Comparison of admission chest computed tomography and lung ultrasound performance for diagnosis of COVID-19 pneumonia in populations with different disease prevalence

Sensitivity of Lung Point-of-Care Ultrasound (POCUS) to Predict Oxygen Requirements in Emerging Viral Infections

OBJECTIVES

The prognostic characteristics of lung point-of-care ultrasound (L-POCUS) to predict respiratory decompensation in patients with emerging infections remains unstudied. Our objective was to examine whether scored lung ultrasounds predict hypoxia among a nonhypoxic, ambulatory population of patients with COVID-19.

METHODS

This was a diagnostic case-control study. Three academic emergency departments across the United States collected a convenience sample of nonhypoxic subjects with COVID-19, scored subjects' hemithorax at 7 locations using lung ultrasound, and followed outcomes for 40 days. We defined cases as hypoxia (≤91% by pulse oxygenation) from 2 hours after index presentation to day 40. Follow-up was by telephone plus home pulse oximeter and by chart review. We conducted a logistic regression to test the association between L-POCUS scores and hypoxia. To evaluate lung ultrasound score prediction of a hypoxic event, we calculated sensitivity and specificity at optimal cut off scores and report receiver operating characteristic curve and area under the curve.

RESULTS

We enrolled 163 subjects but excluded 15 (3 duplicate entries; 12 lost to follow up). Median age was 41 years (interquartile range [IQR] 31-56); 83 (56%) were female, and median body mass index was 29 (IQR 25-35). We classified 47 of 148 as hypoxic cases (32%, 95% confidence interval [CI]: 25-40), leaving 101 controls. L-POCUS scores associated with hypoxia by logistic regression (odds ratio = 1.05, 95% CI: 1.02-1.08), with a 5% increase in odds of hypoxia for each 1-unit increase in L-POCUS score. The optimal cut-off score was 15 (sensitivity, 0.60; specificity, 0.73) and the area under the curve was 0·66 (95% CI 0·58-0·75). The correctly classified proportion was 69% (95% CI: 61-76).

CONCLUSIONS

Among nonhypoxic COVID-19 patients, higher L-POCUS rubric scores were associated with hypoxia but no scoring threshold strongly predicts hypoxia at 40 days.

Pulmonary ultrasound in COVID-19 and non-COVID-19 pneumonia in South Africa: An observational study

Background

Pulmonary ultrasound techniques have historically been applied to acute lung diseases to describe lung lesions, particularly in critical care.

Objectives

To explore the role of lung ultrasound (LUS) in hospitalised patients with hypoxaemic pneumonia during the COVID-19 pandemic.

Methods

This was a single-centre prospective, observational study of two groups of adult patients with hypoxaemic pneumonia: those with COVID-19 pneumonia, and those with non-COVID-19 community-acquired pneumonia (CAP). A pulmonologist performed bedside LUS using the Bedside Lung Ultrasound in Emergency (BLUE) protocol, and the findings were verified by an independent study-blinded radiologist.

Results

We enrolled 48 patients with COVID-19 pneumonia and 24 with non-COVID CAP. The COVID-19 patients were significantly older than those with non-COVID CAP (median (interquartile range (IQR)) age 52 (42 - 62.5) years v. 42.5 (36 - 52.5) years, respectively; p=0.007), and had a lower prevalence of HIV infection (25% v. 54%, respectively; p=0.01) and higher prevalences of hypertension (54% v. 7%; p=0.002) and diabetes mellitus (19% v. 8%; p=0.04). In both groups, close to 30% of the patients had severe acute respiratory distress syndrome. A confluent B-line pattern in the right upper lobe was significantly associated with COVID-19 pneumonia compared with the C pattern (relative risk (RR) 3.8; 95% confidence interval (CI) 1.7 - 8.6). Bilateral changes on LUS rather than unilateral or no changes were associated with COVID-19 pneumonia (RR 1.55; 95% CI 1.004 - 2.387). There were no statistically significant differences in median (IQR) lung scores between patients with COVID-19 pneumonia and those with non-COVID CAP (8 (4 - 11.5) v. 7.5 (4.5 - 12.5), respectively). Patients with COVID-19 pneumonia had a higher than predicted mortality. Logistic regression analysis showed a higher Simplified Acute Physiology Score (SAPS II) (RR 1.11; 95% CI 1.02 - 1.21) and a lower total LUS score indicating B lines v. consolidation (RR 0.80; 95% CI 0.65 - 0.99) to be associated with mortality.

Conclusion

Patients with right upper zone consolidation were more likely to have non-COVID CAP than COVID-19 pneumonia. Finding a B pattern as opposed to consolidation was associated with mortality. The admission LUS score was unable to discriminate between COVID-19 and non-COVID CAP, and did not correlate with the ratio of partial pressure of oxygen to fractional inspired oxygen, clinical severity or mortality.

Study synopsis

What the study adds. During the COVID-19 pandemic, in a resource-limited, high-prevalence setting, lung ultrasound (LUS) patterns on admission to hospital were used to distinguish between COVID-19 and other causes in patients with hypoxaemic pneumonia. Patients with right upper zone consolidation were more likely to have non-COVID-19 community-acquired pneumonia (CAP) than COVID-19 pneumonia.Implications of the findings. The admission LUS score was unable to discriminate between COVID-19 pneumonia and non-COVID CAP, and did not correlate with the ratio of partial pressure of oxygen to fractional inspired oxygen, clinical severity or mortality. The pattern was more valuable than the total LUS score in understanding the disease process.

Evaluation of a Lung Ultrasound Score in Hospitalized Adult Patients with COVID-19 in Barcelona, Spain

Background/Objectives: During the COVID-19 pandemic and the burden on hospital resources, the rapid categorization of high-risk COVID-19 patients became essential, and lung ultrasound (LUS) emerged as an alternative to chest computed tomography, offering speed, non-ionizing, repeatable, and bedside assessments. Various LUS score systems have been used, yet there is no consensus on an optimal severity cut-off. We assessed the performance of a 12-zone LUS score to identify adult COVID-19 patients with severe lung involvement using oxygen saturation (SpO2)/fractional inspired oxygen (FiO2) ratio as a reference standard to define the best cut-off for predicting adverse outcomes. Methods: We conducted a single-centre prospective study (August 2020-April 2021) at Hospital del Mar, Barcelona, Spain. Upon admission to the general ward or intensive care unit (ICU), clinicians performed LUS in adult patients with confirmed COVID-19 pneumonia. Severe lung involvement was defined as a SpO2/FiO2 ratio <315. The LUS score ranged from 0 to 36 based on the aeration patterns. Results: 248 patients were included. The admission LUS score showed moderate performance in identifying a SpO2/FiO2 ratio <315 (area under the ROC curve: 0.71; 95%CI 0.64-0.77). After adjustment for COVID-19 risk factors, an admission LUS score ≥17 was associated with an increased risk of in-hospital death (OR 5.31; 95%CI: 1.38-20.4), ICU admission (OR 3.50; 95%CI: 1.37-8.94) and need for IMV (OR 3.31; 95%CI: 1.19-9.13). Conclusions: Although the admission LUS score had limited performance in identifying severe lung involvement, a cut-off ≥17 score was associated with an increased risk of adverse outcomes. and could play a role in the rapid categorization of COVID-19 pneumonia patients, anticipating the need for advanced care.

Comparing Visual and Software-Based Quantitative Assessment Scores of Lungs' Parenchymal Involvement Quantification in COVID-19 Patients

(1) Background: Computed tomography (CT) plays a paramount role in the characterization and follow-up of COVID-19. Several score systems have been implemented to properly assess the lung parenchyma involved in patients suffering from SARS-CoV-2 infection, such as the visual quantitative assessment score (VQAS) and software-based quantitative assessment score (SBQAS) to help in managing patients with SARS-CoV-2 infection. This study aims to investigate and compare the diagnostic accuracy of the VQAS and SBQAS with two different types of software based on artificial intelligence (AI) in patients affected by SARS-CoV-2. (2) Methods: This is a retrospective study; a total of 90 patients were enrolled with the following criteria: patients' age more than 18 years old, positive test for COVID-19 and unenhanced chest CT scan obtained between March and June 2021. The VQAS was independently assessed, and the SBQAS was performed with two different artificial intelligence-driven software programs (Icolung and CT-COPD). The Intraclass Correlation Coefficient (ICC) statistical index and Bland-Altman Plot were employed. (3) Results: The agreement scores between radiologists (R1 and R2) for the VQAS of the lung parenchyma involved in the CT images were good (ICC = 0.871). The agreement score between the two software types for the SBQAS was moderate (ICC = 0.584). The accordance between Icolung and the median of the visual evaluations (Median R1-R2) was good (ICC = 0.885). The correspondence between CT-COPD and the median of the VQAS (Median R1-R2) was moderate (ICC = 0.622). (4) Conclusions: This study showed moderate and good agreement upon the VQAS and the SBQAS; enhancing this approach as a valuable tool to manage COVID-19 patients and the combination of AI tools with physician expertise can lead to the most accurate diagnosis and treatment plans for patients.

