Sea Storm Analysis: Evaluation of Multiannual Wave Parameters Retrieved from HF Radar and Wave Model

Intense atmospheric disturbances, which impact directly on the sea surface causing a significant increase in wave height and sometimes strong storm surges, have become increasingly frequent in recent years in the Mediterranean Sea, producing extreme concern in highly populated coastal areas, such as the Gulf of Naples (Western Mediterranean Sea, Central Tyrrhenian Sea). In this work, fifty-six months of wave parameters retrieved by an HF radar network are integrated with numerical outputs to analyze the seasonality of extreme events in the study area and to investigate the performance of HF radars while increasing their distances from the coast. The model employed is the MWM (Mediterranean Wind-Wave Model), providing a wind-wave dataset based on numerical models (the hindcast approach) and implemented in the study area with a 0.03° spatial resolution. The integration and comparison with the MWM dataset, carried out using wave parameters and spectral information, allowed us to analyze the availability and accuracy of HF sampling during the investigated period. The statistical comparisons highlight agreement between the model and the HF radars during episodes of sea storms. The results confirm the potential of HF radar systems as long-term monitoring observation platforms, and allow us to give further indications on the seasonality of sea storms under different meteorological conditions and on their energy content in semi-enclosed coastal areas, such as the Gulf of Naples

Ulcerated hemosiderinic dyschromia and iron deposits within lower limbs treated with a topical application of biological chelator

The ulcerative haemosiderinic dyschromia of chronic venous insufficiency is difficult to heal and presents a high accumulation of iron. Lactoferrin, a potent natural iron chelator, could help to scar this ulcerative haemosi - derinic dyschromia. The objective of this study was to determine whether the topical application of a liposomal gel with Lactoferrin favors scarring/degradation of the brown colored spot typical of ulcerative haemosiderinic dyschromia. Nine patients with severe chronic venous insufficiency and ulcerative haemosiderinic dyschromia (CEAP-C6), with a natural evolution of over 12 months, were included in the study. Hemo chromatosis gene mutations were investigated. The levels of serum ferritin, transferrin saturation and blood cell counts were analyzed. The presence of hemosiderin was investigated through periulcerous and ulcer fundus biopsies carried out at baseline and 30 days after treatment with Lactoferrin. The severity of the injuries (CEAP classification) was evaluated at the beginning of and throughout the whole 3-month treatment period. No patient had received compression treatment during the three months previous to this therapy. Significant improvement in these injuries, with a reduction in the dimensions of the brown spot (9 of 9) at Day 90, and complete scarring with a closure time ranging from 15 to 180 days (7 of 9) were observed. The use of topical lactoferrin is a non-invasive therapeutic tool that favors clearance of hemosiderinic dyschromia and scarring of the ulcer. The success of this study was not influenced either by the hemochromatosis genetics or the iron metabolism profile observed

Assessment of aflatoxin M1 enrichment factor in cheese produced with naturally contaminated milk

Aflatoxin M1 (AFM1) is a well-known carcinogenic compound that may contaminate milk and dairy products. Thus, with the regulation 1881/2006, the European Union established a concentration limit for AFM1 in milk and insisted on the importance of defining enrichment factors (EFs) for cheese. In 2019, the Italian Ministry of Health proposed four different EFs based on cheese’s moisture content on a fat-free basis (MMFB) for bovine dairy products. This study aimed to define the EFs of cheese with different MFFB. The milk used for cheesemaking was naturally contaminated with different AFM1 concentrations. Results showed that all the EF average values from this study were lower than those of the Italian Ministry of Health. Hence, the current EFs might need to be reconsidered for a better categorization of AFM1 risk in cheese

Characterization of industrial wastes for their use in steelmaking

Esse trabalho consiste na caracterização do resíduo de mármore, lama fina de aciaria e borra de alumínio, para averiguar a viabilidade técnica da utilização de tais resíduos na dessulfuração e desfosforação de ferro-gusa líquido. A caracterização desses resíduos foi feita através de análises químicas, granulométricas, difração de raios X e microscopia eletrônica de varredura (MEV) com micro análise por Espectroscopia por Energia Dispersiva de Raios X (EDS). A lama fina de aciaria apresenta um teor de FeO de 84,90%, o resíduo de mármore apresentou um teor de 61,5% de CaO e 33,9% de MgO e a borra de alumínio apresentou 36,5% de Al metálico e 62% de Al2O3. A granulometria do resíduo de mármore apresentou um tamanho de grão médio igual 42,810 µm. Já, na borra de alumínio, o tamanho médio foi de 101,803 µm. A lama fina de aciaria LD apresentou, em torno de 54,7% de sua granulometria, entre 0,15 e 0,075mm. Esses resultados apontam para a viabilidade técnica da utilização desses materiais na dessulfuração e desfosforação do ferro-gusa

Assessment of the influence of lung inflation state on the quantitative parameters derived from hyperpolarized gas lung ventilation MRI in healthy volunteers.

