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.

Despite increasing evidence that uveitis is common and consequential in survivors of Ebola virus disease (EVD), the host-pathogen determinants of the clinical phenotype are undefined, including the pathogenetic role of persistent viral antigen, ocular tissue-specific immune responses, and histopathologic characterization. Absent sampling of human intraocular fluids and tissues, these questions might be investigated in animal models of disease; however, challenges intrinsic to the nonhuman primate model and the animal biosafety level 4 setting have historically limited inquiry. In a rhesus monkey survivor of experimental Ebola virus (EBOV) infection, we observed and documented the clinical, virologic, immunologic, and histopathologic features of severe uveitis. Here we show the clinical natural history, resultant ocular pathology, intraocular antigen-specific antibody detection, and persistent intraocular EBOV RNA detected long after clinical resolution. The association of persistent EBOV RNA as a potential driver of severe immunopathology has pathophysiologic implications for understanding, preventing, and mitigating vision-threatening uveitis in EVD survivors.

Significance: Ebola virus (EBOV) infection is a severe, often fatal disease with poorly understood pathophysiology. Here, we performed [ ¹⁸ F]-DPA-714 Positron Emission Tomography (PET) in a macaque model of EBOV infection to longitudinally track and quantify the translocator protein (TSPO), an immune cell marker. The imaging findings, along with immunohistology and other disease markers, showed increasing stem cell proliferation in the bone marrow, along with progressive monocytic and lymphocytic loss in the spleen and lungs. This study provides real-time noninvasive assessment of EBOV pathogenesis and disease progression, as well as the associated host responses, at the organ level. This approach can be similarly used to study other inflammatory and infectious diseases and to test the efficacy of newly developed therapeutics and vaccines.

Ebola virus (EBOV) causes neurological symptoms yet its effects on the central nervous system (CNS) are not well-described. Here, we longitudinally assess the acute effects of EBOV on the brain, using quantitative MR-relaxometry, 18F-Fluorodeoxyglucose PET and immunohistochemistry in a monkey model. We report blood–brain barrier disruption, likely related to high cytokine levels and endothelial viral infection, with extravasation of fluid, Gadolinium-based contrast material and albumin into the extracellular space. Increased glucose metabolism is also present compared to the baseline, especially in the deep gray matter and brainstem. This regional hypermetabolism corresponds with mild neuroinflammation, sporadic neuronal infection and apoptosis, as well as increased GLUT3 expression, consistent with increased neuronal metabolic demands. Neuroimaging changes are associated with markers of disease progression including viral load and cytokine/chemokine levels. Our results provide insight into the pathophysiology of CNS involvement with EBOV and may help assess vaccine/treatment efficacy in real time.

As of May 8, 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused 514 million confirmed coronavirus disease 2019 (COVID-19) cases and over 6 million COVID-19 confirmed deaths worldwide.^1,2 The efficacy of recently approved medical countermeasures for COVID-19 may be circumvented by emergent SARS-CoV-2 variants that are more transmissible and immune-evasive.³ Data from patients during the first few months of the COVID-19 pandemic (in early 2020) showed that chest CT is sensitive to the detection of the radiographic lung abnormalities associated with COVID-19.⁴ Independent of SARS-CoV-2 variants, pathogenesis is similar, and computed tomography (CT) continues to be an option for determining prognosis. However, the use of medical imaging as a means of evaluating medical countermeasure efficacy in randomized clinical trials is critically hindered by the lack of standardized quantitative image analysis methods and reliable animal models.⁵ In animal models of severe COVID-19, quantitative image analysis methods enable accurate, quantifiable, unbiased, and reproducible measurements of COVID-19 pulmonary disease from medical images.⁶ In particular, noninvasive quantitative imaging biomarkers that do not require serial euthanasia are essential to the characterization of disease severity, progression, and pathogenesis in animal models.^{7 – 12} Quantitation of COVID-19-like lung abnormalities using multimodality imaging biomarkers, including volumetric assessment of radiodensity (CT), has been described in crab-eating (cynomolgus) macaques (Macaca fascicularis) exposed to SARS-CoV-2.⁶

Background/Objective: Computed tomography (CT) can be used to non-invasively assess the health of the liver; however, radiologist evaluation and simple thresholding alone are insufficient for diagnosis of hepatic steatosis, necessitating biopsies. This study explored CT radiomics and machine learning to enable non-invasive, objective, and quantitative prediction of steatosis severity across the macaque liver. Methods: In this retrospective study, CT images of 42 crab-eating macaques (age [yr] = 6.1 ± 1.7; sex [male/female] = 26/16) with varying degrees of hepatic steatosis were analyzed, and the results were compared to histology-based steatosis scores of livers from the same animals. After extracting radiomic features, a thorough array of statistical analyses, feature selection techniques, and machine learning models were applied to identify a distinct radiomic signature of histologically defined hepatic steatosis. Results: We identified 12 radiomic features that correlated with steatosis scores, and hierarchical clustering based on radiomic attributes alone revealed clusters roughly aligning with steatosis severity groups. The k-nearest neighbors model architecture best predicted histopathologic steatosis scores in both classification and regression tasks (area under the receiver operating characteristic curve [AUC ROC] = 0.89 ± 0.09; root-mean-square error [RMSE] = 0.60 ± 0.10). Feature analyses identified seven key radiomic features (six first-order features and one gray-level co-occurrence matrix feature) that were most important when predicting steatosis. Conclusions: We identified a CT radiomic signature of steatosis and demonstrated that histology-based steatosis scores can be predicted non-invasively and objectively using machine learning and CT radiomics as a potential alternative to invasive core biopsies. Given the strong similarities in liver structure, liver function, and hepatic steatosis pathophysiology between macaques and humans, these findings have the potential to translate to humans.