Study on Accuracy of Judgments by Chinese Fingerprint Examiners

The interpretation of fingerprint evidence depends on the judgments of fingerprint examiners. This study assessed the accuracy of different judgments made by fingerprint examiners following the Analysis, Comparison, and Evaluation (ACE) process. Each examiner was given five marks for analysis, comparison, and evaluation. We compared the experts' judgments against the ground truth and used an annotation platform to evaluate how Chinese fingerprint examiners document their comparisons during the identification process. The results showed that different examiners demonstrated different accuracy of judgments and different mechanisms to reach them.

Accuracy and Precision of Head Motion Information in Multi-Channel Free Induction Decay Navigators for Magnetic Resonance Imaging.

Free induction decay (FID) navigators were found to qualitatively detect rigid-body head movements, yet it is unknown to what extent they can provide quantitative motion estimates. Here, we acquired FID navigators at different sampling rates and simultaneously measured head movements using a highly accurate optical motion tracking system. This strategy allowed us to estimate the accuracy and precision of FID navigators for quantification of rigid-body head movements. Five subjects were scanned with a 32-channel head coil array on a clinical 3T MR scanner during several resting and guided head movement periods. For each subject we trained a linear regression model based on FID navigator and optical motion tracking signals. FID-based motion model accuracy and precision was evaluated using cross-validation. FID-based prediction of rigid-body head motion was found to be with a mean translational and rotational error of 0.14±0.21 mm and 0.08±0.13(°) , respectively. Robust model training with sub-millimeter and sub-degree accuracy could be achieved using 100 data points with motion magnitudes of ±2 mm and ±1(°) for translation and rotation. The obtained linear models appeared to be subject-specific as inter-subject application of a "universal" FID-based motion model resulted in poor prediction accuracy. The results show that substantial rigid-body motion information is encoded in FID navigator signal time courses. Although, the applied method currently requires the simultaneous acquisition of FID signals and optical tracking data, the findings suggest that multi-channel FID navigators have a potential to complement existing tracking technologies for accurate rigid-body motion detection and correction in MRI.

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

Accuracy of MRI for the diagnosis of metastatic cervical lymphadenopathy in patients with thyroid cancer.

PURPOSE: The aim of this study was to systematically compare a comprehensive array of magnetic resonance (MR) imaging features in terms of their sensitivity and specificity to diagnose cervical lymph node metastases in patients with thyroid cancer. MATERIALS AND METHODS: The study included 41 patients with thyroid malignancy who underwent surgical excision of cervical lymph nodes and had preoperative MR imaging ≤4weeks prior to surgery. Three head and neck neuroradiologists independently evaluated all the MR images. Using the pathology results as reference, the sensitivity, specificity and interobserver agreement of each MR imaging characteristic were calculated. RESULTS: On multivariate analysis, no single imaging feature was significantly correlated with metastasis. In general, imaging features demonstrated high specificity, but poor sensitivity and moderate interobserver agreement at best. CONCLUSIONS: Commonly used MR imaging features have limited sensitivity at correctly identifying cervical lymph node metastases in patients with thyroid cancer. A negative neck MR scan should not dissuade a surgeon from performing a neck dissection in patients with thyroid carcinomas.

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.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Physician behavioral adaptability: A model to outstrip a "one size fits all" approach

Objective: Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. Method: This literature review is based on a literature search of the PsycINFO1 and MEDLINE1 databases. Results: The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Practice implications: Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes.

PKA antagonizes CLASP-dependent microtubule stabilization to re-localize Pom1 and buffer cell size upon glucose limitation.

Cells couple growth with division and regulate size in response to nutrient availability. In rod-shaped fission yeast, cell-size control occurs at mitotic commitment. An important regulator is the DYRK-family kinase Pom1, which forms gradients from cell poles and inhibits the mitotic activator Cdr2, itself localized at the medial cortex. Where and when Pom1 modulates Cdr2 activity is unclear as Pom1 medial cortical levels remain constant during cell elongation. Here we show that Pom1 re-localizes to cell sides upon environmental glucose limitation, where it strongly delays mitosis. This re-localization is caused by severe microtubule destabilization upon glucose starvation, with microtubules undergoing catastrophe and depositing the Pom1 gradient nucleator Tea4 at cell sides. Microtubule destabilization requires PKA/Pka1 activity, which negatively regulates the microtubule rescue factor CLASP/Cls1/Peg1, reducing CLASP's ability to stabilize microtubules. Thus, PKA signalling tunes CLASP's activity to promote Pom1 cell side localization and buffer cell size upon glucose starvation.

