Instability indices and forecasting thunderstorms: the case of 30 April 2009

In this paper, one meteorological case study for two Iranian airports are presented. Attempts have been made to study the predefined threshold amounts of some instability indices such as vertical velocity and relative humidity. Two important output variables from a numerical weather prediction model have been used to survey thunderstorms. The climatological state of thunder days in Iran has been determined to aid in choosing the airports for the case studies. The synoptic pattern, atmospheric thermodynamics and output from a numerical weather prediction model have been studied to evaluate the occurrence of storms and to verify the threshold instability indices that are based on Gordon and Albert (2000) and Miller (1972). <br><br> Using data from the Statistics and Data Center of the Iran Meteorological Organization, 195 synoptic stations were used to study the climatological pattern of thunderstorm days in Iran during a 15-yr period (1991–2005). Synoptic weather maps and thermodynamic diagrams have been drawn using data from synoptic stations and radiosonde data. A 15-km resolution version of the WRF numerical model has been implemented for the Middle East region with the assistance of global data from University Corporation for Atmospheric Research (UCAR). <br><br> The Tabriz airport weather station has been selected for further study due to its high frequency of thunderstorms (more than 35 thunderstorm days per year) and the existence of an upper air station. Despite the fact that storms occur less often at the Tehran weather station, the station has been chosen as the second case study site due to its large amount of air traffic. Using these two case studies (Tehran at 00:00 UTC, 31 April 2009 and Tabriz at 12:00 UTC, 31 April 2009), the results of this research show that the threshold amounts of 30 °C for KI, −2 °C for LI and −3 °C for SI suggests the occurrence and non-occurrence of thunderstorms at the Tehran and Tabriz stations, respectively. The WRF model output of vertical velocity and relative humidity are the two most important indices for examining storm occurrence, and they have a numerical threshold of 1 m s<sup>−1</sup> and 80%, respectively. These results are comparable to other studies that have examined thunderstorm occurrence

Is metal artefact reduction mandatory in cardiac PET/CT imaging in the presence of pacemaker and implantable cardioverter defibrillator leads?

Abstract Purpose Cardiac PET/CT imaging is often performed in patients with pacemakers and implantable cardioverter defibrillator (ICD) leads. However, metallic implants usually produce artefacts on CT images which might propagate to CTbased attenuation-corrected (CTAC) PET images. The impact of metal artefact reduction (MAR) for CTAC of cardiac PET/ CT images in the presence of pacemaker, ICD and ECG leads was investigated using both qualitative and quantitative analysis in phantom and clinical studies. Methods The study included 14 patients with various leads undergoing perfusion and viability examinations using dedicated cardiac PET/CT protocols. The PET data were corrected for attenuation using both artefactual CT images and CT images corrected using the MAR algorithm. The severity and magnitude of metallic artefacts arising from these leads were assessed on both linear attenuation coefficient maps (μ-maps) and attenuation-corrected PET images. CT and PET emission data were obtained using an anthropomorphic thorax phantom and a dedicated heart phantom made in-house incorporating pacemaker and ICD leads attached at the right ventricle of the heart. Volume of interest-based analysis and regression plots were performed for regions related to the lead locations. Bull's eye view analysis was also performed on PET images corrected for attenuation with and without the MAR algorithm. Results In clinical studies, the visual assessment of PET images by experienced physicians and quantitative analysis did not reveal erroneous interpretation of the tracer distribution or significant differences when PET images were corrected for attenuation with and without MAR. In phantom studies, the mean differences between tracer Nucl Med Mol Imaging (2011) 38:252-262 DOI 10.1007/s00259-010-1635 uptake obtained without and with MAR were 10.16±2.1% and 6.86±2.1% in the segments of the heart in the vicinity of metallic ICD or pacemaker leads, and were 4.43±0.5% and 2.98±0.5% in segments far from the leads. Conclusion Although the MAR algorithm was able to effectively improve the quality of μ-maps, its clinical impact on the interpretation of PET images was not significant. Therefore cardiac PET images corrected for attenuation using CTAC in the presence of metallic leads can be interpreted without correction for metal artefacts. It should however be emphasized that in some special cases with multiple ICD leads attached to the myocardium wall, MAR might be useful for accurate attenuation correction. Eur

