Year: 2021
Type: article
Study design: Observational Study
Abstract: A better understanding of temporal relationships between chest CT and labs may provide a reference for disease severity over the disease course. Generalized curves of lung opacity volume and density over time can be used as standardized references from well before symptoms develop to over a month after recovery, when residual lung opacities remain. 739 patients with COVID-19 underwent CT and RT-PCR in an outbreak setting between January 21st and April 12th, 2020. 29 of 739 patients had serial exams (121 CTs and 279 laboratory measurements) over 50 ± 16 days, with an average of 4.2 sequential CTs each. Sequential volumes of total lung, overall opacity and opacity subtypes (ground glass opacity [GGO] and consolidation) were extracted using deep learning and manual segmentation. Generalized temporal curves of CT and laboratory measurements were correlated. Lung opacities appeared 3.4 ± 2.2 days prior to symptom onset. Opacity peaked 1 day after symptom onset. GGO onset was earlier and resolved later than consolidation. Lactate dehydrogenase, and C-reactive protein peaked earlier than procalcitonin and leukopenia. The temporal relationships of quantitative CT features and clinical labs have distinctive patterns and peaks in relation to symptom onset, which may inform early clinical course in patients with mild COVID-19 pneumonia, or may shed light upon chronic lung effects or mechanisms of medical countermeasures in clinical trials.
Source: Scientific Reports
Authors: Michael T. Kassin, Nicole Varble, Maxime Blain, Sheng Xu, Evrim B. Turkbey, Stephanie Harmon, Dong Yang, Ziyue Xu, Holger Roth, Daguang Xu, Mona Flores, Amel Amalou, Kaiyun Sun, Sameer Kadri, Francesca Patella, Maurizio Cariati, Alice Scarabelli, Elvira Stellato, Anna Maria Ierardi, Gianpaolo Carrafiello, Peng An, Baris Turkbey, Bradford J. Wood
Institutions: National Institutes of Health, National Cancer Institute, National Institutes of Health Clinical Center, Frederick National Laboratory for Cancer Research, Nvidia (United States), Fogarty International Center, Azienda Socio Sanitaria Territoriale Santi Paolo e Carlo, University of Milan, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Hubei University of Medicine, Xiang Yang No.1 People's Hospital, National Institute of Biomedical Imaging and Bioengineering
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,990
OpenAlex ID: W3138664636
