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.

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.

A prospective development study investigating focal irreversible electroporation in men with localised prostate cancer: Nanoknife Electroporation Ablation Trial (NEAT).

INTRODUCTION: Focal therapy may reduce the toxicity of current radical treatments while maintaining the oncological benefit. Irreversible electroporation (IRE) has been proposed to be tissue selective and so might have favourable characteristics compared to the currently used prostate ablative technologies. The aim of this trial is to determine the adverse events, genito-urinary side effects and early histological outcomes of focal IRE in men with localised prostate cancer. METHODS: This is a single centre prospective development (stage 2a) study following the IDEAL recommendations for evaluating new surgical procedures. Twenty men who have MRI-visible disease localised in the anterior part of the prostate will be recruited. The sample size permits a precision estimate around key functional outcomes. Inclusion criteria include PSA ≤ 15 ng/ml, Gleason score ≤ 4 + 3, stage T2N0M0 and absence of clinically significant disease outside the treatment area. Treatment delivery will be changed in an adaptive iterative manner so as to allow optimisation of the IRE protocol. After focal IRE, men will be followed during 12 months using validated patient reported outcome measures (IPSS, IIEF-15, UCLA-EPIC, EQ-5D, FACT-P, MAX-PC). Early disease control will be evaluated by mpMRI and targeted transperineal biopsy of the treated area at 6 months. DISCUSSION: The NEAT trial will assess the early functional and disease control outcome of focal IRE using an adaptive design. Our protocol can provide guidance for designing an adaptive trial to assess new surgical technologies in the challenging landscape of health technology assessment in prostate cancer treatment.

Situating forensic traces in time

Situating events and traces in time is an essential problem in investigations. To date, among the typical ques- 21¦tions issued in forensic science, time has generally been unexplored. The reason for this can be traced to the 22¦complexity of the overall problem, addressed by several scientists in very limited projects usually stimulated 23¦by a specific case. Considering that such issues are recurrent and transcending the treatment of each trace 24¦separately, the formalisation of a framework to address dating issues in criminal investigation is undeniably 25¦needed. Through an iterative process consisting of extracting recurrent aspects discovered from the study of 26¦problems encountered by practitioners and reported in the literature, common mechanisms were extracted 27¦and provide understanding of underlying factors encountered in forensic practise. Three complementary ap- 28¦proaches are thus highlighted and described to formalise a preliminary framework that can be applied for the 29¦dating of traces, objects, persons and indirectly events.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

Médecine d'urgence [Emergency medicine: updates 2013].

New evidences published this year are susceptible to change the management of several medical emergencies. Combined antiplatelet therapy might be beneficial for the management of TIA or minor stroke and rapid blood pressure lowering might improve the outcome in patients with intracerebral hemorrhage. A restrictive red cell transfusion strategy is indicated in case of upper digestive bleeding and coagulation factors concentrates are superior to fresh frozen plasma for urgent warfarin reversal. Prolonged systemic steroid therapy is not warranted in case of acute exacerbation of BPCO, and iterative physiotherapy is not beneficial after acute whiplash. Finally, family presence during cardiopulmonary resuscitation may reduce post-traumatic stress disorder among relatives.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

Etude de la composition initiale et du vieillissement des traces digitales: vers le développement d'une méthode de datation?