The influence of using different reconstruction algorithms on sensitivity of quantitative 18F-FDG-PET volumetric measures to background activity variation

Introduction: This study aims to investigate the influence of background activity variation on image quantification in differently reconstructed PET/CT images. Methods: Measurements were performed on a Discovery-690 PET/CT scanner using a custom-built NEMA-like phantom. A background activity level of 5.3 and 2.6 kBq/ml 18F-FDG were applied. Images were reconstructed employing four different reconstruction algorithms: HD (OSEM with no PSF or TOF), PSF only, TOF only, and TOFPSF, with Gaussian filters of 3 and 6.4 mm in FWHM. SUVmax and SUVpeak were obtained and used as cut-off thresholding; Metabolic Tumor Volume (MTV) and Total Lesion Glycolysis (TLG) were measured. The volume recovery coefficients (VRCs), the relative percent error (�MTV), and Dice similarity coefficient were assessed with respect to true values. Results: SUVmax and SUVpeak decreased and MTV increased as function of increasing the background dose. The most differences occur in smaller volumes with 3-mm filter; Non-TOF and Non-PSF reconstruction methods were more sensitive to increasing the background activity in the smaller and larger volumes, respectively. The TLG values were affected in the small lesions (decrease up to 12). In a range of target volumes, differences between the mean �MTV in the high and low background dose varied from -11.8 to 7.2 using SUVmax and from 2.1 to 7.6 using SUVpeak inter reconstruction methods. Conclusion: The effect of the background activity variation on SUV-based quantification in small lesion was more noticeable than large lesion. The HD and TOFPSF algorithms had the lowest and the highest sensitivity to background activity, respectively. © 2018 Iranian Journal of Nuclear Medicine. All Rights Reserved

Is correction for metallic artefacts mandatory in cardiac SPECT/CT imaging in the presence of pacemaker and implantable cardioverter defibrillator leads?

Introduction: Metallic artifacts due to pacemaker/ implantable cardioverter defibrillator (ICD) leads in CT images can produce artifactual uptake in cardiac SPECT/CT images. The aim of this study was to determine the influence of the metallic artifacts due to pacemaker and ICD leads on myocardial SPECT/CT imaging. Methods: The study included 9 patients who underwent myocardial perfusion imaging (MPI). A cardiac phantom with an inserted solid defect was used. The SPECT images were corrected for attenuation using both artifactual CT and CT corrected using metal artifact reduction (MAR). VOI-based analysis was performed in artifactual regions. Results: In phantom studies, mean-of-relative-difference in white-region, between artifact-free attenuation-map without/with MAR were changed from 9.2 and 2.1 to 3.7 and 1.2 for ICD and pacemaker lead, respectively. However, these values for typical patient were 9.7±7.0 and 3.8±2.4 for ICD and pacemaker leads respectively, in white-region. MAR effectively reduces the artifacts in white-regions while this reduction is not significant in black-regions. Conclusion: Following application of MAR, visual and quantification analyses revealed that while quality of CT images were significantly improved, the improvements in the SPECT/CT images were not as pronounced or significant. Therefore cardiac SPECT images corrected for attenuation using CT in the presence of metallic-leads can be interpreted without correction for metal artefacts. © 2018 Tehran University of Medical Sciences. All rights reserved

