Probabilistic combination of eigenlungs-based classifiers for COVID-19 diagnosis in chest CT images

The outbreak of the COVID-19 (Coronavirus disease 2019) pandemic has changed the world. According to the World Health Organization (WHO), there have been more than 100 million confirmed cases of COVID-19, including more than 2.4 million deaths. It is extremely important the early detection of the disease, and the use of medical imaging such as chest X-ray (CXR) and chest Computed Tomography (CCT) have proved to be an excellent solution. However, this process requires clinicians to do it within a manual and time-consuming task, which is not ideal when trying to speed up the diagnosis. In this work, we propose an ensemble classifier based on probabilistic Support Vector Machine (SVM) in order to identify pneumonia patterns while providing information about the reliability of the classification. Specifically, each CCT scan is divided into cubic patches and features contained in each one of them are extracted by applying kernel PCA. The use of base classifiers within an ensemble allows our system to identify the pneumonia patterns regardless of their size or location. Decisions of each individual patch are then combined into a global one according to the reliability of each individual classification: the lower the uncertainty, the higher the contribution. Performance is evaluated in a real scenario, yielding an accuracy of 97.86%. The large performance obtained and the simplicity of the system (use of deep learning in CCT images would result in a huge computational cost) evidence the applicability of our proposal in a real-world environment.Comment: 15 pages, 9 figure

Brain structures identification based on feature descriptor

Traumatic Brain Injury -TBI- -1- is defined as an acute event that causes certain damage to areas of the brain. TBI may result in a significant impairment of an individuals physical, cognitive and psychosocial functioning. The main consequence of TBI is a dramatic change in the individuals daily life involving a profound disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges of TBI Neuroimaging is to develop robust automated image analysis methods to detect signatures of TBI, such as: hyper-intensity areas, changes in image contrast and in brain shape. The final goal of this research is to develop a method to identify the altered brain structures by automatically detecting landmarks on the image where signal changes and to provide comprehensive information to the clinician about them. These landmarks identify injured structures by co-registering the patient?s image with an atlas where landmarks have been previously detected. The research work has been initiated by identifying brain structures on healthy subjects to validate the proposed method. Later, this method will be used to identify modified structures on TBI imaging studies

Validation of a Questionnaire to Assess the Perception of Women with Atopic Dermatitis in Family Planning

Introduction: Atopic dermatitis (AD) is a highly frequent chronic inflammatory skin disease. It is important to know how women with AD approach family planning together with their disease. The aim of the present research is to develop and validate a questionnaire for women diagnosed with AD in order to measure their level of desire and gestational information. Materials and Methods: A multicenter cross-sectional study was conducted. Women between 18 and 45 years old with mild, moderate, and severe forms of the disease were included and disease-free controls. An exploratory factorial analysis of the primary components and varimax rotation was used to measure the validity of the construct. Cronbach’s α was used to measure the reliability of the individual scales and the global questionnaire. Results: In total, 150 valid questionnaires were included. The final questionnaire consisted of 23 items that converged on six factors. The six scales had adequate reliability: “Pregnancy” (Cronbach’s alpha = 0.95), “Conception” (Cronbach’s alpha = 0.93), “Concern- information” (Cronbach’s alpha = 0.82), “Breastfeeding” (Cronbach’s alpha = 0.81), “Sexual life” (Cronbach’s alpha = 0.79), and “Family planning” (Cronbach’s alpha = 0.67). The total Cronbach’s alpha of the questionnaire was 0.94. Discussion: This questionnaire is the first specific measurement instrument developed for women with AD of childbearing age that has demonstrated adequate levels of reliability and construct validity. We consider it useful and valuable to study aspects such as family planning in this patient profile, and that can influence their decision to have offsprin

Immunotherapy moves to the early-stage setting in non-small cell lung cancer: emerging evidence and the role of biomarkers

Despite numerous advances in targeted therapy and immunotherapy in the last decade, lung cancer continues to present the highest mortality rate of all cancers. Targeted therapy based on specific genomic alterations, together with PD-1 and CTLA-4 axis blocking-based immunotherapy, have significantly improved survival in advanced non-small cell lung cancer (NSCLC) and both therapies are now well-established in this clinical setting. However, it is time for immunotherapy to be applied in patients with early-stage disease, which would be an important qualitative leap in the treatment of lung cancer patients with curative intent. Preliminary data from a multitude of studies are highly promising, but therapeutic decision-making should be guided by an understanding of the molecular features of the tumour and host. In the present review, we discuss the most recently published studies and ongoing clinical trials, controversies, future challenges and the role of biomarkers in the selection of best therapeutic options

