Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions

The aim of the study was to estimate the diagnostic accuracy of textural, morpho- logical and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy for benign lesions. In total, 91 samples of 85 patients were ana- lyzed. Furthermore, 48 textural metrics, 15 morphological and 81 dynamic parameters were extracted by manually segmenting regions of interest. Statistical analyses including univariate and multivari- ate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. Results: The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance (accuracy (ACC) = 0.78; AUC = 0.78) was reached with all 48 metrics and an LDA trained with balanced data. The best performance (ACC = 0.75; AUC = 0.80) using morphological features was reached with an SVM trained with 10-fold cross-variation (CV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of five robust morphological features (circularity, rectangularity, sphericity, gleaning and surface). The best performance (ACC = 0.82; AUC = 0.83) using dynamic features was reached with a trained SVM and balanced data (with ADASYN function). Conclusion: Multivariate analyses using pattern recognition approaches, including all morphological, textural and dynamic features, optimized by adaptive synthetic sampling and feature selection operations obtained the best results and showed the best performance in the discrimination of benign and malignant lesions

Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification.

To compare diagnostic performance of contrast-enhanced dual-energy digital mammography (CEDM) and digital breast tomosynthesis (DBT) alone and in combination compared to 2D digital mammography (MX) and dynamic contrast-enhanced MRI (DCE-MRI) in women with breast lesions. We enrolled 100 consecutive patients with breast lesions (BIRADS 3-5 at imaging or clinically suspicious). CEDM, DBT, and DCE-MRI 2D were acquired. Synthetized MX was obtained by DBT. A total of 134 lesions were investigated on 111 breasts of 100 enrolled patients: 53 were histopathologically proven as benign and 81 as malignant. Nonparametric statistics and receiver operating characteristic (ROC) curve were performed. Two-dimensional synthetized MX showed an area under ROC curve (AUC) of 0.764 (sensitivity 65%, specificity 80%), while AUC was of 0.845 (sensitivity 80%, specificity 82%) for DBT, of 0.879 (sensitivity 82%, specificity 80%) for CEDM, and of 0.892 (sensitivity 91%, specificity 84%) for CE-MRI. DCE-MRI determined an AUC of 0.934 (sensitivity 96%, specificity 88%). Combined CEDM with DBT findings, we obtained an AUC of 0.890 (sensitivity 89%, specificity 74%). A difference statistically significant was observed only between DCE-MRI and CEDM (P = .03). DBT, CEDM, CEDM combined to tomosynthesis, and DCE-MRI had a high ability to identify multifocal and bilateral lesions with a detection rate of 77%, 85%, 91%, and 95% respectively, while 2D synthetized MX had a detection rate for multifocal lesions of 56%. DBT and CEDM have superior diagnostic accuracy of 2D synthetized MX to identify and classify breast lesions, and CEDM combined with DBT has better diagnostic performance compared with DBT alone. The best results in terms of diagnostic performance were obtained by DCE-MRI. Dynamic information obtained by time-intensity curve including entire phase of contrast agent uptake allows a better detection and classification of breast lesions

Physical activity and risk of Metabolic Syndrome in an urban Mexican cohort

Abstract Background In the Mexican population metabolic syndrome (MS) is highly prevalent. It is well documented that regular physical activity (PA) prevents coronary diseases, type 2 diabetes and MS. Most studies of PA have focused on moderate-vigorous leisure-time activity, because it involves higher energy expenditures, increase physical fitness, and decrease the risk of MS. However, for most people it is difficult to get a significant amount of PA from only moderately-vigorous leisure activity, so workplace activity may be an option for working populations, because, although may not be as vigorous in terms of cardio-respiratory efforts, it comprises a considerable proportion of the total daily activity with important energy expenditure. Since studies have also documented that different types and intensity of daily PA, including low-intensity, seem to confer important health benefits such as prevent MS, we sought to assess the impact of different amounts of leisure-time and workplace activities, including low-intensity level on MS prevention, in a sample of urban Mexican adults. Methods The study population consisted of 5118 employees and their relatives, aged 20 to 70 years, who were enrolled in the baseline evaluation of a cohort study. MS was assessed according to the criteria of the National Cholesterol Education Program, ATP III and physical activity with a validated self-administered questionnaire. Associations between physical activity and MS risk were assessed with multivariate logistic regression models. Results The prevalence of the components of MS in the study population were: high glucose levels 14.2%, high triglycerides 40.9%, high blood pressure 20.4%, greater than healthful waist circumference 43.2% and low-high density lipoprotein 76.9%. The prevalence of MS was 24.4%; 25.3% in men and 21.8% in women. MS risk was reduced among men (OR 0.72; 95%CI 0.57–0.95) and women (OR 0.78; 95%CI 0.64–0.94) who reported an amount of ≥30 minutes/day of leisure-time activity, and among women who reported an amount of ≥3 hours/day of workplace activity (OR 0.75; 95%CI 0.59–0.96). Conclusion Our results indicate that both leisure-time and workplace activity at different intensity levels, including low-intensity significantly reduce the risk of MS. This finding highlights the need for more recommendations regarding the specific amount and intensity of leisure-time and workplace activity needed to prevent MS

