CT in coronavirus disease 2019 (COVID-19): a systematic review of chest CT findings in 4410 adult patients

Impact of the coronavirus disease 2019 pandemic on hospital admissions for idiopathic pulmonary fibrosis: a nationwide population-based study

BACKGROUND

Previous studies have consistently reported a decrease in hospital admissions for respiratory diseases during the coronavirus disease 2019 (COVID-19) pandemic. However, the impact of the pandemic on idiopathic pulmonary fibrosis (IPF) admissions remains unknown.

METHODS

This study used data from the Korean National Health Insurance Service database. IPF was defined based on the International Classification of Diseases 10th Revision (ICD-10) and rare intractable disease (RID) codes. The rate of IPF admissions was calculated by dividing the number of IPF admissions by the prevalence of IPF. The rate of IPF admissions during the COVID-19 pandemic (2020-2021) was compared with the mean rate of admissions during the prepandemic period (2017-2019) and presented as the rate ratio (RR). A sensitivity analysis was conducted on patients treated with systemic corticosteroids during IPF admission.

RESULTS

In patients with IPF defined based on the ICD-10 (analysis 1), the RRs significantly decreased from March in 2020 to December 2021, except for June and September in 2020. Similarly, in patients with IPF defined based on the ICD-10 and RID (analysis 2), the RRs significantly decreased from March 2020 to December 2021, except for June and September 2020. In the sensitivity analysis of analysis 1, the RR significantly decreased in 2020 (0.93; 95%CI: 0.88-0.99; P = 0.029), whereas the RR in 2021 was not significantly different. The RRs in the sensitivity analysis of analysis 2 significantly decreased to 0.85 (0.79-0.92; P < 0.001) in 2020 and 0.82 (0.76-0.88; P < 0.001) in 2021. In the subgroup analysis, the rates of IPF admissions significantly decreased in 2020 and 2021 across both sexes, patients aged ≥ 60 years, and all household income groups.

CONCLUSIONS

The rate of IPF admissions significantly decreased during the COVID-19 pandemic. This result indicates that preventive measures against COVID-19 may effectively mitigate IPF exacerbation. Therefore, it is assumed that there is a close relationship between respiratory viral infections and IPF exacerbations.

Exploring the prevalence and chest CT predictors of Long COVID in children: a comprehensive study from Shanghai and Linyi

Introduction

COVID-19 constitutes a pandemic of significant detriment to human health. This study aimed to investigate the prevalence of Long COVID following SARS-CoV-2 infection, analyze the potential predictors of chest CT for the development of Long COVID in children.

Methods

A cohort of children who visited the respiratory outpatient clinics at Shanghai Children's Medical Center or Linyi Maternal and Child Health Care Hospital from December 2022 to February 2023 and underwent chest CT scans within 1 week was followed up. Data on clinical characteristics, Long COVID symptoms, and chest CT manifestations were collected and analyzed. Multivariate logistic regression models and decision tree models were employed to identify factors associated with Long COVID.

Results

A total of 416 children were included in the study. Among 277 children who completed the follow-up, the prevalence of Long COVID was 23.1%. Chronic cough, fatigue, brain fog, and post-exertional malaise were the most commonly reported symptoms. In the decision tree model for Long COVID, the presence of increased vascular markings, the absence of normal CT findings, and younger age were identified as predictors associated with a higher likelihood of developing Long COVID in children. However, no significant correlation was found between chest CT abnormality and the occurrence of Long COVID.

Discussion

Long COVID in children presents a complex challenge with a significant prevalence rate of 23.1%. Chest CT scans of children post-SARS-CoV-2 infection, identified as abnormal with increased vascular markings, indicate a higher risk of developing Long COVID.

Interest of Chest CT to Assess the Prognosis of SARS-CoV-2 Pneumonia: An In-Hospital-Based Experience in Sub-Saharan Africa

Methods

We included all patients with respiratory symptoms (dyspnea, fever, and cough) and/or respiratory failure admitted to the SOS Médecins de nuit SARL hospital, DR Congo, during the 2nd and 3rd waves of the COVID-19 pandemic. The diagnosis of COVID-19 was established based on RT-PCR anti-SARS-CoV-2 tests (G1 (RT-PCR positive) vs. G2 (RT-PCR negative)), and all patients had a chest CT on the day of admission. We retrieved the digital files of patients, precisely the clinical, biological, and chest CT parameters of the day of admission as well as the vital outcome (survival or death). Chest CT were read by a very high-definition console using Advantage Windows software and exported to the hospital network using the RadiAnt DICOM viewer. To determine the threshold for the percentage of lung lesions associated with all-cause mortality, we used ROC curves. Factors associated with death, including chest CT parameters, were investigated using logistic regression analysis.

Results

The study included 200 patients (average age 56.2 ± 15.2 years; 19% diabetics and 4.5% obese), and COVID-19 was confirmed among 56% of them (G1). Chest CT showed that ground glass (72.3 vs. 39.8%), crazy paving (69.6 vs. 17.0%), and consolidation (83.9 vs. 22.7%), with bilateral and peripheral locations (68.8 vs. 30.7%), were more frequent in G1 vs. G2 (p < 0.001). No case of pulmonary embolism and fibrosis had been documented. The lung lesions affecting 30% of the parenchyma were informative in predicting death (area under the ROC curve at 0.705, p = 0.017). In multivariate analysis, a percentage of lesions affecting 50% of the lung parenchyma increased the risk of dying by 7.194 (1.656-31.250).

Conclusion

The chest CT demonstrated certain characteristic lesions more frequently in patients in whom the diagnosis of COVID-19 was confirmed. The extent of lesions affecting at least half of the lung parenchyma from the first day of admission to hospital increases the risk of death by a factor of 7.

Quantitative CT Texture Analysis of COVID-19 Hospitalized Patients during 3-24-Month Follow-Up and Correlation with Functional Parameters

BACKGROUND

To quantitatively evaluate CT lung abnormalities in COVID-19 survivors from the acute phase to 24-month follow-up. Quantitative CT features as predictors of abnormalities' persistence were investigated.

METHODS

Patients who survived COVID-19 were retrospectively enrolled and underwent a chest CT at baseline (T0) and 3 months (T3) after discharge, with pulmonary function tests (PFTs). Patients with residual CT abnormalities repeated the CT at 12 (T12) and 24 (T24) months after discharge. A machine-learning-based software, CALIPER, calculated the CT percentage of the whole lung of normal parenchyma, ground glass (GG), reticulation (Ret), and vascular-related structures (VRSs). Differences (Δ) were calculated between time points. Receiver operating characteristic (ROC) curve analyses were performed to test the baseline parameters as predictors of functional impairment at T3 and of the persistence of CT abnormalities at T12.

RESULTS

The cohort included 128 patients at T0, 133 at T3, 61 at T12, and 34 at T24. The GG medians were 8.44%, 0.14%, 0.13% and 0.12% at T0, T3, T12 and T24. The Ret medians were 2.79% at T0 and 0.14% at the following time points. All Δ significantly differed from 0, except between T12 and T24. The GG and VRSs at T0 achieved AUCs of 0.73 as predictors of functional impairment, and area under the curves (AUCs) of 0.71 and 0.72 for the persistence of CT abnormalities at T12.

CONCLUSIONS

CALIPER accurately quantified the CT changes up to the 24-month follow-up. Resolution mostly occurred at T3, and Ret persisting at T12 was almost unchanged at T24. The baseline parameters were good predictors of functional impairment at T3 and of abnormalities' persistence at T12.

The Multisystem Impact of Long COVID: A Comprehensive Review

(1) Background: COVID-19 was responsible for the latest pandemic, shaking and reshaping healthcare systems worldwide. Its late clinical manifestations make it linger in medical memory as a debilitating illness over extended periods. (2) Methods: the recent literature was systematically analyzed to categorize and examine the symptomatology and pathophysiology of Long COVID across various bodily systems, including pulmonary, cardiovascular, gastrointestinal, neuropsychiatric, dermatological, renal, hematological, and endocrinological aspects. (3) Results: The review outlines the diverse clinical manifestations of Long COVID across multiple systems, emphasizing its complexity and challenges in diagnosis and treatment. Factors such as pre-existing conditions, initial COVID-19 severity, vaccination status, gender, and age were identified as influential in the manifestation and persistence of Long COVID symptoms. This condition is highlighted as a debilitating disease capable of enduring over an extended period and presenting new symptoms over time. (4) Conclusions: Long COVID emerges as a condition with intricate multi-systemic involvement, complicating its diagnosis and treatment. The findings underscore the necessity for a nuanced understanding of its diverse manifestations to effectively manage and address the evolving nature of this condition over time.

Natural language processing to convert unstructured COVID-19 chest-CT reports into structured reports

Background

Structured reporting has been demonstrated to increase report completeness and to reduce error rate, also enabling data mining of radiological reports. Still, structured reporting is perceived by radiologists as a fragmented reporting style, limiting their freedom of expression.

Purpose

A deep learning-based natural language processing method was developed to automatically convert unstructured COVID-19 chest CT reports into structured reports.

Methods

Two hundred-two COVID-19 chest CT were retrospectively reviewed by two experienced radiologists, who wrote for each exam a free-form text radiological report and coherently filled the template provided by the Italian Society of Medical and Interventional Radiology, used as ground-truth. A semi-supervised convolutional neural network was implemented to extract 62 categorical variables from the report. Two iterations were carried-out, the first without fine-tuning, the second one performing a fine-tuning. The performance was measured using the mean accuracy and the F1 mean score. An error analysis was performed to identify errors entirely attributable to incorrect processing of the model.