Pulmonary Findings in Hospitalized COVID-19 Patients Assessed by Lung Ultrasonography (LUS) - A Prospective Registry Study

PURPOSE

This prospective two-centre study investigated localisation-dependent lesion patterns in COVID-19 with standard lung ultrasonography (LUS) and their relationship with thoracic computed tomography (CT) and clinical parameters.

MATERIALS AND METHODS

Between April 2020 and April 2021, 52 SARS-CoV-2-positive patients in two hospitals were examined by means of LUS for "B-lines", fragmented pleura, consolidation and air bronchogram in 12 lung regions and for pleural effusions. A newly developed LUS score based on the number of features present was correlated with clinical parameters (respiration, laboratory parameters) and the CT and analysed with respect to the 30- and 60-day outcome. All patients were offered an outpatient LUS follow-up.

RESULTS

The LUS and CT showed a bilateral, partially posteriorly accentuated lesion distribution pattern. 294/323 (91%) of CT-detected lesions were pleural. The LUS score showed an association with respiratory status and C-reactive protein; the correlation with the CT score was weak (Spearman's rho = 0.339, p < 0.001). High LUS scores on admission were also observed in patients who were discharged within 30 days. LUS during follow-up showed predominantly declining LUS scores.

CONCLUSION

The LUS score reflected the clinical condition of the patients. No conclusion could be made on the prognostic value of the LUS, because of the low event rate. The LUS and CT score showed no sufficient correlation. This is probably due to different physical principles, which is why LUS could be of complementary value.

Lung Ultrasound and High-Resolution Computed Tomography in Suspected COVID-19 Patients Admitted to the Emergency Department: A Comparison

Objective

To analyze the diagnostic accuracy of lung ultrasonography (LUS) and high-resolution computed tomography (HRCT), to detect COVID-19.

Materials and Methods

This study recruited all patients admitted to the emergency medicine unit, due to a suspected COVID-19 infection, during the first wave of the COVID-19 pandemic. These patients also who underwent a standardized LUS examination and a chest HRCT. The signs detected by both LUS and HRCT were reported, as well as the sensitivity, specificity, positive predictive value, and negative predictive value for LUS and HRCT.

Results

This cohort included 159 patients, 101 (63%) were diagnosed with COVID-19. COVID-19 patients showed more often confluent subpleural consolidations and parenchymal consolidations in lower lung regions of LUS. They also had "ground glass" opacities and "crazy paving" on HRCT, while pleural effusion and pulmonary consolidations were more common in non-COVID-19 patients. LUS had a sensitivity of 0.97 (95% CI 0.92-0.99) and a specificity of 0.24 (95% CI 0.07-0.5) for COVID-19 lung infections. HRCT abnormalities resulted in a 0.98 sensitivity (95% CI 0.92-0.99) and 0.1 specificity (95% CI 0.04-0.23) for COVID-19 lung infections.

Conclusion

In this cohort, LUS proved to be a noninvasive, diagnostic tool with high sensitivity for lung abnormalities that were likewise detected by HRCT. Furthermore, LUS, despite its lower specificity, has a high sensitivity for COVID-19, which could prove to be as effective as HRCT in excluding a COVID-19 lung infection.

Could initial CT chest manifestation in patients hospitalized with COVID 19 pneumonia predict outcome on short term basis

Chest computed tomography (CT) can be used to monitor the course of the disease or response to therapy. Therefore, our study was designed to identify chest CT manifestations that can predict the outcome of patients on short term follow-up. This was a retrospective study wherein we reviewed chest CT scans of 112 real-time reverse transcription polymerase chain reaction positive patients admitted to our hospital. All 112 patients underwent follow-up chest CT at a time interval of 4 to 42 days. Our study included 83 male and 29 female who were positive for COVID 19 infection and admitted to the hospital with positive chest CT findings. All patients underwent follow-up chest CT, and the outcomes were categorized as resolution, regression, residual fibrosis, progression, or death. These proportions were 5.4%, 48.2%, 24.1%, 14.3%, and 8%, respectively. The only significant factor in determining the complete resolution of chest CT was oligo-segmental affection (P = .0001). The main CT feature that significantly affected the regression of chest CT manifestations was diffuse nodular shadows (P = .039). The CT features noted in patients with residual fibrosis were interstitial thickening, with a P value of .017. The mono-segmental process significantly affected progression (P = .044). The significant factors for fatality were diffuse crazy paving, pleural effusion, and extra-thoracic complications (P = .033, .029, and .007, respectively). The prognostic value of the first admission CT can help assess disease outcomes in the earliest phases of onset. This can improve resource distribution.

Role of Imaging in the Management of Patients with SARS-CoV-2 Lung Involvement Admitted to the Emergency Department: A Systematic Review

During the waves of the coronavirus disease (COVID-19) pandemic, emergency departments were overflowing with patients suffering with suspected medical or surgical issues. In these settings, healthcare staff should be able to deal with different medical and surgical scenarios while protecting themselves against the risk of contamination. Various strategies were used to overcome the most critical issues and guarantee quick and efficient diagnostic and therapeutic charts. The use of saliva and nasopharyngeal swab Nucleic Acid Amplification Tests (NAAT) in the diagnosis of COVID-19 was one of the most adopted worldwide. However, NAAT results were slow to report and could sometimes create significant delays in patient management, especially during pandemic peaks. On these bases, radiology has played and continues to play an essential role in detecting COVID-19 patients and solving differential diagnosis between different medical conditions. This systematic review aims to summarize the role of radiology in the management of COVID-19 patients admitted to emergency departments by using chest X-rays (CXR), computed tomography (CT), lung ultrasounds (LUS), and artificial intelligence (AI).

Diagnostic accuracy of point-of-care lung ultrasound for COVID-19: a systematic review and meta-analysis

BACKGROUND

Point-of-care (POC) lung ultrasound (LUS) is widely used in the emergency setting and there is an established evidence base across a range of respiratory diseases, including previous viral epidemics. The necessity for rapid testing combined with the limitations of other diagnostic tests has led to the proposal of various potential roles for LUS during the COVID-19 pandemic. This systematic review and meta-analysis focused specifically on the diagnostic accuracy of LUS in adult patients presenting with suspected COVID-19 infection.

METHODS

Traditional and grey-literature searches were performed on 1 June 2021. Two authors independently carried out the searches, selected studies and completed the Quality Assessment Tool for Diagnostic Test Accuracy Studies (QUADAS-2). Meta-analysis was carried out using established open-source packages in R. We report overall sensitivity, specificity, positive and negative predictive values, and the hierarchical summary receiver operating characteristic curve for LUS. Heterogeneity was determined using the I² statistic.

RESULTS

Twenty studies were included, published between October 2020 and April 2021, providing data from a total of 4314 patients. The prevalence and admission rates were generally high across all studies. Overall, LUS was found to be 87.2% sensitive (95% CI 83.6 to 90.2) and 69.5% specific (95% CI 62.2 to 72.5) and demonstrated overall positive and negative likelihood ratios of 3.0 (95% CI 2.3 to 4.1) and 0.16 (95% CI 0.12 to 0.22), respectively. Separate analyses for each reference standard revealed similar sensitivities and specificities for LUS. Heterogeneity was found to be high across the studies. Overall, the quality of studies was low with a high risk of selection bias due to convenience sampling. There were also applicability concerns because all studies were undertaken during a period of high prevalence.

CONCLUSION

During a period of high prevalence, LUS had a sensitivity of 87% for the diagnosis of COVID-19 infection. However, more research is required to confirm these results in more generalisable populations, including those less likely to be admitted to hospital.

PROSPERO REGISTRATION NUMBER

CRD42021250464.

Lung ultrasound in the diagnosis of COVID-19-associated pneumonia

Over the past decades, lung ultrasound in the diagnosis of lung diseases has become widespread. Ultrasound examination has a number of advantages (no radiation exposure, real-time imaging, clear visualization of the subpleural lung regions and costophrenic angles), which make it possible to use ultrasound to monitor the dynamics of pneumonia in children and pregnant women. Currently, in the context of the COVID-19 pandemic, lung ultrasound is widely used due to its high diagnostic efficiency, which is comparable with classical radiography and X-ray computed tomography (CT) by a number of parameters.