Diagnosis of endocrine disease: High-yield thyroid fine-needle aspiration cytology: an update focused on ancillary techniques improving its accuracy.

Thyroid fine-needle aspiration (FNA) cytology is a fast growing field. One of the most developing areas is represented by molecular tests applied to cytological material. Patients that could benefit the most from these tests are those that have been diagnosed as 'indeterminate' on FNA. They could be better stratified in terms of malignancy risk and thus oriented with more confidence to the appropriate management. Taking in to consideration the need to improve and keep high the yield of thyroid FNA, professionals from various fields (i.e. molecular biologists, endocrinologists, nuclear medicine physicians and radiologists) are refining and fine-tuning their diagnostic instruments. In particular, all these developments aim at increasing the negative predictive value of FNA to improve the selection of patients for diagnostic surgery. These advances involve terminology, the application of next-generation sequencing to thyroid FNA, the use of immunocyto- and histo-chemistry, the development of new sampling techniques and the increasing use of nuclear medicine as well as molecular imaging in the management of patients with a thyroid nodule. Herein, we review the recent advances in thyroid FNA cytology that could be of interest to the 'thyroid-care' community, with particular focus on the indeterminate diagnostic category.

Environmental control of the Pom1-dependent cell-size regulation pathway in fission yeast

Cells couple their growth and division rate in response to nutrient availability to maintain a constant size. This co-ordination happens either at the G1-S or the G2-M transition of the cell cycle. In the rod-shaped fission yeast, size regulation happens at the G2-M transition prior to mitotic commitment. Recent studies have focused on the role of the DYRK-family protein kinase Pom1, which forms gradients emanating from cell poles and inhibits the mitotic activator kinase Cdr2, present at the cell middle. Pom1 was proposed to inhibit Cdr2 until cells reached a critical size before division. However when and where Pom1 inhibits Cdr2 is not clear as medial Pom1 levels do not change during cell elongation. Here I show that Pom1 gradients are susceptible to environmental changes in glucose. Specifically, upon glucose limitation, Pom1 re-localizes from the poles to the cell sides where it delays mitosis through regulating Cdr2. This re-localization occurs due to microtubule de- stabilization and lateral catastrophes leading to transient deposition of the Pom1 gradient nucleator Tea4 along the cell cortex. As Tea4 localization to cell sides is sufficient to recruit Pom1, this explains the mechanism of Pom1 re-localization. Microtubule destabilization and consequently Tea4 and Pom1 spread depends on the activity of the cAMP-dependent Protein Kinase A (PKA/Pka1), as pka1 mutant cells have stable microtubules and retain polar Tea4 and Pom1 under limited glucose. PKA signaling negatively regulates the microtubule rescue factor CLASP/Cls1, thus reducing its ability to stabilize microtubules. Thus PKA signaling tunes CLASP activity to promote microtubule de-stabilization and Pom1 re-localization upon glucose limitation. I show that the side-localized Pom1 delays mitosis and balances the role of the mitosis promoting, mitogen-associated protein kinase (MAPK) protein Sty1. Thus Pom1 re-localization may serve to buffer cell size upon glucose limitation. -- Afin de maintenir une taille constante, les cellules régulent leur croissance ainsi que leur taux de division selon les nutriments disponibles dans le milieu. Dans la levure fissipare, cette régulation de la taille précède l'engagement mitotique et se fait à la transition entre les phases G2 à M du cycle cellulaire. Des études récentes se sont focalisées sur le rôle de la protéine Pom1, membre de la famille des DYRK kinase. Celle-ci forme un gradient provenant des pôles de la cellule et inhibe l'activateur mitotique Cdr2 présent au centre de la cellule. Le model propose que Pom1 inhibe Cdr2 jusqu'à atteindre une taille critique avant la division. Cependant quand et à quel endroit dans la cellulle Pom1 inhibe Cdr2 n'était pas clair car les niveaux médians de Pom1 ne changent pas au cours de la l'élongation des cellules. Dans cette étude, je montre que les gradients de Pom1 sont sensibles aux changements environnementaux du taux de glucose. Plus spécifiquement, en conditions limitantes de glucose, Pom1 se relocalise des pôles de la cellule pour se distribuer sur les côtés de celle-ci. Par conséquent, un délai d'entrée en mitose est observé dû à l'inhibition Cdr2 par Pom1. Cette délocalisation est due à la déstabilisation des microtubules qui va conduire à une déposition transitoire de Tea4, le nucléateur du gradient de Pom1, tout au long du cortex de la cellule. Comme la localisation de Tea4 sur les côtés de la cellule est suffisante pour recruter la protéine Pom1, ceci explique le mécanisme de relocalisation de celle-ci. La déstabilisation des microtubules et par conséquent la diffusion de Tea4 et Pom1 dépendent de l'activité de la protéine kinase A dépendante de l'AMP cyclique (PKA/Pka1). En absence de pka1, la stabilité des microtubules n'est pas affectée ce qui permet la rétention de Tea4 et Pom1 aux pôles de la