Results

The algorithm achieved a mean accuracy of 93.7% and an F1 score 93.8% in the first iteration. Most of the errors were exclusively attributable to wrong inference (46%). In the second iteration the model achieved for both parameters 95,8% and percentage of errors attributable to wrong inference decreased to 26%.

Conclusions

The convolutional neural network achieved an optimal performance in the automated conversion of free-form text into structured radiological reports, overcoming all the limitation attributed to structured reporting and finally paving the way for data mining of radiological report.

Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes

BACKGROUND

COVID-19 is a pandemic disease affecting predominantly the respiratory apparatus with clinical manifestations ranging from asymptomatic to respiratory failure. Chest CT is a crucial tool in diagnosing and evaluating the severity of pulmonary involvement through dedicated scoring systems. Nonetheless, many questions regarding the relationship of radiologic and clinical features of the disease have emerged in multidisciplinary meetings. The aim of this retrospective study was to explore such relationship throughout an innovative and alternative approach.

MATERIALS AND METHODS

This study included 550 patients (range 25-98 years; 354 males, mean age 66.1; 196 females, mean age 70.9) hospitalized for COVID-19 with available radiological and clinical data between 1 March 2021 and 30 April 2022. Radiological data included CO-RADS, chest CT score, dominant pattern, and typical/atypical findings detected on CT examinations. Clinical data included clinical score and outcome. The relationship between such features was investigated through the development of the main four frequently asked questions summarizing the many issues arisen in multidisciplinary meetings, as follows 1) CO-RADS, chest CT score, clinical score, and outcomes; 2) the involvement of a specific lung lobe and outcomes; 3) dominant pattern/distribution and severity score for the same chest CT score; 4) additional factors and outcomes.

RESULTS

1) If CT was suggestive for COVID, a strong correlation between CT/clinical score and prognosis was found; 2) Middle lobe CT involvement was an unfavorable prognostic criterion; 3) If CT score < 50%, the pattern was not influential, whereas if CT score > 50%, crazy paving as dominant pattern leaded to a 15% increased death rate, stacked up against other patterns, thus almost doubling it; 4) Additional factors usually did not matter, but lymph-nodes and pleural effusion worsened prognosis.

CONCLUSIONS

This study outlined those radiological features of COVID-19 most relevant towards disease severity and outcome with an innovative approach.

Cough and sputum in long COVID are associated with severe acute COVID-19: a Japanese cohort study

BACKGROUND

Multiple prolonged symptoms are observed in patients who recover from acute coronavirus disease 2019 (COVID-19), defined as long COVID. Cough and sputum are presented by patients with long COVID during the acute and post-acute phases. This study aimed to identify specific risk factors for cough and sputum in patients with long COVID.

METHODS

Hospitalized patients with COVID-19 aged 18 years were enrolled in a multicenter cohort study at 26 medical institutions. Clinical data during hospitalization and patient-reported outcomes after discharge were collected from medical records, paper-based questionnaires, and smartphone apps.

RESULTS

At the 3-, 6-, and 12-month follow-ups, there were no differences in the incidence rates of wet and dry coughs. In contrast, the proportion of patients presenting sputum without coughing increased over time compared to those with sputum and coughing. Univariate analyses of cough and sputum at all follow-up visits identified intermittent mandatory ventilation (IMV), smoking, and older age as risk factors for prolonged symptoms. At the 12-month follow-up, persistent cough and sputum were associated with the characteristics of severe COVID-19 based on imaging findings, renal and liver dysfunction, pulmonary thromboembolism, and higher serum levels of LDH, KL-6, and HbA1C. The Kaplan-Meier curves showed that the severity of acute COVID-19 infection was correlated with prolonged cough and sputum production. Multivariable logistic regression analysis showed that IMV ventilator management were independent risk factors for prolonged cough and sputum at 12 months.

CONCLUSIONS

In a Japanese population with long COVID, prolonged cough and sputum production were closely associated with severe COVID-19. These findings emphasize that a preventive approach including appropriate vaccination and contact precaution and further development of therapeutic drugs for COVID-19 are highly recommended for patients with risk factors for severe infection to avoid persistent respiratory symptoms.

Moxibustion Treatment of COVID-19 and Rehabilitation Period of COVID-19: A Scoping Review

Objective: The aim of this study is to provide a scoping review of the clinical literature on moxibustion therapy for the treatment of Coronavirus disease 2019 (COVID-19). Design: The PubMed, Embase, Cochrane Library, MEDLINE, CNKI, Wanfang, and VIP databases were searched from January 1, 2020, to August 31, 2022. Essential data were extracted from each article, and the data were displayed using tables and graphs. The study did not require IRB approval. Results: This scoping review included 14 research articles: 8 observational studies, 5 randomized controlled trials, and 1 nonrandomized clinical trial. All the studies were published by Chinese scholars. The findings revealed that moxibustion can contribute to reducing the symptoms of patients with COVID-19, improving inflammation and immune indicators, and shortening the time of nucleic acid negative conversion. Moxibustion confers curative effects on patients of all ages and degrees of illness. In addition, moxibustion can optimize the prognosis of patients in the rehabilitation period. The most commonly chosen acupoints are ST36, RN4, RN8, and RN12. No side effect was mentioned in the included studies. Conclusion: Moxibustion can produce a good effect in the treatment and rehabilitation of patients with COVID-19. It is safe, effective, simple, and noninvasive and should be included as standard care.

Pleural Disease in Acute COVID-19 Pneumonia: A Single Center Retrospective Cohort Study

BACKGROUND

Pleural diseases encompass pleural effusion and pneumothorax (PTX), both of which were uncommon in coronavirus disease of 2019 (COVID-19). We aimed to describe the frequency, characteristics, and main outcomes of these conditions in patients with COVID-19 pneumonia.

METHODS

We performed a retrospective cohort analysis of inpatients with COVID-19 pneumonia between January 1, 2020 and January 1, 2022, at Beth Israel Deaconess Medical Center in Boston, Massachusetts.

RESULTS

Among 4419 inpatients with COVID-19 pneumonia, 109 (2.5%) had concurrent pleural disease. Ninety-four (2.1%) had pleural effusion (50% seen on admission) and 15 (0.3%) had PTX, both with higher rates of underlying conditions such as heart failure, liver disease, kidney disease, and malignancy. A total of 28 (30%) pleural effusions were drained resulting in 32% being exudative, 43% pseudoexudative, and 25% transudative. Regarding PTX, 5 (33%) were spontaneous and 10 (67%) were due to barotrauma while on mechanical ventilation. We found that the presence of underlying lung disease was not associated with an increased risk of developing PTX. In addition, patients with pleural disease had a higher incidence of severe or critical illness as represented by intensive care unit admission and intubation, longer hospital and intensive care unit stay, and a higher mortality rate as compared with patients without the pleural disease.

CONCLUSION

Pleural effusions and pneumothoraces are infrequent findings in patients admitted due to COVID-19 pneumonia, worsened outcomes in these patients likely reflect an interplay between the severity of inflammation and parenchymal injury due to COVID-19 disease and underlying comorbidities.

Which sequence should be used in the thorax magnetic resonance imaging of COVID-19: a comparative study

Background and aim

To evaluate and compare magnetic resonance imaging (MRI) sequences that could potentially be used in the diagnosis of coronavirus disease 2019 (COVID-19).

Materials and methods

Included in the study were 42 patient who underwent thorax computed tomography (CT) for COVID-19 pneumonia and thorax MRI for any reason within 24 h after CT. The T2-weighted fast spin echo periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) (T2W-FSE-P), fast imaging employing steady-state acquisition, T2 fat-saturated FSE, axial T1 liver acquisition with volume acceleration (LAVA) and single-shot FSE images were compared in terms of their ability to show COVID-19 findings.

Results

The mean age of the patients was 47.2 ± 24 years. Of the patients, 22 were male (52.4%) and 20 (47.6%) were female. The interobserver intraclass coefficient (ICC) for the image quality score was the highest in the T2W-FSE-P sequence and lowest in the T1 LAVA sequence. All of the lesion-based evaluations of the interobserver agreement were statistically significant, with the kappa value varying between 0.798 and 0.998.

Conclusion

All 5 sequences evaluated in the study were successful in showing the parenchymal findings of COVID-19. Since the T2W-FSE-P sequence had the best scores in both interobserver agreement and ICC for the image quality score, it was considered that it can be included in thorax MRI examinations to assist the diagnosis of COVID-19.

Pulmonary fibrosis: A short- or long-term sequelae of severe COVID-19?

The pandemic of coronavirus disease 2019 (COVID‑19), caused by a novel severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), has caused an enormous impact on the global healthcare. SARS-CoV-2 infection primarily targets the respiratory system. Although most individuals testing positive for SARS-CoV-2 present mild or no upper respiratory tract symptoms, patients with severe COVID-19 can rapidly progress to acute respiratory distress syndrome (ARDS). ARDS-related pulmonary fibrosis is a recognized sequelae of COVID-19. Whether post-COVID-19 lung fibrosis is resolvable, persistent, or even becomes progressive as seen in human idiopathic pulmonary fibrosis (IPF) is currently not known and remains a matter of debate. With the emergence of effective vaccines and treatments against COVID-19, it is now important to build our understanding of the long-term sequela of SARS-CoV-2 infection, to identify COVID-19 survivors who are at risk of developing chronic pulmonary fibrosis, and to develop effective anti-fibrotic therapies. The current review aims to summarize the pathogenesis of COVID-19 in the respiratory system and highlights ARDS-related lung fibrosis in severe COVID-19 and the potential mechanisms. It envisions the long-term fibrotic lung complication in COVID-19 survivors, in particular in the aged population. The early identification of patients at risk of developing chronic lung fibrosis and the development of anti-fibrotic therapies are discussed.

