Влияние циркуляции вод на загрязнение прибрежных акваторий Керченской бухты соединениями тяжелых металлов и нефтепродуктов

Исследование связи атмосферных переносов над Керченским проливом с загрязнением акватории Керченского морского торгового порта и других прибрежных участков акватории Керченской бухты соединениями тяжелых металлов и нефтепродуктов в 1993 – 2006 гг. позволили установить ключевую роль черноморского типа течений в проливе и локальной циркуляции вод в Керченской бухте в загрязнении исследуемых акваторий.Дослідження зв'язку атмосферних перенесень над Керченською протокою із забрудненням акваторії Керченського морського торгового порту і інших прибережних ділянок акваторії Керченської бухти сполуками важких металів і нафтопродуктів в 1993 – 2006 рр. дозволили встановити ключову роль чорноморського типу течій в протоці і локальної циркуляції вод в Керченській бухті в забрудненні досліджуваних акваторій.Research of connection of atmospheric transport over the Kerch Strait and water area pollution of Kerch Trading Sea Port and other coastal areas of the of the Kerch bay by heavy metals and petroleum products in 1993 – 2006, have established the key role the Black Sea type currents in the strait and the local water circulation in the Bay of Kerch in the pollution study waters

Multi-Modality Imaging for Prevention of Coronary Artery Disease and Myocardial Infarction in the General Population:Ready for Prime Time?

Cardiovascular disease (CVD) remains a leading cause of death and disability worldwide. Acute myocardial infarction (AMI) causes irreversible myocardial damage, heart failure, life-threatening arrythmias and sudden cardiac death (SCD), and is a main driver of CVD mortality and morbidity. To control the forecasted increase in CVD burden for both the individual and society, improved strategies for the prevention of AMI and SCD are required. Current prevention of AMI and SCD is directed towards risk-modifying interventions, guided by risk assessment using clinical risk prediction scores (CRPSs) and the coronary artery calcium score (CACS). Early detection of more advanced coronary artery disease (CAD), beyond risk assessment by CRPSs or CACS, is a promising strategy to allow personalized treatment for the improved prevention of AMI and SCD in the general population. We review evidence for further testing, beyond CRPSs and CACS, and therapies focusing on promising targets, including subclinical obstructive CAD, high-risk plaques, and silent myocardial ischemia. We also evaluate the potential of multi-modality imaging to enhance the conduction of adequately powered trials to provide high-quality evidence on the impact of add-on tests and therapies in the prevention of AMI and SCD in asymptomatic individuals. To conclude, we discuss the occurrence of AMI and SCD in individuals currently estimated to be at "low-risk" by the current strategy based on CRPSs, and methods to improve prevention of AMI and SCD in this "low-risk" population

Quantification of growth patterns of screen-detected lung cancers:The NELSON study

Objectives: Although exponential growth is assumed for lung cancer, this has never been quantified in vivo. Aim of this study was to evaluate and quantify growth patterns of lung cancers detected in the Dutch-Belgian low-dose computed tomography (CT) lung cancer screening trial (NELSON), in order to elucidate the development and progression of early lung cancer.Materials and methods: Solid lung nodules found at &gt;= 3 CT examinations before lung cancer diagnosis were included. Lung cancer volume (V) growth curves were fitted with a single exponential, expressed as V = V-1 exp(t/tau), with t time from baseline (days), V-1 estimated baseline volume (mm(3)), and tau estimated time constant. The R-2 coefficient of determination was used to evaluate goodness of fit. Overall volume-doubling time for the individual lung cancer is given by tau*log(2).Results: Forty-seven lung cancers in 46 participants were included. Forty participants were male (87.0%); mean age was 61.7 years (standard deviation, 6.2 years). Median nodule size at baseline was 99.5 mm(3) (IQR: 46.8-261.8 mm(3)). Nodules were followed for a median of 770 days (inter-quartile range: 383-1102 days) before lung cancer diagnosis. One cancer (2.1%) was diagnosed after six CT examinations, six cancers (12.8%) were diagnosed after five CTs, 14 (29.8%) after four CTs, and 26 cancers (55.3%) after three CTs. Lung cancer growth could be described by an exponential function with excellent goodness of fit (R-2 0.98). Median overall volume-doubling time was 348 days (inter-quartile range: 222-492 days).Conclusion: This study based on CT lung cancer screening provides in vivo evidence that growth of cancerous small-to-intermediate sized lung nodules detected at low-dose CT lung cancer screening can be described by an exponential function such as volume-doubling time. (C) 2017 Elsevier B.V. All rights reserved.</p

