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In this paper, we study a continuum mechanics model of gastrointestinal stroma tumor (GIST) evolution under the action of two specific treatments. The first-line treatment is a specific tyrosine kinase inhibitor (TKI), with a cytotoxic effect, that induces direct cell death. The second-line treatment is a multi-targeted TKI, with both cytotoxic and anti-angiogenic effect. The model is a coupled hyperbolic/elliptic system based on mass balance equations on cell densities coupled with a diffusion equation on the nutrients and oxygen concentrations. The tumor model involves 3 proliferating cell densities and a necrotic phase. Each proliferating cell density responds differently to the treatments: \(P_1\)-cells are killed by both treatments, \(P_2\)-cells are affected by the second-line treatment only, and \(P_3\) cells are resistant to both therapies. The necrotic cells are eliminated at a rate \(1/\tau \). We first prove the well-posedness of the model for any non-negative \(\tau \). Then we study the asymptotic behavior of the solution as \(\tau \) goes to zero. In particular, we proved that the limit problem correspond to a tumor growth model without necrosis. This is of great interest regarding the modeling, since it proves the continuity with respect to \(\tau \) of the family of \(\tau \)-dependent, ensuring the consistency of the modeling.

Objective. To evaluate the impact of image harmonization on outcome prediction models using radiomics. Approach. 234 patients from the Brain Tumor Image Segmentation Benchmark (BRATS) dataset with T1 MRI were enrolled in this study. Images were harmonized to a reference image using histogram matching (HHM) and a generative adversarial network (GAN)-based method (HGAN). 88 radiomics features were extracted on HHM, HGAN and original (HNONE) images. Wilcoxon paired test was used to identify features significantly impacted by the harmonization protocol used. Radiomic prediction models were built using feature selection with the Least Absolute Shrinkage and Selection Operator (LASSO) and Kaplan–Meier analysis. Main results. More than 50% of the features (49/88) were statistically modified by the harmonization with HHM and 55 with HGAN (adjusted p-value none, 62% for HHM and 71% for HGAN). Both image-based harmonization methods allowed to split patients into two groups with significantly different survival (pGAN images, we were also able to build and validate a model using only features impacted by the harmonization (median survivals of 189 versus 437 days, p = 0.006) Significance. Data harmonization in a multi-institutional cohort allows to recover the predictive value of some radiomics features that was lost due to differences in the image properties across centers. In terms of ability to build survival prediction models in the BRATS dataset, the loss of power from impacted histogram and heterogeneity features was compensated by the selection of additional shape features. The harmonization using a GAN-based approach outperformed the histogram matching technique, supporting the interest for the development of new advanced harmonization techniques for radiomic analysis purposes.

This essay is concerned with long-crested waves such as those arising in bore propagation. Such motions obtain on rivers when a surge of water invades an otherwise constantly flowing stretch and in the run-up of waves in the near-shore zone of large bodies of water. The dominating feature of the motion is that, in a standard \begin{document}$ xyz- $\end{document} coordinate system in which \begin{document}$ z $\end{document} increases in the direction opposite to which gravity acts and \begin{document}$ x $\end{document} increases in the principal direction of propagation, the depth of the fluid approaches a constant value \begin{document}$ h_0>0 $\end{document} as \begin{document}$ x \to +\infty $\end{document} and another value \begin{document}$ h_1>h_0 $\end{document} as \begin{document}$ x \to -\infty $\end{document} . In an earlier work, the authors developed theory for an idealized model for such waves based on a Boussinesq system of equations. The local well-posedness theory developed in that article applies to the sort of initial data arising in modeling bore propagation. However, well-posedness on the longer, Boussinesq time scale was not dealt with in the case of bore propagation, though such results were established for motions where \begin{document}$ h_1 = h_0 $\end{document} . We argue that without a well-posedness theory at least on the Boussinesq time scale, such models for bore-propagation may not be of any practical use. The issue of well-posedness is complicated by the fact that the total energy of the idealized initial data is infinite. The theory makes its way via the derivation of suitable approximations with which to compare the full solution. An interesting feature of the theory is the determination of dynamical boundary behavior that is not prescribed, but which the solution necessarily satisfies.

8542 Background: The NADIM trial (NCT03081689), led by the Spanish Lung Cancer Group, assessed the antitumor activity and safety of neoadjuvant chemoimmunotherapy for resectable stage IIIA NSCLC. Patients received neoadjuvant nivolumab and paclitaxel-carboplatin for three cycles before surgical resection, followed by one year of adjuvant nivolumab. At 24 months, progression-free survival (PFS) was 77%, suggesting that neoadjuvant chemoimmunotherapy represents a promising option in this setting. Pathological complete response (pCR) could potentially be used as an important surrogate endpoint for survival. We present here a re-analysis of the NADIM cohort aiming to develop a machine learning algorithm to predict the pCR status based on multimodal baseline data. Methods: We combined baseline clinical data (e.g., age, smoking status), biological data (e.g., tumor histology, mutations), radiology reports and radiomics analysis of the baseline CT scan in a multimodal analysis. While 46 patients were enrolled in the NADIM trial, only 28 had a complete set of data available for this retrospective study. For each patient, tumors were segmented on the baseline CT-scan in 3D by a Deep Learning algorithm. Radiomics features were extracted following the IBSI standards and combined with the other data modalities. A filter-based variable selection method was applied before training several machine learning algorithms. The optimization criterion was the Area Under the ROC Curve (AUC). Due to the small size of the cohort, a leave-one-out cross-validation approach was used to properly estimate the model performance. For a sub-cohort of 20 patients for which data have been collected longitudinally during the neoadjuvant treatment, an additional Delta-radiomics model was used to predict the pCR status. Results: An XGBoost algorithm with a linear base learner displayed an AUC of 0.69, a precision of 75%, a sensitivity of 83% and a specificity of 50%. Features with highest weight in the algorithm were a mix of radiological, radiomics, biological and clinical features (including the neutrophils to lymphocytes ratio, mutations and histology) highlighting the importance of a truly multimodal analysis. Indeed, withdrawing a specific data modality (e.g., radiomics or biological features), led to a decrease of ̃15% of the AUC. Inclusion of the Delta-radiomics analysis on the data collected longitudinally prior to surgery led to an improved AUC of 0.76 in that patient sub-cohort. Conclusions: This study is, to our knowledge, the first to offer a multimodal analysis of the response to neoadjuvant treatment for surgically resectable stage IIIA NSCLC and is a proof of concept that a machine learning algorithm can be used to predict the pCR in this context. These preliminary results are being confirmed in the ongoing NADIM II trial. Clinical trial information: NCT03838159.

