An automatic deep learning approach for coronary artery calcium segmentation

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed tomography (CT) images. The proposed system uses a supervised deep learning algorithm, i.e. convolutional neural network (CNN) for the segmentation and classification of candidate lesions as coronary or not, previously extracted in the region of the heart using a cardiac atlas. We trained our network with 45 CT volumes; 18 volumes were used to validate the model and 56 to test it. Individual lesions were detected with a sensitivity of 91.24%, a specificity of 95.37% and a positive predicted value (PPV) of 90.5%; comparing calcium score obtained by the system and calcium score manually evaluated by an expert operator, a Pearson coefficient of 0.983 was obtained. A high agreement (Cohen's k = 0.879) between manual and automatic risk prediction was also observed. These results demonstrated that convolutional neural networks can be effectively applied for the automatic segmentation and classification of coronary calcifications

Nuove specie minerali al Somma-Vesuvio: wulfenite

To the 247 species, of which 20 are doubtful, occurring at the Somma-Vesuvius volcanic complex, after the recent updating of the fluoro-edenite (despite the collecting ban) it has to be added the identification of a new common species, never occurred before. A sample belonging to Luigi Chiappino, found in 1989 at San Vito quarry, Ercolano, Napoli, was analyzed through SEM-EDX and the analysis identified the wulfenite on massive galena, as millimetrical, bipyramidal crystals, resinous, of yellow-orange colour, associated with calcite, cerussite and sphalerite

Current therapeutic strategies for advanced pancreatic cancer: A review for clinicians

Pancreatic cancer (PC) would become the second leading cause of cancer death in the near future, despite representing only 3% of new cancer diagnosis. Survival improvement will come from a better knowledge of risk factors, earlier diagnosis, better integration of locoregional and systemic therapies, as well as the development of more efficacious drugs rising from a deeper understanding of disease biology. For patients with unresectable, non-metastatic disease, combined strategies encompassing primary chemotherapy and radiation seems to be promising. In fit patients, new polychemotherapy regimens can lead to better outcomes in terms of slight but significant survival improvement associated with a positive impact on quality of life. The upfront use of these regimes can also increase the rate of radical resections in borderline resectable and locally advanced PC. Second line treatments showed to positively affect both overall survival and quality of life in fit patients affected by metastatic disease. At present, oxaliplatin-based regimens are the most extensively studied. Nonetheless, other promising drugs are currently under evaluation. Presently, in addition to surgery and conventional radiation therapy, new locoregional treatment techniques are emerging as alternative options in the multimodal approach to patients or diseases not suitable for radical surgery. As of today, in contrast with other types of cancer, targeted therapies failed to show relevant activity either alone or in combination with chemotherapy and, thus, current clinical practice does not include them. Up to now, despite the fact of extremely promising results in different tumors, also immunotherapy is not in the actual therapeutic armamentarium for PC. In the present paper, we provide a comprehensive review of the current state of the art of clinical practice and research in PC aiming to offer a guide for clinicians on the most relevant topics in the management of this disease

Patient Perceptions and Knowledge of Ionizing Radiation from Medical Imaging

Importance: Although imaging has become a standard tool of modern medicine, its widespread use has been paralleled by an increasing cumulative radiation dose to patients despite technological advancements and campaigns calling for better awareness and minimization of unnecessary exposures. Objective: To assess patients' knowledge about medical radiation and related risks. Design, Setting, and Participants: A survey study of hospitals in Italy was conducted; all patients in waiting rooms for medical imaging procedures before undergoing imaging examinations at 16 teaching and nonteaching hospitals were approached to take the survey. The survey was performed from June 1, 2019, to May 31, 2020. Main Outcomes and Measures: Survey respondents' basic knowledge of ionizing radiation levels and health risks, earlier imaging tests performed, and information and communication about radiation protection issues. Results: Among 3039 patients invited to participate, the response rate was 94.3% (n = 2866). Participants included 1531 women (53.4%); mean (SD) age was 44.9 (17.3) years. Of the 2866 participants, 1529 (53.3%) were aware of the existence of natural sources of ionizing radiation. Mammography (1101 [38.4%]) and magnetic resonance imaging (1231 [43.0%]) were categorized as radiation-based imaging modalities. More than half of the 2866 patients (1579 [55.1%]; P =.03) did not know that chest computed tomography delivers a larger dose of radiation than chest radiography, and only 1499 (52.3%) knew that radiation can be emitted after nuclear medicine examinations (P =.004). A total of 667 patients (23.3%) believed that radiation risks were unrelated to age, 1273 (44.4%) deemed their knowledge about radiation risks inadequate, and 2305 (80.4%) preferred to be informed about radiation risks by medical staff. A better knowledge of radiation issues was associated with receiving information from health care professionals (odds ratio [OR], 1.71; 95% CI, 1.43-2.03; P <.001) and having a higher educational level (intermediate vs low: OR, 1.48; 95% CI, 1.17-1.88; P <.001; high vs low: OR, 2.68; 95% CI, 2.09-3.43; P <.001). Conclusions and Relevance: The results of this survey suggest that patients undergoing medical imaging procedures have overall limited knowledge about medical radiation. Intervention to achieve better patient awareness of radiation risks related to medical exposures may be beneficial