«Quel est l'âge de cette trace digitale?» Cette question est relativement souvent soulevée au tribunal ou lors d'investigations, lorsque la personne suspectée admet avoir laissé ses empreintes digitales sur une scène de crime mais prétend l'avoir fait à un autre moment que celui du crime et pour une raison innocente. Toutefois, aucune réponse ne peut actuellement être donnée à cette question, puisqu'aucune méthodologie n'est pour l'heure validée et acceptée par l'ensemble de la communauté forensique. Néanmoins, l'inventaire de cas américains conduit dans cette recherche a montré que les experts fournissent tout de même des témoignages au tribunal concernant l'âge de traces digitales, même si ceux-­‐ci sont majoritairement basés sur des paramètres subjectifs et mal documentés. Il a été relativement aisé d'accéder à des cas américains détaillés, ce qui explique le choix de l'exemple. Toutefois, la problématique de la datation des traces digitales est rencontrée dans le monde entier, et le manque de consensus actuel dans les réponses données souligne la nécessité d'effectuer des études sur le sujet. Le but de la présente recherche est donc d'évaluer la possibilité de développer une méthode de datation objective des traces digitales. Comme les questions entourant la mise au point d'une telle procédure ne sont pas nouvelles, différentes tentatives ont déjà été décrites dans la littérature. Cette recherche les a étudiées de manière critique, et souligne que la plupart des méthodologies reportées souffrent de limitations prévenant leur utilisation pratique. Néanmoins, certaines approches basées sur l'évolution dans le temps de composés intrinsèques aux résidus papillaires se sont montrées prometteuses. Ainsi, un recensement détaillé de la littérature a été conduit afin d'identifier les composés présents dans les traces digitales et les techniques analytiques capables de les détecter. Le choix a été fait de se concentrer sur les composés sébacés détectés par chromatographie gazeuse couplée à la spectrométrie de masse (GC/MS) ou par spectroscopie infrarouge à transformée de Fourier. Des analyses GC/MS ont été menées afin de caractériser la variabilité initiale de lipides cibles au sein des traces digitales d'un même donneur (intra-­‐variabilité) et entre les traces digitales de donneurs différents (inter-­‐variabilité). Ainsi, plusieurs molécules ont été identifiées et quantifiées pour la première fois dans les résidus papillaires. De plus, il a été déterminé que l'intra-­‐variabilité des résidus était significativement plus basse que l'inter-­‐variabilité, mais que ces deux types de variabilité pouvaient être réduits en utilisant différents pré-­‐ traitements statistiques s'inspirant du domaine du profilage de produits stupéfiants. Il a également été possible de proposer un modèle objectif de classification des donneurs permettant de les regrouper dans deux classes principales en se basant sur la composition initiale de leurs traces digitales. Ces classes correspondent à ce qui est actuellement appelé de manière relativement subjective des « bons » ou « mauvais » donneurs. Le potentiel d'un tel modèle est élevé dans le domaine de la recherche en traces digitales, puisqu'il permet de sélectionner des donneurs représentatifs selon les composés d'intérêt. En utilisant la GC/MS et la FTIR, une étude détaillée a été conduite sur les effets de différents facteurs d'influence sur la composition initiale et le vieillissement de molécules lipidiques au sein des traces digitales. Il a ainsi été déterminé que des modèles univariés et multivariés pouvaient être construits pour décrire le vieillissement des composés cibles (transformés en paramètres de vieillissement par pré-­‐traitement), mais que certains facteurs d'influence affectaient ces modèles plus sérieusement que d'autres. En effet, le donneur, le substrat et l'application de techniques de révélation semblent empêcher la construction de modèles reproductibles. Les autres facteurs testés (moment de déposition, pression, température et illumination) influencent également les résidus et leur vieillissement, mais des modèles combinant différentes valeurs de ces facteurs ont tout de même prouvé leur robustesse dans des situations bien définies. De plus, des traces digitales-­‐tests ont été analysées par GC/MS afin d'être datées en utilisant certains des modèles construits. Il s'est avéré que des estimations correctes étaient obtenues pour plus de 60 % des traces-­‐tests datées, et jusqu'à 100% lorsque les conditions de stockage étaient connues. Ces résultats sont intéressants mais il est impératif de conduire des recherches supplémentaires afin d'évaluer les possibilités d'application de ces modèles dans des cas réels. Dans une perspective plus fondamentale, une étude pilote a également été effectuée sur l'utilisation de la spectroscopie infrarouge combinée à l'imagerie chimique (FTIR-­‐CI) afin d'obtenir des informations quant à la composition et au vieillissement des traces digitales. Plus précisément, la capacité de cette technique à mettre en évidence le vieillissement et l'effet de certains facteurs d'influence sur de larges zones de traces digitales a été investiguée. Cette information a ensuite été comparée avec celle obtenue par les spectres FTIR simples. Il en a ainsi résulté que la FTIR-­‐CI était un outil puissant, mais que son utilisation dans l'étude des résidus papillaires à des buts forensiques avait des limites. En effet, dans cette recherche, cette technique n'a pas permis d'obtenir des informations supplémentaires par rapport aux spectres FTIR traditionnels et a également montré des désavantages majeurs, à savoir de longs temps d'analyse et de traitement, particulièrement lorsque de larges zones de traces digitales doivent être couvertes. Finalement, les résultats obtenus dans ce travail ont permis la proposition et discussion d'une approche pragmatique afin d'aborder les questions de datation des traces