The article describes the method of lung ultrasound and the radiographic pattern of COVID-19-associated pneumonia. It also provides a review of the literature, according to which the severity of pneumonia was determined, depending on the radiographic pattern, and the need for a lung ultrasound was identified.

The article indicates that information on assessment of the radiographic pattern of the lungs at runtime in different variants of the course of coronavirus infection, as well as many methodological issues, including the frequency of second-look lung ultrasound, has not been sufficiently studied.

The use of lung ultrasound in COVID-19

This review article addresses the role of lung ultrasound in patients with coronavirus disease 2019 (COVID-19) for diagnosis and disease management. As a simple imaging procedure, lung ultrasound contributes to the early identification of patients with clinical conditions suggestive of COVID-19, supports decisions about hospital admission and informs therapeutic strategy. It can be performed in various clinical settings (primary care facilities, emergency departments, hospital wards, intensive care units), but also in outpatient settings using portable devices. The article describes typical lung ultrasound findings for COVID-19 pneumonia (interstitial pattern, pleural abnormalities and consolidations), as one component of COVID-19 diagnostic workup that otherwise includes clinical and laboratory evaluation. Advantages and limitations of lung ultrasound use in COVID-19 are described, along with equipment requirements and training needs. To infer on the use of lung ultrasound in different regions, a literature search was performed using key words "COVID-19", "lung ultrasound" and "imaging". Lung ultrasound is a noninvasive, rapid and reproducible procedure; can be performed at the point of care; requires simple sterilisation; and involves non-ionising radiation, allowing repeated exams on the same patient, with special benefit in children and pregnant women. However, physical proximity between the patient and the ultrasound operator is a limitation in the current pandemic context, emphasising the need to implement specific infection prevention and control measures. Availability of qualified staff adequately trained to perform lung ultrasound remains a major barrier to lung ultrasound utilisation. Training, advocacy and awareness rising can help build up capacities of local providers to facilitate lung ultrasound use for COVID-19 management, in particular in low- and middle-income countries.

Evolution of Lung Abnormalities on Lung Ultrasound in Recovery From COVID-19 Disease-A Prospective, Longitudinal Observational Cohort Study

OBJECTIVES

SARS-CoV-2 can cause respiratory diseases with various manifestations. However, little is known about its potential for lung recovery. Lung ultrasound has shown characteristic changes during COVID-19 and has proven to be useful for triage, diagnosis, and therapy. This study investigated how the recovery process from COVID-19 respiratory disease can be monitored using 12-zone lung ultrasound.

METHODS

This prospective observational cohort study was conducted in a busy urban emergency department in London, United Kingdom, over a 20-week period between April and October 2020. We followed 24 patients recovering from COVID-19 with varying disease severity using 12-zone lung ultrasound at 2-week intervals and monitored the changes in the prevalence of lung abnormalities previously described in COVID-19 infection (irregular pleura, subpleural consolidation, B-lines, and small localized effusions).

RESULTS

Lung ultrasound showed that the lung recovers significantly over 20 weeks postdisease. Individual lung abnormalities also resolved at different rates. The entire rib space occupied by confluent B-lines wane after the acute phase, whereas irregular pleura and subpleural consolidations resolved more gradually. Separate wide B-lines moving with the pleura during respiration may represent more stable features, indicating residual fibrotic changes. Small, localized effusions appear transiently after the initial acute phase of the disease, peaking at approximately 10 weeks after infection. The measured lung abnormalities were strong predictors of perceived shortness of breath during ambulation.

CONCLUSION

Lung ultrasound can be a useful tool for long-term monitoring of COVID-19 lung disease, avoiding repeated exposure to ionizing radiation, and may distinguish between acute and past infections.

Comparative analysis of chest radiography and lung ultrasound to predict intra-hospital prognosis of patients admitted for acute SARS-CoV-2 pneumonia (COVID-19)

Background

Point of care lung ultrasound (POCUS) has been recently used to assess prognosis in COVID-19 patients. However, there are no data comparing POCUS and chest-X ray, a technique widely used.

Patients and methods

Retrospective analysis in stable COVID-19 patients. Schalekamp radiological lung scale and LUZ-Score ultrasound scale were compared. Primary end-point was in-hospital death and/or need for Intensive Care Unit admission.

Results

A total of 138 patients were included. Median Schalekamp scale was 2 (2) and median LUZ-Score scale was 21 (10). No significant correlation was observed between both techniques. Patients with a LUZ-Score ≥ 21 points at admission had worse lung function and higher concentrations of LDH, CRP and Interleuquine-6. Schalekamp scale failed to identify patients at a higher risk at admission for the primary end-point. Addition of POCUS to a previous clinical model, improved risk prediction (AUC 0.805 [95% CI: 0.662-0.948]; P = <0.001).

Conclusions

Chest X-ray and POCUS showed no correlation at admission in this analysis. Only POCUS identified a group of patients with greater clinical and analytical involvement. POCUS improved, previous clinical model, while chest X-ray did not add relevant predictive information for the primary endpoint.

Speckled Tracking of Pleura-A Novel Tool for Lung Ultrasound; Distinguishing COVID-19 from Acute Heart Failure

For the acutely dyspneic patient, discerning bedside between acute decompensated heart failure (ADHF) and COVID-19 is crucial. A lung ultrasound (LUS) is sensitive for detecting these conditions, but not in distinguishing between them; both have bilateral B-lines. The Blue protocol uses pleural sliding to differentiate decreased pneumonia; however, this is not the case in ADHF. Nonetheless, this pleural sliding has never been quantified. Speckled tracking is a technology utilized in the echocardiography field that quantifies the motion of tissues by examining the movement of ultrasound speckles. We conducted a retrospective study of LUS performed in emergency room patients during the COVID-19 pandemic. Speckled tracking of the pleura by applying software to the B-mode of pleura was compared between COVID-19 patients, ADHF patients, and patients with no respiratory complaints. A significant difference was found between the patient groups on speckled tracking both in respect of displacement and velocity. ADHF had the highest displacement, followed by COVID-19, and then non-respiratory patients: 1.63 ± 1.89, 0.59 ± 0.71, and 0.24 ± 0.45, respectively (p < 0.01). A similar trend was seen in velocity with ADHF having the highest velocity 0.34 ± 0.37, followed by COVID-19 0.14 ± 0.71, and non-respiratory patients 0.02 ± 0.09 (p <0.01). Speckled tracking of the pleura is a potential tool for discerning between different causes of dyspnea.

Efficacy of a short course of lung ultrasound for primary care physicians in the assessment of COVID-19-positive patients

INTRODUCTION

Lung ultrasound (LUS) has become the first diagnostic imaging approach to assess lung involvement in COVID-19. While LUS proved to be safe, reliable, and accurate, not many primary care physicians (PCP) are capable to employ this instrument in the first evaluation of COVID-19 outpatients. The aim of this study was to determine the effectiveness of a brief training program in LUS for PCP.

METHODS

Italian local authorities promoted a training program in LUS for PCP engaged in COVID-19 outpatients' evaluation. The course took place in a COVID-19 unit and included a hands-on practice on real COVID-19 patients. We conducted a qualitative and quantitative analysis of the results of the training program.

RESULTS

A total of 32 PCP completed the training. About 100% of participants reported an increase in competence and confidence in the use of LUS after the training. Self-reported confidence in detecting major COVID-19 LUS abnormalities was high (B-lines 8/10, pleural abnormalities 6.5/10). B-lines were accurately identified with a reliability of 81%, with a sensitivity of 96%, and a negative predictive value of 98%. Trainees were some less accurate in detecting pleural abnormalities (reliability 63%) but with a high specificity (99%).

CONCLUSIONS

This study showed that a short training program, but comprising a hands-on practice, is capable to bring even almost novices to achieve a high overall accuracy and reliability in detecting lung involvement in COVID-19. This may result in a significant improvement of the performances of PCP involved in the first evaluation of COVID-19 cases in primary care facilities.