601 Background: Triple negative breast cancer (TNBC) is a biologically and clinically heterogenous disease, associated with poorer outcomes when compared with other subtypes of breast cancer. In early-stage TNBC, surgery with curative intent remains the mainstay of therapy. Neoadjuvant chemotherapy is often given prior to surgery and achieving pathological complete response (pCR) has been associated with improved long-term outcomes in terms of progression-free survival (PFS) and overall survival (OS). There is thus high clinical interest in the ability to accurately predict pCR status using baseline data. Methods: A retrospective cohort of 57 patients with early-stage TNBC treated with neoadjuvant chemotherapy was analyzed to develop a machine learning-based algorithm predictive of pCR likelihood at the individual patient level. Multimodal baseline data were collected including clinical, biological (e.g., histology, genomic profile including CDC2, CDC20, KPNA2, MYBL2, complete blood count, Ki67), imaging data (baseline PET/CT scan), the radiology report and clinical outcomes data (pCR, PFS, OS). For each patient, tumors were segmented in 3D by an experimented nuclear physician using the SOPHiA Radiomics platform. Radiomics features were then extracted following the IBSI standards and then combined with the other data modalities. A filter-based variable selection method was applied before training several machine learning algorithms. The optimization criterion was the Area Under the ROC Curve (AUC). Due to the small size of the cohort, a nested leave-pair-out cross-validation approach was used to properly estimate the model performance. Results: The best result was obtained with the SVM algorithm with a linear kernel, reaching an AUC of 0.82, a precision of 71%, a sensitivity of 71% and a specificity of 70%. The features with highest weight in the algorithm were a mix of radiological, radiomics, biological and clinical features, highlighting the importance of a truly multimodal analysis. Indeed, withdrawing a specific data modality (e.g., radiomics features or biological features), led to a decrease of ̃10% of the AUC. Patients were then stratified into two groups based upon their predicted pCR status. These two groups displayed a statistically significant difference in PFS (p

4547 Background: Surgery is the standard of care for localized kidney cancer. Diagnostic imaging plays a critical role in disease staging and informs the extent of surgical resection (partial or radical nephrectomy, extended resection). In clinical routine, up to 15% of the tumors initially assessed as T1-T2 on imaging is upgraded to pT3a status post-surgery, implying a higher risk of relapse. The ability to correctly predict pT3a status pre-surgery would inform the surgical approach. An individualized prediction of the risk of clinical T1 or T2 tumors to be upstaged to pT3a is thus of high surgical interest. Methods: UroCCR is a French national network of 37 multidisciplinary teams for kidney cancer management that collects longitudinal data on the routine clinical care of its patients. A retrospective cohort of 4,395 cases of clinical T1-T2 kidney tumors was analyzed to develop a machine learning-based algorithm predictive of post-surgical pT3a upstaging risk at the individual patient level. For each patient, pre-surgical data were collected, including gender, age, symptoms, tumor size, tumor location, RENAL score, ECOG performance status, ASA score, and post-surgical pathological status. Sites were randomly assigned to the training or testing cohort, and their respective patient cases split between cohorts in a 60/40 ratio. Missing values were addressed through imputation performed with a k-nearest neighbor algorithm. Algorithms were trained on a data set of 2,636 patients and hyperparameters were optimized using a Bayes cross-validation (10-fold) approach. The area under the precision-recall curve (prAUC) was used as optimization metric. The performance of the algorithms for pT3a status prediction was then evaluated on the test dataset of 1,759 patients using precision-recall curves. Results: A logistic regression algorithm reached an AUC of 0.77 and a prAUC of 0.41. Higher values of the tumor size or age at surgery, the hilar location and the presence of symptoms at diagnosis were all associated with an increase of the predicted probability of pT3a upstaging. For each patient, Shapley values graphs were generated to display the pT3a upstaging probability and the relative contribution of each feature to the prediction. Three risk groups were defined based on the relative computed probability of pT3a upstaging, which displayed a statistically significant difference in Disease-Free Survival (DFS) (p < 0.0001), suggesting that pre-surgical multimodal data analysis could help predict long-term outcomes. Conclusions: This study suggests that machine learning applied to pre-surgical multimodal data can predict the risk of pT3a upstaging of a localized kidney tumor and inform long-term outcomes at the individual patient level. The results have been validated on an external cohort of 1,759 patients with data from the clinical routine.

Background We aimed to improve the assessment of the drug activity in meningioma clinical trials based on the study of the 3D volume growth rate (3DVGR) in a series of aggressive meningiomas. We secondarily aimed to correlate 3DVGR study with patient outcome. Methods We performed a post hoc analysis based on volume data and 3DVGR extracted from CEVOREM study including 18 patients with 32 recurrent high-grade meningiomas and treated with everolimus and octreotide. The joint latent class model was used to classify tumor 3DVGR undertreatment. Results Class 1 includes lesions responding to treatment with decrease in volume in the first 3 months, and then a stabilization thereafter (9.5% of tumors) (mean pretreatment 3DVGR = 6.13%/month; mean undertreatment 3DVGR = −18.7%/month within 3 first months and −0.14%/month after the 3 first months). Class 2 includes lesions considered as stable or with a slight increase in volume undertreatment (65.5%) (mean pretreatment 3DVGR = 6.09%/month; undertreatment 3DVGR = −0.09% within the first 3 months). Class 3 includes lesions without 3DVGR decrease (25%) (mean pretreatment 3DVGR = 46.9%/month; mean undertreatment 3DVGR = 19.2%/month within the first 3 months). Patients with class 3 lesions had a significantly worse progression-free survival (PFS) rate than class 1 and 2 ones. Conclusions Tumor 3DVGR could be helpful to detect early signal of drugs antitumoral activity or nonactivity. This volume response classification could help in the assessment of drug activity in tumors with mostly volume stabilization and rare response as aggressive meningiomas even with a low number of patients in complement to 6 months PFS.

International audience

International audience; Non-small-cell lung carcinoma is a frequent type of lung cancer with a bad prognosis. Depending on the stage, genomics, several therapeutical approaches are used. Tyrosine Kinase Inhibitors (TKI) may be successful for a time in the treatment of EGFR-mutated non-small cells lung carcinoma. Our objective is here to propose a survival assessment as their efficacy in the long run is challenging to evaluate. The study includes 17 patients diagnosed as of EGFR-mutated non-small cell lung cancer and exposed to an EGFR-targeting TKI with 3 computed tomography (CT) scans of the primitive tumor (one before the TKI introduction and two after). An imaging biomarker based on the texture heterogeneity evolution between the first and the third exams is derived and computed from a mathematical model and patient data. Defining the overall survival as the time between the introduction of the TKI treatment and the patient death, we obtain a statistically significant correlation between the overall survival and our imaging marker (p = 0:009). Using the ROC curve, the patients are separated into two populations and the comparison of the survival curves is statistically significant (p = 0:025). The baseline exam seems to have a significant role in the prediction of response to TKI treatment. More precisely, our imaging biomarker defined using only the CT scan before the TKI introduction allows to determine a first classification of the population which is improved over time using the imaging marker as soon as more CT scans are available. This exploratory study leads us to think that it is possible to obtain a survival assessment using only few CT scans of the primary tumor.

