European radiology
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Smoking is a major risk factor for both cardiovascular disease (CVD) and lung cancer. Aortic valve calcification (AVC) and coronary artery calcification (CAC) are both due to atherosclerotic disease. We aim to investigate whether AVC on low-dose CT (LDCT) predicts death from CVD in smokers beyond that provided by CAC. ⋯ • Aortic valve calcification (AVC) and coronary artery calcification (CAC) are both due to atherosclerotic disease. The prevalence of AVC in lung cancer screening cohort significantly increased with the increasing severity of CAC. • CAC and AVC were significant predictors of cardiovascular disease (CVD) death when considered alone. Participants who underwent lung cancer screening with AVC > 0 and CAC ≥ 4 had more than a 2-fold increased risk of CVD death than the group with AVC = 0 and CAC < 4, when adjusted for other risk factors.
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To compare the chest computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) to other non-COVID viral pneumonia. ⋯ • Most common CT findings of coronavirus disease 2019 (COVID-19) were a predominant pattern of ground-glass opacity (GGO), followed by a mixed pattern of GGO and consolidation, bilateral disease, peripheral distribution, and lower lobe involvement. • Most frequent CT findings of non-COVID viral pneumonia were a predominantly mixed pattern of GGO and consolidation, followed by a predominant pattern of GGO, bilateral disease, random or diffuse distribution, and lower lobe involvement. • COVID-19 pneumonia presented a higher prevalence of peripheral distribution, and involvement of upper and middle lobes compared with non-COVID viral pneumonia.
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Observational Study
Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation.
Lombardy (Italy) was the epicentre of the COVID-19 pandemic in March 2020. The healthcare system suffered from a shortage of ICU beds and oxygenation support devices. In our Institution, most patients received chest CT at admission, only interpreted visually. Given the proven value of quantitative CT analysis (QCT) in the setting of ARDS, we tested QCT as an outcome predictor for COVID-19. ⋯ • Quantitative computer-aided analysis of chest CT (QCT) provides new metrics of COVID-19. • The compromised lung volume measured in the - 500, 100 HU interval predicts oxygenation support and intubation and is a risk factor for in-hospital death. • Compromised lung values in the 6-23% range prompt oxygenation therapy; values above 23% increase the need for intubation.
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To develop and validate a radiomics model for predicting 2019 novel coronavirus (COVID-19) pneumonia. ⋯ • A radiomics model showed good performance for prediction 2019 novel coronavirus pneumonia and favorable discrimination for other types of pneumonia on CT images. • A central or peripheral distribution, a maximum lesion range > 10 cm, the involvement of all five lobes, hilar and mediastinal lymph node enlargement, and no pleural effusion is associated with an increased risk of 2019 novel coronavirus pneumonia. • A radiomics model was superior to a clinical model in predicting 2019 novel coronavirus pneumonia.
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To determine normal pericoronary adipose tissue mean attenuation (PCATMA) values for left the anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) in patients without plaques on coronary CT angiography (cCTA), taking into account tube voltage influence. ⋯ • In patients without plaque on cCTA, PCATMA differs slightly by coronary artery (LAD, LCX, RCA). • Tube voltage of cCTA affects PCATMA measurement, with mean PCATMA increasing linearly with increasing kV. • For longitudinal cCTA analysis of PCATMA , the use of equal kV setting is strongly recommended.