A novel, automated, quantification of abnormal lung parenchyma in patients with COVID-19 infection: Initial description of feasibility and association with clinical outcome

OBJECTIVE: Ground-glass opacities are the most frequent radiologic features of COVID-19 patients. We aimed to determine the feasibility of automated lung volume measurements, including ground-glass volumes, on the CT of suspected COVID-19 patients. Our goal was to create an automated and quantitative measure of ground-glass opacities from lung CT images that could be used clinically for diagnosis, triage and research. DESIGN: Single centre, retrospective, observational study. MEASUREMENTS: Demographic data, respiratory support treatment (synthetised in the maximal respiratory severity score) and CT-images were collected. Volume of abnormal lung parenchyma was measured with conventional semi-automatic software and with a novel automated algorithm based on voxels X-Ray attenuation. We looked for the relationship between the automated and semi-automated evaluations. The association between the ground-glass opacities volume and the maximal respiratory severity score was assessed. MAIN RESULTS: Thirty-seven patients were included in the main outcome analysis. The mean duration of automated and semi-automated volume measurement process were 15 (2) and 93 (41) min, respectively (p = 8.05*10(−8)). The intraclass correlation coefficient between the semi-automated and automated measurement of ground-glass opacities and restricted normally aerated lung were both superior to 0.99. The association between the automated measured lung volume and the maximal clinical severity score was statistically significant for the restricted normally aerated (p = 0.0097, effect-size: −385 mL) volumes and for the ratio of ground-glass opacities/restricted normally aerated volumes (p = 0.027, effect-size: 3.3). CONCLUSION: The feasibility and preliminary validity of automated impaired lung volume measurements in a high-density COVID-19 cluster was confirmed by our results.