Relationship between the number of new nodules and lung cancer probability in incidence screening rounds of CT lung cancer screening:The NELSON study

textabstractBackground: New nodules are regularly found after the baseline round of low-dose computed tomography (LDCT) lung cancer screening. The relationship between a participant's number of new nodules and lung cancer probability is unknown. Methods: Participants of the ongoing Dutch-Belgian Randomized Lung Cancer Screening (NELSON) Trial with (sub)solid nodules detected after baseline and registered as new by the NELSON radiologists were included. The correlation between a participant's new nodule count and the largest new nodule size was assessed using Spearman's rank correlation. To evaluate the new nodule count as predictor for new nodule lung cancer together with largest new nodule size, a multivariable logistic regression analysis was performed. Results: In total, 705 participants with 964 new nodules were included. In 48% (336/705) of participants no nodule had been found previously during baseline screening and in 22% (154/705) of participants >1 new nodule was detected (range 1–12 new nodules). Eventually, 9% (65/705) of the participants had lung cancer in a new nodule. In 100% (65/65) of participants with new nodule lung cancer, the lung cancer was the largest or only new nodule at initial detection. The new nodule lung cancer probability did not differ significantly between participants with 1 (10% [56/551], 95%CI 8–13%) or >1 new nodule (6% [9/154], 95%CI 3–11%, P =.116). An increased number of new nodules positively correlated with a participant's largest nodule size (P < 0.001, Spearman's rho 0.177). When adjusted for largest new nodule size, the new nodule count had a significant negative association with lung cancer (odds ratio 0.59, 0.37–0.95, P =.03). Conclusion: A participant's new nodule count alone only has limited association with lung cancer. However, a higher new nodule count correlates with an increased largest new nodule size, while the lung cancer probability remains equivalent, and may improve lung cancer risk prediction by size only

New Fissure-Attached Nodules in Lung Cancer Screening:A Brief Report From The NELSON Study

Introduction: In incidence lung cancer screening rounds, new pulmonary nodules are regular findings. They have a higher lung cancer probability than baseline nodules. Previous studies have shown that baseline perifissural nodules (PFNs) represent benign lesions. Whether this is also the case for incident PFNs is unknown. This study evaluated newly detected nodules in the Dutch-Belgian randomized-controlled NELSON study with respect to incidence of fissure-attached nodules, their classification, and lung cancer probability. Methods: Within the NELSON trial, 7557 participants underwent baseline screening between April 2004 and December 2006. Participants with new nodules detected after baseline were included. Nodules were classified based on location and attachment. Fissure-attached nodules were re-evaluated to be classified as typical, atypical, or non-PFN by two radiologists without knowledge of participant lung cancer status. Results: One thousand four hundred eighty-four new nodules were detected in 949 participants (77.4% male, median age 59 years [interquartile range: 55–63 years]) in the second, third, and final NELSON screening round. Based on 2-year follow-up or pathology, 1393 nodules (93.8%) were benign. In total, 97 (6.5%) were fissure-attached, including 10 malignant nodules. None of the new fissure-attached malignant nodules was classified as typical or atypical PFN. Conclusions: In the NELSON study, 6.5% of incident lung nodules were fissure-attached. None of the lung cancers that originated from a new fissure-attached nodule in the incidence lung cancer screening rounds was classified as a typical or atypical PFN. Our results suggest that also in the case of a new PFN, it is highly unlikely that these PFNs will be diagnosed as lung cancer

Association of epicardial adipose tissue with different stages of coronary artery disease:A cross-sectional UK Biobank cardiovascular magnetic resonance imaging substudy

Objective: Increased epicardial adipose tissue (EAT) has been identified as a risk factor for the development of coronary artery disease (CAD). However, the exact role of EAT in the development of CAD is unclear. This study aims to compare EAT volumes between healthy controls and individuals with stable CAD and a history of myocardial infarction (MI). Furthermore, associations between clinical and biochemical parameters with EAT volumes are examined.& nbsp;Methods: This retrospective cross-sectional study included 171 participants from the United Kingdom Biobank (56 healthy controls; 60 stable CAD; 55 post MI), whom were balanced for age, sex and body mass index (BMI). EAT volumes were quantified on end-diastolic cardiac magnetic resonance (CMR) imaging short-axis slices along the left and right ventricle and indexed for body surface area (iEAT) and iEAT volumes were compared between groups.& nbsp;Results: iEAT volumes were comparable between control, CAD and MI cases (median [IQR]: 66.1[54.4-77.0] vs. 70.9[55.8-85.5] vs. 67.6[58.6-82.3] mL/m(2), respectively (p > 0.005 for all). Increased HDL-cholesterol was associated with decreased iEAT volume (8 =-14.8, CI =-24.6 to-4.97, p = 0.003) and suggestive associations (P-value = 0.005) were observed between iEAT and triglycerides (beta = 3.26, CI = 0.42 to 6.09, p = 0.02), Apo-lipoprotein A (beta =-16.3, CI =-30.3 to-2.24, p = 0.02) and LDL-cholesterol (beta = 3.99, CI =-7.15 to-0.84, p = 0.01).& nbsp;Conclusions: No significant differences in iEAT volumes were observed between patients with CAD, MI and healthy controls. Our results indicate the importance of correcting for confounding by CVD risk factors, including circulating lipid levels, when studying the relationship between EAT volume and CAD. Further mechanistic studies on causal pathways and the role of EAT composition are warranted

Influence of lung nodule margin on volume- and diameter-based reader variability in CT lung cancer screening

