Comparative Analysis of Clinical and CT Findings in Patients with SARS-CoV-2 Original Strain, Delta and Omicron Variants.

OBJECTIVES: To compare the clinical characteristics and chest CT findings of patients infected with Omicron and Delta variants and the original strain of COVID-19. METHODS: A total of 503 patients infected with the original strain (245 cases), Delta variant (90 cases), and Omicron variant (168 cases) were retrospectively analyzed. The differences in clinical severity and chest CT findings were analyzed. We also compared the infection severity of patients with different vaccination statuses and quantified pneumonia by a deep-learning approach. RESULTS: The rate of severe disease decreased significantly from the original strain to the Delta variant and Omicron variant (27% vs. 10% vs. 4.8%, p < 0.001). In the Omicron group, 44% (73/168) of CT scans were categorized as abnormal compared with 81% (73/90) in the Delta group and 96% (235/245, p < 0.05) in the original group. Trends of a gradual decrease in total CT score, lesion volume, and lesion CT value of AI evaluation were observed across the groups (p < 0.001 for all). Omicron patients who received the booster vaccine had less clinical severity (p = 0.015) and lower lung involvement rate than those without the booster vaccine (36% vs. 57%, p = 0.009). CONCLUSIONS: Compared with the original strain and Delta variant, the Omicron variant had less clinical severity and less lung injury on CT scans.

Longitudinal Assessment of Chest CT Findings and Pulmonary Function after COVID-19 Infection.

Background Information on pulmonary sequelae and pulmonary function 2 years after recovery from SARS-CoV-2 infection is lacking. Purpose To longitudinally assess changes in chest CT abnormalities and pulmonary function in individuals after SARS-CoV-2 infection. Materials and Methods In this prospective study, participants discharged from the hospital after SARS-CoV-2 infection from January 20 to March 10, 2020, were considered for enrollment. Participants without chest CT scans at admission or with complete resolution of lung abnormalities at discharge were excluded. Serial chest CT scans and pulmonary function test results were obtained 6 months (June 20 to August 31, 2020), 12 months (December 20, 2020, to February 3, 2021), and 2 years (November 16, 2021, to January 10, 2022) after symptom onset. The term interstitial lung abnormality (ILA) and two subcategories, fibrotic ILAs and nonfibrotic ILAs, were used to describe residual CT abnormalities on follow-up CT scans. Differences between groups were compared with the χ2 test, Fisher exact test, or independent samples t test. Results Overall, 144 participants (median age, 60 years [range, 27-80 years]; 79 men) were included. On 2-year follow-up CT scans, 39% of participants (56 of 144) had ILAs, including 23% (33 of 144) with fibrotic ILAs and 16% (23 of 144) with nonfibrotic ILAs. The remaining 88 of 144 participants (61%) showed complete radiologic resolution. Over 2 years, the incidence of ILAs gradually decreased (54%, 42%, and 39% of participants at 6 months, 12 months, and 2 years, respectively; P < .001). Respiratory symptoms (34% vs 15%, P = .007) and abnormal diffusing capacity of lung for carbon monoxide (43% vs 20%, P = .004) occurred more frequently in participants with ILAs than in those with complete radiologic resolution. Conclusion More than one-third of participants had persistent interstitial lung abnormalities 2 years after COVID-19 infection, which were associated with respiratory symptoms and decreased diffusion pulmonary function. Chinese Clinical Trial Registry no. ChiCTR2000038609 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by van Beek in this issue.

Simulation of COVID-19 symptoms in a genetically engineered mouse model: implications for the long haulers.