Bio-inspired relevant interaction modelling in cognitive crowd management

Cognitive algorithms, integrated in intelligent systems, represent an important innovation in designing interactive smart environments. More in details, Cognitive Systems have important applications in anomaly detection and management in advanced video surveillance. These algorithms mainly address the problem of modelling interactions and behaviours among the main entities in a scene. A bio-inspired structure is here proposed, which is able to encode and synthesize signals, not only for the description of single entities behaviours, but also for modelling cause–effect relationships between user actions and changes in environment configurations. Such models are stored within a memory (Autobiographical Memory) during a learning phase. Here the system operates an effective knowledge transfer from a human operator towards an automatic systems called Cognitive Surveillance Node (CSN), which is part of a complex cognitive JDL-based and bio-inspired architecture. After such a knowledge-transfer phase, learned representations can be used, at different levels, either to support human decisions, by detecting anomalous interaction models and thus compensating for human shortcomings, or, in an automatic decision scenario, to identify anomalous patterns and choose the best strategy to preserve stability of the entire system. Results are presented in a video surveillance scenario , where the CSN can observe two interacting entities consisting in a simulated crowd and a human operator. These can interact within a visual 3D simulator, where crowd behaviour is modelled by means of Social Forces. The way anomalies are detected and consequently handled is demonstrated, on synthetic and also on real video sequences, in both the user-support and automatic modes

The calculation of the cardiac troponin T 99th percentile of the reference population is affected by age, gender, and population selection: A multicenter study in Italy.

Background: The aim of this study is to determine the 99th upper-reference limit (URL) for cardiac troponin T (cTnT) in Italian apparently healthy subjects. Methods: The reference population was selected from 5 cities: Bolzano (n = 290), Milano (CAMELIA-Study, n = 287), Montignoso (MEHLP-Study, n = 306), Pisa (n = 182), and Reggio Calabria (MAREA-Study, n = 535). Subjects having cardiac/systemic acute/chronic diseases were excluded. Participants to MEHLP project underwent cardiac imaging investigation. High-sensitive cTnT was measured with Cobas-e411 (Roche Diagnostics). Results: We enrolled 1600 healthy subjects [54.6%males; age range 10–90 years; mean (SD): 36.4 (21.2) years], including 34.6% aged b20 years, 54.5% between 20 and 64 years, and 10.9% over 65 years. In the youngest the 99th URL was 10.9 ng/L in males and 6.8 ng/L in females; in adults 23.2 ng/L and 10.2 ng/L; and in elderly 36.8 ng/L and 28.6 ng/L. After the exclusion of outliers the 99th URL values were significantly decreased (P b 0.05) in particular those of the oldest (13.8 ng/L and 14 ng/L). MEHLP participants were divided in healthy and asymptomatic, according to known cardiovascular risk factors (HDL, LDL, glucose, C-reactive protein): the 99th URL of cTnT values of these subgroups was significantly different (19.5 vs. 22.7, P b 0.05). Conclusions: 99th URL of cTnT valueswas strongly affected by age, gender, selection of subjects and the statistical evaluation of outliers

From transformation to chronification of migraine: Pathophysiological and clinical aspects

Chronic migraine is a neurological disorder characterized by 15 or more headache days per month of which at least 8 days show typical migraine features. The process that describes the development from episodic migraine into chronic migraine is commonly referred to as migraine transformation or chronification. Ample studies have attempted to identify factors associated with migraine transformation fr

From transformation to chronification of migraine : pathophysiological and clinical aspects

Chronic migraine is a neurological disorder characterized by 15 or more headache days per month of which at least 8 days show typical migraine features. The process that describes the development from episodic migraine into chronic migraine is commonly referred to as migraine transformation or chronification. Ample studies have attempted to identify factors associated with migraine transformation from different perspectives. Understanding CM as a pathological brain state with trigeminovascular participation where biological changes occur, we have completed a comprehensive review on the clinical, epidemiological, genetic, molecular, structural, functional, physiological and preclinical evidence available