Mathematical modeling and scientific computing are part of the general scientific landscape and universally used in almost all industrial sectors. Car manufacturers use it to optimize their vehicles. In aeronautics, models and calculations are used to design aircraft. In energy, calculations can be used to explore extreme regimes (e.g., by simulating an accident in a nuclear power plant or a dam failure) that cannot of course be reached experimentally. Calculation can also be used to explain complex phenomena or to predict the future. This is the case in climatology.

We propose in this article a rapid review of the main physical quantities related to the image quality, the Holy Grail of every detector manufacturer. We stress the importance of understanding the complex physics of the detector dark current, which carries important information on the achievable performance. We illustrate our assertion with the help of experimental results achieved on our III-V product lines, most especially InGaAs (SWIR) and InSb (MWIR) planar photodiode Focal Plane Arrays (FPAs).

Introduction Le Pembrolizumab est indique dans le cancer bronchique non a petites cellules (CBNPC) en 1re ligne pour les tumeurs exprimant PD-L1 ≥ 50 %. Le taux de reponse etait de 45 % dans l’essai d’enregistrement [1] . Les enjeux medico-economiques de la place de l’immunotherapie sont importants. L’objectif de notre etude est de rechercher des facteurs predictifs cliniques, biologiques, histologiques, moleculaires et radiologiques de reponse au Pembrolizumab en 1re ligne dans les CBNPC. Methodes Etude retrospective monocentrique incluant 65 patients ayant recu du Pembrolizumab en 1re ligne entre aout 2017 et octobre 2019. Le critere de jugement principal etait la reponse au Pembrolizumab a la premiere evaluation. Les criteres de jugement secondaires etaient la survie sans progression (SSP) et la survie globale (SG). Resultats Parmi les 65 patients inclus, 36 (55,3 %) presentaient une reponse partielle ou stabilite et 9 (13,8 %) etaient decedes a la 1re evaluation. La mediane de suivi etait de 5,8 mois (3 jours–28,6 mois). La mediane de SSP etait de 3,6 mois (IC95 % 2,03–5,73) et celle de SG etait de 7,46 mois (IC95 % 4,73–13,5). En analyse multivariee, le facteur predictif de reponse etait le PS a 0/1 [Odd Ratio (OR) 0,37 (Intervalle de confiance (IC) 95 % 0,03–1,00) : Variable Importance (VI) = 0,94]. Les facteurs predictifs de non reponse etaient: stade IV [OR 3,49 (IC95 % 1,00–53,05) : VI = 0,96], CRP > 50 mg/l [OR 1,20 (IC95 % 0,97–14,43) : VI = 0,91], monocytes > 650/mm3 [OR 1,87 (IC95 % 1,00–18,25) : VI = 0,83], NLR ≥ 5 [OR 1,49 (IC95 % 0,95–10,17) : VI = 0,78], mutation KRAS [OR 1,13 (IC95 % 0,93–7,14) : VI = 0,82], nombre de sites metastatiques > 2 [OR 1,65 (IC95 % 1,00–17,31) : VI = 0,82] et un RECIST important [OR1,04 (IC95 % 1,00–1,32) : VI = 0,77]. De meme pour la SSP et la SG, le facteur de bon pronostic etait le PS 0/1, les facteurs de mauvais pronostic etaient un NLR ≥ 5, la CRP > 50 mg/l et la mutation KRAS : avec en plus pour la SSP, le stade IV et un nombre de sites metastatiques > 2. Conclusion Cette etude suggere que le PS 0/1, une inflammation plus legere et un faible « tumor burden » sont des facteurs predictifs de reponse a l’immunotherapie.

International audience; As cancer evolution is challenging to evaluate, there is dire need of novel approaches offering clinicians a better insight on the disease. For instance, having an estimation of the growth of slowly evolving tumors that have to be monitored or of the risk of relapse after treatment may be invaluable for clinicians. In this article, two approaches (statistical learning and mechanistic modelling) are presented that aim at addressing these clinical questions. As we wish to use data available in the clinical routine for solid tumors, medical images will be a major source of insight on the disease.

BACKGROUND Meningioma therapy efficiency is used to being assessed by 6 months progression survival rate (PFS6), which remains the most consensual criterion. Nevertheless, different patterns of meningiomas intrinsic aggressiveness and growth rates directly impact the PFS6 leading to unreliability of drug effect assessment. Moreover, therapeutic response remains rare in meningiomas. These points lead to consider classical and updated RANO criteria as not fully adapted to meningiomas. Based on phase II CEVOREM trial experience, we aim to improve the assessment of drugs efficiency in meningiomas via the determination of growth rate before and under treatment. MATERIAL AND METHODS Twenty patients were included in Cevorem trial which tested the combination of octreotide and everolimus as previously described. MRI assessment was performed in the 3 to 6 preinclusion months, at inclusion then every 3 months. Progression was assessed by investigators according to RANO criteria. An independent central review was performed with 2 reviewers and 1 adjudicator: largest diameter, 2D maximal area as 3D volume were assessed by autosegmentation software (Brainlab). Results from central review were correlated to investigators assessment. 3D volume growth rate (3DVGR) was calculated using 2 different processes (one simple and one complex). Comparison of 3DVGR before vs. under treatment was performed. Meningioma growth under treatment was compared to theoretical meningioma growth based on preinclusion data using a model of meningioma growth. RESULTS PFS6 assessed via the independent central review was in accordance with PFS6 assessed by investigators following RANO criteria. Then, we analyzed 3DVGR before and during therapy. Standard deviation was higher using the complex 3DVGR calculation process. A decrease of more than 50% of the 3DVGR was observed in 30/36 tumors at 3 months with the both calculation modes and could be considered as a threshold of drugs activity. Median volume growth rate decreased from 88.3 or 17.2%/3 months before inclusion to -2.2 or à -0.6 %/3mo at 3 months depending of the calculation mode (p CONCLUSION 3DVGR measurement during versus before seems as a sensitive and reliable tool which provides valuable comparison in a phase 2 study to assess drugs activity in meningioma in complement to PFS6. 3DVGR assessment should be considered in future clinical trials.