cellule même en conditions limitantes de glucose. La signalisation via PKA régule négativement le facteur de sauvetage des microtubules CLASP/Cls1 et permet donc de réduire sa fonction de déstabilisation des microtubules. Ainsi la signalisation via PKA affine l'activité des CLASP pour promouvoir la déstabilisation des microtubules et la relocalisation de Pom1 en conditions limitantes de glucose. Je montre que la localisation sur les côtés retarde l'entrée en mitose et compense l'action de la protéine Sty1, connue pour être une MAPK qui induit l'entrée en mitose. Ainsi, la relocalisation de Pom1 pourrait servir à tamponner la taille de la cellule en condition limitantes de glucose. -- Various cell types in the environment such as bacterial, plant or animal cells have a distinct cellular size. Maintaining a constant cell size is important for fitness in unicellular organisms and for diverse functions in multicellular organisms. Cells regulate their size by coordinating their growth rate to their division rate. This coupling is important otherwise cells would get progressively smaller or larger after each successive cell cycle. In their natural environment cells may face fluctuations in the available nutrient supply. Thus cells have to coordinate their division rate to the variable growth rates shown under different nutrient conditions. During my PhD, I worked with a single-celled rod shaped yeast called the fission yeast. These cells are longer when the nutrient supply is abundant and shorter when the nutrient supply is scarce. A protein that senses changes in the external carbon source (glucose) is called Protein Kinase A (PKA). The rod shape of fission yeast cells is maintained thanks to a structural backbone called the cytoskeleton. One of the components of this backbone is called microtubules, which are small tube like structures spanning the length of the cell. They transport a protein called Tea4, which in turn is important for the proper localization of another protein Pom1 to the cell ends. Pom1 helps to maintain proper shape and size of these rod shaped yeast cells. My thesis work showed that upon reduction in the external nutrient (glucose) levels, microtubules become less stable and show an alteration in their organization. A significant percentage of the microtubules contact the side of the cell instead of touching only the cell tip. This leads to the spreading of the protein Pom1 away from the tips all around the cell periphery. This helps fission yeast cells to maintain the proper size required under these conditions of limited glucose supply. I further showed that the protein PKA regulates microtubule stability and organization and thus Pom1 spreading and maintenance of proper cell size. Thus my work led to the discovery of a novel pathway by which fission yeast cells maintain their size under limited supply of glucose. -- Divers types cellulaires dans l'environnement tels que les bactéries, les plantes ou les cellules animales ont une taille précise. Le maintien d'une taille cellulaire constante est importante pour le fitness des organismes unicellulaire ainsi que pour multiples fonctions dans les organismes multicellulaires. Les cellules régulent leur taille en coordonnant le taux de croissance avec le taux de division. Ce couplage est essentiel sinon les cellules deviendraient progressivement plus petites ou plus grandes après chaque cycle cellulaire. Dans leur habitat naturels les cellules peuvent faire face a des fluctuations dans le taux de nutriment disponible. Les cellules doivent donc coordonner leur taux de division aux taux variables de croissances perçus dans les différentes conditions nutritionnels. Pendant ma thèse, j'ai travaillée sur une levure unicellulaire, en forme de bâtonnet, nommé levure fissipare ou levure de fission. La taille de ces cellules est plus grande quand le taux de nutriments est grand et plus courte quand celui-ci est plus faible. Une protéine qui perçoit les changements dans le taux externe de la source de carbone (glucose) est nommée PKA pour protéine kinase A. La forme en bâtonnet de la cellule est due aux caractères structuraux du cytosquelette. Une composante importante de ce cytosquelette sont les microtubules, dont la structures ressemble à des petit tubes qui vont d'un bout à l'autre de la cellule. Ces microtubules transportent une protéine importante nommée Tea4 qui à leur tour importante pour la bonne localisation d'une autre protéine Pom1 aux extrémités de la cellule. La protéine Pom1 aide à maintenir la taille appropriée des levures fissipares. Mon travail de thèse a montré qu'en présence de taux faible de nutriments (glucose) les microtubules deviennent de moins en moins stables et montrent une désorganisation globale. Un pourcentage significatif des microtubules touche les côtés de la cellule aux lieu d'atteindre uniquement les extrémités. Ceci a pour conséquence une diffusion de Pom1 tout au long du cortex de la cellule. Ceci aide les levures fissipares à maintenir la taille appropriée pendant ce stress nutritionnel. De plus, je montre que PKA régule la stabilité et l'organisation des microtubules et par conséquent la diffusion de Pom1 et le maintien d'une taille constante. En conclusion, mon travail a conduit à la découverte d'un nouveau mécanisme par lequel la levure fissipare maintient sa taille dans des conditions limitantes en glucose.