Dominant CT Patterns and Immune Responses during the Early Infection Phases of Different SARS-CoV-2 Variants

Ground-glass opacity (GGO) and organizing pneumonia (OP) are dominant pulmonary CT lesions associated with COVID-19. However, the role of different immune responses in these CT patterns remains unclear, particularly following the emergence of the Omicron variant. In this prospective observational study, we recruited patients hospitalized with COVID-19, before and after the emergence of Omicron variants. Semi-quantitative CT scores and dominant CT patterns were retrospectively determined for all patients within five days of symptom onset. Serum levels of IFN-α, IL-6, CXCL10, and VEGF were assessed using ELISA. Serum-neutralizing activity was measured using a pseudovirus assay. We enrolled 48 patients with Omicron variants and 137 with precedent variants. While the frequency of GGO patterns was similar between the two groups, the OP pattern was significantly more frequent in patients with precedent variants. In patients with precedent variants, IFN-α and CXCL10 levels were strongly correlated with GGO, whereas neutralizing activity and VEGF were correlated with OP. The correlation between IFN-α levels and CT scores was lower in patients with Omicron than in those with precedent variants. Compared to preceding variants, infection with the Omicron variant is characterized by a less frequent OP pattern and a weaker correlation between serum IFN-α and CT scores.

A Case Series of Persistent SARS-CoV-2 Infection in Immunocompromised Pediatric Patients

Diagnosis and management of SARS-CoV-2 infection in immunocompromised patients are extremely challenging. These patients can have atypical clinical courses, and there is a paucity of data regarding clinical features, diagnostic findings, and the safety and efficacy of available therapeutic agents used to treat COVID-19 in these patients. In this case series, we report atypical COVID-19 presentations in 4 immunocompromised pediatric patients who were admitted with acute respiratory failure after an initial diagnosis of COVID-19 a few weeks earlier. All patients included in this cohort showed persistent worsening respiratory symptoms for several weeks before hospital presentation. While they manifested common COVID-19 sequelae, they also had rare COVID-19-related pathognomonic and radiographic features developed along their hospital course. Multiple therapeutic agents were used in their COVID-19 management, including corticosteroids, remdesivir, and monoclonal antibodies. All three patients who have received concurrent therapy with remdesivir, hydrocortisone, and monoclonal antibodies survived, and only one patient died as a direct complication of COVID-19 ARDS with secondary pulmonary mucormycosis. Our outcomes suggest the potential benefit of remdesivir use in combination with hydrocortisone and monoclonal antibodies in the management of severe COVID-19 ARDS in this group, as well as the importance of close surveillance and early administration of broad empirical antimicrobial and antifungal coverage if clinically indicated in this high-risk population.

COVID-19: Findings in nuclear medicine from head to toe

COVID-19 is a multisystemic disease, and hence its potential manifestations on nuclear medicine imaging can extend beyond the lung. Therefore, it is important for the nuclear medicine physician to recognize these manifestations in the clinic. While FDG-PET/CT is not indicated routinely in COVID-19 evaluation, its unique capability to provide a functional and anatomical assessment of the entire body means that it can be a powerful tool to monitor acute, subacute, and long-term effects of COVID-19. Single-photon scintigraphy is routinely used to assess conditions such as pulmonary embolism, cardiac ischemia, and thyroiditis, and COVID-19 may present in these studies. The most common nuclear imaging finding of COVID-19 vaccination to date is hypermetabolic axillary lymphadenopathy. This may pose important diagnostic and management dilemmas in oncologic patients, particularly those with malignancies where the axilla constitutes a lymphatic drainage area. This article aims to summarize the relevant literature published since the beginning of the pandemic on the intersection between COVID-19 and nuclear medicine.

Otolaryngologic Symptom Severity Post SARS-CoV-2 Infection

Objective(s)

To assess laryngologic symptomatology following SARS-CoV-2 infection and determine whether symptom severity correlates with disease severity.

Methods

Single-institution survey study in participants with documented SARS-CoV-2 infection between March 2020 and February 2021. Data acquired included demographic, infection severity characteristics, comorbidities, and current upper aerodigestive symptoms via validated patient reported outcome measures.  Primary outcomes of interest were scores of symptom severity questionnaires. COVID-19 severity was defined by hospitalization status. Descriptive subgroup analyses were performed to investigate differences in demographics, comorbidities, and symptom severity in hospitalized participants stratified by ICU status. Multivariate logistical regression was used to evaluate significant differences in symptom severity scores by hospitalization status.

Results

Surveys were distributed to 5300 individuals with upper respiratory infections. Ultimately, 470 participants with COVID-19 were included where 352 were hospitalized and 118 were not hospitalized. Those not hospitalized were younger (45.87 vs. 56.28 years), more likely female (74.17 vs. 58.92%), and less likely white (44.17 vs. 52.41%). Severity of dysphonia, dyspnea, cough, and dysphagia was significantly worse in hospitalized patients overall and remained worse at all time points. Cough severity paradoxically worsened in hospitalized respondents over time. Dyspnea scores remained abnormally elevated in respondents even 12 months after resolution of infection.

Conclusion

Results indicate that laryngologic symptoms are expected to be worse in patients hospitalized with COVID-19. Dyspnea and cough symptoms can be expected to persist or even worsen by one-year post infection in those who were hospitalized. Dysphagia and dysphonia symptoms were mild. Non-hospitalized participants tended to have minimal residual symptoms by one year after infection.

Association of subpleural ground-glass opacities with respiratory failure and RNAemia in COVID-19

OBJECTIVES

To examine the radiological patterns specifically associated with hypoxemic respiratory failure in patients with coronavirus disease (COVID-19).

METHODS

We enrolled patients with COVID-19 confirmed by qPCR in this prospective observational cohort study. We explored the association of clinical, radiological, and microbiological data with the development of hypoxemic respiratory failure after COVID-19 onset. Semi-quantitative CT scores and dominant CT patterns were retrospectively determined for each patient. The microbiological evaluation included checking the SARS-CoV-2 viral load by qPCR using nasal swab and serum specimens.

RESULTS

Of the 214 eligible patients, 75 developed hypoxemic respiratory failure and 139 did not. The CT score was significantly higher in patients who developed hypoxemic respiratory failure than in those did not (median [interquartile range]: 9 [6-14] vs 0 [0-3]; p < 0.001). The dominant CT patterns were subpleural ground-glass opacities (GGOs) extending beyond the segmental area (n = 44); defined as "extended GGOs." Multivariable analysis showed that hypoxemic respiratory failure was significantly associated with extended GGOs (odds ratio [OR] 29.6; 95% confidence interval [CI], 9.3-120; p < 0.001), and a CT score  > 4 (OR 12.7; 95% CI, 5.3-33; p < 0.001). The incidence of RNAemia was significantly higher in patients with extended GGOs (58.3%) than in those without any pulmonary lesion (14.7%; p < 0.001).

CONCLUSIONS

Extended GGOs along the subpleural area were strongly associated with hypoxemia and viremia in patients with COVID-19.

KEY POINTS

• Extended ground-glass opacities (GGOs) along the subpleural area and a CT score  > 4, in the early phase of COVID-19, were independently associated with the development of hypoxemic respiratory failure. • The absence of pulmonary lesions on CT in the early phase of COVID-19 was associated with a lower risk of developing hypoxemic respiratory failure. • Compared to patients with other CT findings, the extended GGOs and a higher CT score were also associated with a higher incidence of RNAemia.

Parenchymal lung abnormalities following hospitalisation for COVID-19 and viral pneumonitis: a systematic review and meta-analysis

INTRODUCTION

Persisting respiratory symptoms in COVID-19 survivors may be related to development of pulmonary fibrosis. We assessed the proportion of chest CT scans and pulmonary function tests consistent with parenchymal lung disease in the follow-up of people hospitalised with COVID-19 and viral pneumonitis.

METHODS

Systematic review and random effects meta-analysis of proportions using studies of adults hospitalised with SARS-CoV-2, SARS-CoV, MERS-CoV or influenza pneumonia and followed up within 12 months. Searches performed in MEDLINE and Embase. Primary outcomes were proportion of radiological sequelae on CT scans; restrictive impairment; impaired gas transfer. Heterogeneity was explored in meta-regression.

RESULTS

Ninety-five studies (98.9% observational) were included in qualitative synthesis, 70 were suitable for meta-analysis including 60 SARS-CoV-2 studies with a median follow-up of 3 months. In SARS-CoV-2, the overall estimated proportion of inflammatory sequelae was 50% during follow-up (0.50; 95% CI 0.41 to 0.58; I2=95%), fibrotic sequelae were estimated in 29% (0.29; 95% CI 0.22 to 0.37; I2=94.1%). Follow-up time was significantly associated with estimates of inflammatory sequelae (-0.036; 95% CI -0.068 to -0.004; p=0.029), associations with fibrotic sequelae did not reach significance (-0.021; 95% CI -0.051 to 0.009; p=0.176). Impaired gas transfer was estimated at 38% of lung function tests (0.38 95% CI 0.32 to 0.44; I2=92.1%), which was greater than restrictive impairment (0.17; 95% CI 0.13 to 0.23; I2=92.5%), neither were associated with follow-up time (p=0.207; p=0.864).

