients who were ill in between or not cured at day 14 were followed until recovery or death. Primary outcome was rate of complications, secondary outcome rate of antibiotic prescriptions.Results 1062 children were recruited. Main diagnoses were URTI 26%, pneumonia 19% and gastroenteritis (9.4%). 98% (531/541) were cured at D14 in the Almanach arm and 99.6% (519/521) in controls. Rate of secondary hospitalization was 0.2% in each. One death occurred in controls. None of the complications was due to withdrawal of antibiotics or antimalarials at day 0. Rate of antibiotic use was 19% in the Almanach arm and 84% in controls.Conclusion Evidence suggests that the new algorithm, primarily aimed at the rational use of drugs, is as safe as standard practice and leads to a drastic reduction of antibiotic use. The Almanach is currently being tested for clinician adherence to proposed procedures when used on paper or a mobile phone

Genetic algorithm for sequencing in midex model non-permutation flowshops using constrained buffers

Este trabajo presenta un Algoritmo Genético (GA) del problema de secuenciar unidades en una línea de producción. Se tiene en cuenta la posibilidad de cambiar la secuencia de piezas mediante estaciones con acceso a un almacén intermedio o centralizado. El acceso al almacén además está restringido, debido al tamaño de las piezas.AbstractThis paper presents a Genetic Algorithm (GA) for the problem of sequencing in a mixed model non-permutation flowshop. Resequencingis permitted where stations have access to intermittent or centralized resequencing buffers. The access to a buffer is restricted by the number of available buffer places and the physical size of the products.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

Conditional maximum likelihood timing recovery: estimators and bounds

This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulationthat is systematically applied in the literature for the derivationof non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB)[which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statisticalaccuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained boundis not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRBis obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.

Alternative tests for correct specification of conditional predictive densities

We propose new methods for evaluating predictive densities that focus on the models' actual predictive ability in finite samples. The tests offer a simple way of evaluatingthe correct specification of predictive densities, either parametric or non-parametric.The results indicate that our tests are well sized and have good power in detecting mis-specification in predictive densities. An empirical application to the Survey ofProfessional Forecasters and a baseline Dynamic Stochastic General Equilibrium modelshows the usefulness of our methodology.

Quantitative morphometry analysis of the fetal brain using clinical MR imaging

In vivo fetal magnetic resonance imaging provides aunique approach for the study of early human braindevelopment [1]. In utero cerebral morphometry couldpotentially be used as a marker of the cerebralmaturation and help to distinguish between normal andabnormal development in ambiguous situations. However,this quantitative approach is a major challenge becauseof the movement of the fetus inside the amniotic cavity,the poor spatial resolution provided by very fast MRIsequences and the partial volume effect. Extensiveefforts are made to deal with the reconstruction ofhigh-resolution 3D fetal volumes based on severalacquisitions with lower resolution [2,3,4]. Frameworkswere developed for the segmentation of specific regionsof the fetal brain such as posterior fossa, brainstem orgerminal matrix [5,6], or for the entire brain tissue[7,8], applying the Expectation-Maximization MarkovRandom Field (EM-MRF) framework. However, many of theseprevious works focused on the young fetus (i.e. before 24weeks) and use anatomical atlas priors to segment thedifferent tissue or regions. As most of the gyraldevelopment takes place after the 24th week, acomprehensive and clinically meaningful study of thefetal brain should not dismiss the third trimester ofgestation. To cope with the rapidly changing appearanceof the developing brain, some authors proposed a dynamicatlas [8]. To our opinion, this approach however faces arisk of circularity: each brain will be analyzed /deformed using the template of its biological age,potentially biasing the effective developmental delay.Here, we expand our previous work [9] to proposepost-processing pipeline without prior that allow acomprehensive set of morphometric measurement devoted toclinical application. Data set & Methods: Prenatal MRimaging was performed with a 1-T system (GE MedicalSystems, Milwaukee) using single shot fast spin echo(ssFSE) sequences (TR 7000 ms, TE 180 ms, FOV 40 x 40 cm,slice thickness 5.4mm, in plane spatial resolution1.09mm). For each fetus, 6 axial volumes shifted by 1 mmwere acquired under motherâeuro?s sedation (about 1min pervolume). First, each volume is segmentedsemi-automatically using region-growing algorithms toextract fetal brain from surrounding maternal tissues.Inhomogeneity intensity correction [10] and linearintensity normalization are then performed. Brain tissues(CSF, GM and WM) are then segmented based on thelow-resolution volumes as presented in [9]. Ahigh-resolution image with isotropic voxel size of 1.09mm is created as proposed in [2] and using B-splines forthe scattered data interpolation [11]. Basal gangliasegmentation is performed using a levet setimplementation on the high-resolution volume [12]. Theresulting white matter image is then binarized and givenas an input in FreeSurfer software(http://surfer.nmr.mgh.harvard.edu) to providetopologically accurate three-dimensional reconstructionsof the fetal brain according to the local intensitygradient. References: [1] Guibaud, Prenatal Diagnosis29(4) (2009). [2] Rousseau, Acad. Rad. 13(9), 2006. [3]Jiang, IEEE TMI 2007. [4] Warfield IADB, MICCAI 2009. [5]Claude, IEEE Trans. Bio. Eng. 51(4) 2004. [6] Habas,MICCAI 2008. [7] Bertelsen, ISMRM 2009. [8] Habas,Neuroimage 53(2) 2010. [9] Bach Cuadra, IADB, MICCAI2009. [10] Styner, IEEE TMI 19(39 (2000). [11] Lee, IEEETrans. Visual. And Comp. Graph. 3(3), 1997. [12] BachCuadra, ISMRM 2010.

Kumar's algorithm for solving Toeplitz systems of equations over finite fields

Adaptació de l'algorisme de Kumar per resoldre sistemes d'equacions amb matrius de Toeplitz sobre els reals a cossos finits en un temps 0 (n log n).