Vitamin B12 in Cats: Nutrition, Metabolism, and Disease

Cobalamin is a water-soluble molecule that has an important role in cellular metabolism, especially in DNA synthesis, methylation, and mitochondrial metabolism. Cobalamin is bound by intrinsic factor (IF) and absorbed in the ileal tract. The IF in cats is synthesized exclusively by pancreatic tissue. About 75% of the total plasma cobalamin in cats is associated with transcobalamin II, while in this species, transcobalamin I is not present. In cats, the half-life of cobalamin is 11–14 days. Diagnostic biomarkers for B12 status in cats include decreased levels of circulating total cobalamin and increased levels of methylmalonic acid. The reference interval for serum cobalamin concentrations in cats is 290–1500 ng/L, and for the serum methylmalonic acid concentration, it is 139–897 nmol/L. Therapy for hypocobalaminemia mainly depends on the underlying disease. In some cases, subcutaneous or intramuscular injection of 250 μg/cat is empirically administered. In recent years, it has been demonstrated that oral cobalamin supplementation can also be used successfully in dogs and cats as a less invasive alternative to parental administration. This review describes the current knowledge regarding B12 requirements and highlights improvements in diagnostic methods as well as the role of hypocobalaminemia in its associated diseases

Early Life Factors and Inter-Country Heterogeneity in BMI Growth Trajectories of European Children : The IDEFICS Study

Background Starting from birth, this explorative study aimed to investigate between-country differences in body mass index (BMI) trajectories and whether early life factors explain these differences. Methods The sample included 7,644 children from seven European countries (Belgium, Cyprus, Germany, Hungary, Italy, Spain, Sweden) participating in the multi-centre IDEFICS study. Information on early life factors and in total 53,409 repeated measurements of height and weight from 0 to <12 years of age were collected during the baseline (2007/2008) and follow-up examination (2009/2010) supplemented by records of routine child health visits. Country-specific BMI growth curves were estimated using fractional polynomial mixed effects models. Several covariates focussing on early life factors were added to the models to investigate their role in the between-countries differences. Results Large between-country differences were observed with Italian children showing significantly higher mean BMI values at all ages ≥ 3 years compared to the other countries. For instance, at age 11 years mean BMI values in Italian boys and girls were 22.3 [21.9;22.8; 99% confidence interval] and 22.0 [21.5;22.4], respectively, compared to a range of 18.4 [18.1;18.8] to 20.3 [19.8;20.7] in boys and 18.2 [17.8;18.6] to 20.3 [19.8;20.7] in girls in the other countries. After adjustment for early life factors, differences between country-specific BMI curves became smaller. Maternal BMI was the factor being most strongly associated with BMI growth (p<0.01 in all countries) with associations increasing during childhood. Gestational weight gain (GWG) was weakly associated with BMI at birth in all countries. In some countries, positive associations between BMI growth and children not being breastfed, mothers’ smoking during pregnancy and low educational level of parents were found. Conclusion Early life factors seem to explain only some of the inter-country variation in growth. Maternal BMI showed the strongest association with children’s BMI growth

Effect estimates and 99% confidence intervals of the covariate-adjusted growth models for BMI for the seven countries.

<p>Continuous variables were centred to receive meaningful effect estimates (mother’s BMI centred at 20 kg/m², mother’s age at birth centred at 30 years, gestational weight gain centred at 10 kg).</p

Predicted BMI growth trajectories of children having parents with high (ISCED 5,6; solid) vs. low educational level (ISCED 0,1,2; dashed) by sex (girls: black; boys: grey) and country; all other covariates were set to a constant value (continuous covariates were set to 0 (i.e. to the value used for centring), categorical variables were set to the reference category).

<p>Predicted BMI growth trajectories of children having parents with high (ISCED 5,6; solid) vs. low educational level (ISCED 0,1,2; dashed) by sex (girls: black; boys: grey) and country; all other covariates were set to a constant value (continuous covariates were set to 0 (i.e. to the value used for centring), categorical variables were set to the reference category).</p