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Objective: We demonstrate the feasibility of direct generation of attenuation and scatter-corrected images from uncorrected images (PET-nonASC) using deep residual networks in whole-body 18F-FDG PET imaging. Methods: Two- and three-dimensional deep residual networks using 2D successive slices (DL-2DS), 3D slices (DL-3DS) and 3D patches (DL-3DP) as input were constructed to perform joint attenuation and scatter correction on uncorrected whole-body images in an end-to-end fashion. We included 1150 clinical whole-body 18F-FDG PET/CT studies, among which 900, 100 and 150 patients were randomly partitioned into training, validation and independent validation sets, respectively. The images generated by the proposed approach were assessed using various evaluation metrics, including the root-mean-squared-error (RMSE) and absolute relative error (ARE ) using CT-based attenuation and scatter-corrected (CTAC) PET images as reference. PET image quantification variability was also assessed through voxel-wise standardized uptake value (SUV) bias calculation in different regions of the body (head, neck, chest, liver-lung, abdomen and pelvis). Results: Our proposed attenuation and scatter correction (Deep-JASC) algorithm provided good image quality, comparable with those produced by CTAC. Across the 150 patients of the independent external validation set, the voxel-wise REs () were � 1.72 ± 4.22, 3.75 ± 6.91 and � 3.08 ± 5.64 for DL-2DS, DL-3DS and DL-3DP, respectively. Overall, the DL-2DS approach led to superior performance compared with the other two 3D approaches. The brain and neck regions had the highest and lowest RMSE values between Deep-JASC and CTAC images, respectively. However, the largest ARE was observed in the chest (15.16 ± 3.96) and liver/lung (11.18 ± 3.23) regions for DL-2DS. DL-3DS and DL-3DP performed slightly better in the chest region, leading to AREs of 11.16 ± 3.42 and 11.69 ± 2.71, respectively (p value < 0.05). The joint histogram analysis resulted in correlation coefficients of 0.985, 0.980 and 0.981 for DL-2DS, DL-3DS and DL-3DP approaches, respectively. Conclusion: This work demonstrated the feasibility of direct attenuation and scatter correction of whole-body 18F-FDG PET images using emission-only data via a deep residual network. The proposed approach achieved accurate attenuation and scatter correction without the need for anatomical images, such as CT and MRI. The technique is applicable in a clinical setting on standalone PET or PET/MRI systems. Nevertheless, Deep-JASC showing promising quantitative accuracy, vulnerability to noise was observed, leading to pseudo hot/cold spots and/or poor organ boundary definition in the resulting PET images. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature

Characterization of scattered radiation profile in volumetric 64 slice CT scanner: Monte Carlo study using GATE

It is commonly understood that scattered radiation in X-ray computed tomography (CT) reduces the CT number and degrades the quality of reconstructed images. This effect is more pronounced in multi detector CT scanners with extended detector aperture mostly using cone-beam configurations, which are much less immune to scatter than fan-beam and single-slice CT scanners. To perform accurate scatter correction, it is essential to characterize scattered radiation in Volumetric CT. As characterization of scattered radiation behavior using experimental measurement is a difficult and time consuming approach, Monte Carlo simulation can be an ideal method. In this study we used Geant4-based simulation package, GATE, to model x-ray photon interactions in the phantom and detector. The Monte Carlo simulation was validated through comparison with experimental measurement data. Thereafter, the effect of different parameters such as tube voltage and phantom material on the scatter profile and Scatter to Primary Ratio (SPR) was calculated. We also compared the simulated SPR curves with experimental data which was measured with array blocker method. The experimental technique assumed to be the gold standard technique. The comparison between simulation and experimental data in SPR showed error less than 5 . The results indicate that the GATE Monte Carlo code is a useful tool for investigation of scattered radiation characterization in CT scanners. Moreover, there is a possibility of take advantage of GATE for simulation of PET and CT scanners in order to simultaneously asses the contribution of scattered radiation in PET/CT scanners. © 2011 IEEE

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Numerical simulation of the impact of Anatolian and Caucasus Mountains on the precipitation distribution over the Black Sea

An attempt is made to examine the role of Anatolian and Caucasus mountain ranges in the precipitation distribution over the Black Sea region and to clarify the dynamical and physical mechanisms responsible for precipitation distribution over the region. Existence of a complex topography in the southern and eastern part of the Black Sea region makes it an important region for cyclogenesis. In this study the effect of Anatolian and Caucasus Mountains on the precipitating synoptic systems forming over the Black Sea are investigated. To this end, the Weather Research and Forecasting (WRF) model at 15-km horizontal grid spacing has been used to evaluate the lifetime of a low pressure system that was accompanied with heavy precipitation on 14 March 2009 over the coastal region of the Black Sea. Two experiments were conducted. In the control experiment (CTL), the topographical features of the region were retained. In the sensitivity experiment (EXP), the Anatolian and Caucasus mountain ranges were removed. It is found that in the EXP, some fields including vertical motion, relative vorticity, humidity, geopotential height in low level, cloud water content and precipitation distribution in the region undergo significant changes. As such, in the EXP, the vorticity, and the cut-off low system over the Black Sea intensified. It is also seen that, under favorable conditions for precipitation occurrence, the precipitation intensity in the south and east coasts of the Black Sea decreased and the region of maximum precipitation shifted toward the "Sea of Azov" region, in the direction of the surface southerly winds