digitales. Cette approche permet ainsi d'identifier quel type d'information le scientifique serait capable d'apporter aux enquêteurs et/ou au tribunal à l'heure actuelle. De plus, le canevas proposé décrit également les différentes étapes itératives de développement qui devraient être suivies par la recherche afin de parvenir à la validation d'une méthodologie de datation des traces digitales objective, dont les capacités et limites sont connues et documentées. -- "How old is this fingermark?" This question is relatively often raised in trials when suspects admit that they have left their fingermarks on a crime scene but allege that the contact occurred at a time different to that of the crime and for legitimate reasons. However, no answer can be given to this question so far, because no fingermark dating methodology has been validated and accepted by the whole forensic community. Nevertheless, the review of past American cases highlighted that experts actually gave/give testimonies in courts about the age of fingermarks, even if mostly based on subjective and badly documented parameters. It was relatively easy to access fully described American cases, thus explaining the origin of the given examples. However, fingermark dating issues are encountered worldwide, and the lack of consensus among the given answers highlights the necessity to conduct research on the subject. The present work thus aims at studying the possibility to develop an objective fingermark dating method. As the questions surrounding the development of dating procedures are not new, different attempts were already described in the literature. This research proposes a critical review of these attempts and highlights that most of the reported methodologies still suffer from limitations preventing their use in actual practice. Nevertheless, some approaches based on the evolution of intrinsic compounds detected in fingermark residue over time appear to be promising. Thus, an exhaustive review of the literature was conducted in order to identify the compounds available in the fingermark residue and the analytical techniques capable of analysing them. It was chosen to concentrate on sebaceous compounds analysed using gas chromatography coupled with mass spectrometry (GC/MS) or Fourier transform infrared spectroscopy (FTIR). GC/MS analyses were conducted in order to characterize the initial variability of target lipids among fresh fingermarks of the same donor (intra-­‐variability) and between fingermarks of different donors (inter-­‐variability). As a result, many molecules were identified and quantified for the first time in fingermark residue. Furthermore, it was determined that the intra-­‐variability of the fingermark residue was significantly lower than the inter-­‐variability, but that it was possible to reduce both kind of variability using different statistical pre-­‐ treatments inspired from the drug profiling area. It was also possible to propose an objective donor classification model allowing the grouping of donors in two main classes based on their initial lipid composition. These classes correspond to what is relatively subjectively called "good" or "bad" donors. The potential of such a model is high for the fingermark research field, as it allows the selection of representative donors based on compounds of interest. Using GC/MS and FTIR, an in-­‐depth study of the effects of different influence factors on the initial composition and aging of target lipid molecules found in fingermark residue was conducted. It was determined that univariate and multivariate models could be build to describe the aging of target compounds (transformed in aging parameters through pre-­‐ processing techniques), but that some influence factors were affecting these models more than others. In fact, the donor, the substrate and the application of enhancement techniques seemed to hinder the construction of reproducible models. The other tested factors (deposition moment, pressure, temperature and illumination) also affected the residue and their aging, but models combining different values of these factors still proved to be robust. Furthermore, test-­‐fingermarks were analysed with GC/MS in order to be dated using some of the generated models. It turned out that correct estimations were obtained for 60% of the dated test-­‐fingermarks and until 100% when the storage conditions were known. These results are interesting but further research should be conducted to evaluate if these models could be used in uncontrolled casework conditions. In a more fundamental perspective, a pilot study was also conducted on the use of infrared spectroscopy combined with chemical imaging in order to gain information about the fingermark composition and aging. More precisely, its ability to highlight influence factors and aging effects over large areas of fingermarks was investigated. This information was then compared with that given by individual FTIR spectra. It was concluded that while FTIR-­‐ CI is a powerful tool, its use to study natural fingermark residue for forensic purposes has to be carefully considered. In fact, in this study, this technique does not yield more information on residue distribution than traditional FTIR spectra and also suffers from major drawbacks, such as long analysis and processing time, particularly when large fingermark areas need to be covered. Finally, the results obtained in this research allowed the proposition and discussion of a formal and pragmatic framework to approach the fingermark dating questions. It allows identifying which type of information the scientist would be able to bring so far to investigators and/or Justice. Furthermore, this proposed framework also describes the different iterative development steps that the research should follow in order to achieve the validation of an objective fingermark dating methodology, whose capacities and limits are well known and properly documented.