DISCUSSION

Sequelae consistent with parenchymal lung disease were observed following COVID-19 and other viral pneumonitis. Estimates should be interpreted with caution due to high heterogeneity, differences in study casemix and initial severity.

PROSPERO REGISTRATION NUMBER

CRD42020183139.

Pleural Effusion in COVID-19 Pneumonia: Clinical and Prognostic Implications-An Observational, Retrospective Study

BACKGROUND

COVID-19 presents with a wide spectrum of clinical and radiological manifestations, including pleural effusion. The prevalence and prognostic impact of pleural effusion are still not entirely clear.

PATIENTS AND METHODS

This is a retrospective, single-center study including a population of consecutive patients admitted to the University Hospital of Cisanello (Pisa) from March 2020 to January 2021 with a positive SARS-CoV-2 nasopharyngeal swab and SARS-CoV-2-related pneumonia. The patients were divided into two populations based on the presence (n = 150) or absence (n = 515) of pleural effusion on chest CT scan, excluding patients with pre-existing pleural effusion. We collected laboratory data (hemoglobin, leukocytes, platelets, C-reactive protein, procalcitonin), worst PaO₂/FiO₂ ratio as an index of respiratory gas exchange impairment, the extent of interstitial involvement related to SARS-CoV-2 pneumonia and data on intensity of care, length of stay and outcome (discharge or death).

RESULTS

The prevalence of pleural effusion was 23%. Patients with pleural effusion showed worse gas exchange (p < 0.001), longer average hospital stay (p < 0.001), need for more health care resources (p < 0.001) and higher mortality (p < 0.001) compared to patients without pleural effusion. By multivariate analysis, pleural effusion was found to be an independent negative prognostic factor compared with other variables such as increased C-reactive protein, greater extent of pneumonia and older age. Pleural effusion was present at the first CT scan in most patients (68%).

CONCLUSIONS

Pleural effusion associated with SARS-CoV-2 pneumonia is a relatively frequent finding that is confirmed to be a negative prognostic factor. Identifying early prognostic factors in an endemic-prone disease such as COVID-19 is necessary to optimize its clinical management. Further clinical studies aimed at better characterizing pleural effusion in these patients will be appropriate in order to clarify its pathogenetic role.

Effect of vaccine on prognosis and mortality in COVID-19

INTRODUCTION:The purpose of our study is to reveal the factors affecting the clinical course of the Covid-19 infection and mortality in the immunized and non-immunized 65-year-old and older patients. METHOD AND MATERIAL: The study was conducted by screening the files of 1,642 65-year-old and older Covid-19 cases in total.1337 cases enrolled in the study were categorized into two groups as follows: the patients vaccinated with the 2nd dose of CoronaVac but infected with Covid-19 after the 14-day period during which immunization is supposed to develop (Group I) and the patients who have never been vaccinated, who have been vaccinated with a single dose, or who have been infected with Covid-19 before the 14-day period is completed in spite of being vaccinated with the 2nd dose (Group II).The groups were compared with each other with regard to mortality and the factors affecting mortality. RESULTS: The length of ICU stay and the total length of hospital stay were significantly longer in Group II than Group I ( p

Effect of Tocilizumab on Mortality in Patients with SARS-CoV-2 Pneumonia Caused by Delta or Omicron Variants: A Propensity-Matched Analysis in Nimes University Hospital, France

We aimed to assess the factors associated with mortality in patients treated with tocilizumab for a SARS-CoV-2 pneumonia due to the delta or omicron variants of concern (VOC) and detect an effect of tocilizumab on mortality. We conducted a prospective cohort study in a tertiary hospital from 1 August 2021 to 31 March 2022 including patients with severe COVID-19, treated with tocilizumab. Factors associated with mortality were assessed in a Cox model; then, the 60-day mortality rates of COVID-19 patients treated with standard of care (SoC) +/- tocilizumab were compared after 1:1 propensity score matching. The mortality rate was 22% (N = 26/118) and was similar between delta and omicron cases (p = 0.6). The factors independently associated with mortality were age (HR 1.06; 95% CI (1.02-1.11), p = 0.002), Charlson index (HR 1.33; 95% CI (1.11-1.6), p = 0.002), WHO-CPS (HR 2.56; 95% CI (1.07-6.22) p = 0.03), and tocilizumab infusion within the first 48 h following hospital admission (HR 0.37, 95% CI (0.14-0.97), p = 0.04). No significant differences in mortality between the tocilizumab plus SoC and SoC alone groups (p = 0.5) were highlighted. However, the patients treated with tocilizumab within the 48 h following hospital admission had better survival (p = 0.04). In conclusion, our results suggested a protective effect on mortality of the early administration of tocilizumab in patients with severe COVID-19 regardless of the VOC involved.

Plitidepsin in adult patients with COVID-19 requiring hospital admission: A long-term follow-up analysis

Introduction

The APLICOV-PC study assessed the safety and preliminary efficacy of plitidepsin in hospitalized adult patients with COVID-19. In this follow-up study (E-APLICOV), the incidence of post-COVID-19 morbidity was evaluated and any long-term complications were characterized.

Methods

Between January 18 and March 16, 2022, 34 of the 45 adult patients who received therapy with plitidepsin in the APLICOV-PC study were enrolled in E-APLICOV (median time from plitidepsin first dose to E-APLICOV enrollment, 16.8 months [range, 15.2-19.5 months]). All patients were functionally autonomous with regard to daily living (Barthel index: 100) and had normal physical examinations.

Results

From the APLICOV-PC date of discharge to the date of the extension visit, neither Common Terminology Criteria for Adverse Events version 5.0 (CTCAE v5) grade 3-4 complications nor QT prolongation or significant electrocardiogram (EKG) abnormalities were reported. Five (14.7%) patients had another COVID-19 episode after initial discharge from APLICOV-PC, and in 2 patients (5.9%), previously unreported chest X-ray findings were documented. Spirometry and lung-diffusion tests were normal in 29 (85.3%) and 27 (79.4%) patients, respectively, and 3 patients needed additional oxygen supplementation after initial hospital discharge. None of these patients required subsequent hospital readmission for disease-related complications.

Discussion

In conclusion, plitidepsin has demonstrated a favorable long-term safety profile in adult patients hospitalized for COVID-19. With the constraints of a low sample size and a lack of control, the rate of post-COVID-19 complications after treatment with plitidepsin is in the low range of published reports. (ClinicalTrials.gov Identifier: NCT05121740; https://clinicaltrials.gov/ct2/show/NCT05121740).

Nintedanib: a review of the properties, function, and usefulness to minimize COVID-19-induced lung injury

INTRODUCTION

In severe COVID-19 patients, acute respiratory distress syndrome (ARDS)-induced lung injury regularly causes a pulmonary fibrotic phase. There is no approved therapy for the COVID-19-induced pulmonary fibrosis. However, administration of an anti-fibrotic agent, in the early acute phase of the severe COVID-19 with ARDS, may improve the infection outcomes.

AREAS COVERED

In this review, the main characteristics of nintedanib and its usefulness to treat COVID-19-induced fibrosis were studied. In July 2022, a literature search was performed from PubMed, Google Scholar, and the WHO databases for studies focusing on the properties, function, efficacy, and safety of nintedanib against different lung injuries.

EXPERT OPINION

Nintedanib interferes with lung fibrosis and tumor angiogenesis by targeting multiple receptor tyrosine kinases (RTKs). Loss of RTKs activity leads to blocking downstream signaling cascades and inhibiting the proliferation and migration of lung fibroblasts. Targeting RTKs may be useful in the treatment of COVID-19 lung fibrosis. Nintedanib may be a superior agent compared to pirfenidone for the treatment of COVID-19 ARDS-related pulmonary fibrosis. Investigation of the efficacy and safety of nintedanib in the early stages of COVID-19-induced ARDS is critical since it may decrease the oxygen dependency and degree of lung fibrosis after the hospital discharge.

In Vivo Visualization and Quantification of Neutrophil Elastase in Lungs of COVID-19 Patients: A First-in-Humans PET Study with 11C-NES

Coronavirus disease 2019 (COVID-19) can cause life-threatening lung inflammation that is thought to be mediated by neutrophils. The aim of the present work was to evaluate a novel PET tracer for neutrophil elastase (NE). Methods: In this first-in-humans study, 4 patients with hypoxia due to COVID-19 and 2 healthy controls were investigated with PET using ¹¹C-NES and ¹⁵O-water for visualization and quantification of NE and perfusion in the lungs, respectively. Results: ¹¹C-NES accumulated selectively in lung areas with COVID-19 opacities on CT scans, suggesting high levels of NE there. In the same areas, perfusion was severely reduced in comparison to healthy lung tissue as measured with ¹⁵O-water. Conclusion: The data suggest that NE is associated with severe lung inflammation in COVID-19 patients and that inhibition of NE could potentially reduce the acute inflammatory process and improve the condition.