In this study, the effect of lung volume on quantitative measures of lung ventilation was investigated using MRI with hyperpolarized 3He and 129Xe. Six volunteers were imaged with hyperpolarized 3He at five different lung volumes (residual volume (RV), RV+1L, functional residual capacity (FRC), FRC+1L and total lung capacity (TLC)), and three were also imaged with hyperpolarized 129Xe. Imaging at each of the lung volumes was repeated twice on the same day with corresponding 1H lung anatomical images. Percentage lung ventilated volume (%VV) and variation of signal intensity (heterogeneity score, Hscore) were evaluated. Increased ventilation heterogeneity, quantified by reduced %VV and increased Hscore, was observed at lower lung volumes with the least ventilation heterogeneity observed at TLC. For 3He MRI data, the coefficient of variation of %VV was less than 1.5% and less than 5.5% for Hscore at all lung volumes, whilst for 129Xe data the values were 4% and 10% respectively. Generally, %VV generated from 129Xe images was lower than that seen from 3He images. The good repeatability of 3He %VV found here supports prior publications showing that percentage lung ventilated volume is a robust method for assessing global lung ventilation. The greater ventilation heterogeneity observed at lower lung volumes indicates that there may be partial airway closure in healthy lungs and that lung volume should be carefully considered for reliable longitudinal measurements of %VV and Hscore. The results suggest that imaging patients at different lung volumes may help to elucidate obstructive disease pathophysiology and progression

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation:A Multi-center, Multi-vendor, and Multi-disease Study

Background: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters.Purpose: Develop a generalizable CNN for lung segmentation in 1H-MRI, robust to pathology, acquisition protocol, vendor, and center.Study type: Retrospective.Population: A total of 809 1H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85); 42% females) and 31 healthy participants (median age (range): 34 (23–76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets.Field Strength/Sequence: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1H-MRI.Assessment: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance.Statistical Tests: Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of &lt;0.05 was considered statistically significant.Results: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data.Data Conclusion: The 3D CNN generated accurate 1H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center.Evidence Level: 4.Technical Efficacy: Stage 1.</p

The Lung Image Database Consortium (LIDC):A comparison of different size metrics for pulmonary nodule measurements

RATIONALE AND OBJECTIVES: To investigate the effects of choosing between different metrics in estimating the size of pulmonary nodules as a factor both of nodule characterization and of performance of computer aided detection systems, since the latters are always qualified with respect to a given size range of nodules. MATERIALS AND METHODS: This study used 265 whole-lung CT scans documented by the Lung Image Database Consortium using their protocol for nodule evaluation. Each inspected lesion was reviewed independently by four experienced radiologists who provided boundary markings for nodules larger than 3 mm. Four size metrics, based on the boundary markings, were considered: a uni-dimensional and two bi-dimensional measures on a single image slice and a volumetric measurement based on all the image slices. The radiologist boundaries were processed and those with four markings were analyzed to characterize the inter-radiologist variation, while those with at least one marking were used to examine the difference between the metrics. RESULTS: The processing of the annotations found 127 nodules marked by all of the four radiologists and an extended set of 518 nodules each having at least one observation with three-dimensional sizes ranging from 2.03 to 29.4 mm (average 7.05 mm, median 5.71 mm). A very high inter-observer variation was observed for all these metrics: 95% of estimated standard deviations were in the following ranges [0.49, 1.25], [0.67, 2.55], [0.78, 2.11], and [0.96, 2.69] for the three-dimensional, the uni-dimensional, and the two bi-dimensional size metrics respectively (in mm). Also a very large difference among the metrics was observed: 0.95 probability-coverage region widths for the volume estimation conditional on uni-dimensional, and the two bi-dimensional size measurements of 10mm were 7.32, 7.72, and 6.29 mm respectively. CONCLUSIONS: The selection of data subsets for performance evaluation is highly impacted by the size metric choice. The LIDC plans to include a single size measure for each nodule in its database. This metric is not intended as a gold standard for nodule size; rather, it is intended to facilitate the selection of unique repeatable size limited nodule subsets

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Growth Pattern Analysis of Murine Lung Neoplasms by Advanced Semi-Automated Quantification of Micro-CT Images

Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed an advanced semi-automated algorithm for efficient and accurate tumor volume measurement. Tumor volumes determined by the algorithm were first validated by comparison with results from manual methods for volume determination as well as direct physical measurements. A longitudinal study was then performed to investigate in vivo murine lung tumor growth patterns. Individual mice were imaged at least three times, with at least three weeks between scans. The tumors analyzed exhibited an exponential growth pattern, with an average doubling time of 57.08 days. The accuracy of the algorithm in the longitudinal study was also confirmed by comparing its output with manual measurements. These results suggest an exponential growth model for lung neoplasms and establish a new advanced semi-automated algorithm to measure lung tumor volume in mice that can aid efforts to improve lung cancer diagnosis and the evaluation of therapeutic responses