Image quality in CT: From physical measurements to model observers.

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

The new final Clinical Skills examination in human medicine in Switzerland: Essential steps of exam development, implementation and evaluation, and central insights from the perspective of the national Working Group.

OBJECTIVE: Since 2011, the new national final examination in human medicine has been implemented in Switzerland, with a structured clinical-practical part in the OSCE format. From the perspective of the national Working Group, the current article describes the essential steps in the development, implementation and evaluation of the Federal Licensing Examination Clinical Skills (FLE CS) as well as the applied quality assurance measures. Finally, central insights gained from the last years are presented. METHODS: Based on the principles of action research, the FLE CS is in a constant state of further development. On the foundation of systematically documented experiences from previous years, in the Working Group, unresolved questions are discussed and resulting solution approaches are substantiated (planning), implemented in the examination (implementation) and subsequently evaluated (reflection). The presented results are the product of this iterative procedure. RESULTS: The FLE CS is created by experts from all faculties and subject areas in a multistage process. The examination is administered in German and French on a decentralised basis and consists of twelve interdisciplinary stations per candidate. As important quality assurance measures, the national Review Board (content validation) and the meetings of the standardised patient trainers (standardisation) have proven worthwhile. The statistical analyses show good measurement reliability and support the construct validity of the examination. Among the central insights of the past years, it has been established that the consistent implementation of the principles of action research contributes to the successful further development of the examination. CONCLUSION: The centrally coordinated, collaborative-iterative process, incorporating experts from all faculties, makes a fundamental contribution to the quality of the FLE CS. The processes and insights presented here can be useful for others planning a similar undertaking.

Objective assessment of low contrast detectability in computed tomography with Channelized Hotelling Observer.

PURPOSE: Iterative algorithms introduce new challenges in the field of image quality assessment. The purpose of this study is to use a mathematical model to evaluate objectively the low contrast detectability in CT. MATERIALS AND METHODS: A QRM 401 phantom containing 5 and 8 mm diameter spheres with a contrast level of 10 and 20 HU was used. The images were acquired at 120 kV with CTDIvol equal to 5, 10, 15, 20 mGy and reconstructed using the filtered back-projection (FBP), adaptive statistical iterative reconstruction 50% (ASIR 50%) and model-based iterative reconstruction (MBIR) algorithms. The model observer used is the Channelized Hotelling Observer (CHO). The channels are dense difference of Gaussian channels (D-DOG). The CHO performances were compared to the outcomes of six human observers having performed four alternative forced choice (4-AFC) tests. RESULTS: For the same CTDIvol level and according to CHO model, the MBIR algorithm gives the higher detectability index. The outcomes of human observers and results of CHO are highly correlated whatever the dose levels, the signals considered and the algorithms used when some noise is added to the CHO model. The Pearson coefficient between the human observers and the CHO is 0.93 for FBP and 0.98 for MBIR. CONCLUSION: The human observers' performances can be predicted by the CHO model. This opens the way for proposing, in parallel to the standard dose report, the level of low contrast detectability expected. The introduction of iterative reconstruction requires such an approach to ensure that dose reduction does not impair diagnostics.

Quality assessment of primary care for common mental disorders in isolated communities: Taking advantage of health records.

INTRODUCTION: This article is part of a research study on the organization of primary health care (PHC) for mental health in two of Quebec's remote regions. It introduces a methodological approach based on information found in health records, for assessing the quality of PHC offered to people suffering from depression or anxiety disorders. METHODS: Quality indicators were identified from evidence and case studies were reconstructed using data collected in health records over a 2-year observation period. Data collection was developed using a three-step iterative process: (1) feasibility analysis, (2) development of a data collection tool, and (3) application of the data collection method. The adaptation of quality-of-care indicators to remote regions was appraised according to their relevance, measurability and construct validity in this context. RESULTS: As a result of this process, 18 quality indicators were shown to be relevant, measurable and valid for establishing a critical quality appraisal of four recommended dimensions of PHC clinical processes: recognition, assessment, treatment and follow-up. CONCLUSIONS: There is not only an interest in the use of health records to assess the quality of PHC for mental health in remote regions but also a scientific value for the rigorous and meticulous methodological approach developed in this study. From the perspective of stakeholders in the PHC system of care in remote areas, quality indicators are credible and provide potential for transferability to other contexts. This study brings information that has the potential to identify gaps in and implement solutions adapted to the context.