The Hidden Pandemic of COVID-19-Induced Organizing Pneumonia

Since the beginning of the COVID-19 pandemic, clinical, radiological, and histopathological studies have provided evidence that organizing pneumonia is a possible consequence of the SARS-CoV2 infection. This post-COVID-19 organizing pneumonia (PCOP) causes persisting dyspnea, impaired pulmonary function, and produces radiological abnormalities for at least 5 weeks after onset of symptoms. While most patients with PCOP recover within a year after acute COVID-19, 5-25% of cases need specialized treatment. However, despite substantial resources allocated worldwide to finding a solution to this problem, there are no approved treatments for PCOP. Oral corticosteroids produce a therapeutic response in a majority of such PCOP patients, but their application is limited by the anticipated high-relapse frequency and the risk of severe adverse effects. Herein, we conduct a systematic comparison of the epidemiology, pathogenesis, and clinical presentation of the organizing pneumonias caused by COVID-19 as well as other viral infections. We also use the clinical efficacy of corticosteroids in other postinfection OPs (PIOPs) to predict the therapeutic response in the treatment of PCOP. Finally, we discuss the potential application of a candidate anti-inflammatory and antifibrotic therapy for the treatment of PCOP based on the analysis of the latest clinical trials data.

Traditional Chinese Medicine in Treatment of COVID-19 and Viral Disease: Efficacies and Clinical Evidence

Coronavirus disease 2019 (COVID-19) remains an uncontained, worldwide pandemic. While battling the disease in China, the Chinese government has actively promoted the use of traditional Chinese medicine, and many studies have been conducted to determine the efficacy of traditional Chinese medicine for treating COVID-19. The present review discusses the effectiveness and safety of traditional Chinese medicine in curing COVID-19 and provides clinical evidence from all confirmed cases in China. Applications of traditional Chinese medicine and specific recipes for treating other viral infections, such as those caused by severe acute respiratory syndrome coronavirus and influenza A viruses (including H1N1), are also discussed. Studies have reported that traditional Chinese medicine treatment plays a significant role in improving clinical symptoms. Therefore, further investigation may be of high translational value in revealing novel targeted therapies for COVID-19.

CD147 contributes to SARS-CoV-2-induced pulmonary fibrosis

COVID-19 patients can develop clinical and histopathological features associated with fibrosis, but the pathogenesis of fibrosis remains poorly understood. CD147 has been identified as a universal receptor for SARS-CoV-2 and its variants, which could initiate COVID-19-related cytokine storm. Here, we systemically analyzed lung pathogenesis in SARS-CoV-2- and its delta variant-infected humanized CD147 transgenic mice. Histopathology and Transmission Electron Microscopy revealed inflammation, fibroblast expansion and pronounced fibrotic remodeling in SARS-CoV-2-infected lungs. Consistently, RNA-sequencing identified a set of fibrosis signature genes. Furthermore, we identified CD147 as a crucial regulator for fibroblast activation induced by SARS-CoV-2. We found conditional knockout of CD147 in fibroblast suppressed activation of fibroblasts, decreasing susceptibility to bleomycin-induced pulmonary fibrosis. Meplazumab, a CD147 antibody, was able to inhibit the accumulation of activated fibroblasts and the production of ECM proteins, thus alleviating the progression of pulmonary fibrosis caused by SARS-CoV-2. In conclusion, we demonstrated that CD147 contributed to SARS-CoV-2-triggered progressive pulmonary fibrosis and identified CD147 as a potential therapeutic target for treating patients with post-COVID-19 pulmonary fibrosis.

Therapeutic Efficacy and Outcomes of Remdesivir versus Remdesivir with Tocilizumab in Severe SARS-CoV-2 Infection

The infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) generated many challenges to find an effective drug combination for hospitalized patients with severe forms of coronavirus disease 2019 (COVID-19) pneumonia. We conducted a retrospective cohort study, including 182 patients with severe COVID-19 pneumonia hospitalized between March and October 2021 in a Pneumology Hospital from Cluj-Napoca, Romania. Among patients treated with standard of care, 100 patients received remdesivir (R group) and 82 patients received the combination of remdesivir plus tocilizumab (RT group). We compared the clinical outcomes, the inflammatory markers, superinfections, oxygen requirement, intensive care unit (ICU) admission and mortality rate before drug administration and 7 days after in R group and RT group. Borg score and oxygen support showed an improvement in the R group (p < 0.005). Neutrophiles, C-reactive protein (CRP) and serum ferritin levels decreased significantly in RT group but with a higher rate of superinfection in this group. ICU admission and death did not differ significantly between groups. The combination of remdesivir plus tocilizumab led to a significantly improvement in the inflammatory markers and a decrease in the oxygen requirement. Although the superinfection rate was higher in RT group than in R group, no significant difference was found in the ICU admission and mortality rate between the groups.

Rapid artificial intelligence solutions in a pandemic-The COVID-19-20 Lung CT Lesion Segmentation Challenge

Artificial intelligence (AI) methods for the automatic detection and quantification of COVID-19 lesions in chest computed tomography (CT) might play an important role in the monitoring and management of the disease. We organized an international challenge and competition for the development and comparison of AI algorithms for this task, which we supported with public data and state-of-the-art benchmark methods. Board Certified Radiologists annotated 295 public images from two sources (A and B) for algorithms training (n=199, source A), validation (n=50, source A) and testing (n=23, source A; n=23, source B). There were 1,096 registered teams of which 225 and 98 completed the validation and testing phases, respectively. The challenge showed that AI models could be rapidly designed by diverse teams with the potential to measure disease or facilitate timely and patient-specific interventions. This paper provides an overview and the major outcomes of the COVID-19 Lung CT Lesion Segmentation Challenge - 2020.

Systematic lung ultrasound in Omicron-type vs. wild-type COVID-19

AIMS

Preliminary data suggested that patients with Omicron-type-Coronavirus-disease-2019 (COVID-19) have less severe lung disease compared with the wild-type-variant. We aimed to compare lung ultrasound (LUS) parameters in Omicron vs. wild-type COVID-19 and evaluate their prognostic implications.

METHODS AND RESULTS

One hundred and sixty-two consecutive patients with Omicron-type-COVID-19 underwent LUS within 48 h of admission and were compared with propensity-matched wild-type patients (148 pairs). In the Omicron patients median, first and third quartiles of the LUS-score was 5 [2-12], and only 9% had normal LUS. The majority had either mild (≤5; 37%) or moderate (6-15; 39%), and 15% (≥15) had severe LUS-score. Thirty-six percent of patients had patchy pleural thickening (PPT). Factors associated with LUS-score in the Omicron patients included ischaemic-heart-disease, heart failure, renal-dysfunction, and C-reactive protein. Elevated left-filling pressure or right-sided pressures were associated with the LUS-score. Lung ultrasound-score was associated with mortality [odds ratio (OR): 1.09, 95% confidence interval (CI): 1.01-1.18; P = 0.03] and with the combined endpoint of mortality and respiratory failure (OR: 1.14, 95% CI: 1.07-1.22; P < 0.0001). Patients with the wild-type variant had worse LUS characteristics than the matched Omicron-type patients (PPT: 90 vs. 34%; P < 0.0001 and LUS-score: 8 [5, 12] vs. 5 [2, 10], P = 0.004), irrespective of disease severity. When matched only to the 31 non-vaccinated Omicron patients, these differences were attenuated.

CONCLUSION

Lung ultrasound-score is abnormal in the majority of hospitalized Omicron-type patients. Patchy pleural thickening is less common than in matched wild-type patients, but the difference is diminished in the non-vaccinated Omicron patients. Nevertheless, even in this milder form of the disease, the LUS-score is associated with poor in-hospital outcomes.

Bronchiectasis and COVID-19 infection: a two-way street

ABSTRACT

Bronchiectasis (BE) has been linked to past viral infections such as influenza, measles, or adenovirus. Two years ago, a new pandemic viral infection severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out and it still persists today, and a significant proportion of surviving patients have radiological and clinical sequelae, including BE. Our aim was to thoroughly review the information available in the literature on the bidirectional relationship between SARS-CoV-2 infection and the development of BE, as well as the impact of this infection on patients already suffering from BE. Available information indicates that only a small percentage of patients in the acute phase of coronavirus disease 2019 (COVID-19) pneumonia develop BE, although the latter is recognized as one of the radiological sequelae of COVID-19 pneumonia, especially when it is caused by traction. The severity of the initial pneumonia is the main risk factor for the development of future BE, but during the COVID-19 pandemic, exacerbations in BE patients were reduced by approximately 50%. Finally, the impact of BE on the prognosis of patients with COVID-19 pneumonia is not yet known.

Deep Transfer Learning for COVID-19 Detection and Lesion Recognition Using Chest CT Images

Starting from December 2019, the global pandemic of coronavirus disease 2019 (COVID-19) is continuously expanding and has caused several millions of deaths worldwide. Fast and accurate diagnostic methods for COVID-19 detection play a vital role in containing the plague. Chest computed tomography (CT) is one of the most commonly used diagnosis methods. However, a complete CT-scan has hundreds of slices, and it is time-consuming for radiologists to check each slice to diagnose COVID-19. This study introduces a novel method for fast and automated COVID-19 diagnosis using the chest CT scans. The proposed models are based on the state-of-the-art deep convolutional neural network (CNN) architecture, and a 2D global max pooling (globalMaxPool2D) layer is used to improve the performance. We compare the proposed models to the existing state-of-the-art deep learning models such as CNN based models and vision transformer (ViT) models. Based off of metric such as area under curve (AUC), sensitivity, specificity, accuracy, and false discovery rate (FDR), experimental results show that the proposed models outperform the previous methods, and the best model achieves an area under curve of 0.9744 and accuracy 94.12% on our test datasets. It is also shown that the accuracy is improved by around 1% by using the 2D global max pooling layer. Moreover, a heatmap method to highlight the lesion area on COVID-19 chest CT images is introduced in the paper. This heatmap method is helpful for a radiologist to identify the abnormal pattern of COVID-19 on chest CT images. In addition, we also developed a freely accessible online simulation software for automated COVID-19 detection using CT images. The proposed deep learning models and software tool can be used by radiologist to diagnose COVID-19 more accurately and efficiently.