Different Lung Parenchyma Quantification Using Dissimilar Segmentation Software: A Multi-Center Study for COVID-19 Patients

Background: Chest Computed Tomography (CT) imaging has played a central role in the diagnosis of interstitial pneumonia in patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and can be used to obtain the extent of lung involvement in COVID-19 pneumonia patients either qualitatively, via visual inspection, or quantitatively, via AI-based software. This study aims to compare the qualitative/quantitative pathological lung extension data on COVID-19 patients. Secondly, the quantitative data obtained were compared to verify their concordance since they were derived from three different lung segmentation software. Methods: This double-center study includes a total of 120 COVID-19 patients (60 from each center) with positive reverse-transcription polymerase chain reaction (RT-PCR) who underwent a chest CT scan from November 2020 to February 2021. CT scans were analyzed retrospectively and independently in each center. Specifically, CT images were examined manually by two different and experienced radiologists for each center, providing the qualitative extent score of lung involvement, whereas the quantitative analysis was performed by one trained radiographer for each center using three different software: 3DSlicer, CT Lung Density Analysis, and CT Pulmo 3D. Results: The agreement between radiologists for visual estimation of pneumonia at CT can be defined as good (ICC 0.79, 95% CI 0.73–0.84). The statistical tests show that 3DSlicer overestimates the measures assessed; however, ICC index returns a value of 0.92 (CI 0.90–0.94), indicating excellent reliability within the three software employed. ICC was also performed between each single software and the median of the visual score provided by the radiologists. This statistical analysis underlines that the best agreement is between 3D Slicer “LungCTAnalyzer” and the median of the visual score (0.75 with a CI 0.67–82 and with a median value of 22% of disease extension for the software and 25% for the visual values). Conclusions: This study provides for the first time a direct comparison between the actual gold standard, which is represented by the qualitative information described by radiologists, and novel quantitative AI-based techniques, here represented by three different commonly used lung segmentation software, underlying the importance of these specific values that in the future could be implemented as consistent prognostic and clinical course parameters.

The Value of Lung Ultrasound to Detect the Early Pleural and Pulmonary Pathologies in Nonhospitalized COVID-19-Suspected Cases in a Population With a Low Prevalence of COVID-19 Infection: A Prospective Study in 297 Subjects

OBJECTIVES

This prospective study aimed to evaluate the value of B-mode lung ultrasound (LUS) for the early diagnosis of coronavirus disease 2019 (COVID-19) infection in nonhospitalized COVID-19 suspected cases in a population with a low prevalence of disease.

METHODS

From April 2020 to June 2020, in an ambulatory testing center for COVID-19-suspected cases, 297 subjects were examined by LUS before a nasopharyngeal swab was taken for a reverse transcription polymerase chain reaction (RT-PCR) test. The following LUS findings were defined as pathological ultrasound findings and were analyzed: the presence of 1) pleural effusion, 2) B-lines, 3) fragmented visceral pleura, 4) consolidation, and 5) air bronchogram in the consolidation. The LUS findings were compared with the RT-PCR test results.

RESULTS

The result of the RT-PCR test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was positive in 11 and negative in 286 subjects, and the prevalence of COVID-19 infection in the study participants was 3.7%. On LUS, a pathological finding could be detected in 56/297 (18.9%) study participants. The LUS revealed a sensitivity of 27.3%, a specificity of 81.5%, a positive predictive value of 5.4%, a negative predictive value of 96.7%, and a diagnostic accuracy of 79.9% for the identification of COVID-19 infection.

CONCLUSIONS

For the identification of COVID-19 infection, LUS is highly sensitive to the patient spectrum and to the prevalence of the disease. Due to the low diagnostic performance in nonhospitalized COVID-19 cases in low-prevalence areas, LUS cannot be considered to be an adequate method for making a diagnosis in this group.

The diagnostic performance of lung ultrasound for detecting COVID-19 in emergency departments: A systematic review and meta-analysis

PURPOSE

To perform a systematic review and meta-analysis of published literature investigating the use of lung ultrasound (LUS) on COVID-19 patients, in emergency point of care settings, and to determine its diagnostic value compared with lung computed tomography (LCT) diagnostic performance. Whilst using the real-time polymerase chain reaction test as the 'gold standard'.

METHODS

Literature searches were performed on MEDLINE, Embase, Web of Science, and PubMed databases for eligible studies. The LUS and LCT pooled diagnostic performance were measured using DerSimonian-Laird random effect method.

RESULT

Out of a total of 158 studies, 16 met the eligibility criteria and were included in this review. The pooled sensitivity, specificity, positive and negative likelihood ratios were 86.9%, 62.4%, 2.4 and 0.19, respectively for LUS and 93.5%, 72.6%, 3.3 and 0.05, respectively for LCT.

CONCLUSION

The lung ultrasound (LUS) demonstrated acceptable sensitivity but poor specificity when used independently to diagnose COVID-19 pneumonia patients in emergency departments, while the lung computed tomography showed higher performance. Thus, LUS can be used to supplement existing diagnostic tools and possibly for the triage of patients.

Diagnostic Performance of Antigen Rapid Diagnostic Tests, Chest Computed Tomography, and Lung Point-of-Care-Ultrasonography for SARS-CoV-2 Compared with RT-PCR Testing: A Systematic Review and Network Meta-Analysis

(1) Background: The comparative performance of various diagnostic methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains unclear. This study aimed to investigate the comparison of the 3 index test performances of rapid antigen diagnostic tests (RDTs), chest computed tomography (CT), and lung point-of-care-ultrasonography (US) with reverse transcription-polymerase chain reaction (RT-PCR), the reference standard, to provide more evidence-based data on the appropriate use of these index tests. (2) Methods: We retrieved data from electronic literature searches of PubMed, Cochrane Library, and EMBASE from 1 January 2020, to 1 April 2021. Diagnostic performance was examined using bivariate random-effects diagnostic test accuracy (DTA) and Bayesian network meta-analysis (NMA) models. (3) Results: Of the 3992 studies identified in our search, 118 including 69,445 participants met our selection criteria. Among these, 69 RDT, 38 CT, and 15 US studies in the pairwise meta-analysis were included for DTA with NMA. CT and US had high sensitivity of 0.852 (95% credible interval (CrI), 0.791-0.914) and 0.879 (95% CrI, 0.784-0.973), respectively. RDT had high specificity, 0.978 (95% CrI, 0.960-0.996). In accuracy assessment, RDT and CT had a relatively higher than US. However, there was no significant difference in accuracy between the 3 index tests. (4) Conclusions: This meta-analysis suggests that, compared with the reference standard RT-PCR, the 3 index tests (RDTs, chest CT, and lung US) had similar and complementary performances for diagnosis of SARS-CoV-2 infection. To manage and control COVID-19 effectively, future large-scale prospective studies could be used to obtain an optimal timely diagnostic process that identifies the condition of the patient accurately.

Thoracic imaging tests for the diagnosis of COVID-19

BACKGROUND

Our March 2021 edition of this review showed thoracic imaging computed tomography (CT) to be sensitive and moderately specific in diagnosing COVID-19 pneumonia. This new edition is an update of the review.

OBJECTIVES

Our objectives were to evaluate the diagnostic accuracy of thoracic imaging in people with suspected COVID-19; assess the rate of positive imaging in people who had an initial reverse transcriptase polymerase chain reaction (RT-PCR) negative result and a positive RT-PCR result on follow-up; and evaluate the accuracy of thoracic imaging for screening COVID-19 in asymptomatic individuals. The secondary objective was to assess threshold effects of index test positivity on accuracy.

SEARCH METHODS

We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 17 February 2021. We did not apply any language restrictions.

SELECTION CRITERIA

We included diagnostic accuracy studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19. Studies had to assess chest CT, chest X-ray, or ultrasound of the lungs for the diagnosis of COVID-19, use a reference standard that included RT-PCR, and report estimates of test accuracy or provide data from which we could compute estimates. We excluded studies that used imaging as part of the reference standard and studies that excluded participants with normal index test results.

DATA COLLECTION AND ANALYSIS

The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using QUADAS-2. We presented sensitivity and specificity per study on paired forest plots, and summarized pooled estimates in tables. We used a bivariate meta-analysis model where appropriate.

