ABSTRACT
Background: The aim of the current study was to investigate the distribution and extent of lung involvement in patients with COVID-19 with AI-supported, automated computer analysis and to assess the relationship between lung involvement and the need for intensive care unit (ICU) admission. A secondary aim was to compare the performance of computer analysis with the judgment of radiological experts. 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 computed tomography (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 analyzed. 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 of the lungs 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 expert rating by radiological experts. Conclusion: 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.
ABSTRACT
OBJECTIVES: Organ-based tube current modulation aims to reduce exposure to radiosensitive organs like the breasts by considering their anatomical location and altering tube current during rotation. Former phantom studies demonstrated a dose reduction of 20-37 %. Our study aimed to estimate the potential of dose reduction with this technique in relation to the actual location of breast tissue in a large clinical cohort. METHODS: A 1-year cohort of chest CTs of females (N=1,263) was retrospectively evaluated. To estimate the relative dose effect, breast location was analysed by measuring the angle range of glandular tissue within the different dose zones. Relative exposure compared with constant tube current was calculated. Descriptive statistics and Wilcoxon-test were applied. RESULTS: Only 63 % of angle range of glandular breast tissue was found inside the reduced dose zone. The estimated mean relative dose reduction was lower than observed in former phantom studies(16 % vs. 20-37 %) but still significant compared to constant tube current (p<0.0001). CONCLUSIONS: Although organ-based tube current modulation results in a significant reduction of breast exposure compared to non-modulated irradiation, the technique cannot unfold its full potential, because breast tissue is often located outside the reduced dose zone, resulting in significantly lower dose reduction than expected. KEY POINTS: ⢠OBTCM results in significant dose reduction compared to constant tube current scans. ⢠A substantial portion of glandular tissue lies outside the reduced dose zone. ⢠Potential dose reduction using organ-based tube current modulation may be overestimated.