Objectives To evaluate the performance of dynamic contrast-enhanced MRI measurement of glomerular filtration rate (GFR) compared with the reference standard technique of urinary clearance of 51Cr-EDTA. Patients and methods All kidney transplant recipients (KTRs) with an indication for non-urgent contrast-enhanced MRI at our institution were prospectively included between 2008 and 2012. Renographies were acquired by low-dose dynamic contrast-enhanced MRI (DCE-MRI) then fitted with a two-compartment pharmacokinetic model. MR-GFR was compared with reference isotopic measurements using Bland-Altman diagrams, intraclass correlation coefficient (ICC) and concordance rates. Results Forty-two KTRs (mean age 51.5 years, 26–74) were analyzed. Mean estimated GFR was 48.5 ± 27 mL/min/1.73m2 (24–178 mL/min). The mean bias was +13.2 mL/min (6.4–20.0, +36.9%) ranging from -31.0 mL/min (-41.7%) to +101.4 mL/min (+89.2%) with a large variability (standard-deviation: 22.3 mL/min; limits of agreement: [-30.6 (-43.3–-18.9); +57.0 (45.3–68.7)]). The ICC was 0.32 (0.02–0.56) and the concordance rate was 28.6% (14.9–42.2). Conclusions The large variability of MR-GFR compared with the reference technique precludes its use in KTRs, whose anatomical peculiarities make standardization of arterial input function (AIF) difficult.

EGFR-mutated non-small cells lung carcinoma are treated with Tyrosine Kinase Inhibitors (TKI). Very often, the disease is only responding for a while before relapsing. TKI efficacy in the long run is therefore challenging to evaluate. Our objective is to derive a new imaging biomarker that could offer better insights on the disease response to treatment. This study includes 17 patients diagnosed as EGFR-mutated non-small cell lung cancer and exposed to an EGFR-targeting TKI. The early response to treatment is evaluated with 3 computed tomography (CT) scans of the primitive tumor (one before the TKI introduction and two after). Using our knowledge of the disease, an imaging biomarker based on the tumor heterogeneity evolution between the first and the third exams is defined and computed using a novel mathematical model calibrated on patient data. Defining the overall survival as the time between the introduction of the TKI treatment and the patient death, we obtain a statistically significant correlation between the overall survival and our imaging marker (p = 0.009). Using the ROC curve, the patients are separated into two populations hence the comparison of the survival curves is statistically significant (p = 0.025). Initial state of the tumor seems to have a role for the prognosis of the response to TKI treatment. More precisely, the imaging marker - defined using only the CT scan before the TKI introduction - allows us to determine a first classification of the population which is refined over time using the imaging marker as more CT scans become available. This exploratory study leads us to think that it is possible to obtain a survival assessment using only few CT scans of the primary tumor.

SOFRADIR is the worldwide leader on the cooled IR detector market for high-performance space, military and security applications thanks to a well mastered Mercury Cadmium Telluride (MCT) technology, and recently thanks to the acquisition of III-V technologies including Indium Gallium Arsenide (InGaAs). As a result, strong and continuous development efforts are deployed to deliver cutting edge products with improved performances in terms of spatial and thermal resolution, dark current, quantum efficiency, low excess noise and operability. Recent years have evidenced significant progress with InGaAs process maturity enabling low noise detectors operable at room temperature, with no cooling requirement. This new generation of so called Tecless devices meets a surging interest for affordable Short-Wave Infrared (SWIR) detectors for use in volume applications such as industrial machine vision, science imaging or surveillance applications. For these systems, the latest uncooled InGaAs sensors allow major cost savings without sacrificing performance. In this talk we will review and analyze the impact of temperature on InGaAs detectors. We will also discuss implementation and optimization tradeoffs which should be considered when using uncooled InGaAs SWIR detectors.

International audience; MultiCellular Tumor Spheroids are 3D cell cultures that can accurately reproduce the behavior of solid tumors. It has been experimentally observed that large spheroids exhibit a decreasing gradient of proliferation from the periphery to the center of these multicellular 3D models: the proportion of proliferating cells is higher in the periphery while the non-proliferating quiescent cells increase in depth. In this paper, we propose to investigate the key mechanisms involved in the establishment of this gradient with a Partial Differential Equations model that mimics the experimental setup of growing spheroids under different nutrients supply conditions. The model consists of mass balance equations on the two cell populations observed in the data: the proliferating cells and the quiescent cells. The spherical symmetry is used to rewrite the model in radial and relative coordinates. Thanks to a rigorous data postprocessing the model is then fit and compared quantitatively with the experimental quantification of the percentage of proliferating cells from EdU immun-odetection on 2D spheroid cryosection images. The results of this calibration show that the proliferation gradient observed in spheroids can be quantitatively reproduced by our model.

Background and Objective Mathematical modeling of tumor growth draws interest from the medical community as they have the potential to improve patients’ care and the use of public health resources. The main objectives of this work are to model the growth of meningiomas – slow-growing benign tumors requiring extended imaging follow-up – and to predict tumor volume and shape at a later desired time using only two times examinations. Methods We develop two variants of a 3D partial differential system of equations (PDE) which yield after a spatial integration systems of ordinary differential equations (ODE) that relate tumor volume with time. Estimation of models parameters is a crucial step to obtain a personalized model for a patient that can be used for descriptive or predictive purposes. As PDE and ODE systems share the same parameters, they are both estimated by fitting the ODE systems to the tumor volumes obtained from MRI examinations acquired at different times. A population approach allows to compensate for sparse sampling times and measurement uncertainties by constraining the variability of the parameters in the population. Results Description capabilities of the models are investigated in 39 patients with benign asymptomatic meningiomas who had had at least three surveillance MRI examinations. The two models can fit to the data accurately and more realistically than a naive linear regression. Prediction performances are validated for 33 patients using a population approach. Mean relative errors in volume predictions are less than 10 % with ODE systems versus 12.5 % with the naive linear model using only two times examinations. Concerning the shape, the mean Sorensen-Dice coefficients are 85 % with the PDE systems in a subset of 10 representative patients. Conclusions Our strategy – based on personalization of mathematical model – provides a good insight on meningioma growth and may help decide whether to extend the follow-up or to treat the tumor.

