Multicenter Assessment of CT Pneumonia Analysis Prototype for Predicting Disease Severity and Patient Outcome

Abstract

To perform a multicenter assessment of the CT Pneumonia Analysis prototype for predicting disease severity and patient outcome in COVID-19 pneumonia both without and with integration of clinical information. Our IRB-approved observational study included consecutive 241 adult patients (> 18 years; 105 females; 136 males) with RT-PCR-positive COVID-19 pneumonia who underwent non-contrast chest CT at one of the two tertiary care hospitals (site A: Massachusetts General Hospital, USA; site B: Firoozgar Hospital Iran). We recorded patient age, gender, comorbid conditions, laboratory values, intensive care unit (ICU) admission, mechanical ventilation, and final outcome (recovery or death). Two thoracic radiologists reviewed all chest CTs to record type, extent of pulmonary opacities based on the percentage of lobe involved, and severity of respiratory motion artifacts. Thin-section CT images were processed with the prototype (Siemens Healthineers) to obtain quantitative features including lung volumes, volume and percentage of all-type and high-attenuation opacities (≥ −200 HU), and mean HU and standard deviation of opacities within a given lung region. These values are estimated for the total combined lung volume, and separately for each lung and each lung lobe. Multivariable analyses of variance (MANOVA) and multiple logistic regression were performed for data analyses. About 26% of chest CTs (62/241) had moderate to severe motion artifacts. There were no significant differences in the AUCs of quantitative features for predicting disease severity with and without motion artifacts (AUC 0.94-0.97) as well as for predicting patient outcome (AUC 0.7-0.77) (p > 0.5). Combination of the volume of all-attenuation opacities and the percentage of high-attenuation opacities (AUC 0.76-0.82, 95% confidence interval (CI) 0.73-0.82) had higher AUC for predicting ICU admission than the subjective severity scores (AUC 0.69-0.77, 95% CI 0.69-0.81). Despite a high frequency of motion artifacts, quantitative features of pulmonary opacities from chest CT can help differentiate patients with favorable and adverse outcomes.

CT Quantification of COVID-19 Pneumonia at Admission Can Predict Progression to Critical Illness: A Retrospective Multicenter Cohort Study

“…Previous studies have shown that quantitative CT is comparable or superior to visual CT score in assessment of the severity of COVID-19 (28,45,46). Recently, several studies have used quantitative CT to predict clinical outcomes via AI software in patients with COVID-19 (43,47,48). Liu et al found that quantitative CT features on days 0 and 4 as well as changes from days 0 to 4 could predict the progression to severe illness in COVID-19 patients, which outperformed the acute physiology and chronic health evaluation II score, NLR, and D-Dimer (43).…”

“…Liu et al found that quantitative CT features on days 0 and 4 as well as changes from days 0 to 4 could predict the progression to severe illness in COVID-19 patients, which outperformed the acute physiology and chronic health evaluation II score, NLR, and D-Dimer (43). Homayounieh et al found that despite a high frequency of motion artifacts, quantitative features of pulmonary opacities from chest CT can help stratify patients with favorable and adverse outcomes (47). Salvatore et al demonstrated that quantification of the consolidation, emphysema, and residual healthy lung parenchyma on chest CT images were independent predictors of outcome in patients with COVID-19 pneumonia (48).…”

COVID-19 pandemic in flu season. Chest computed tomography – what we know so far

“…The prototype estimates: lung volume (in ml), percentage of all-attenuation opacities (POO) and their volume, percentage of high-attenuation opacities (PHO) and their volume, lung severity score (LSS – measures the extent of all-attenuation in each lobe), and mean HU and standard deviations for lung parenchyma and pulmonary opacities ( Figure 7 ). The values are given separately for both lungs combined, for each lung, and for each lobe [ 44 ]. Moreover, the prototype helps to assess COVID-19 probability, especially with conjunction with RT-PCR tests, and when there are limited resources and the crunch of time (the evidence is, however, still preliminary) [ 45 ].…”

“…Although the prototype is still not permitted in clinical use, it gives particularly important data and seems to be an interesting and important proposal for further studies [ 44 ].…”

The Imaging Informatics Response to a Pandemic

“…Fortunately, CT has been shown to be a sensitive but only slightly less specific triaging tool that can supplement and even substitute for PCR testing where needed [1]. Even as PCR and other forms of serological testing became widely available, CT and chest radiography imaging features were shown to continue to aid both diagnosis and prognosis [2,3].…”