MAIN RESULTS

We included 98 studies in this review. Of these, 94 were included for evaluating the diagnostic accuracy of thoracic imaging in the evaluation of people with suspected COVID-19. Eight studies were included for assessing the rate of positive imaging in individuals with initial RT-PCR negative results and positive RT-PCR results on follow-up, and 10 studies were included for evaluating the accuracy of thoracic imaging for imagining asymptomatic individuals. For all 98 included studies, risk of bias was high or unclear in 52 (53%) studies with respect to participant selection, in 64 (65%) studies with respect to reference standard, in 46 (47%) studies with respect to index test, and in 48 (49%) studies with respect to flow and timing. Concerns about the applicability of the evidence to: participants were high or unclear in eight (8%) studies; index test were high or unclear in seven (7%) studies; and reference standard were high or unclear in seven (7%) studies. Imaging in people with suspected COVID-19 We included 94 studies. Eighty-seven studies evaluated one imaging modality, and seven studies evaluated two imaging modalities. All studies used RT-PCR alone or in combination with other criteria (for example, clinical signs and symptoms, positive contacts) as the reference standard for the diagnosis of COVID-19. For chest CT (69 studies, 28285 participants, 14,342 (51%) cases), sensitivities ranged from 45% to 100%, and specificities from 10% to 99%. The pooled sensitivity of chest CT was 86.9% (95% confidence interval (CI) 83.6 to 89.6), and pooled specificity was 78.3% (95% CI 73.7 to 82.3). Definition for index test positivity was a source of heterogeneity for sensitivity, but not specificity. Reference standard was not a source of heterogeneity. For chest X-ray (17 studies, 8529 participants, 5303 (62%) cases), the sensitivity ranged from 44% to 94% and specificity from 24 to 93%. The pooled sensitivity of chest X-ray was 73.1% (95% CI 64. to -80.5), and pooled specificity was 73.3% (95% CI 61.9 to 82.2). Definition for index test positivity was not found to be a source of heterogeneity. Definition for index test positivity and reference standard were not found to be sources of heterogeneity. For ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases), the sensitivity ranged from 73% to 94% and the specificity ranged from 21% to 98%. The pooled sensitivity of ultrasound was 88.9% (95% CI 84.9 to 92.0), and the pooled specificity was 72.2% (95% CI 58.8 to 82.5). Definition for index test positivity and reference standard were not found to be sources of heterogeneity. Indirect comparisons of modalities evaluated across all 94 studies indicated that chest CT and ultrasound gave higher sensitivity estimates than X-ray (P = 0.0003 and P = 0.001, respectively). Chest CT and ultrasound gave similar sensitivities (P=0.42). All modalities had similar specificities (CT versus X-ray P = 0.36; CT versus ultrasound P = 0.32; X-ray versus ultrasound P = 0.89). Imaging in PCR-negative people who subsequently became positive For rate of positive imaging in individuals with initial RT-PCR negative results, we included 8 studies (7 CT, 1 ultrasound) with a total of 198 participants suspected of having COVID-19, all of whom had a final diagnosis of COVID-19. Most studies (7/8) evaluated CT. Of 177 participants with initially negative RT-PCR who had positive RT-PCR results on follow-up testing, 75.8% (95% CI 45.3 to 92.2) had positive CT findings. Imaging in asymptomatic PCR-positive people For imaging asymptomatic individuals, we included 10 studies (7 CT, 1 X-ray, 2 ultrasound) with a total of 3548 asymptomatic participants, of whom 364 (10%) had a final diagnosis of COVID-19. For chest CT (7 studies, 3134 participants, 315 (10%) cases), the pooled sensitivity was 55.7% (95% CI 35.4 to 74.3) and the pooled specificity was 91.1% (95% CI 82.6 to 95.7).

AUTHORS' CONCLUSIONS

Chest CT and ultrasound of the lungs are sensitive and moderately specific in diagnosing COVID-19. Chest X-ray is moderately sensitive and moderately specific in diagnosing COVID-19. Thus, chest CT and ultrasound may have more utility for ruling out COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. The uncertainty resulting from high or unclear risk of bias and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.

Ultrasound findings of lung ultrasonography in COVID-19: A systematic review

PURPOSE

To identify the defining lung ultrasound (LUS) findings of COVID-19, and establish its association to the initial severity of the disease and prognostic outcomes.

METHOD

Systematic review was conducted according to the PRISMA guidelines. We queried PubMed, Embase, Web of Science, Cochrane Database and Scopus using the terms ((coronavirus) OR (covid-19) OR (sars AND cov AND 2) OR (2019-nCoV)) AND (("lung ultrasound") OR (LUS)), from 31st of December 2019 to 31st of January 2021. PCR-confirmed cases of SARS-CoV-2 infection, obtained from original studies with at least 10 participants 18 years old or older, were included. Risk of bias and applicability was evaluated with QUADAS-2.

RESULTS

We found 1333 articles, from which 66 articles were included, with a pooled population of 4687 patients. The most examined findings were at least 3 B-lines, confluent B-lines, subpleural consolidation, pleural effusion and bilateral or unilateral distribution. B-lines, its confluent presentation and pleural abnormalities are the most frequent findings. LUS score was higher in intensive care unit (ICU) patients and emergency department (ED), and it was associated with a higher risk of developing unfavorable outcomes (death, ICU admission or need for mechanical ventilation). LUS findings and/or the LUS score had a good negative predictive value in the diagnosis of COVID-19 compared to RT-PCR.

CONCLUSIONS

The most frequent ultrasound findings of COVID-19 are B-lines and pleural abnormalities. High LUS score is associated with developing unfavorable outcomes. The inclusion of pleural effusion in the LUS score and the standardisation of the imaging protocol in COVID-19 LUS remains to be defined.

Análisis comparativo de la radiografía de tórax y la ecografía pulmonar para predecir el pronóstico intra-hospitalario de pacientes ingresados por neumonía secundaria a SARS-COV2 (COVID-19)

Antecedentes

La ecografía torácica es una técnica novedosa para estratificar el riesgo de los pacientes COVID-19. Sin embargo, no existen datos que comparen dicha técnica con la radiografía de tórax, una técnica ampliamente utilizada en esta enfermedad.

Pacientes y métodos

Análisis retrospectivo en pacientes estables COVID-19. Se compararon la escala de daño pulmonar radiológica de Schalekamp y ecográfica de LUZ-Score. El objetivo primario fue la muerte intrahospitalaria o la necesidad de ingreso en la UCI para tratamiento con ventilación mecánica.

Resultados

Se reclutaron 138 pacientes. La mediana de la escala de Schalekamp fue de 2 (2) y la del LUZ-Score de 21 (10). No se objetivó una correlación significativa entre ambas escalas. Los pacientes con un LUZ-Score ≥ 21 puntos al ingreso presentaron peor función pulmonar y mayores concentraciones de LDH, PCR e interleucina-6. La escala radiológica de Schalekamp no logró identificar a una población de mayor riesgo. Únicamente la adición de la ecografía pulmonar a un modelo de valoración clínica mejoró de manera significativa el área bajo la curva para el objetivo primario (ABC 0,805 [IC 95%: 0,662-0,948]; p ≤ 0,001).

Conclusiones

No se objetivó una correlación entre la afectación radiológica y la ecográfica. Únicamente la ecografía pulmonar identificó un subgrupo de pacientes con una mayor afectación clínico-analítica. La ecografía pulmonar mejoró el modelo de predicción clínico, mientras que la radiografía de tórax no añadió información relevante.

The use of ultrasound in establishing COVID-19 infection as part of a trauma evaluation

Purpose

The use of lung ultrasound for diagnosis of COVID-19 has emerged during the pandemic as a beneficial diagnostic modality due to its rapid availability, bedside use, and lack of radiation. This study aimed to determine if routine ultrasound (US) imaging of the lungs of trauma patients with COVID-19 infections who undergo extended focused assessment with sonography for trauma (EFAST) correlates with computed tomography (CT) imaging and X-ray findings, as previously reported in other populations.

Methods

This was a prospective, observational feasibility study performed at two level 1 trauma centers. US, CT, and X-ray imaging were retrospectively reviewed by a surgical trainee and a board-certified radiologist to determine any correlation of imaging findings in patients with active COVID-19 infection.

Results

There were 53 patients with lung US images from EFAST available for evaluation and COVID-19 testing. The overall COVID-19 positivity rate was 7.5%. COVID-19 infection was accurately identified by one patient on US by the trainee, but there was a 15.1% false-positive rate for infection based on the radiologist examination.

Conclusions

Evaluation of the lung during EFAST cannot be used in the trauma setting to identify patients with active COVID-19 infection or to stratify patients as high or low risk of infection. This is likely due to differences in lung imaging technique and the presence of concomitant thoracic injury.