Les corticosurrenalomes representent une cause rare d’incidentalomes surrenaliens. Leur cinetique tumorale spontanee est mal connue en raison de leur rarete et de la necessite d’une prise en charge rapide. Lorsque l’imagerie est realisee pour un motif autre, il arrive qu’une lesion surrenalienne suspecte soit decrite sans etre prise en charge immediatement. L’objectif de ce travail est d’etudier retrospectivement la cinetique tumorale spontanee de ces formes de corticosurrenalomes incidentaux dans le cadre d’une etude europeenne ENSAT. Chez des patients avec un corticosurrenalome ayant eu plusieurs imageries avant le diagnostic histologique, la cinetique tumorale, les caracteristiques morphologiques et les variations de texture des imageries ont ete etudiees par une equipe de mathematiciens. Ces donnees ont ete correlees avec les differentes caracteristiques biologiques, histologiques, et pronostiques des patients. 44 patients ont ete inclus, 88 % de femme, d’âge median 55 ans (21–83), avec une duree moyenne entre la 1ere imagerie et le diagnostic de 4 mois (1–57). 48 % presentaient une secretion hormonale infraclinique. La taille tumorale mediane etait de 85 mm (20–160) au diagnostic histologique. Le score de Weiss median etait de 5/9 (2–8) avec un Ki67 median a 10 %. L’analyse mathematique des imageries identifie 2 groupes de patients avec une pente tumorale « lente » ou « rapide ». La correlation entre les caracteristiques des patients, des imageries initiales et ces profils de cinetique tumorale pourra etre exposee lors du congres. Une meilleure connaissance des caracteristiques morphologique des corticosurrenalomes incidentaux pourrait guider le clinicien a choisir qui operer plus rapidement en cas d’incidentalome.

International audience; Biological tissues accumulate mechanical stress during their growth. The mere measurement of the stored stress is not an easy task. We address here the spherical case and our experiments consist in performing an incision of a spherical microtissue (tumor spheroid) grown in vitro. On the theoretical part we derive a compatibility condition on the stored stress in spherical symmetry, which imposes a relation between the circumferential and radial stored stress. The numerical implementation uses the hyperelastic model of Ciarlet and Geymonat. A parametric study is performed to assess the influence of each parameter on the shape of the domain after the incision. As a conclusion, the total radial stored stress can be confidently estimated from the measurement of the opening after incision. We validate the approach with experimental data.

International audience; Biological tissues accumulate mechanical stress during their growth. The mere measurement of the stored stress is not an easy task. We address here the spherical case and our experiments consist in performing an incision of a spherical microtissue (tumor spheroid) grown in vitro. On the theoretical part we derive a compatibility condition on the stored stress in spherical symmetry, which imposes a relation between the circumferential and radial stored stress. The numerical implementation uses the hyperelastic model of Ciarlet and Geymonat. A parametric study is performed to assess the influence of each parameter on the shape of the domain after the incision. As a conclusion, the total radial stored stress can be confidently estimated from the measurement of the opening after incision. We validate the approach with experimental data.

Background Response evaluation criteria in solid tumours (RECIST) has significant limitations in terms of variability and reproducibility, which may not be independent. The aim of the study was to evaluate the precision of manual bi-dimensional segmentation of lung, liver metastases, and to quantify the uncertainty in tumour response assessment. Methods A total of 520 segmentations of metastases from six livers and seven lungs were independently performed by ten physicians and ten scientists on CT images, reflecting the variability encountered in clinical practice. Operators manually contoured the tumours, firstly independently according to the RECIST and secondly on a preselected slice. Diameters and areas were extracted from the segmentations. Mean standard deviations were used to build regression models and 95% confidence intervals (95% CI) were calculated for each tumour size and for limits of progressive disease (PD) and partial response (PR) derived from RECIST 1.1. Results Thirteen aberrant segmentations (2.5%) were observed without significant differences between the physicians and scientists; only the mean area of liver tumours (p = 0.034) and mean diameter of lung tumours (p = 0.021) differed significantly. No difference was observed between the methods. Inter-observer agreement was excellent (intra-class correlation >0.90) for all variables. In liver, overlaps of the 95% CI with the 95% CI of limits of PD or PR were observed for diameters above 22.7 and 37.9 mm, respectively. An overlap of 95% CIs was systematically observed for area. No overlaps were observed in lung. Conclusions Although the experience of readers might not affect the precision of segmentation in lung and liver, the results of manual segmentation performed for tumour response assessment remain uncertain for large liver metastases. Electronic supplementary material The online version of this article (doi:10.1186/s41747-017-0015-4) contains supplementary material, which is available to authorized users.

Glioblastoma multiforme (GBM) causes significant neurological morbidity and short survival times. Brain invasion by GBM is associated with poor prognosis. Recent clinical trials of bevacizumab in newly-diagnosed GBM found no beneficial effects on overall survival times. We have reported a mathematical model of GBM growth and invasion, built at the scale of clinical magnetic resonance imaging. Here, we replicate the patterns of progression of GBM patients treated with bevacizumab. The model is interrogated to derive a mechanistic explanation for each type of recurrence. Citation Format: Elizabeth Scribner, Olivier Saut, Thierry Colin, Hassan M. Fathallah-Shaykh. Mechanisms of GBM progression on bevacizumab: Model predictions. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-18.

International audience; La notion de compétence collective soulève de nombreux débats et paradoxes, à la fois évidence, lorsque l’on constate que les capacités opérationnelles mises en œuvre par un collectif donné ne se limitent pas et ne se déduisent pas de la somme des capacités individuelles des membres de ce collectif, et énigme, lorsque l’on se trouve démuni pour la décrire, la répertorier ou l’évaluer.Cet article examine les effets produits sur la compétence collective par une instrumentation de gestion dont l’un des objectifs est de développer des processus d’apprentissage à différents niveaux. Il s’appuie d’un point de vue empirique sur une étude de cas, l’entreprise AUTO, qui a fait le choix d’implémenter les méthodes de gestion inspirées du Lean. Sur le plan théorique, il mobilise les théories de l’activité, dont l’intérêt est de permettre de lier analytiquement activité, instrument de gestion et production de compétence collective. Les résultats montrent que la médiation jouée par les instruments de gestion ne conduit à la production de compétence collective que sous certaines conditions : le système d’activité doit laisser suffisamment de marges d’interprétation aux différents acteurs, les règles d’incitation individuelles doivent être construites en cohérence avec le fonctionnement structurel du système d’activité, et il faut accorder toute son importance au rôle de pilote de la compétence collective que doit jouer le manager de proximité.

International audience; Understanding the endothelial cell migration on micropatterned polymers, as well as the cell orientation is a critical issue in tissue engineering, since it is the preliminary step towards cell polarization and that possibly leads to the blood vessel formation. In this paper, we derive a simple agent-based model to describe the migration and the orientation of endothelial cells seeded on bioactive micropatterned polymers. The aim of the modeling is to provide a simple model that corroborates quantitatively the experiments, without considering the complex phenomena inherent to cell migration. Our model is obtained thanks to a classical mechanics approach based on experimental observations. Even though its simplicity, it provides numerical results that are quantitatively in accordance with the experimental data, and thus our approach can be seen as a preliminary way towards a simple modeling of cell migration.