Vestibular Schwannoma: The Evolution of Hearing and Tumor Size in Natural Course and after Treatment by LINAC Stereotactic Radiosurgery.

OBJECTIVE: To review the natural course of tumor size and hearing during conservative management of 151 patients with unilateral vestibular schwannoma (VS), and to evaluate the same parameters for the part of the group (n = 84) who were treated by LINAC stereotactic radiosurgery (SRS). METHODS: In prospectively collected data, patients underwent MRI and complete audiovestibular tests at inclusion, during the conservative management period and after SRS. Hearing was graded according to the Gardner-Robertson (GR) scale and tumor size according to Koos. Statistics were performed using Kaplan-Meier survival analysis and multivariate analyses including linear and logistic regression. Specific insight was given to patients with serviceable hearing. RESULTS: During the conservative management period (mean follow-up time: 24 months, range: 6-96), the annual risk of GR class degradation was 6% for GRI and 15% for GR II patients. Hearing loss as an initial symptom was highly predictive of further hearing loss (p = 0.003). Tumor growth reached 25%. For SRS patients, functional hearing preservation was 51% at 1 year and 36% at 3 years. Tumor control was 94 and 91%, respectively. CONCLUSION: In VS patients, hearing loss at the time of diagnosis is a predictor of poorer hearing outcome. LINAC SRS is efficient for tumor control. Patients who preserved their pretreatment hearing presented less hearing loss per year after SRS than before treatment, suggesting a protective effect of SRS when cochlear function can be preserved.

On evaluating the accuracy and biological plausibility of diffusion MRI tractograms

In diffusion MRI, traditional tractography algorithms do not recover truly quantitative tractograms and the structural connectivity has to be estimated indirectly by counting the number of fiber tracts or averaging scalar maps along them. Recently, global and efficient methods have emerged to estimate more quantitative tractograms by combining tractography with local models for the diffusion signal, like the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) framework. In this abstract, we show the importance of using both (i) proper multi-compartment diffusion models and (ii) adequate multi-shell acquisitions, in order to evaluate the accuracy and the biological plausibility of the tractograms.

Accuracy of cognitive MRI-targeted biopsy in hitting prostate cancer-positive regions of interest.

PURPOSE: Prostate cancer (PCa) diagnosis relies on clinical suspicion leading to systematic transrectal ultrasound-guided biopsy (TRUSGB). Multiparametric magnetic resonance imaging (mpMRI) allows for targeted biopsy of suspicious areas of the prostate instead of random 12-core biopsy. This method has been shown to be more accurate in detecting significant PCa. However, the precise spatial accuracy of cognitive targeting is unknown. METHODS: Consecutive patients undergoing mpMRI-targeted TRUSGB with cognitive registration (MRTB-COG) followed by robot-assisted radical prostatectomy were included in the present analysis. The regions of interest (ROIs) involved by the index lesion reported on mpMRI were subsequently targeted by two experienced urologists using the cognitive approach. The 27 ROIs were used as spatial reference. Mapping on radical prostatectomy specimen was used as reference to determine true-positive mpMRI findings. Per core correlation analysis was performed. RESULTS: Forty patients were included. Overall, 40 index lesions involving 137 ROIs (mean ROIs per index lesion 3.43) were identified on MRI. After correlating these findings with final pathology, 117 ROIs (85 %) were considered as true-positive lesions. A total of 102 biopsy cores directed toward such true-positive ROIs were available for final analysis. Cognitive targeted biopsy hit the target in 82 % of the cases (84/102). The only identified risk factor for missing the target was an anterior situated ROI (p = 0.01). CONCLUSION: In experienced hands, cognitive MRTB-COG allows for an accuracy of 82 % in hitting the correct target, given that it is a true-positive lesion. Anterior tumors are less likely to be successfully targeted.