Coronavirus Disease 2019 Phenotypes, Lung Ultrasound, Chest Computed Tomography and Clinical Features in Critically Ill Mechanically Ventilated Patients

Chest computed tomography (CT) may provide insights into the pathophysiology of coronavirus disease 2019 (COVID-19), although it is not suitable for a timely bedside dynamic assessment of patients admitted to intensive care unit (ICU); therefore, lung ultrasound (LUS) has been proposed as a complementary diagnostic tool. The aims of this study were to investigate different lungs phenotypes in patients with COVID-19 and to assess the differences in CT and LUS scores between ICU survivors and non-survivors. We also explored the association between CT and LUS, and oxygenation (arterial partial pressure of oxygen [PaO₂]/fraction of inspired oxygen [FiO_2]) and clinical parameters. The study included 39 patients with COVID-19. CT scans revealed types 1, 2 and 3 phenotypes in 62%, 28% and 10% of patients, respectively. Among survivors, pattern 1 was prevalent (p < 0.005). Chest CT and LUS scores differed between survivors and non-survivors both at ICU admission and 10 days after and were associated with ICU mortality. Chest CT score was positively correlated with LUS findings at ICU admission (r = 0.953, p < 0.0001) and was inversely correlated with PaO₂/FiO₂ (r = -0.375, p = 0.019) and C-reactive protein (r = 0.329, p = 0.041). LUS score was inversely correlated with PaO₂/FiO₂ (r = -0.345, p = 0.031). COVID-19 presents distinct phenotypes with differences between survivors and non-survivors. LUS is a valuable monitoring tool in an ICU setting because it may correlate with CT findings and mortality, although it cannot predict oxygenation changes.

Italian Society of Anesthesia, Analgesia, Resuscitation, and Intensive Care expert consensus statement on the use of lung ultrasound in critically ill patients with coronavirus disease 2019 (ITACO)

BACKGROUND

To produce statements based on the available evidence and an expert consensus (as members of the Lung Ultrasound Working Group of the Italian Society of Analgesia, Anesthesia, Resuscitation, and Intensive Care, SIAARTI) on the use of lung ultrasound for the management of patients with COVID-19 admitted to the intensive care unit.

METHODS

A modified Delphi method was applied by a panel of anesthesiologists and intensive care physicians expert in the use of lung ultrasound in COVID-19 intensive critically ill patients to reach a consensus on ten clinical questions concerning the role of lung ultrasound in the following: COVID-19 diagnosis and monitoring (with and without invasive mechanical ventilation), positive end expiratory pressure titration, the use of prone position, the early diagnosis of pneumothorax- or ventilator-associated pneumonia, the process of weaning from invasive mechanical ventilation, and the need for radiologic chest imaging.

RESULTS

A total of 20 statements were produced by the panel. Agreement was reached on 18 out of 20 statements (scoring 7-9; "appropriate") in the first round of voting, while 2 statements required a second round for agreement to be reached. At the end of the two Delphi rounds, the median score for the 20 statements was 8.5 [IQR 8.9], and the agreement percentage was 100%.

CONCLUSION

The Lung Ultrasound Working Group of the Italian Society of Analgesia, Anesthesia, Resuscitation, and Intensive Care produced 20 consensus statements on the use of lung ultrasound in COVID-19 patients admitted to the ICU. This expert consensus strongly suggests integrating lung ultrasound findings in the clinical management of critically ill COVID-19 patients.

An outlook on coronavirus disease 2019 detection methods

Diagnostic testing plays a fundamental role in the mitigation and containment of coronavirus disease 2019 (COVID-19), as it enables immediate quarantine of those who are infected and contagious and is essential for the epidemiological characterization of the virus and estimating the number of infected cases worldwide. Confirmation of viral infections, such as COVID-19, can be achieved through two general approaches: nucleic acid amplification tests (NAATs) or molecular tests, and serological or antibody-based tests. The genetic material of the pathogen is detected in NAAT, and in serological tests, host antibodies produced in response to the pathogen are identified. Other methods of diagnosing COVID-19 include radiological imaging of the lungs and in vitro detection of viral antigens. This review covers different approaches available to diagnosing COVID-19 by outlining their advantages and shortcomings, as well as appropriate indications for more accurate testing.

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Diagnostic tests to detect coronavirus disease 2019 (COVID-19).

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Advantages and disadvantages associated with each detection method.

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Implications for a more accurate and rapid testing of COVID-19 or other similar future emergent viruses.

The role of chest imaging in the diagnosis, management, and monitoring of coronavirus disease 2019 (COVID-19)

Coronavirus disease 2019 (COVID-19) pandemic has posed a major public health crisis all over the world. The role of chest imaging, especially computed tomography (CT), has evolved during the pandemic paralleling the accumulation of scientific evidence. In the early stage of the pandemic, the performance of chest imaging for COVID-19 has widely been debated especially in the context of comparison to real-time reverse transcription polymerase chain reaction. Current evidence is against the use of chest imaging for routine screening of COVID-19 contrary to the initial expectations. It still has an integral role to play, however, in its work up and staging, especially when assessing complications or disease progression. Chest CT is gold standard imaging modality for COVID-19 pneumonia; in some situations, chest X-ray or ultrasound may be an effective alternative. The most important role of radiologists in this context is to be able to identify those patients at greatest risk of imminent clinical decompensation by learning to stratify cases of COVID-19 on the basis of radiologic imaging in the most efficient and timely fashion possible. The present availability of multiple and more refined CT grading systems and classification is now making this task easier and thereby contributing to the recent improvements achieved in COVID-19 treatment and outcomes. In this article, evidence of chest imaging regarding diagnosis, management and monitoring of COVID-19 will be chronologically reviewed.

CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict

Purpose

Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test.

Materials and Methods

We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%-96%) and specificity of 37% (95% CI: 26%-50%), and applied to the early outbreak in Wuhan, New York, and Italy.

Results

From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2-6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710-56755) to 44840 (TPR, 38%; 95% CI: 35161-68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks.

Conclusion

Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.

Point-of-care lung ultrasound assessment for risk stratification and therapy guiding in COVID-19 patients: a prospective noninterventional study

BACKGROUND

Lung ultrasound is feasible for assessing lung injury caused by coronavirus disease 2019 (COVID-19). However, the prognostic meaning and time-line changes of lung injury assessed by lung ultrasound in COVID-19 hospitalised patients are unknown.

METHODS

Prospective cohort study designed to analyse prognostic value of lung ultrasound in COVID-19 patients by using a quantitative scale (lung ultrasound Zaragoza (LUZ)-score) during the first 72 h after admission. The primary end-point was in-hospital death and/or admission to the intensive care unit. Total length of hospital stay, increase of oxygen flow and escalation of medical treatment during the first 72 h were secondary end-points.

RESULTS

130 patients were included in the final analysis; mean±sd age was 56.7±13.5 years. Median (interquartile range) time from the beginning of symptoms to admission was 6 (4-9) days. Lung injury assessed by LUZ-score did not differ during the first 72 h (21 (16-26) points at admission versus 20 (16-27) points at 72 h; p=0.183). In univariable logistic regression analysis, estimated arterial oxygen tension/inspiratory oxygen fraction ratio (PAFI) (hazard ratio 0.99, 95% CI 0.98-0.99; p=0.027) and LUZ-score >22 points (5.45, 1.42-20.90; p=0.013) were predictors for the primary end-point.

CONCLUSIONS

LUZ-score is an easy, simple and fast point-of-care ultrasound tool to identify patients with severe lung injury due to COVID-19, upon admission. Baseline score is predictive of severity along the whole period of hospitalisation. The score facilitates early implementation or intensification of treatment for COVID-19 infection. LUZ-score may be combined with clinical variables (as estimated by PAFI) to further refine risk stratification.

Prognostic Significance of Chest Imaging by LUS and CT in COVID-19 Inpatients: The ECOVID Multicenter Study

Background

Point-of-care lung ultrasound (LUS) score is a semiquantitative score of lung damage severity. High-resolution computed tomography (HRCT) is the gold standard method to evaluate the severity of lung involvement from the novel coronavirus disease (COVID-19). Few studies have investigated the clinical significance of LUS and HRCT scores in patients with COVID-19. Therefore, the aim of this study was to evaluate the prognostic yield of LUS and of HRCT in COVID-19 patients.

Methods

We carried out a multicenter, retrospective study aimed at evaluating the prognostic yield of LUS and HRCT by exploring the survival curve of COVID-19 inpatients. LUS and chest CT scores were calculated retrospectively by 2 radiologists with >10 years of experience in chest imaging, and the decisions were reached in consensus. LUS score was calculated on the basis of the presence or not of pleural line abnormalities, B-lines, and lung consolidations. The total score (range 0–36) was obtained from the sum of the highest scores obtained in each region. CT score was calculated for each of the 5 lobes considering the anatomical extension according to the percentage parenchymal involvement. The resulting overall global semiquantitative CT score was the sum of each single lobar score and ranged from 0 (no involvement) to 25 (maximum involvement).