The topology and creation energy of domain walls in different magnetic chains (called Single-Chain Magnets or SCMs) are discussed. As these domain walls, that can be seen as ``defects'', are known to control both static and dynamic properties of these one-dimensional systems, their study and understanding are necessary first steps before a deeper discussion of the SCM properties at finite temperature. The starting point of the paper is the simple regular ferromagnetic chain for which the characteristics of the domain walls are well known. Then two cases will be discussed (i) the ``mixed chains'' in which isotropic and anisotropic classical spins alternate, and (ii) the so-called ``canted chains'' where two different easy axis directions are present. In particular, we show that ``strictly narrow'' domain walls no longer exist in these more complex cases, while a cascade of phase transitions is found for canted chains as the canting angle approaches ${45}^{\ensuremath{\circ}}$. The consequence for thermodynamic properties is briefly discussed in the last part of the paper.

International audience; La prise en compte de la dimension territoriale offre à la fonction RH de nouvelles opportunités d’action. Une alternative semble se dessiner entre une gestion « territorialisée » des RH qui ne ferait qu’élargir le périmètre d’action du DRH sans en modifier le contenu et une gestion des RH « territoriale » correspondant à un nouveau modèle de GRH. Cette alternative est questionnée au regard d’une enquête prospective menée auprès de DRH de la région Grand Est. Les résultats montrent une vision contrastée des professionnels sur les opportunités offertes par le territoire. Ils sont analysés et mis en perspective au regard de la littérature existante et de la méthodologie prospective utilisée.

International audience; This paper aims at modeling breast cancer transition from the in situ stage –when the tumor is confined to the duct– to the invasive phase. Such a transition occurs thanks to the degradation of the duct membrane under the action of specific enzymes so-called matrix metallo-proteinases (MMPs). The model consists of advection–reaction equations that hold in the duct and in the surrounding tissue, in order to describe the proliferation and the necrosis of the cancer cells in each subdomain. The divergence of the velocity is given by the increase of the cell densities. Darcy law is imposed in order to close the system. The key-point of the modeling lies in the description of the transmission conditions across the duct. Nonlinear Kedem-Katchalsky transmission conditions across the membrane describe the discontinuity of the pressure as a linear function of the flux. These transmission conditions make it possible to describe the transition from the in situ stage to the invasive phase at the macroscopic level. More precisely, the membrane permeability increases with respect to the local concentration of MMPs. The cancer cells are no more confined to the duct and the tumor invades the surrounding tissue. The model is enriched by the description of nutrients concentration, tumor necrosis factors, and MMPs production. The mathematical model is implemented in a 3D C ++-code, which is based on well-adapted finite difference schemes on Cartesian grid. The membrane interface is described by a level-set, and the transmission conditions are precisely approached at the second order thanks to well-suited sharp stencils. Our continuous approach provides new significant insights in the macroscopic modeling of the breast cancer phase transition, due to the membrane degradation by MMP enzymes.

e14607 Background: Medical imaging techniques play a central role in the evaluation of lung cancer and proper images analysis is essential for determining the location and stage of tumors, for diagnosis and prognosis assessment, guiding therapeutic decisions and for monitoring tumor response during and after treatment. It also supports interventional radiology acts (i.e. biopsies, thermo-ablations or embolization). Yet, this source of information, which is critical for the decision-making process, is not being used to its full potential. Besides, NGS technics allow the precise characterization of the genomic profile of a tumor by detecting mutations, evaluating the TMB and providing additional information such as the PD-L1 status. Methods: We have used an AI-based strategy to improve the stratification of cohorts of patients suffering from lung cancer. Using an advanced segmentation technology, we were able to quickly and precisely extract 3D Radiomic characteristics from the images. We then combined extracted heterogeneity and texture indicators with the biology information thanks to a machine learning based methodology. Results: We have applied this strategy to stage 4 NSCLC with EGFR mutation treated with TKI and have shown that stratification of the cohort with respect to the OS can be delivered using the base-line CT-scan and the first two exams used for the evaluation of the early response to the treatment. The same strategy was developed for the monitoring of lung metastases in order to help scheduling thermo-ablation by providing a prediction of the growth of the lesion in oligo-metastatic cases. Conclusions: This study paves the way to a near future when Artificial Intelligence will provide precise evaluation of lung tumors and full integration of all the medical information available for each patient to support the decision making within the tumor board.

We present a finite volume method to solve elliptic equations with immersed interface conditions. This method allows discontinuities on the solution and its normal derivatives on an interface inside the domain on a Cartesian grid. The main idea is to use a piecewise polynomial representation of the solution on a dual grid that avoid distinctions between the different interface configurations. The method achieves second order accuracy with a compact nine-point stencil. Moreover, we show that this method applies to solve embedded Dirichlet and Neumann problems.

The future challenges in oncology imaging are to assess the response to treatment even earlier. As an addition to functional imaging, mathematical modeling based on the imaging is an alternative, cross-disciplinary area of development. Modeling was developed in oncology not only in order to understand and predict tumor growth, but also to anticipate the effects of targeted and untargeted therapies. A very wide range of these models exist, involving many stages in the progression of tumors. Few models, however, have been proposed to reproduce in vivo tumor growth because of the complexity of the mechanisms involved. Morphological imaging combined with ''spatial'' models appears to perform well although functioning imaging could still provide further information on metabolism and the micro-architecture. The combina- tion of imaging and modeling can resolve complex problems and describe many facets of tumor growth or response to treatment. It is now possible to consider its clinical use in the medium term. This review describes the basic principles of mathematical modeling and describes the advantages, limitations and future prospects for this in vivo approach based on imaging data. © 2013 Editions francaises de radiologie. Published by Elsevier Masson SAS. All rights reserved. Nowadays, imaging lies at the heart of patient management, particularly in oncology. Apart from the time when a disease is diagnosed, the different imaging methods are used to assess the effectiveness of both local (surgery, radiotherapy, heat ablation) and systemic (chemotherapy, targeted therapy) treatments during follow-up. The protocols usually rec- ommend assessment criteria such as the RECIST, WHO or CHOI, although these are less than perfect (1).

Inscrit dans le courant Decision as Practice, cet article montre que les managers de proximite participent a la construction du sens d’une decision strategique en mobilisant des dispositifs RH. Partant d’une etude de cas dans le secteur du logement social, les auteurs montrent que les managers de proximite contribuent a redefinir le contenu de la decision strategique en faisant passer l’objectif de la notion de « qualite de service » a celle de « proximite ». Ils mettent egalement en evidence que le plan de formation, ainsi que d’autres dispositifs RH, parfois moins formels, jouent un role dans cette redefinition.