The ongoing pandemic (also known as coronavirus disease-19; COVID-19) by a constantly emerging viral agent commonly referred as the severe acute respiratory syndrome corona virus 2 or SARS-CoV-2 has revealed unique pathological findings from infected human beings, and the postmortem observations. The list of disease symptoms, and postmortem observations is too long to mention; however, SARS-CoV-2 has brought with it a whole new clinical syndrome in "long haulers" including dyspnea, chest pain, tachycardia, brain fog, exercise intolerance, and extreme fatigue. We opine that further improvement in delivering effective treatment, and preventive strategies would be benefited from validated animal disease models. In this context, we designed a study, and show that a genetically engineered mouse expressing the human angiotensin converting enzyme 2; ACE-2 (the receptor used by SARS-CoV-2 agent to enter host cells) represents an excellent investigative resource in simulating important clinical features of the COVID-19. The ACE-2 mouse model (which is susceptible to SARS-CoV-2) when administered with a recombinant SARS-CoV-2 spike protein (SP) intranasally exhibited a profound cytokine storm capable of altering the physiological parameters including significant changes in cardiac function along with multi-organ damage that was further confirmed via histological findings. More importantly, visceral organs from SP treated mice revealed thrombotic blood clots as seen during postmortem examination. Thus, the ACE-2 engineered mouse appears to be a suitable model for studying intimate viral pathogenesis thus paving the way for identification, and characterization of appropriate prophylactics as well as therapeutics for COVID-19 management.

Mechanism of Blood‐Heart‐Barrier Leakage: Implications for COVID‐19 induced Cardiovascular Injury

Although blood‐heart‐barrier (BHB) leakage is the hallmark of congestive (cardio‐pulmonary) heart failure (CHF), the primary cause of death in elderly, and during viral myocarditis resulting from the novel coronavirus such as the severe acute respiratory syndrome novel corona virus 2 (SARS‐CoV‐2) known as COVI‐19, the mechanism is unclear. The goal of this project is to determine the mechanism BHB in CHF. Endocardial endothelium (EE) is the BHB against leakage of blood from endocardium to the interstitium;however, this BHB is broken during CHF. Previous studies from our laboratory, and others have shown a robust activation of matrix metalloproteinase‐9 (MMP‐9) during CHF. MMP‐9 degrades connexins leading to EE dysfunction. We demonstrated juxtacrine coupling of EE with myocyte, and mitochondria (Mito) but how it works still remains at large. To test whether activation of MMP‐9 causes EE barrier dysfunction, we hypothesized that if that were the case then treatment with hydroxychloroquine (HCQ) could, in fact, inhibit MMP‐9, and thus preserve the EE barrier/juxtacrine signaling, and synchronous endothelial‐myocyte coupling. To determine this, CHF was created by aorta‐vena cava fistula (AVF) employing the mouse as a model system. The sham, and AVF mice were treated with HCQ. Cardiac hypertrophy, tissue remodeling‐induced mitochondrial‐myocyte, and endothelial‐myocyte contractions were measured. Microvascular leakage was measured using FITC‐albumin conjugate. The cardiac function was measured by echocardiography (Echo). Results suggest that MMP‐9 activation, endocardial endothelial leakage, endothelial‐myocyte (E‐M) uncoupling, dyssynchronous mitochondrial fusion‐fission (Mfn2/Drp1 ratio) and mito‐myocyte uncoupling in AVF heart failure were found to be rampant however, treatment with HCQ successfully mitigated some of the deleterious cardiac alterations during CHF. The findings have direct relevance to the gamut of cardiac manifestations, and the resultant phenotypes arising from the ongoing complications of COVID‐19 in human subjects.

Quantitative inspiratory-expiratory chest CT findings in COVID-19 survivors at the 6-month follow-up.

We evaluated pulmonary sequelae in COVID-19 survivors by quantitative inspiratory-expiratory chest CT (QCT) and explored abnormal pulmonary diffusion risk factors at the 6-month follow-up. This retrospective study enrolled 205 COVID-19 survivors with baseline CT data and QCT scans at 6-month follow-up. Patients without follow-up pulmonary function tests were excluded. All subjects were divided into group 1 (carbon monoxide diffusion capacity [DLCO] < 80% predicted, n = 88) and group 2 (DLCO ≥ 80% predicted, n = 117). Clinical characteristics and lung radiological changes were recorded. Semiquantitative total CT score (0-25) was calculated by adding five lobes scores (0-5) according to the range of lesion involvement (0: no involvement; 1: < 5%; 2: 5-25%; 3: 26-50%; 4: 51-75%; 5: > 75%). Data was analyzed by two-sample t-test, Spearman test, etc. 29% survivors showed air trapping by follow-up QCT. Semiquantitative CT score and QCT parameter of air trapping in group 1 were significantly greater than group 2 (p < 0.001). Decreased DLCO was negatively correlated with the follow-up CT score for ground-glass opacity (r = - 0.246, p = 0.003), reticulation (r = - 0.206, p = 0.002), air trapping (r = - 0.220, p = 0.002) and relative lung volume changes (r = - 0.265, p = 0.001). COVID-19 survivors with lung diffusion deficits at 6-month follow-up tended to develop air trapping, possibly due to small-airway impairment.