Clinical and computed tomography features of patients suspected of COVID-19 in the university hospital of Oran, Algeria

BACKGROUND

The analysis of the clinical and radiological characteristics of COVID-19 patients around the world observed a rich semiology, different from one country to another, and within the same country.

AIM

To analyze the clinical, computed tomography (CT) features, and the outcome of patients suspected of COVID-19 hospitalized in a COVID-19 unit of Oran university hospital (Algeria).

METHODS

We collected retrospectively the files of patients suspected of COVID-19 admitted in a COVID-19 unit during July 2020. Data were collected on standardized questionnaire with prior coding of parameters. Patients were admitted according to a triage based on their clinical situation and the chest CT aspects suggestive of COVID-19. Two physicians reviewed the high-resolution CT (HR-CT) images independently, and discrepancies were resolved by consensus with the input of two others experimented physicians.

RESULTS

112 patients (64% males, median age: 68 (18-88) years) were included. The main symptoms were dyspnea (51.7%), cough (34%), fatigue (14%). Almost the half (49.1%) of patients had hypoxemia. The HR-CT findings were typical of COVID-19 in 96% of patients. Although 61% of patients had favorable prognosis, mortality rate was 30%. Mutlivariate analysis of risk factors for death showed that patients aged > 60 years had a 4-fold risk of death (95% confidence interval: [1.27-12.58], p=0.018).

CONCLUSION

Dyspnea, cough and fatigue were predominant symptoms, moderate and severe COVID-19 characterized our patients. Age > 60 years was a major risk factor for the deaths of our patients.

AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions

Background and objective

In recent years, Artificial Intelligence has had an evident impact on the way research addresses challenges in different domains. It has proven to be a huge asset, especially in the medical field, allowing for time-efficient and reliable solutions. This research aims to spotlight the impact of deep learning and machine learning models in the detection of COVID-19 from medical images. This is achieved by conducting a review of the state-of-the-art approaches proposed by the recent works in this field.

Methods

The main focus of this study is the recent developments of classification and segmentation approaches to image-based COVID-19 detection. The study reviews 140 research papers published in different academic research databases. These papers have been screened and filtered based on specified criteria, to acquire insights prudent to image-based COVID-19 detection.

Results

The methods discussed in this review include different types of imaging modality, predominantly X-rays and CT scans. These modalities are used for classification and segmentation tasks as well. This review seeks to categorize and discuss the different deep learning and machine learning architectures employed for these tasks, based on the imaging modality utilized. It also hints at other possible deep learning and machine learning architectures that can be proposed for better results towards COVID-19 detection. Along with that, a detailed overview of the emerging trends and breakthroughs in Artificial Intelligence-based COVID-19 detection has been discussed as well.

Conclusion

This work concludes by stipulating the technical and non-technical challenges faced by researchers and illustrates the advantages of image-based COVID-19 detection with Artificial Intelligence techniques.

Evaluation of diaphragm thickness to predict intubation requirement and mortality in critical COVID-19 patients

OBJECTIVES

To investigate the value of measuring the diaphragm thickness (DT) on thorax computed tomography (CT) at intensive care unit (ICU) admission for predicting intubation requirement and mortality among COVID-19 patients.

METHODS

This study was carried out in Ankara City Hospital, Ankara, Turkey, from September 2020 to January 2021, with 94 critical COVID-19 patients. The patients' demographic characteristics, laboratory parameters, DT measurements, mechanical ventilation (MV) requirements, and mortality statuses were retrospectively screened. The relationships between DT on initial CT, MV requirement, and mortality were investigated.

RESULTS

Diaphragm thickness was lower in patients who required intubation after ICU admission than in non-intubated patients (p=0.006); it was also lower in non-survivors (p=0.009). The threshold values for MV need was 3.35 mm (p=0.004) and 3.275 mm for mortality (p=0.006), according to the receiver operating characteristic analysis used to assess the predictive potential of DT. The non-survivor group had a greater neutrophil-to-lymphocyte ratio (p=0.026). Absolute neutrophil count (p=0.017), neutrophil-to-lymphocyte ratio (p=0.010), and interleukin-6 levels (p=0.027) were higher among patients requiring MV than among non-intubated patients.

CONCLUSION

Mortality and MV requirements can be predicted from DT measurements. Diaphragm thickness can facilitate the identification of high-risk patients on CT evaluation at ICU admission.

Automatized lung disease quantification in patients with COVID-19 as a predictive tool to assess hospitalization severity

The pandemic of COVID-19 led to a dramatic situation in hospitals, where staff had to deal with a huge number of patients in respiratory distress. To alleviate the workload of radiologists, we implemented an artificial intelligence (AI) - based analysis named CACOVID-CT, to automatically assess disease severity on chest CT scans obtained from those patients. We retrospectively studied CT scans obtained from 476 patients admitted at the University Hospital of Liege with a COVID-19 disease. We quantified the percentage of COVID-19 affected lung area (% AA) and the CT severity score (total CT-SS). These quantitative measurements were used to investigate the overall prognosis and patient outcome: hospital length of stay (LOS), ICU admission, ICU LOS, mechanical ventilation, and in-hospital death. Both CT-SS and % AA were highly correlated with the hospital LOS, the risk of ICU admission, the risk of mechanical ventilation and the risk of in-hospital death. Thus, CAD4COVID-CT analysis proved to be a useful tool in detecting patients with higher hospitalization severity risk. It will help for management of the patients flow. The software measured the extent of lung damage with great efficiency, thus relieving the workload of radiologists.

Association of diaphragm thickness and density measured on chest CT with disease severity in COVID-19 patients

Introduction

A decrease in muscle mass of the diaphragm could be a significant risk factor for pneumonia. The aim of our study was to evaluate whether diaphragm thickness (DT) and density measured on chest computed tomography (CT) were associated with clinical course and mortality in adult patients with coronavirus disease 2019 (COVID-19) in emergency department admission.

Methods

We retrospectively analyzed 404 patients with a positive polymerase chain reaction test for COVID-19 and pneumonia findings on chest CT between September 1 and November 1, 2020. Bilateral DT measurements were performed at the level of the celiac artery origin, and the total mean diaphragm thickness (TMDT) was estimated. Hemidiaphragm density was measured at the level of the celiac artery origin. The relationship between demographic characteristics, comorbidities, TMDT, mean hemidiaphragm density (MHD) and clinical outcomes was investigated using the logistic regression analyses. The reliability of the measurement of the two observers was evaluated by intraclass correlation analyses.

Results

Intraclass correlation analyses demonstrated almost perfect inter-observer agreement for TMDT and substantial agreement for MHD. There was a statistically significant relationship between the presence of a thinner diaphragm and mortality (p < 0.001). Bilateral diaphragm densities were lower in the patients with severe disease and mortality (p < 0.001). The threshold values of TMDT were 3.67 mm and 3.47 mm for the prediction of ICU admission and mortality, respectively. TMDT (odds ratio [OR]: 0.634, 95% confidence interval [CI]: 0.447–0.901), age (OR: 1.053, 95% CI: 1.027–1.081) and MHD (OR: 0.920, 95% CI: 0.883–0.959) were found to be independent predictors for severe disease in the multivariable model. In addition, MHD (OR: 0.883, 95% CI: 0.827–0.942) and age (OR: 1.040, 95% CI: 1.003–1.078) were independent risk factors for mortality.

Conclusion

Our study demonstrated that a low diaphragm thickness and density measured on chest CT were associated with severe disease in patients with COVID-19 and could be evaluated as poor prognostic markers.

Conventional and pathogenic Th2 cells in inflammation, tissue repair, and fibrosis

Type 2 helper T (Th2) cells, a subset of CD4⁺ T cells, play an important role in the host defense against pathogens and allergens by producing Th2 cytokines, such as interleukin-4 (IL-4), IL-5, and IL-13, to trigger inflammatory responses. Emerging evidence reveals that Th2 cells also contribute to the repair of injured tissues after inflammatory reactions. However, when the tissue repair process becomes chronic, excessive, or uncontrolled, pathological fibrosis is induced, leading to organ failure and death. Thus, proper control of Th2 cells is needed for complete tissue repair without the induction of fibrosis. Recently, the existence of pathogenic Th2 (Tpath2) cells has been revealed. Tpath2 cells produce large amounts of Th2 cytokines and induce type 2 inflammation when activated by antigen exposure or tissue injury. In recent studies, Tpath2 cells are suggested to play a central role in the induction of type 2 inflammation whereas the role of Tpath2 cells in tissue repair and fibrosis has been less reported in comparison to conventional Th2 cells. In this review, we discuss the roles of conventional Th2 cells and pathogenic Th2 cells in the sequence of tissue inflammation, repair, and fibrosis.

Functional Alterations Due to COVID-19 Lung Lesions-Lessons From a Multicenter V/Q Scan-Based Registry

PURPOSE

In coronavirus disease 2019 (COVID-19) patients, clinical manifestations as well as chest CT lesions are variable. Lung scintigraphy allows to assess and compare the regional distribution of ventilation and perfusion throughout the lungs. Our main objective was to describe ventilation and perfusion injury by type of chest CT lesions of COVID-19 infection using V/Q SPECT/CT imaging.

