Role of computed tomography in predicting critical disease in patients with covid-19 pneumonia: A retrospective study using a semiautomatic quantitative method

Abstract

Background So far, only a few studies evaluated the correlation between CT features and clinical outcome in patients with COVID-19 pneumonia. Purpose To evaluate CT ability in differentiating critically ill patients requiring invasive ventilation from patients with less severe disease. Methods We retrospectively collected data from patients admitted to our institution for COVID-19 pneumonia between March 5th-24th. Patients were considered critically ill or non-critically ill, depending on the need for mechanical ventilation. CT images from both groups were analyzed for the assessment of qualitative features and disease extension, using a quantitative semiautomatic method. We evaluated the differences between the two groups for clinical, laboratory and CT data. Analyses were conducted on a per-protocol basis. Results 189 patients were analyzed. PaO 2 /FIO 2 ratio and oxygen saturation (SaO 2 ) were decreased in critically ill patients. At CT, mixed pattern (ground glass opacities (GGO) and consolidation) and GGO alone were more frequent respectively in critically ill and in non-critically ill patients (p < 0.05). Lung volume involvement was significantly higher in critically ill patients (38.5 % vs. 5.8 %, p < 0.05). A cut-off of 23.0 % of lung involvement showed 96 % sensitivity and 96 % specificity in distinguishing critically ill patients from patients with less severe disease. The fraction of involved lung was related to lactate dehydrogenase (LDH) levels, PaO 2 /FIO 2 ratio and SaO 2 (p < 0.05). Conclusion Lung disease extension, assessed using quantitative CT, has a significant relationship with clinical severity and may predict the need for invasive ventilation in patients with COVID-19.

COVID-19 Imaging: What We Know Now and What Remains Unknown

“…Another semiquantitative study of 106 inpatients with COVID-19 pneumonia showed significant positive correlations between CT severity and levels of inflammatory cytokines such as interleukin-6 and interleukin-2R (27). Additional studies have observed similar correlations (22,28,29) CT severity scoring may show promise for clinical triage and assessment of prognosis, and higher CT severity scores predict clinical outcomes in COVID-19 (29,30). In a study of 572 hospitalized patients, 70% of patients with total lung involvement greater than 50% were admitted to the intensive care unit or died within seven days of a CT performed at admission, while these rates were lower for lung involvement of 26-50% (41%) and <25% (23%) (18).…”

“…Several studies have shown correlations between extent of parenchymal involvement at CT and clinical assessment of COVID-19 disease severity as defined by parameters such as severity of symptoms, oxygenation status, and certain laboratory measures of infection and inflammation. Semiquantitative and quantitative studies have shown significantly higher CT severity scores for patients with severe and critical disease than for those with less severe disease (17,(22)(23)(24)(25). For example, in one study of 189 inpatients, the average volume of lung involvement measured by semiautomated segmentation of parenchymal opacities on CT was higher in critically ill patients (38.5%) than in non-critically ill patients (5.8%), with a threshold of 23% distinguishing these two groups with 96% sensitivity and specificity (22).…”

“…Semiquantitative and quantitative studies have shown significantly higher CT severity scores for patients with severe and critical disease than for those with less severe disease (17,(22)(23)(24)(25). For example, in one study of 189 inpatients, the average volume of lung involvement measured by semiautomated segmentation of parenchymal opacities on CT was higher in critically ill patients (38.5%) than in non-critically ill patients (5.8%), with a threshold of 23% distinguishing these two groups with 96% sensitivity and specificity (22). In another study of 78 patients, a semiquantitative total CT severity score ranging from 0 to 20 distinguished mild, moderate, and severe clinical disease with high accuracy (82.6% sensitivity and 100% specificity for a cutoff score of 7.5) and a high interclass correlation between readers (0.976) (17).…”

Correlation between Chest CT Severity Scores and the Clinical Parameters of Adult Patients with COVID-19 Pneumonia

“…Moreover, the disease severity can be ascertained from the imaging findings, significantly supporting the clinicians in their clinical judgment and ensuring effective and timely management [ 7 ]. Prognosis can also be affected by the severity of the disease in the critically ill patients allowing appropriate selection of early involvement of the intensive care [ 8 , 9 ].…”

Spotlight on Cardiovascular Scoring Systems in Covid-19: Severity Correlations in Real-world Setting

“…Recent reports suggest that the CXR [16] as well as chest CT [17] are able to predict whether the course of the disease will be moderate or severe in relation to the extent and morphology of pulmonary infiltrates on admission.…”