biostudies-literatureUnknown40(1)Noll E<h4>Objective</h4>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.<h4>Design</h4>Single centre, retrospective, observational study.<h4>Measurements</h4>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 attAnaesthesia, critical care & pain medicine100780https://www.ebi.ac.uk/biostudies/studies/S-EPMC7664353biostudies-literatureA novel, automated, quantification of abnormal lung parenchyma in patients with COVID-19 infection: Initial description of feasibility and association with clinical outcome.PMC7664353Diemunsch PSchneider FGoichot BOhana MSoler LPottecher JBennett-Guerrero EVeillon FLudes POMeyer NNoll EfalseA novel, automated, quantification of abnormal lung parenchyma in patients with COVID-19 infection: Initial description of feasibility and association with clinical outcome.<h4>Objective</h4>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.<h4>Design</h4>Single centre, retrospective, observational study.<h4>Measurements</h4>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 att2021-01-01T00:00:00Z2021 Feb2025-04-26T06:59:33.797Z2020-11-22T09:49:31ZS-EPMC76643533319763810.1016/j.accpm.2020.10.014