30 pages; International audience; The present essay is concerned with a model for the propagation ofthree-dimensional, surface water waves. Of especial interest will be long-crestedwaves such as those sometimes observed in canals and in near-shore zones oflarge bodies of water. Such waves propagate primarily in one direction, taken tobe the x−direction in a Cartesian framework, and variations in the horizontaldirection orthogonal to the primary direction, the y−direction, say, are oftenignored. However, there are situations where weak variations in the secondaryhorizontal direction need to be taken into account.Our results are developed in the context of Boussinesq models, so they areapplicable to waves that have small amplitude and long wavelength when comparedwith the undisturbed depth. Included in the theory are well-posednessresults on the long, Boussinesq time scale. As mentioned, particular interestis paid to the lateral dynamics, which turn out to satisfy a reduced Boussinesqsystem. Waves corresponding to disturbances which are localized in thex−direction as well as bore-like disturbances that have infinite energy are takenup in the discussion.

This thesis is dedicated to the development of numerical simulation tools allowing to understand complex multi-physics phenomena (thermal, solid mechanics, fluid mechanics and sciences materials) involved in TIG (Tungsten Inert Gas) welding operations of 316L thin plate used in the food industry. The local fusion of the elements to be assembled by welding has indeedthe disadvantage of inducing significant local deformations that complicate the assembly of parts. Another The disadvantage is the appearance of residual stresses that impact the durability of the welded structure. In order to predict these deformations and constraints during the design phase, for example in order to minimize them in playing on parameters such as the speed of execution and the intensity of the welding current, digital tools Predictors have been developed as part of this work.A model finite elements 3D of coupling between the thermal one and the mechanics, in the transient and nonlinear domains,was programmed in Ansys Parametric Design Language (APDL) using the software multi-physics ANSYS. The mobile source of heat by welding has been represented by a Gaussian profile whose parameters have been calibrated to optimize the geometric shape of the cord. To do this, the surface of Response of a factorial experiment plan was used. The numerical results obtained are quite satisfactory since the parameters of the Gaussian heat source identified using the factorial experiment planallow a faithful reproduction of the geometry of the cord. The comparison between the experimental values ​​and Calculated deviation also shows good consistency with a relative difference of less than 5%. In order to study the voltage and the electrical conductivity during the priming and the maintenance of the welding arc, a Two-dimensional axisymmetric model of the electric arc was realized using FLUENT software. Geometry actual torch components such as the gas diffuser, the nozzle and the electrode were taken into account. The model integrates a fluid-structure coupling in which the electromagnetic and thermal equations are resolved in the solid cathode. The additional equations governing the flow are considered in the gaseous domain where the arc is generated. For the maintenance of the arc, these equations, which have been programmed in C ++, make it possible to overcome the artificial conductivity often used in the literature. The model allows to obtain the plasma temperature fields, the voltage drops at the anode and at the cathode of the welding, the voltage in the arc as well as the efficiency of the energy input. Numerical results indicate that plasma temperature and flow velocity increase with the intensity of the current and with the inter-electrode distance. The same goes for the electric potential but with a stronger influence of the inter-electrode distance. Finally, the gas flow plays no role on the temperature and on the electric potential. It influences the speed of flow of the plasma. The higher the flow, the higher the Plasma flow rate is low.; Cette thèse est consacrée au développement d'outils de simulation numérique permettant d'appréhender les phénomènes multi-physiques complexes (thermique, mécanique des solides, mécanique des fluides et sciences des matériaux) mis en jeu lors d'opérations de soudage TIG (Tungsten Inert Gas) de tôles minces de type 316L utilisées dans l'industrie agroalimentaire. La fusion locale des éléments à assembler par soudage présente en effet l'inconvénient d'induire des déformations locales importantes qui compliquent le montage des pièces. Un autre désavantage est l'apparition de contraintes résiduelles qui impactent la durabilité de la structure soudée. Afin de prédire ces déformations et contraintes pendant la phase de conception, en vue par exemple de les minimiser en jouant sur des paramètres tels que la vitesse d'exécution et l'intensité du courant de soudage, des outils numériques prédictifs ont été développés dans le cadre de ce travail.Un modèle éléments finis 3D de couplage entre la thermique et la mécanique, dans les domaines transitoire et nonlinéaire,a notamment été programmé en langage APDL (Ansys Parametric Design Language) à l'aide du logiciel multi-physique ANSYS. La source mobile de chaleur par soudage a été représentée par un profil Gaussien dont les paramètres ont été calibrés de manière à optimiser la forme géométrique du cordon. Pour ce faire, la surface de réponse d'un plan d'expérience factoriel a été utilisée. Les résultats numériques obtenus sont tout à fait satisfaisants puisque les paramètres de la source de chaleur gaussienne identifiés à l'aide du plan d'expérience factoriel permettent une reproduction fidèle de la géométrie du cordon. La comparaison entre les valeurs expérimentales et calculées de la déviation montre par ailleurs une bonne cohérence avec un écart relatif inférieur à 5%. Afin d'étudier la tension et la conductibilité électrique lors de l'amorçage et du maintien de l'arc de soudure, un modèle axisymétrique bidimensionnel de l'arc électrique a été réalisé en utilisant le logiciel FLUENT. La géométrie réelle des composantes de la torche telles que le diffuseur de gaz, la buse et l'électrode a été prise en compte. Lemodèle intègre un couplage fluide-structure dans lequel les équations électromagnétiques et thermiques sont résolues dans la cathode solide. Les équations supplémentaires régissant l'écoulement sont considérées dans le domaine gazeux où l'arc est généré. Pour le maintien de l'arc, ces équations, qui ont été programmées en langage C++, permettent de s'affranchir de la conductibilité artificielle souvent utilisée dans la littérature. Le modèle permet d'obtenir les champs de température du plasma, les chutes de tension à l'anode et à la cathode de l'appareil de soudage, la tension dans l'arc ainsi que le rendement de l'apport d'énergie. Les résultats numériques indiquent que la température et la vitesse d'écoulement du plasma augmentent avecl'intensité du courant et avec la distance inter électrode. Il en va de même pour le potentiel électrique mais avec une influence plus forte de la distance inter électrode. Enfin, le débit de gaz ne joue aucun rôle sur la température et sur le potentiel électrique. Il influe par contre sur la vitesse d'écoulement du plasma. Plus le débit est élevé, plus la vitesse d'écoulement du plasma est faible.

