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[en] The authors compared measurements of hindfoot alignment on MR imaging with weight-bearing CT (WB-CT) to establish the degree of correlation. Forty-seven feet in 44 patients had weight-bearing CT and MRI studies performed on the same day. Hindfoot alignment on MRI was assessed by two radiologists who calculated tibiocalcaneal angle (TCA) and calcaneofibular ligament angle (CFLA). On WB-CT, foot ankle offset (FAO), calcaneal offset (CO) and hindfoot angle (HA) were assessed by a senior Foot and Ankle Surgeon using dedicated software. Pearson correlation coefficient was used to evaluate the correlation between these measurements. The study group comprised 27 males and 17 females with a mean age of 45 years (range 13–79 years). A statistically significant positive correlation was identified between TCA on MRI and all measurements of hindfoot alignment on WB-CT (p = 0.001–0.005). The CFLA on MRI only had significant correlation with CO on WB-CT (p = 0.03). A significant negative correlation was observed between both MRI parameters (p < 0.001). A highly significant correlation between tibiocalcaneal angle on non-weight-bearing ankle MR imaging and hindfoot alignment measurements on weight-bearing CT was identified.
[en] Dynamic PET (dPET) studies have been used until now primarily within research purposes. Although it is generally accepted that the information provided by dPET is superior to that of conventional static PET acquisitions acquired usually 60 min post injection of the radiotracer, the duration of dynamic protocols, the limited axial field of view (FOV) of current generation clinical PET systems covering a relatively small axial extent of the human body for a dynamic measurement, and the complexity of data evaluation have hampered its implementation into clinical routine. However, the development of new-generation PET/CT scanners with an extended FOV as well as of more sophisticated evaluation software packages that offer better segmentation algorithms, automatic retrieval of the arterial input function, and automatic calculation of parametric imaging, in combination with dedicated shorter dynamic protocols, will facilitate the wider use of dPET. This is expected to aid in oncological diagnostics and therapy assessment. The aim of this review is to present some general considerations about dPET analysis in oncology by means of kinetic modeling, based on compartmental and noncompartmental approaches, and parametric imaging. Moreover, the current clinical applications and future perspectives of the modality are outlined.
[en] To assess the coronary atherosclerosis profile by coronary computed tomography angiography (CTA) in patients with end-stage liver disease (ESLD) due to alcohol-related liver disease (ARLD) evaluated for liver transplantation (LT), in a retrospective matched case-controlled cohort study. One hundred forty patients (age 60.6 years ± 9.8, 20.7% females) who underwent coronary CTA were included. Seventy patients with ESLD due to ARLD (ESLD-alc) were propensity score (1:1) matched for age, gender, and the major 5 cardiovascular risk factors with healthy controls. CTA analysis included the following: stenosis severity according to CAD-RADS as (0) = no, (1) minimal < 25%, (2) mild 25–50%, (3) moderate 50–70%, and (4) severe > 70% stenosis, total mixed plaque burden weighted for non-calcified component (G-score) and high-risk plaque criteria (Napkin-Ring, low attenuation plaque, spotty calcification, positive remodeling). Prevalence of coronary artery disease (CAD) was high (84.4%) in the ESLD-alc group but similar to controls. Stenosis severity was similar (CAD-RADS, 1.9 vs. 2.2, p = 0.289). High-grade stenosis (> 70%) was observed in 12.5% of ESLD-alc patients. High-risk plaques were less frequent in the ESLD-alc cohort as compared to controls (4.5% vs. 37.5%, p < 0.001), and total mixed plaque burden was lower (G-score, 4.9 versus 7.4, p = 0.001). Plaque density was lower in controls (56.6HU ± 3.2 vs. 91.3HU ± 4.5, p = 0.007) indicating more lipid-rich in controls, but higher mixed fibro-calcific plaque component in those with alcohol-related ESLD. Patients with alcohol-related ESLD exhibit more mixed fibro-calcified plaques but less plaque with high-risk features and less fibro-fatty plaque burden, while total CAD prevalence is high.
