Dense breast on screening mammography: utility and futility of additional ultrasound.

High breast density decreases the sensitivity of mammography. Regardless of masking effect, it is also a stronger predictor for breast cancer than most other risk factors, including family history. Up to 50% of women have dense breast (categories C+D). The relative risk is 2.1 to 2.3 in women with extremely dense breast (category d). There is little consensus on the potential need of additional measures. Breast Ultrasound (US) may be proposed as an adjunctive test, as it is non-invasive and non-irradiating. Since 2012, our program for breast cancer screening propose to realise an additional US to the women with category d breasts. An evaluation of the data of the first year showed that less 50% of the women act upon the recommendation. In spite of the low compliance supplementary cancers were found. Since, no more evaluation was performed. The aim of this study was: To evaluate the effect of the recommendation in term of additional cancer's identification, additional biopsies and additional investigations. To identify the reasons of non compliance

Analysis of Endothelial Protein C Receptor Functionality on Living Cells’

Activated protein C (APC) is a major control system of blood coagulation. APC prevents coagulation pathway by degrading Va and VIIIa plasma’s coagulation factors. Protein C activation requires its binding to specific endothelial cell receptor (EPCR). APC binding to EPCR also activates a wide range of defense mechanisms (anti-inflammatory, antiapoptosis…). EPCR expression by cells can be detected by various methods, including immunoanalysis and molecular biology. However, no assays evaluate its functionality. A method, inspired of a standard fibrinoformation time assay, was developed to estimate EPCR ability to bind APC on living cell surface in vitro. Endothelial cells were incubated with APC and fibrinoformation on cells was followed by spectrophotometry (plasma absorbance increases with fibrin polymerization). Membrane-bound EPCR retain APC, thus prolonging fibrinoformation time in a dose-dependent manner. Control was realized with EPCR-negative cells. This new method can be used on any cell type to study the expression of other coagulation receptors

Establishment and characterization of three cell lines from Aedes triseriatus (Diptera : Culicidae)

International audienc

Reply to Dr. Takeuchi: PRES after epidural anesthesia

[No abstract available

Convolutional Neural Network for Material Decomposition in Spectral CT Scans

Spectral computed tomography acquires energy-resolved data that allows recovery of densities of constituents of an object. This can be achieved by decomposing the measured spectral projection into material projections, and passing these decomposed projections through a tomographic reconstruction algorithm, to get the volumetric mass density of each material. Material decomposition is a nonlinear inverse problem that has been traditionally solved using model-based material decomposition algorithms. However, the forward model is difficult to estimate in real prototypes. Moreover, the traditional regularizers used to stabilized inversions are not fully relevant in the projection domain.In this study, we propose a deep-learning method for material decomposition in the projection domain. We validate our methodology with numerical phantoms of human knees that are created from synchrotron CT scans. We consider four different scans for training, and one for validation. The measurements are corrupted by Poisson noise, assuming that at most 10 5 photons hit the detector. Compared to a regularized Gauss-Newton algorithm, the proposed deep-learning approach provides a compromise between noise and resolution, which reduces the computation time by a factor of 100

Material Decomposition in Spectral CT using deep learning: A Sim2Real transfer approach

The state-of-the art for solving the nonlinear material decomposition problem in spectral computed tomography is based on variational methods, but these are computationally slow and critically depend on the particular choice of the regularization functional. Convolutional neural networks have been proposed for addressing these issues. However, learning algorithms require large amounts of experimental data sets. We propose a deep learning strategy for solving the material decomposition problem based on a U-Net architecture and a Sim2Real transfer learning approach where the knowledge that we learn from synthetic data is transferred to a real-world scenario. In order for this approach to work, synthetic data must be realistic and representative of the experimental data. For this purpose, numerical phantoms are generated from human CT volumes of the KiTS19 Challenge dataset, segmented into specific materials (soft tissue and bone). These volumes are projected into sinogram space in order to simulate photon counting data, taking into account the energy response of the scanner. We compared projection- and image-based decomposition approaches where the network is trained to decompose the materials either in the projection or in the image domain. The proposed Sim2Real transfer strategies are compared to a regularized Gauss-Newton (RGN) method on synthetic data, experimental phantom data and human thorax data

