ABSTRACT
Background: The increased frequency of chest computed tomography utilization in the fight against COVID-19 has made usage of low-dose computed tomography necessary to reduce the radiation dose while preserving diagnostic quality. However, in the published literature, there were no data on the effect of body mass index on low-dose computed tomography accuracy in patients with COVID-19. Aim: To assess the effect of patient body mass index on the level of agreement between radiologists interpreting standard-dose computed tomography and low-dose computed tomography in COVID-19-associated pneumonia using visual semiquantitative CT 0–4 scale. Materials and methods: In this retrospective multicenter study, each participant underwent two consecutive chest scans at a single visit using standard-dose and low-dose protocols. Standard-dose and low-dose computed tomography with pulmonary and soft tissue kernels were interpreted using a visual semiquantitative CT 0–4 grading system. Data for each protocol were grouped by body mass index value (threshold value for pathology was equal to 25 kg/m2). Agreement was calculated based on binary and weighted classifications. One-way ANOVA analysis of variance was used to assess the presence of statistically significant differences in the mean for the groups. Results: Two hundred thirty patients met the established inclusion criteria for the study. The experts processed 4 studies for each patient: standard-dose and low-dose computed tomography with pulmonary and soft tissue kernels. The proportion of normal-weight patients was 31% (71 subjects), and the sample's median body mass index was 27.5 (18.3;48.3) kg/m2. There were no statistically significant differences in intergroup pairwise comparisons for both the binary and weighted classifications (p values were 0.09 and 0.12, respectively). The group of overweight patients was further subdivided according to the degrees of obesity;however, the results were invariant to this division (no statistically significant differences: for the most different body mass index groups "normal” and "3rd degree obesity” p-value 0.17). Conclusion: Body mass index does not affect chest standard-dose and low-dose computed tomography interpretation in COVID-19 using the visual semiquantitative CT 0–4 grading system. © Authors, 2022.
ABSTRACT
Introduction. Chest computed tomography (CT) plays a prominent role in determining the extent of pulmonary parenchymal lesions in COVID-19. At the same time, subjectivity of lung lesion volume assessment using 0-4 CT scale in COVID-19 and gradual introduction of low-dose CT (LDCT) requires an investigation of semi-automated lung segmentation accuracy in LDCT compared to CT. Study Objective. To compare the accuracy of affected lung tissue volume calculation between CT and LDCT in COVID-19 using a semi-automatic segmentation program. Material and Methods. The retrospective study was performed on data from the earlier prospective multicenter study registered at ClinicalTrials.gov, NCT04379531. CT and LDCT data were processed in 3D Slicer software with Lung CT Segmenter and Lung CT Analyzer extensions, and the volume of affected lung tissue and lung volume were determined by thresholding. Results. The sample size was 84 patients with signs of COVID-19-associated pneumonia. Mean age was 50.6 ± 13.3 years, and the median body mass index (BMI) was 28.15 [24.85;31.31] kg/m2. The effective doses were 10.1 ± 3.26 mSv for the standard CT protocol and 2.64 mSv [1.99;3.67] for the developed LDCT protocol. The analysis of absolute lung lesion volume in cubic centimeters with Wilcoxon Signed Ranks Test revealed a statistically significant difference between CT and LDCT (p-value < 0.001). No statistically significant differences were found in the relative values of lung tissue lesion volume (lesion volume/lung volume) between CT and LDCT using Wilcoxon Signed Ranks Test (p-value = 0.95). Conclusion. The reliability of developed LDCT protocol in COVID-19 for the semi-automated calculation of affected tissue percentage was comparable to the standard chest CT protocol when using 3D Slicer with Lung CT Segmenter and Lung CT Analyzer extensions. © 2022 Tomsk State University. All rights reserved.
ABSTRACT
Coronavirus pandemic in 2020 posed new challenges for supply chains, requiring a rethinking of risk assessment approaches, with a focus on post-pandemic recovery and SC's ability to adapt to new business conditions. This study is aimed at performing a descriptive and comparative analysis of the potential risks of supply chains in a number of countries, as well as at assessing the processes of their integration into global supply chains based on the Global Resilience Index FM 2020 as a parameter of resilience of an entity to disruptive events, which fully meets the requirements for a comprehensive assessment of supply chain risks. According to the findings, when formulating a supply chain risk management strategy, the focus should be on an analysis of the external environment and the sustainability of the supply chain. The results and methods of this study can be applied by top managers of supply chain risk management, while government officials can use the results and methods of this article to determine policy for supply chain management. © 2022 Inderscience Enterprises Ltd.. All rights reserved.