PATIENTS AND METHODS

We explored a national registry including V/Q SPECT/CT performed during a proven acute SARS-CoV-2 infection. Chest CT findings of COVID-19 disease were classified in 3 elementary lesions: ground-glass opacities, crazy-paving (CP), and consolidation. For each type of chest CT lesions, a semiquantitative evaluation of ventilation and perfusion was visually performed using a 5-point scale score (0 = normal to 4 = absent function).

RESULTS

V/Q SPECT/CT was performed in 145 patients recruited in 9 nuclear medicine departments. Parenchymal lesions were visible in 126 patients (86.9%). Ground-glass opacities were visible in 33 patients (22.8%) and were responsible for minimal perfusion impairment (perfusion score [mean ± SD], 0.9 ± 0.6) and moderate ventilation impairment (ventilation score, 1.7 ± 1); CP was visible in 43 patients (29.7%) and caused moderate perfusion impairment (2.1 ± 1.1) and moderate-to-severe ventilation impairment (2.5 ± 1.1); consolidation was visible in 89 patients (61.4%) and was associated with moderate perfusion impairment (2.1 ± 1) and severe ventilation impairment (3.0 ± 0.9).

CONCLUSIONS

In COVID-19 patients assessed with V/Q SPECT/CT, a large proportion demonstrated parenchymal lung lesions on CT, responsible for ventilation and perfusion injury. COVID-19-related pulmonary lesions were, in order of frequency and functional impairment, consolidations, CP, and ground-glass opacity, with typically a reverse mismatched or matched pattern.

Extent and Distribution of Parenchymal Abnormalities in Baseline CT-Scans Do Not Predict Awake Prone Positioning Response in COVID-19 Related ARDS

Prone positioning is frequently used for non-intubated hypoxemic patients with COVID-19, although conclusive evidence is still lacking. The aim of the present study was to investigate whether baseline CT-scans could predict the improvement in oxygenation in COVID-19 related Acute respira-tory syndrome (ARDS) patients when pronated. Methods: A retrospective study of COVID-19 patients who underwent non-invasive ventilation (NIV) and prone positioning was conducted. Results: Forty-five patients were included. On average, 50% of the overall lung volume was affected by the disease, as observed in the CT-scans, with ground glass opacities (GGOs) and consolidations accounting for 44% and 4%, respectively. The abnormalities were mainly posterior, as demonstrated by posterior/anterior distribution ratios of 1.5 and 4.4 for GGO and consolidation, respectively. The median PaO₂/FiO₂ ratio during NIV in a supine position (SP1) was 140 [IQR 108–169], which improved by 67% (+98) during prone positioning, on average. Once supine positioning was resumed (SP2), the improvement in oxygenation was maintained in 28 patients (62% of the overall population, categorized as “responders”). We found no significant differences between responders and non-responders in terms of the extent (p = 0.92) and the distribution of parenchymal abnormalities seen in the baseline CT (p = 0.526). Conclusion: Despite the lack of a priori estimation of the sample size, considering the absence of any trends in the differences and correlations, we can reasonably conclude that the baseline chest CT-scan does not predict a gas-exchange response in awake prone-positioned patients with COVID-19 related ARDS. Physicians dealing with this category of patients should not rely on the imaging at presentation when evaluating whether to pronate patients.

Correlation of Lung Damage on CT Scan with Laboratory Inflammatory Markers in COVID-19 Patients: A Single-Center Study from Romania

(1) Background: This study aims to evaluate the association of CRP, NLR, IL-6, and Procalcitonin with lung damage observed on CT scans; (2) Methods: A cross-sectional study was performed among 106 COVID-19 patients hospitalized in Timisoara Municipal Emergency Hospital. Chest CT and laboratory analysis were performed in all patients. The rank Spearmen correlation was used to assess the association between inflammatory markers and lung involvement. In addition, ROC curve analysis was used to determine the accuracy of inflammatory markers in the diagnosis of severe lung damage; (3) Results: CRP, NLR, and IL-6 were significantly positively correlated with lung damage. All inflammatory markers had good accuracy for diagnosis of severe lung involvement. Moreover, IL-6 has the highest AUC- ROC curve; (4) Conclusions: The inflammatory markers are associated with lung damage and can be used to evaluate COVID-19 severity.

Mediastinal lymph node enlargement in COVID-19: Relationships with mortality and CT findings

BACKGROUND

The presence of mediastinal lymph node enlargement (MLNE) in computed tomography (CT) of Coronavirus disease 2019 (COVID-19) patients can be associated with disease severity.

OBJECTIVES

To investigate the relationship between MLNE with intensive care unit admission (ICU), mortality rates, and CT findings, especially in early-stage COVID-19 patients.

METHODS

This single-center retrospective case-control study, included aged ≥18 years, 250 COVID-19 patients with positive RT-PCR tests. We included two patient groups, 125/250 with and without MLNE. Demographic information of the patients, laboratory findings, length of stay in hospital or ICU, mortality rates, initial CT imaging findings and CT severity scores (CT-SS) were recorded and their relationship with MLNE was investigated.

RESULTS

Patients with MLNE were older (69.61 ± 11.16; p < 0.001) and had a higher CT-SS (14.67 ± 7.55; p < 0.001). There was a significant difference between the presence of MLNE with mortality (58/77, 75.3%; p < 0.001) and ICU admission (49/61, 80.3%; p < 0.001). Also, a statistical association was found between MLNE with ICU admission (p = 0.001) and (p < 0.001) mortality rates in patients with CORADS≤2 CT findings. In multivariate logistic regression analysis, MLNE was 8.8-fold (95% CI: 1.62-47.86, p =  0.01) more correlated with linear opacity and 0.25-fold with bronchial wall thickening (95% CI: 0.07-0.92, p =  0.04).

CONCLUSION

Mediastinal lymph node enlargement is an important CT finding that can predict the severe prognosis of COVID-19 patients. Even in patients without lung involvement on initial CT, the presence of MLNE should be carefully examined as it is associated with disease severity.

Genomics in Egypt: Current Status and Future Aspects

Egypt is the third most densely inhabited African country. Due to the economic burden and healthcare costs of overpopulation, genomic and genetic testing is a huge challenge. However, in the era of precision medicine, Egypt is taking a shift in approach from “one-size-fits all” to more personalized healthcare via advancing the practice of medical genetics and genomics across the country. This shift necessitates concrete knowledge of the Egyptian genome and related diseases to direct effective preventive, diagnostic and counseling services of prevalent genetic diseases in Egypt. Understanding disease molecular mechanisms will enhance the capacity for personalized interventions. From this perspective, we highlight research efforts and available services for rare genetic diseases, communicable diseases including the coronavirus 2019 disease (COVID19), and cancer. The current state of genetic services in Egypt including availability and access to genetic services is described. Drivers for applying genomics in Egypt are illustrated with a SWOT analysis of the current genetic/genomic services. Barriers to genetic service development in Egypt, whether economic, geographic, cultural or educational are discussed as well. The sensitive topic of communicating genomic results and its ethical considerations is also tackled. To understand disease pathogenesis, much can be gained through the advancement and integration of genomic technologies via clinical applications and research efforts in Egypt. Three main pillars of multidisciplinary collaboration for advancing genomics in Egypt are envisaged: resources, infrastructure and training. Finally, we highlight the recent national plan to establish a genome center that will aim to prepare a map of the Egyptian human genome to discover and accurately determine the genetic characteristics of various diseases. The Reference Genome Project for Egyptians and Ancient Egyptians will initialize a new genomics era in Egypt. We propose a multidisciplinary governance system in Egypt to support genomic medicine research efforts and integrate into the healthcare system whilst ensuring ethical conduct of data.

Mesenteric ischemia in patients with COVID-19: an updated systematic review of abdominal CT findings in 75 patients

Background

Acute mesenteric ischemia (AMI) is a less common but devastating complication of COVID-19 disease. The aim of this systematic review was to assess the most common CT imaging features of AMI in COVID-19 and also provide an updated review of the literature on symptoms, treatment, histopathological and operative findings, and follow-up of these patients.

Methods

A systematic literature search of four databases: Pubmed, EMBASE, WHO database, and Google Scholar, was performed to identify all the articles which described abdominal CT imaging findings of AMI in COVID-19.

Results

A total of 47 studies comprising 75 patients were included in the final review. Small bowel ischemia (46.67%) was the most prevalent abdominal CT finding, followed by ischemic colitis (37.3%). Non-occlusive mesenteric ischemia (NOMI; 67.9%) indicating microvascular involvement was the most common pattern of bowel involvement. Bowel wall thickening/edema (50.9%) was more common than bowel hypoperfusion (20.7%). While ileum and colon both were equally involved bowel segments (32.07% each), SMA (24.9%), SMV (14.3%), and the spleen (12.5%) were the most commonly involved artery, vein, and solid organ, respectively. 50% of the patients receiving conservative/medical management died, highlighting high mortality without surgery. Findings on laparotomy and histopathology corroborated strikingly with CT imaging findings.

Conclusion

In COVID-19 patients with AMI, small bowel ischemia is the most prevalent imaging diagnosis and NOMI is the most common pattern of bowel involvement. Contrast-enhanced CT is a powerful decision-making tool for prompt diagnosis of AMI in COVID-19, thereby potentially improving time to treat as well as clinical outcomes.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00261-021-03337-9.