This thesis is dedicated to the development of numerical simulation tools allowing to understand complex multi-physics phenomena (thermal, solid mechanics, fluid mechanics and sciences materials) involved in TIG (Tungsten Inert Gas) welding operations of 316L thin plate used in the food industry. The local fusion of the elements to be assembled by welding has indeedthe disadvantage of inducing significant local deformations that complicate the assembly of parts. Another The disadvantage is the appearance of residual stresses that impact the durability of the welded structure. In order to predict these deformations and constraints during the design phase, for example in order to minimize them in playing on parameters such as the speed of execution and the intensity of the welding current, digital tools Predictors have been developed as part of this work.A model finite elements 3D of coupling between the thermal one and the mechanics, in the transient and nonlinear domains,was programmed in Ansys Parametric Design Language (APDL) using the software multi-physics ANSYS. The mobile source of heat by welding has been represented by a Gaussian profile whose parameters have been calibrated to optimize the geometric shape of the cord. To do this, the surface of Response of a factorial experiment plan was used. The numerical results obtained are quite satisfactory since the parameters of the Gaussian heat source identified using the factorial experiment planallow a faithful reproduction of the geometry of the cord. The comparison between the experimental values ​​and Calculated deviation also shows good consistency with a relative difference of less than 5%. In order to study the voltage and the electrical conductivity during the priming and the maintenance of the welding arc, a Two-dimensional axisymmetric model of the electric arc was realized using FLUENT software. Geometry actual torch components such as the gas diffuser, the nozzle and the electrode were taken into account. The model integrates a fluid-structure coupling in which the electromagnetic and thermal equations are resolved in the solid cathode. The additional equations governing the flow are considered in the gaseous domain where the arc is generated. For the maintenance of the arc, these equations, which have been programmed in C ++, make it possible to overcome the artificial conductivity often used in the literature. The model allows to obtain the plasma temperature fields, the voltage drops at the anode and at the cathode of the welding, the voltage in the arc as well as the efficiency of the energy input. Numerical results indicate that plasma temperature and flow velocity increase with the intensity of the current and with the inter-electrode distance. The same goes for the electric potential but with a stronger influence of the inter-electrode distance. Finally, the gas flow plays no role on the temperature and on the electric potential. It influences the speed of flow of the plasma. The higher the flow, the higher the Plasma flow rate is low.; Cette thèse est consacrée au développement d'outils de simulation numérique permettant d'appréhender les phénomènes multi-physiques complexes (thermique, mécanique des solides, mécanique des fluides et sciences des matériaux) mis en jeu lors d'opérations de soudage TIG (Tungsten Inert Gas) de tôles minces de type 316L utilisées dans l'industrie agroalimentaire. La fusion locale des éléments à assembler par soudage présente en effet l'inconvénient d'induire des déformations locales importantes qui compliquent le montage des pièces. Un autre désavantage est l'apparition de contraintes résiduelles qui impactent la durabilité de la structure soudée. Afin de prédire ces déformations et contraintes pendant la phase de conception, en vue par exemple de les minimiser en jouant sur des paramètres tels que la vitesse d'exécution et l'intensité du courant de soudage, des outils numériques prédictifs ont été développés dans le cadre de ce travail.Un modèle éléments finis 3D de couplage entre la thermique et la mécanique, dans les domaines transitoire et nonlinéaire,a notamment été programmé en langage APDL (Ansys Parametric Design Language) à l'aide du logiciel multi-physique ANSYS. La source mobile de chaleur par soudage a été représentée par un profil Gaussien dont les paramètres ont été calibrés de manière à optimiser la forme géométrique du cordon. Pour ce faire, la surface de réponse d'un plan d'expérience factoriel a été utilisée. Les résultats numériques obtenus sont tout à fait satisfaisants puisque les paramètres de la source de chaleur gaussienne identifiés à l'aide du plan d'expérience factoriel permettent une reproduction fidèle de la géométrie du cordon. La comparaison entre les valeurs expérimentales et calculées de la déviation montre par ailleurs une bonne cohérence avec un écart relatif inférieur à 5%. Afin d'étudier la tension et la conductibilité électrique lors de l'amorçage et du maintien de l'arc de soudure, un modèle axisymétrique bidimensionnel de l'arc électrique a été réalisé en utilisant le logiciel FLUENT. La géométrie réelle des composantes de la torche telles que le diffuseur de gaz, la buse et l'électrode a été prise en compte. Lemodèle intègre un couplage fluide-structure dans lequel les équations électromagnétiques et thermiques sont résolues dans la cathode solide. Les équations supplémentaires régissant l'écoulement sont considérées dans le domaine gazeux où l'arc est généré. Pour le maintien de l'arc, ces équations, qui ont été programmées en langage C++, permettent de s'affranchir de la conductibilité artificielle souvent utilisée dans la littérature. Le modèle permet d'obtenir les champs de température du plasma, les chutes de tension à l'anode et à la cathode de l'appareil de soudage, la tension dans l'arc ainsi que le rendement de l'apport d'énergie. Les résultats numériques indiquent que la température et la vitesse d'écoulement du plasma augmentent avecl'intensité du courant et avec la distance inter électrode. Il en va de même pour le potentiel électrique mais avec une influence plus forte de la distance inter électrode. Enfin, le débit de gaz ne joue aucun rôle sur la température et sur le potentiel électrique. Il influe par contre sur la vitesse d'écoulement du plasma. Plus le débit est élevé, plus la vitesse d'écoulement du plasma est faible.

Bistability in magnetism has been extensively used, in particular to store information. Here we propose an alternative route by using tetrastable magnetic domains. Using numerical and analytical calculations we show that a spin chain with a canting angle of {\pi}/4 possesses four energy-equivalent states. We discuss the static properties of such chain such as the profile and the energy of the domain walls as they govern the relaxation of the magnetization. The realisation of such spin chain could enable the encoding of the information on four bits which is a potential alternative toward the increase of storage density., Comment: 4 pages, 5 figures, supplementary material available

International audience; Glioblastoma multiforme is a malignant brain tumor with poor prognosis and high morbidity due to its invasiveness. Hypoxia-driven motility and concentration-driven motility are two mechanisms of glioblastoma multiforme invasion in the brain. The use of anti-angiogenic drugs has uncovered new progression patterns of glioblastoma multiforme associated with significant differences in overall survival. Here, we apply a mathematical model of glioblas- toma multiforme growth and invasion in humans and design computational trials using agents that target angiogenesis, tumor replication rates, or motility. The findings link highly- dispersive, moderately-dispersive, and hypoxia-driven tumors to the patterns observed in glioblastoma multiforme treated by anti-angiogenesis, consisting of progression by Expand- ing FLAIR, Expanding FLAIR + Necrosis, and Expanding Necrosis, respectively. Further- more, replication rate-reducing strategies (e.g. Tumor Treating Fields) appear to be effective in highly-dispersive and moderately-dispersive tumors but not in hypoxia-driven tumors. The latter may respond to motility-reducing agents. In a population computational trial, with all three phenotypes, a correlation was observed between the efficacy of the rate- reducing agent and the prolongation of overall survival times. This research highlights the potential applications of computational trials and supports new hypotheses on glioblastoma multiforme phenotypes and treatment options.