Fish sentience denial: Muddying the waters

Recent empirical studies have reported evidence that many aquatic species, including fish, cephalopods and crustaceans, have the capacity for nociception and pain, and that their welfare should be taken into consideration. Some sceptics, rejecting the precautionary principle, have denied that any study demonstrates pain or other aspects of sentience in fish. This target article discusses some of the scientific shortcomings of these critiques through a detailed analysis of a study exploring nociception and analgesia in larval zebrafish

Obstructive Sleep Apnoea Syndrome, Endothelial Function and Markers of Endothelialization. Changes after CPAP

Study objectives This study tries to assess the endothelial function in vivo using flow-mediated dilatation (FMD) and several biomarkers of endothelium formation/restoration and damage in patients with obstructive sleep apnoea (OSA) syndrome at baseline and after three months with CPAP therapy. Design Observational study, before and after CPAP therapy. Setting and Patients We studied 30 patients with apnoea/hypopnoea index (AHI) > 15/h that were compared with themselves after three months of CPAP therapy. FMD was assessed non-invasively in vivo using the Laser-Doppler flowmetry. Circulating cell-free DNA (cf-DNA) and microparticles (MPs) were measured as markers of endothelial damage and the vascular endothelial growth factor (VEGF) was determined as a marker of endothelial restoration process. Measurements and results After three month with CPAP, FMD significantly increased (1072.26 +/- 483.21 vs. 1604.38 +/- 915.69 PU, p<0.005) cf-DNA and MPs significantly decreased (187.93 +/- 115.81 vs. 121.28 +/- 78.98 pg/ml, p<0.01, and 69.60 +/- 62.60 vs. 39.82 +/- 22.14 U/mu L, p<0.05, respectively) and VEGF levels increased (585.02 +/- 246.06 vs. 641.11 +/- 212.69 pg/ml, p<0.05). These changes were higher in patients with more severe disease. There was a relationship between markers of damage (r = -0.53, p< 0.005) but not between markers of damage and restoration, thus suggesting that both types of markers should be measured together. Conclusions CPAP therapy improves FMD. This improvement may be related to an increase of endothelial restoration process and a decrease of endothelial damage

Hypertriglyceridemia Influences the Degree of Postprandial Lipemic Response in Patients with Metabolic Syndrome and Coronary Artery Disease: From the Cordioprev Study

Objective To determine whether metabolic syndrome traits influence the postprandial lipemia response of coronary patients, and whether this influence depends on the number of MetS criteria. Materials and Methods 1002 coronary artery disease patients from the CORDIOPREV study were submitted to an oral fat load test meal with 0.7 g fat/kg body weight (12% saturated fatty acids, 10% polyunsaturated fatty acids, 43% monounsaturated fatty acids), 10% protein and 25% carbohydrates. Serial blood test analyzing lipid fractions were drawn at 0, 1, 2, 3 and 4 hours during the postprandial state. Total and incremental area under the curves of the different postprandial parameters were calculated following the trapezoid rule to assess the magnitude of change during the postprandial state Results Postprandial lipemia response was directly related to the presence of metabolic syndrome. We found a positive association between the number of metabolic syndrome criteria and the response of postprandial plasma triglycerides (p<0.001), area under the curve of triglycerides (p<0.001) and incremental area under the curve of triglycerides (p<0.001). However, the influence of them on postprandial triglycerides remained statistically significant only in those patients without basal hypertriglyceridemia. Interestingly, in stepwise multiple linear regression analysis with the AUC of triglycerides as the dependent variable, only fasting triglycerides, fasting glucose and waist circumference appeared as significant independent (P<0.05) contributors. The multiple lineal regression (R) was 0.77, and fasting triglycerides showed the greatest effect on AUC of triglycerides with a standardized coefficient of 0.75. Conclusions Fasting triglycerides are the major contributors to the postprandial triglycerides levels. MetS influences the postprandial response of lipids in patients with coronary heart disease, particularly in non-hypertriglyceridemic patients

Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury

The number and grade of injured neuroanatomic structures and the type of injury determine the degree of impairment after a brain injury event and the recovery options of the patient. However, the body of knowledge and clinical intervention guides are basically focused on functional disorder and they still do not take into account the location of injuries. The prognostic value of location information is not known in detail either. This paper proposes a feature-based detection algorithm, named Neuroanatomic-Based Detection Algorithm (NBDA), based on SURF (Speeded Up Robust Feature) to label anatomical brain structures on cortical and sub-cortical areas. Themain goal is to register injured neuroanatomic structures to generate a database containing patient?s structural impairment profile. This kind of information permits to establish a relation with functional disorders and the prognostic evolution during neurorehabilitation procedures