Characteristic and quantifiable COVID-19-like abnormalities in CT- and PET/CT-imaged lungs of SARS-CoV-2-infected crab-eating macaques (Macaca fascicularis)

感染 SARS-CoV-2 的食蟹猕猴(Macaca fascicularis)的肺部 CT 和 PET/CT 成像显示存在特征性和可量化的 COVID-19 样异常

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作者:Courtney L Finch, Ian Crozier, Ji Hyun Lee, Russ Byrum, Timothy K Cooper, Janie Liang, Kaleb Sharer, Jeffrey Solomon, Philip J Sayre, Gregory Kocher, Christopher Bartos, Nina M Aiosa, Marcelo Castro, Peter A Larson, Ricky Adams, Brett Beitzel, Nicholas Di Paola, Jeffrey R Kugelman, Jonathan R Kurtz,

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing an exponentially increasing number of coronavirus disease 19 (COVID-19) cases globally. Prioritization of medical countermeasures for evaluation in randomized clinical trials is critically hindered by the lack of COVID-19 animal models that enable accurate, quantifiable, and reproducible measurement of COVID-19 pulmonary disease free from observer bias. We first used serial computed tomography (CT) to demonstrate that bilateral intrabronchial instillation of SARS-CoV-2 into crab-eating macaques (Macaca fascicularis) results in mild-to-moderate lung abnormalities qualitatively characteristic of subclinical or mild-to-moderate COVID-19 (e.g., ground-glass opacities with or without reticulation, paving, or alveolar consolidation, peri-bronchial thickening, linear opacities) at typical locations (peripheral>central, posterior and dependent, bilateral, multi-lobar). We then used positron emission tomography (PET) analysis to demonstrate increased FDG uptake in the CT-defined lung abnormalities and regional lymph nodes. PET/CT imaging findings appeared in all macaques as early as 2 days post-exposure, variably progressed, and subsequently resolved by 6-12 days post-exposure. Finally, we applied operator-independent, semi-automatic quantification of the volume and radiodensity of CT abnormalities as a possible primary endpoint for immediate and objective efficacy testing of candidate medical countermeasures.

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