[en] Anomalous origin of the coronary arteries, though uncommon, is of great clinical concern. It can be the cause of sudden cardiac death and abnormal cardiac hemodynamics. Advances in electrocardiographically (ECG)-gated multi-detector CT have increased diagnostic accuracy in detecting anomalous origin of coronary arteries and their interarterial and intramural courses. Recent advances in multi-detector CT image processing software have allowed the creation of virtual endoluminal views of the aortic root and improved assessment of the intramural course (the length and relationship to the intercoronary commissure) of the coronary artery, which is of considerable surgical importance. We review our experience with virtual endoluminal imaging in our first 19 cases of interarterial coronary artery anomalies (17 cases of interarterial with intramural segment and 2 cases of purely interarterial course) diagnosed preoperatively and proven surgically.
[en] The accident at the Japanese nuclear power plant (NPP) Fukushima-1 in March 2011 showed that possibility of accidents with potentially serious radiation consequences could not be excluded with large-scale measures for improvement of safety level. For spent nuclear fuel storage facilities, one of such accidents may be the interruption of heat removal from spent nuclear fuel (SNF) due to the failure of the cooling system as a result of disruption of the power supply system with the failure of backup power sources or rapid full dehydration of the wet SNF storage as a result of the destruction of building structures and its depressurization. The decision to take preventive measures in advance to minimize exposure to personnel and the public is based on conservative estimates of possible radioactive discharges. To perform such assessments, the operating organizations carry out a calculated justification of the thermal and hydraulic characteristics of the SNF system in the accident scenarios with long-term blackout and a violation of heat removal. APROS is one of the software tools that are used in SEC NRS for calculating the thermal-hydraulic characteristics of systems in transient modes by solving the equations of heat and mass transfer in a steam-water mixture. For more detailed calculations of the structural elements of spent fuel assemblies (SFA) temperature, the ANSYS software is used, which implements the finite element method. The results obtained with the help of the above simulation tools are used by specialists of SEC NRS to assess the protective measures developed by operating organizations.
[en] As well as nuclear power plants, research reactors are subject to a strict licensing process, requiring different studies to certify that the project is capable to safely withstand transients, without radiological consequences for people or environment. Thus, this work aims to develop a computational tool to investigate the behavior of MTR research reactors, including the Brazilian Multi-Purpose Reactor (RMB), by using a numerical-analytical approach for coupled thermohydraulic and neutronic analysis in a cooling subchannel. The modeling consists of the heat conduction equations on a fuel plate, the coolant energy transport equation in the subchannel and point kinetics equations with six groups of delayed neutrons. Improved lumped formulations are adopted for heat conduction in the transversal direction of the fuel and cladding, while the fluid energy equation is discretized along the subchannel by the finite difference method. The resulting system of ordinary differential equations is solved numerically by using the NDSolve function of the Mathematica software. The code is verified against the IAEA MTR 10 MW benchmark problems, showing good agreement with literature data. The Serpent 2 Monte Carlo code is employed to calculate the RMB kinetic parameters of the NPK equations and the steady state power distribution. The analysis results demonstrates that RMB operates safely under the events of loss of flow and reactivity insertion. (author)
[en] To develop and test computer software to detect, quantify, and monitor progression of pneumonia associated with COVID-19 using chest CT scans. One hundred twenty chest CT scans from subjects with lung infiltrates were used for training deep learning algorithms to segment lung regions and vessels. Seventy-two serial scans from 24 COVID-19 subjects were used to develop and test algorithms to detect and quantify the presence and progression of infiltrates associated with COVID-19. The algorithm included (1) automated lung boundary and vessel segmentation, (2) registration of the lung boundary between serial scans, (3) computerized identification of the pneumonitis regions, and (4) assessment of disease progression. Agreement between radiologist manually delineated regions and computer-detected regions was assessed using the Dice coefficient. Serial scans were registered and used to generate a heatmap visualizing the change between scans. Two radiologists, using a five-point Likert scale, subjectively rated heatmap accuracy in representing progression. There was strong agreement between computer detection and the manual delineation of pneumonic regions with a Dice coefficient of 81% (CI 76–86%). In detecting large pneumonia regions (> 200 mm), the algorithm had a sensitivity of 95% (CI 94–97%) and specificity of 84% (CI 81–86%). Radiologists rated 95% (CI 72 to 99) of heatmaps at least "acceptable" for representing disease progression. The preliminary results suggested the feasibility of using computer software to detect and quantify pneumonic regions associated with COVID-19 and to generate heatmaps that can be used to visualize and assess progression.