Results

One hundred fifty-three COVID-19 inpatients (mean age 65 ± 15 years; 65% M), including 23 (15%) in-hospital deaths for any cause over a mean follow-up of 14 days were included. Mean LUS and CT scores were 19 ± 12 and 10 ± 7, respectively. A strong positive linear correlation between LUS and CT scores (Pearson correlation r = 0.754; R² = 0.568; p < 0.001) was observed. By ROC curve analysis, the optimal cut-point for mortality prediction was 20 for LUS score and 4.5 for chest CT score. According to Kaplan-Meier survival analysis, in-hospital mortality significantly increased among COVID-19 patients presenting with an LUS score ≥20 (log-rank 0.003; HR 9.87, 95% CI: 2.22–43.83) or a chest CT score ≥4.5 (HR 4.34, 95% CI: 0.97–19.41). At multivariate Cox regression analysis, LUS score was the sole independent predictor of in-hospital mortality yielding an adjusted HR of 7.42 (95% CI: 1.59–34.5).

Conclusion

LUS score is useful to stratify the risk in COVID-19 patients, predicting those that are at high risk of mortality.

Differential diagnosis of COVID-19 at the chest computed tomography scan: A review with special focus on cancer patients

BACKGROUND

Given the several radiological features shared by coronavirus disease 2019 pneumonia and other infective or non-infective diseases with lung involvement, the differential diagnosis is often tricky, and no unequivocal tool exists to help the radiologist in the proper diagnosis. Computed tomography is considered the gold standard in detecting pulmonary illness caused by severe acute respiratory syndrome coronavirus 2.

AIM

To conduct a systematic review including the available studies evaluating computed tomography similarities and discrepancies between coronavirus disease 2019 pneumonia and other pulmonary illness, then providing a discussion focus on cancer patients.

METHODS

Using pertinent keywords, we performed a systematic review using PubMed to select relevant studies published until October 30, 2020.

RESULTS

Of the identified 133 studies, 18 were eligible and included in this review.

CONCLUSION

Ground-glass opacity and consolidations are the most common computed tomography lesions in coronavirus disease 2019 pneumonia and other respiratory diseases. Only two studies included cancer patients, and the differential diagnosis with early lung cancer and radiation pneumonitis was performed. A single lesion associated with pleural effusion and lymphadenopathies in lung cancer and the onset of the lesions in the radiation field in the case of radiation pneumonitis allowed the differential diagnosis. Nevertheless, the studies were heterogeneous, and the type and prevalence of lesions, distributions, morphology, evolution, and additional signs, together with epidemiological, clinical, and laboratory findings, are crucial to help in the differential diagnosis.

Prevalence and significance of pulmonary disease on lung ultrasonography in outpatients with SARS-CoV-2 infection

BACKGROUND

The majority of patients with SARS-CoV-2 infection are diagnosed and managed as outpatients; however, little is known about the burden of pulmonary disease in this setting. Lung ultrasound (LUS) is a convenient tool for detection of COVID-19 pneumonia. Identifying SARS-CoV-2 infected outpatients with pulmonary disease may be important for early risk stratification.

OBJECTIVES

To investigate the prevalence, natural history and clinical significance of pulmonary disease in outpatients with SARS-CoV-2.

METHODS

SARS-CoV-2 PCR positive outpatients (CV(+)) were assessed with LUS to identify the presence of interstitial pneumonia. Studies were considered positive based on the presence of B-lines, pleural irregularity and consolidations. A subset of patients underwent longitudinal examinations. Correlations between LUS findings and patient symptoms, demographics, comorbidities and clinical outcomes over 8 weeks were evaluated.

RESULTS

102 CV(+) patients underwent LUS with 42 (41%) demonstrating pulmonary involvement. Baseline LUS severity scores correlated with shortness of breath on multivariate analysis. Of the CV(+) patients followed longitudinally, a majority showed improvement or resolution in LUS findings after 1-2 weeks. Only one patient in the CV(+) cohort was briefly hospitalised, and no patient died or required mechanical ventilation.

CONCLUSION

We found a high prevalence of LUS findings in outpatients with SARS-CoV-2 infection. Given the pervasiveness of pulmonary disease across a broad spectrum of LUS severity scores and lack of adverse outcomes, our findings suggest that LUS may not be a useful as a risk stratification tool in SARS-CoV-2 in the general outpatient population.

Lung Ultrasound in the Diagnosis of COVID-19 Pneumonia: Not Always and Not Only What Is COVID-19 "Glitters"

Background: In the current coronavirus disease-2019 (COVID-19) pandemic, lung ultrasound (LUS) has been extensively employed to evaluate lung involvement and proposed as a useful screening tool for early diagnosis in the emergency department (ED), prehospitalization triage, and treatment monitoring of COVID-19 pneumonia. However, the actual effectiveness of LUS in characterizing lung involvement in COVID-19 is still unclear. Our aim was to evaluate LUS diagnostic performance in assessing or ruling out COVID-19 pneumonia when compared with chest CT (gold standard) in a population of SARS-CoV-2-infected patients. Methods: A total of 260 consecutive RT-PCR confirmed SARS-CoV-2-infected patients were included in the study. All the patients underwent both chest CT scan and concurrent LUS at admission, within the first 6-12 h of hospital stay. Results: Chest CT scan was considered positive when showing a "typical" or "indeterminate" pattern for COVID-19, according to the RSNA classification system. Disease prevalence for COVID-19 pneumonia was 90.77%. LUS demonstrated a sensitivity of 56.78% in detecting lung alteration. The concordance rate for the assessment of abnormalities by both methods increased in the case of peripheral distribution and middle-lower lung location of lesions and in cases of more severe lung involvement. A total of nine patients had a "false-positive" LUS examination. Alternative diagnosis included chronic heart disease (six cases), bronchiectasis (two cases), and subpleural emphysema (one case). LUS specificity was 62.50%. Collateral findings indicative of overlapping conditions at chest CT were recorded also in patients with COVID-19 pneumonia and appeared distributed with increasing frequency passing from the group with mild disease (17 cases) to that with severe disease (40 cases). Conclusions: LUS does not seem to be an adequate tool for screening purposes in the ED, due to the risk of missing some lesions and/or to underestimate the actual extent of the disease. Furthermore, the not specificity of LUS implies the possibility to erroneously classify pre-existing or overlapping conditions as COVID-19 pneumonia. It seems more safe to integrate a positive LUS examination with clinical, epidemiological, laboratory, and radiologic findings to suggest a "virosis." Viral testing confirmation is always required.

A comprehensive review of imaging findings in COVID-19 - status in early 2021

Medical imaging methods are assuming a greater role in the workup of patients with COVID-19, mainly in relation to the primary manifestation of pulmonary disease and the tissue distribution of the angiotensin-converting-enzyme 2 (ACE 2) receptor. However, the field is so new that no consensus view has emerged guiding clinical decisions to employ imaging procedures such as radiography, computer tomography (CT), positron emission tomography (PET), and magnetic resonance imaging, and in what measure the risk of exposure of staff to possible infection could be justified by the knowledge gained. The insensitivity of current RT-PCR methods for positive diagnosis is part of the rationale for resorting to imaging procedures. While CT is more sensitive than genetic testing in hospitalized patients, positive findings of ground glass opacities depend on the disease stage. There is sparse reporting on PET/CT with [18F]-FDG in COVID-19, but available results are congruent with the earlier literature on viral pneumonias. There is a high incidence of cerebral findings in COVID-19, and likewise evidence of gastrointestinal involvement. Artificial intelligence, notably machine learning is emerging as an effective method for diagnostic image analysis, with performance in the discriminative diagnosis of diagnosis of COVID-19 pneumonia comparable to that of human practitioners.

Impact of the COVID-19 pandemic on the selection of chest imaging modalities and reporting systems: a survey of Italian radiologists

PURPOSE

Chest imaging modalities play a key role for the management of patient with coronavirus disease (COVID-19). Unfortunately, there is no consensus on the optimal chest imaging approach in the evaluation of patients with COVID-19 pneumonia, and radiology departments tend to use different approaches. Thus, the main objective of this survey was to assess how chest imaging modalities have been used during the different phases of the first COVID-19 wave in Italy, and which diagnostic technique and reporting system would have been preferred based on the experience gained during the pandemic.

MATERIAL AND METHODS

The questionnaire of the survey consisted of 26 questions. The link to participate in the survey was sent to all members of the Italian Society of Medical and Interventional Radiology (SIRM).

RESULTS

The survey gathered responses from 716 SIRM members. The most notable result was that the most used and preferred chest imaging modality to assess/exclude/monitor COVID-19 pneumonia during the different phases of the first COVID-19 wave was computed tomography (51.8% to 77.1% of participants). Additionally, while the narrative report was the most used reporting system (55.6% of respondents), one-third of participants would have preferred to utilize structured reporting systems.