OBJECTIVE: To evaluate the influence of nodule margin on inter- and intra-reader variability in manual diameter measurements and semi-automatic volume measurements of solid nodules detected in low-dose CT lung cancer screening. METHODS: Twenty-five nodules of each morphological category (smooth, lobulated, spiculated and irregular) were randomly selected from 93 participants of the Dutch-Belgian randomized lung cancer screening trial (NELSON). Semi-automatic volume measurements were performed using Syngo LungCARE® software. Three radiologists independently measured mean diameters manually. Impact of nodule margin on inter-reader variability was evaluated based on systematic error and 95% limits of agreement. Inter-reader variability was compared to the nodule growth cutoff as used in Lung-RADS (+1.5mm diameter) and NELSON/British Thoracic Society (+25% volume). RESULTS: For manual diameter measurements, a significant systematic error (up to 1.2mm) between readers was found in all morphological categories. For semi-automatic volume measurements, no statistically significant systematic error was found. The inter-reader variability in mean diameter measurements exceeded the 1.5mm cut-off for nodule growth for all morphological categories (smooth: ±1.9mm [+27%], lobulated: ±2.0mm [+33%], spiculated: ±3.5mm [+133%], irregular: ±4.5mm [+200%]). The 25%-volume growth cut-off was exceeded slightly for spiculated (28% [+12%]) and irregular (27% [+8%]) nodules. CONCLUSION: Lung nodule sizing based on manual diameter measurement is affected by nodule margin. Inter-reader variability increases especially for nodules with spiculated and irregular margins, and may cause misclassification of nodule growth. This effect is much smaller for semi-automated volume measurements. Advances in knowledge: Semi-automatic volume measurements are superior for both size and growth determination of pulmonary nodules

PHP48 COST SENSITIVENESS AND PHYSICIAN TREATMENT CHOICES

Objectives To explore the relationship between nodule count and lung cancer probability in baseline low-dose CT lung cancer screening. Materials and Methods Included were participants from the NELSON trial with at least one baseline nodule (3392 participants [45% of screen-group], 7258 nodules). We determined nodule count per participant. Malignancy was confirmed by histology. Nodules not diagnosed as screen-detected or interval cancer until the end of the fourth screening round were regarded as benign. We compared lung cancer probability per nodule count category. Results 1746 (51.5%) participants had one nodule, 800 (23.6%) had two nodules, 354 (10.4%) had three nodules, 191 (5.6%) had four nodules, and 301 (8.9%) had > 4 nodules. Lung cancer in a baseline nodule was diagnosed in 134 participants (139 cancers; 4.0%). Median nodule count in participants with only benign nodules was 1 (Inter-quartile range [IQR]: 1–2), and 2 (IQR 1–3) in participants with lung cancer (p = NS). At baseline, malignancy was detected mostly in the largest nodule (64/66 cancers). Lung cancer probability was 62/1746 (3.6%) in case a participant had one nodule, 33/800 (4.1%) for two nodules, 17/354 (4.8%) for three nodules, 12/191 (6.3%) for four nodules and 10/301 (3.3%) for > 4 nodules (p = NS). Conclusion In baseline lung cancer CT screening, half of participants with lung nodules have more than one nodule. Lung cancer probability does not significantly change with the number of nodules. Baseline nodule count will not help to differentiate between benign and malignant nodules. Each nodule found in lung cancer screening should be assessed separately independent of the presence of other nodules

Prognostic value of heart valve calcifications for cardiovascular events in a lung cancer screening population

To assess the prognostic value of aortic valve and mitral valve/annulus calcifications for cardiovascular events in heavily smoking men without a history of cardiovascular disease. Heavily smoking men without a cardiovascular disease history who underwent non-contrast-enhanced low-radiation-dose chest CT for lung cancer screening were included. Non-imaging predictors (age, smoking status and pack-years) were collected and imaging-predictors (calcium volume of the coronary arteries, aorta, aortic valve and mitral valve/annulus) were obtained. The outcome was the occurrence of cardiovascular events. Multivariable Cox proportional-hazards regression was used to calculate hazard-ratios (HRs) with 95 % confidence interval (CI). Subsequently, concordance-statistics were calculated. In total 3111 individuals were included, of whom 186 (6.0 %) developed a cardiovascular event during a follow-up of 2.9 (Q1–Q3, 2.7–3.3) years. If aortic (n = 657) or mitral (n = 85) annulus/valve calcifications were present, cardiovascular event incidence increased to 9.0 % (n = 59) or 12.9 % (n = 11), respectively. HRs of aortic and mitral valve/annulus calcium volume for cardiovascular events were 1.46 (95 % CI, 1.09–1.84) and 2.74 (95 % CI, 0.92–4.56) per 500 mm3. The c-statistic of a basic model including age, pack-years, current smoking status, coronary and aorta calcium volume was 0.68 (95 % CI, 0.63–0.72), which did not change after adding heart valve calcium volume. Aortic valve calcifications are predictors of future cardiovascular events. However, there was no added prognostic value beyond age, number of pack-years, current smoking status, coronary and aorta calcium volume for short term cardiovascular events