[en] The CERN cryogenic facilities demand a versatile, distributed, homogeneous and highly reliable control system. For this purpose, CERN conceived and developed several frameworks (JCOP, UNICOS, FESA, CMW), based on current industrial technologies and COTS equipment, such as PC, PLC and SCADA systems complying with the requested constraints. The cryogenic control system nowadays uses these frameworks and allows the joint development of supervision and control layers by defining a common structure for specifications and code documentation. Another important advantage of the CERN frameworks is the possibility to integrate different control systems into a large technical system with communication capability. Such a system is capable of sharing control variables from all accelerator apparatus in order to cope with the operation scenarios.The first implementation of this control architecture started in 2000 for the Large Hadron Collider (LHC). Since then CERN continued developing the hardware and software components of the cryogenic control system, based on the exploitation of the experience gained. These developments are always aimed at increasing the safety and improving the performance. To overcome the long-term maintenance challenges, key strategies such as the use of homogeneous hardware solutions and the optimization of the maintenance procedures were set up. They are easing the development of the control applications and the hardware configuration by allowing a structured and homogeneous approach. Furthermore, they reduce the needed manpower and minimize the financial impact of the periodical maintenance. In that context, the standardization of technical solutions both at hardware and software level simplify also the systems monitoring the operation and maintenance processes, while providing a high level of availability.
[en] CT findings of COVID-19 look similar to other atypical and viral (non-COVID-19) pneumonia diseases. This study proposes a clinical computer-aided diagnosis (CAD) system using CT features to automatically discriminate COVID-19 from non-COVID-19 pneumonia patients. Overall, 612 patients (306 COVID-19 and 306 non-COVID-19 pneumonia) were recruited. Twenty radiological features were extracted from CT images to evaluate the pattern, location, and distribution of lesions of patients in both groups. All significant CT features were fed in five classifiers namely decision tree, K-nearest neighbor, naïve Bayes, support vector machine, and ensemble to evaluate the best performing CAD system in classifying COVID-19 and non-COVID-19 cases. Location and distribution pattern of involvement, number of the lesion, ground-glass opacity (GGO) and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features to classify COVID-19 from non-COVID-19 groups. Our proposed CAD system obtained the sensitivity, specificity, and accuracy of 0.965, 93.54%, 90.32%, and 91.94%, respectively, using ensemble (COVIDiag) classifier. This study proposed a COVIDiag model obtained promising results using CT radiological routine features. It can be considered an adjunct tool by the radiologists during the current COVID-19 pandemic to make an accurate diagnosis.
[en] To construct and validate a nomogram model that integrated the CT radiomic features and the TNM staging for risk stratification of thymic epithelial tumors (TETs). A total of 136 patients with pathology-confirmed TETs who underwent CT examination were collected from two institutions. According to the WHO pathological classification criteria, patients were classified into low-risk and high-risk groups. The TNM staging was determined in terms of the 8th edition AJCC/UICC staging criteria. LASSO regression was performed to extract the optimal features correlated to risk stratification among the 704 radiomic features calculated. A nomogram model was constructed by combining the Radscore and the TNM staging. The clinical performance was evaluated by ROC analysis, calibration curve, and decision curve analysis (DCA). The Kaplan-Meier (KM) analysis was employed for survival analysis. Five optimal features identified by LASSO regression were employed to calculate the Radscore correlated to risk stratification. The nomogram model showed a better performance in both training cohort (AUC = 0.84, 95%CI 0.75–0.91) and external validation cohort (AUC = 0.79, 95%CI 0.69–0.88). The calibration curve and DCA analysis indicated a better accuracy of the nomogram model for risk stratification than either Radscore or the TNM staging alone. The KM analysis showed a significant difference between the two groups stratified by the nomogram model (p = 0.02). A nomogram model that integrated the radiomic signatures and the TNM staging could serve as a reliable model of risk stratification in predicting the prognosis of patients with TETs.