Diffuse optical tomography by using time-resolved single pixel camera

International audienc

Ten-year changes in colorectal cancer screening in Switzerland: The Swiss Health Interview Survey 2007, 2012 and 2017

Recent recommendations for colorectal cancer (CRC) screening suggest fecal occult blood test (FOBT) or colonoscopy. Since 2013, mandatory health insurance in Switzerland reimburse CRC screening. We set out to determine if CRC testing rate and type of CRC screening changed in Switzerland from 2007 to 2017 and between the three main language regions. We extracted data on 50–75-year-olds from the Swiss Health Interview Survey (SHIS) 2007, 2012 and 2017 to determine rates of self-reported testing with FOBT within last 2 years and colonoscopy within last 10 years. We estimated prevalence ratio (PR) in multivariate-adjusted logistic regression models and compared rates in German-, French- and Italian-speaking regions, adjusting for sociodemographic, self-rated health and insurance variables. Overall testing rates (FOBT or colonoscopy) increased in all regions from 2007 to 2017 (German-speaking 33.6% to 48.3%; French-speaking 30.8% to 48.8%; Italian-speaking 37.9% to 46.8%), mainly because of an increase in colonoscopy rate for screening reasons (p < 0.001 in all regions). Rates of FOBT testing fell significantly in the German-speaking region (11.9% to 4.4%, p < 0.001), but not in the Italian- (13.9% to 8.5%, p = 0.052) and French-speaking regions (7.6% to 7.4%, p = 0.138). Overall CRC testing rate rose from 33.2% in 2007 to 48.4% in 2017, mainly because of an increase of colonoscopy rate for screening reasons. Coverage remains below the 65% target of European guidelines. Organized screening programs encouraging FOBT screening could contribute to further increasing the CRC testing rate

Change in colorectal cancer (CRC) testing rates associated with the introduction of the first organized screening program in canton Uri, Switzerland: Evidence from insurance claims data analyses from 2010 to 2018

The first canton in Switzerland to implement an organized colorectal cancer screening program (OSP) was Uri. Starting in 2013, it offered 50–69-year-olds free testing with colonoscopy every 10 years or fecal occult blood test (FOBT) every 2 years. We tested the association between the OSP and testing rates over time. We analyzed claims data of 50–69-year-olds from Uri and neighboring cantons (NB) provided by a large health insurance and complemented it with data from the OSP. We fitted multivariate adjusted logistic regression models to compare overall testing rates and by method (colonoscopy or FOBT/both) We computed the 2018 rate of the population up-to-date with testing (colonoscopy within 9 years/FOBT within 2 years). Yearly overall testing rates in Uri increased from 8.7% in 2010 to 10.8% in 2018 and from 6.5% to 7.9% in NB. In Uri, the proportion tested with FOBT/both increased from 4.7% to 6.0% but decreased from 2.8% to 1.1% in NB. Testing by FOBT/both increased more between 2015 and 2018 than 2010–2012 in Uri than in NB (OR:2.1[95%CI:1.8–2.4]), it increased less for colonoscopy (OR:0.60[95%CI:0.51–0.70]), with no change in overall CRC testing (OR:0.91[95%CI:0.81–1.02]). In 2018 in Uri, 42.5% were up-to-date with testing (FOBT/both:9.2%, colonoscopy:35.7%); in NBs, 40.7% (FOBT/both:2.7%, colonoscopy:39%). Yearly FOBT rates in Uri were always higher than in NB. Though the OSP in Uri was not associated with a greater increase in overall testing rates, the OSP was associated with increased FOBT