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Background: The global coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges for healthcare systems, notably the increased demand for chest computed tomography (CT) scans, which lack automated analysis. Our study addresses this by utilizing artificial intelligence-supported automated computer analysis to investigate lung involvement distribution and extent in COVID-19 patients. Additionally, we explore the association between lung involvement and intensive care unit (ICU) admission, while also comparing computer analysis performance with expert radiologists' assessments. Methods: A total of 81 patients from an open-source COVID database with confirmed COVID-19 infection were included in the study. Three patients were excluded. Lung involvement was assessed in 78 patients using CT scans, and the extent of infiltration and collapse was quantified across various lung lobes and regions. The associations between lung involvement and ICU admission were analysed. Additionally, the computer analysis of COVID-19 involvement was compared against a human rating provided by radiological experts. Results: The results showed a higher degree of infiltration and collapse in the lower lobes compared to the upper lobes (P<0.05). No significant difference was detected in the COVID-19-related involvement of the left and right lower lobes. The right middle lobe demonstrated lower involvement compared to the right lower lobes (P<0.05). When examining the regions, significantly more COVID-19 involvement was found when comparing the posterior vs. the anterior halves and the lower vs. the upper half of the lungs. Patients, who required ICU admission during their treatment exhibited significantly higher COVID-19 involvement in their lung parenchyma according to computer analysis, compared to patients who remained in general wards. Patients with more than 40% COVID-19 involvement were almost exclusively treated in intensive care. A high correlation was observed between computer detection of COVID-19 affections and the rating by radiological experts. Conclusions: The findings suggest that the extent of lung involvement, particularly in the lower lobes, dorsal lungs, and lower half of the lungs, may be associated with the need for ICU admission in patients with COVID-19. Computer analysis showed a high correlation with expert rating, highlighting its potential utility in clinical settings for assessing lung involvement. This information may help guide clinical decision-making and resource allocation during ongoing or future pandemics. Further studies with larger sample sizes are warranted to validate these findings.
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BACKGROUND: Ultrahigh dose-rate radiation (UHDR) produces less hydrogen peroxide (H2O2) in pure water, as suggested by some experimental studies, and is used as an argument for the validity of the theory that FLASH spares the normal tissue due to less reactive oxygen species (ROS) production. In contrast, most Monte Carlo simulation studies suggest the opposite. PURPOSE: We aim to unveil the effect of UHDR on H2O2 production in pure water and its underlying mechanism, to serve as a benchmark for Monte Carlo simulation. We hypothesized that the reaction of solvated electrons ( e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ ) removing hydroxyl radicals (â¢OH), the precursor of H2O2, is the reason why UHDR leads to a lower G-value (molecules/100 eV) for H2O2 (G[H2O2]), because: 1, the third-order reaction between e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ and â¢OH is more sensitive to increased instantaneous ROS concentration by UHDR than a two-order reaction of â¢OH self-reaction producing H2O2; 2, e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ has two times higher diffusion coefficient and higher reaction rate constant than that of â¢OH, which means e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ would dominate the competition for â¢OH and benefit more from the inter-track effect of UHDR. Meanwhile, we also experimentally verify the theory of long-lived radicals causing lower G(H2O2) in conventional irradiation, which is mentioned in some simulation studies. METHODS AND MATERIALS: H2O2 was measured by Amplex UltraRed assay. 430.1 MeV/u carbon ions (50 and 0.1 Gy/s), 9 MeV electrons (600 and 0.62 Gy/s), and 200 kV x-ray tube (10 and 0.1 Gy/s) were employed. For three kinds of water (real hypoxic: 1% O2; hypoxic: 1% O2 and 5% CO2; and normoxic: 21% O2), unbubbled and bubbled samples with N2O, the scavenger of e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , were irradiated by carbon ions and electrons with conventional and UHDR at different absolute dose levels. Normoxic water dissolved with sodium nitrate (NaNO3), another scavenger of e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , and bubbled with N2O was irradiated by x-ray to verify the results of low-LET electron beam. RESULTS: UHDR leads to a lower G(H2O2) than conventional irradiation. O2 and CO2 can both increase G(H2O2). N2O increases G(H2O2) of both UHDR and conventional irradiation and eliminates the difference between them for carbon ions. However, N2O decreases G(H2O2) in electron conventional irradiation but increases G(H2O2) in the case of UHDR, ending up with no dose-rate dependency of G(H2O2). Three-spilled carbon UHDR does not have a lower G(H2O2) than one-spilled UHDR. However, the electron beam shows a lower G(H2O2) for three-spilled UHDR than for one-spilled UHDR. Normoxic water with N2O or NaNO3 can both eliminate the dose rate dependency of H2O2 production for x-ray. CONCLUSIONS: UHDR has a lower G(H2O2) than the conventional irradiation for both high LET carbon and low LET electron and x-ray beams. Both scavengers for e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , N2O and NaNO3, eliminate the dose-rate dependency of G(H2O2), which suggests e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ is the reason for decreased G(H2O2) for UHDR. Three-spilled UHDR versus one-spilled UHDR indicates that the assumption of residual radicals reducing G(H2O2) of conventional irradiation may only be valid for low LET electron beam.