Surfactant protein D: A useful biomarker for distinguishing COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases

Introduction

Computed tomography is useful for the diagnosis of coronavirus disease (COVID‐19) pneumonia. However, many types of interstitial lung diseases and even bacterial pneumonia can show abnormal chest shadows that are indistinguishable from those observed in COVID‐19 pneumonia. Thus, it is necessary to identify useful biomarkers that can efficiently distinguish COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases. Herein, we investigated the usefulness of serum Krebs von den Lungen 6 (KL‐6) and surfactant protein D (SP‐D) for identifying patients with COVID‐19 pneumonia among patients with abnormal chest shadows consistent with COVID‐19 pneumonia.

Method

This was a retrospective cohort study of consecutive patients who underwent evaluation of serum KL‐6 and SP‐D at a single center from February 2019 to December 2020. A total of 54 patients with COVID‐19 pneumonia and 65 patients with COVID‐19 pneumonia‐like diseases were enrolled in this study from the source population. Serum KL‐6 and SP‐D levels in both groups were analyzed.

Result

The serum levels of KL‐6 and SP‐D in patients with COVID‐19 pneumonia were significantly lower than those in patients with COVID‐19 pneumonia‐like disease (median [interquartile range]: 208.5 [157.5–368.5] U/ml vs. 430 [284.5–768.5] U/ml, p < 0.0001 and 24.7 [8.6–51.0] ng/ml vs. 141 [63.7–243.5] ng/ml, p < 0.0001, respectively). According to receiver operating characteristic (ROC) analysis, the areas under the ROC curves (95% confidence intervals) of serum KL‐6 and SP‐D levels for distinguishing COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases were 0.761 (0.675–0.847) and 0.874 (0.812–0.936), respectively. The area under the ROC curve of serum SP‐D was significantly larger than that of serum KL‐6 (p = 0.0213), suggesting that serum SP‐D can more efficiently distinguish COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases.

Conclusion

Serum SP‐D is a promising biomarker for distinguishing COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases. Serum SP‐D can be useful for the management of patients with abnormal chest shadow mimicking COVID‐19 pneumonia.

Computed Tomography Severity Scoring on High-Resolution Computed Tomography Thorax and Inflammatory Markers With COVID-19 Related Mortality in a Designated COVID Hospital

Introduction Radiological Society of the Netherlands introduced the coronavirus disease 2019 (COVID-19) Reporting and Data System (CO-RADS) and the corresponding CT severity score (CTSS) to diagnose COVID-19 severity. However, data regarding the same is very limited. Objectives The objective of this study was to correlate the computed tomography severity scoring (CTSS) on high-resolution computed tomography (HRCT) thorax and inflammatory markers with COVID-19 related mortality. Methods A retrospective observational study was conducted in a tertiary center between June 2020 to May 2021 among 2343 adult patients at the department of radio-diagnosis with suspected and confirmed COVID-19 cases who received an HRCT thorax. Data was collected retrospectively from the records regarding age, sex, and information regarding inflammatory markers such as C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), D-dimer, and neutrophil-to-lymphocyte ratio. Information on HRCT thorax of patients was reviewed for radiological suspicion of COVID-19 related lung changes using CO-RADS scoring and severity of lung involvement using CT-severity scoring. Data was analyzed using SPSS version 22 (IBM Inc., Armonk, New York). Results The mean age was 51.69 ± 16.02 years, and most of the study participants were male (1592, 67.95%). The majority (999, 42.64%) had diabetes as a comorbidity. The reverse transcription polymerase chain reaction (RT-PCR) test was positive in 1571 (67.05%) participants. The majority (1571, 67.05%) had a CO-RADS score of six, and only 150 (6.40%) had CO-RADS score of four. The CT severity score was normal in 147 (6.27%), mild in 724 (30.90%), moderate in 903 (38.54%), and severe in 569 (24.29%) participants. The CRP levels were moderate in 1200 (51.22%) and severe in 428 (18.27%) participants. The mean ferritin, D-dimer and interleukin-6 (IL-6) levels were 321.83 ± 266.42 ng/ml, 1.51 ± 0.85mg/l, and 323.05 ± 95.52pg/ml, respectively. The mean length of hospital stay was 10.25 ± 6.52 days. Most of them (1926 out of 2343, 82.20%) survived, and nearly 417 out of 2343 (17.80%) died. Out of 2343, 569 participants had severe CT severity scores, out of which 205 (36.03%) died, and 364 (63.97%) participants survived. Conclusion A positive correlation was found between CT severity scoring on HRCT thorax and inflammatory markers with COVID-19 related mortality and can be used in early diagnosis and timely management of COVID-19 positive patients.

AI-driven quantification of ground glass opacities in lungs of COVID-19 patients using 3D computed tomography imaging

Objectives

Ground-glass opacity (GGO)—a hazy, gray appearing density on computed tomography (CT) of lungs—is one of the hallmark features of SARS-CoV-2 in COVID-19 patients. This AI-driven study is focused on segmentation, morphology, and distribution patterns of GGOs.

Method

We use an AI-driven unsupervised machine learning approach called PointNet++ to detect and quantify GGOs in CT scans of COVID-19 patients and to assess the severity of the disease. We have conducted our study on the “MosMedData”, which contains CT lung scans of 1110 patients with or without COVID-19 infections. We quantify the morphologies of GGOs using Minkowski tensors and compute the abnormality score of individual regions of segmented lung and GGOs.

Results

PointNet++ detects GGOs with the highest evaluation accuracy (98%), average class accuracy (95%), and intersection over union (92%) using only a fraction of 3D data. On average, the shapes of GGOs in the COVID-19 datasets deviate from sphericity by 15% and anisotropies in GGOs are dominated by dipole and hexapole components. These anisotropies may help to quantitatively delineate GGOs of COVID-19 from other lung diseases.

Conclusion

The PointNet++ and the Minkowski tensor based morphological approach together with abnormality analysis will provide radiologists and clinicians with a valuable set of tools when interpreting CT lung scans of COVID-19 patients. Implementation would be particularly useful in countries severely devastated by COVID-19 such as India, where the number of cases has outstripped available resources creating delays or even breakdowns in patient care. This AI-driven approach synthesizes both the unique GGO distribution pattern and severity of the disease to allow for more efficient diagnosis, triaging and conservation of limited resources.

Post-COVID-19 Pulmonary Fibrosis

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions worldwide with a high mortality rate due to a lack of definitive treatment. Despite having a wide range of clinical features, acute respiratory distress syndrome (ARDS) has emerged as the primary cause of mortality in these patients. Risk factors and comorbidities like advanced age with limited lung function, pre-existing diabetes, hypertension, cardiovascular diseases, and obesity have increased the risk for severe COVID-19 infection. Rise in inflammatory markers like transforming growth factor β (TGF-β), interleukin-6 (IL-6), and expression of matrix metalloproteinase 1 and 7 (MMP-1, MMP-7), along with collagen deposition at the site of lung injury, results in extensive lung scarring and fibrosis. Anti-fibrotic drugs, such as Pirfenidone and Nintedanib, have emerged as potential treatment options for post-COVID-19 pulmonary fibrosis. A lung transplant might be the only life-saving treatment. Despite the current advances in the management of COVID-19, there is still a considerable knowledge gap in the management of long-term sequelae in such patients, especially concerning pulmonary fibrosis. Follow up on the current clinical trials and research to test the efficacy of various anti-inflammatory drugs is needed to prevent long-term sequelae early mortality in these patients.

Air trapping in COVID-19 patients following hospital discharge: retrospective evaluation with paired inspiratory/expiratory thin-section CT

Objectives

The study reports our experience with paired inspiration/expiration thin-section computed tomographic (CT) scans in the follow-up of COVID-19 patients with persistent respiratory symptoms.

Methods

From August 13, 2020, to May 31, 2021, 48 long-COVID patients with respiratory symptoms (27 men and 21 women; median age, 62.0 years; interquartile range: 54.0–69.0 years) underwent follow-up paired inspiration-expiration thin-section CT scans. Patient demographics, length of hospital stay, intensive care unit admission rate, and clinical and laboratory features of acute infection were also included. The scans were obtained on a median of 72.5 days after onset of symptoms (interquartile range: 58.5–86.5) and at least 30 days after hospital discharge. Thin-section CT findings included ground-glass opacity, mosaic attenuation pattern, consolidation, traction bronchiectasis, reticulation, parenchymal bands, bronchial wall thickening, and air trapping. We used a quantitative score to determine the degree of air trapping in the expiratory scans.

Results

Parenchymal abnormality was found in 50% (24/48) of patients and included air trapping (37/48, 77%), ground-glass opacities (19/48, 40%), reticulation (18/48, 38%), parenchymal bands (15/48, 31%), traction bronchiectasis (9/48, 19%), mosaic attenuation pattern (9/48, 19%), bronchial wall thickening (6/48, 13%), and consolidation (2/48, 4%). The absence of air trapping was observed in 11/48 (23%), mild air trapping in 20/48 (42%), moderate in 13/48 (27%), and severe in 4/48 (8%). Independent predictors of air trapping were, in decreasing order of importance, gender (p = 0.0085), and age (p = 0.0182).

Conclusions

Our results, in a limited number of patients, suggest that follow-up with paired inspiratory/expiratory CT in long-COVID patients with persistent respiratory symptoms commonly displays air trapping.

Key Points

• Our experience indicates that paired inspiratory/expiratory CT in long-COVID patients with persistent respiratory symptoms commonly displays air trapping.

• Iterative reconstruction and dose-reduction options are recommended for demonstrating air trapping in long-COVID patients.