Deep diagnostic agent forest (DDAF): A deep learning pathogen recognition system for pneumonia based on CT.

BACKGROUND: Even though antibiotics agents are widely used, pneumonia is still one of the most common causes of death around the world. Some severe, fast-spreading pneumonia can even cause huge influence on global economy and life security. In order to give optimal medication regimens and prevent infectious pneumonia's spreading, recognition of pathogens is important. METHOD: In this single-institution retrospective study, 2,353 patients with their CT volumes are included, each of whom was infected by one of 12 known kinds of pathogens. We propose Deep Diagnostic Agent Forest (DDAF) to recognize the pathogen of a patient based on ones' CT volume, which is a challenging multiclass classification problem, with large intraclass variations and small interclass variations and very imbalanced data. RESULTS: The model achieves 0.899 ± 0.004 multi-way area under curves of receiver (AUC) for level-I pathogen recognition, which are five rough groups of pathogens, and 0.851 ± 0.003 AUC for level-II recognition, which are 12 fine-level pathogens. The model also outperforms the average result of seven human readers in level-I recognition and outperforms all readers in level-II recognition, who can only reach an average result of 7.71 ± 4.10% accuracy. CONCLUSION: Deep learning model can help in recognition pathogens using CTs only, which might help accelerate the process of etiological diagnosis.

Mechanism of Blood-Heart-Barrier Leakage: Implications for COVID-19 Induced Cardiovascular Injury.

Although blood-heart-barrier (BHB) leakage is the hallmark of congestive (cardio-pulmonary) heart failure (CHF), the primary cause of death in elderly, and during viral myocarditis resulting from the novel coronavirus variants such as the severe acute respiratory syndrome novel corona virus 2 (SARS-CoV-2) known as COVID-19, the mechanism is unclear. The goal of this project is to determine the mechanism of the BHB in CHF. Endocardial endothelium (EE) is the BHB against leakage of blood from endocardium to the interstitium; however, this BHB is broken during CHF. Previous studies from our laboratory, and others have shown a robust activation of matrix metalloproteinase-9 (MMP-9) during CHF. MMP-9 degrades the connexins leading to EE dysfunction. We demonstrated juxtacrine coupling of EE with myocyte and mitochondria (Mito) but how it works still remains at large. To test whether activation of MMP-9 causes EE barrier dysfunction, we hypothesized that if that were the case then treatment with hydroxychloroquine (HCQ) could, in fact, inhibit MMP-9, and thus preserve the EE barrier/juxtacrine signaling, and synchronous endothelial-myocyte coupling. To determine this, CHF was created by aorta-vena cava fistula (AVF) employing the mouse as a model system. The sham, and AVF mice were treated with HCQ. Cardiac hypertrophy, tissue remodeling-induced mitochondrial-myocyte, and endothelial-myocyte contractions were measured. Microvascular leakage was measured using FITC-albumin conjugate. The cardiac function was measured by echocardiography (Echo). Results suggest that MMP-9 activation, endocardial endothelial leakage, endothelial-myocyte (E-M) uncoupling, dyssynchronous mitochondrial fusion-fission (Mfn2/Drp1 ratio), and mito-myocyte uncoupling in the AVF heart failure were found to be rampant; however, treatment with HCQ successfully mitigated some of the deleterious cardiac alterations during CHF. The findings have direct relevance to the gamut of cardiac manifestations, and the resultant phenotypes arising from the ongoing complications of COVID-19 in human subjects.