CONCLUSION

This survey shows that the participants' responses did not properly align with the imaging guidelines for managing COVID-19 that have been made by several scientific, including SIRM. Therefore, there is a need for continuing education to keep radiologists up to date and aware of the advantages and limitations of the chest imaging modalities and reporting systems.

Lung Ultrasound Patterns and Clinical-Laboratory Correlates during COVID-19 Pneumonia: A Retrospective Study from North East Italy

Background and Aim. Lung ultrasound (LUS) is a convenient imaging modality in the setting of coronavirus disease-19 (COVID-19) because it is easily available, can be performed bedside and repeated over time. We herein examined LUS patterns in relation to disease severity and disease stage among patients with COVID-19 pneumonia. Methods. We performed a retrospective case series analysis of patients with confirmed SARS-CoV-2 infection who were admitted to the hospital because of pneumonia. We recorded history, clinical parameters and medications. LUS was performed and scored in a standardized fashion by experienced operators, with evaluation of up to 12 lung fields, reporting especially on B-lines and consolidations. Results. We included 96 patients, 58.3% men, with a mean age of 65.9 years. Patients with a high-risk quick COVID-19 severity index (qCSI) were older and had worse outcomes, especially for the need for high-flow oxygen. B-lines and consolidations were located mainly in the lower posterior lung fields. LUS patterns for B-lines and consolidations were significantly worse in all lung fields among patients with high versus low qCSI. B-lines and consolidations were worse in the intermediate disease stage, from day 7 to 13 after onset of symptoms. While consolidations correlated more with inflammatory biomarkers, B-lines correlated more with end-organ damage, including extrapulmonary involvement. Conclusions. LUS patterns provide a comprehensive evaluation of patients with COVID-19 pneumonia that correlated with severity and dynamically reflect disease stage. LUS patterns may reflect different pathophysiological processes related to inflammation or tissue damage; consolidations may represent a more specific sign of localized disease, whereas B-lines seem to be also dependent upon generalized illness due to SARS-CoV-2 infection.

Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study

Purpose

To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient’s symptoms and clinical history.

Methods

This is an international multicenter observational study in 20 US and European hospitals. Patients suspected of COVID-19 were tested with reverse transcription-polymerase chain reaction (RT-PCR) swab test and had an LUS examination. We identified three clinical phenotypes based on pre-existing chronic diseases (mixed phenotype), and on the presence (severe phenotype) or absence (mild phenotype) of signs and/or symptoms of respiratory failure at presentation. We defined the LUS likelihood of COVID-19 pneumonia according to four different patterns: high (HighLUS), intermediate (IntLUS), alternative (AltLUS), and low (LowLUS) probability. The combination of patterns and phenotypes with RT-PCR results was described and analyzed.

Results

We studied 1462 patients, classified in mild (n = 400), severe (n = 727), and mixed (n = 335) phenotypes. HighLUS and IntLUS showed an overall sensitivity of 90.2% (95% CI 88.23–91.97%) in identifying patients with positive RT-PCR, with higher values in the mixed (94.7%) and severe phenotype (97.1%), and even higher in those patients with objective respiratory failure (99.3%). The HighLUS showed a specificity of 88.8% (CI 85.55–91.65%) that was higher in the mild phenotype (94.4%; CI 90.0–97.0%). At multivariate analysis, the HighLUS was a strong independent predictor of RT-PCR positivity (odds ratio 4.2, confidence interval 2.6–6.7, p < 0.0001).

Conclusion

Combining LUS patterns of probability with clinical phenotypes at presentation can rapidly identify those patients with or without COVID-19 pneumonia at bedside. This approach could support and expedite patients’ management during a pandemic surge.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06373-7.

Applying the lessons learned from coronavirus disease 2019 to improve pneumonia management

PURPOSE OF REVIEW

Coronavirus disease 2019 (COVID-19) has produced an extraordinary amount of literature in a short time period. This review focuses on what the new literature has provided in terms of more general information about the management of community-acquired pneumonia (CAP).

RECENT FINDINGS

Measures taken to reduce the spread of COVID-19 have caused a significant drop in influenza worldwide. Improvements in imaging, especially ultrasound, and especially in the application of rapid molecular diagnosis are likely to have significant impact on the management of CAP. Therapeutic advances are so far limited.

SUMMARY

COVID-19 has taught us that we can do far more to prevent seasonal influenza and its associated mortality, morbidity and economic cost. Improvements in imaging and pathogen diagnosis are welcome, as is the potential for secondary benefits of anti-COVID-19 therapies that may have reach effect on respiratory viruses other than severe acute respiratory syndrome coronavirus 2. As community-transmission is likely to persist for many years, recognition and treatment of severe acute respiratory syndrome coronavirus 2 will need to be incorporated into CAP guidelines moving forward.

Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients

Purpose

The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear.

Methods

PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospectively analysed. In both modalities, twelve peripheral lung zones were identified and given a Severity Score basing on main lesion pattern. On CT scans the well-aerated lung volume (%WALV) was visually estimated. Per-patient and per-zone assessments of LUS classification performance taking CT findings as reference were performed, further revisioning the images in case of discordant results. Correlations between number of disease-positive lung zones, Severity Score and %WALV on both LUS and CT were assessed. The area under receiver operating characteristic curve (AUC) was calculated to determine LUS performance in detecting %WALV ≤ 70 %.

Results

The study included 219 COVID-19 patients with abnormal chest CT. LUS correctly identified as positive 217 (99 %) patients, but per-zone analysis showed sensitivity = 75 % and specificity = 66 %. The revision of the 121 (55 %) cases with positive LUS and negative CT revealed COVID-compatible lesions in 42 (38 %) CT scans. Number of disease-positive zones, Severity Score and %WALV between LUS and CT showed moderate correlations. The AUCs for LUS Severity Score and number of LUS-positive zones did not differ in detecting %WALV ≤ 70 %.

Conclusion

LUS in COVID-19 is valuable for case identification but shows only moderate correlation with CT findings as for lesion patterns and severity quantification. The number of disease-positive lung zones in LUS alone was sufficient to discriminate relevant disease burden.

Clinical Characteristics of the COVID-19 Patients with Pneumonia Detected by Computerized Tomography but Negative for Infiltration by X-ray

Coronavirus Disease 2019 (COVID-19) has rapidly spread to all corners of the globe. Different diagnostic tools, such as Chest X-ray (CXR), lung ultrasound (LUS), and computerized tomography (CT), have been used to detect active pneumonic lesions associated with COVID-19 with their varying degrees of sensitivity and specificity. This study was undertaken to investigate the clinical characteristics of COVID-19 patients with a pneumonic lung lesion detected by CT that is not detected by CXR. A total of 156 COVID-19 patients hospitalized at three nationally designated South Korean hospitals with no active lesion detected by CXR but on clinical suspicion of pneumonia underwent the CT examination and were enrolled. Medical records, which included demographic and clinical features, including comorbidity, symptoms, radiological, and laboratory findings on admission, were reviewed and analyzed. The risk factors of pneumonia detected by CT for patients without an active lesion detected by CXR were investigated. Of the 156 patients without an active lesion detected by CXR, 35 (22.44%) patients were found to have pneumonia by CT. The patients with pneumonia defined by CT were older than those without (64.1 years vs. 41.2 years). Comorbidities such as hypertension, diabetes, cardiovascular disease, preexisting stroke, and dementia were more common among patients with pneumonia defined by CT than those without. Serum albumin level, C-reactive protein (CRP), stroke, and age ≥ 70 years were significantly associated with pneumonia defined by CT after adjustment for age. In multivariable regression analysis, serum albumin level (adjusted odds ratio (AOR) = 0.123, 95% CI = (0.035-0.429)) and preexisting stroke (AOR = 11.447, 95% CI = (1.168-112.220)) significantly and independently predicted pneumonia detection by CT. Our results suggest that CT scans should be performed on COVID-19 patients negative for a pneumonic lung lesion by CXR who are suspected to be pneumonic on clinical grounds. In addition, older patients with a lower albumin level and a preexisting stroke should be checked for the presence of pneumonia despite a negative CXR finding for an active lesion.

Qualitative and quantitative chest CT parameters as predictors of specific mortality in COVID-19 patients

PURPOSE

To test the association between death and both qualitative and quantitative CT parameters obtained visually and by software in coronavirus disease (COVID-19) early outbreak.

METHODS

The study analyzed retrospectively patients underwent chest CT at hospital admission for COVID-19 pneumonia suspicion, between February 21 and March 6, 2020. CT was performed in case of hypoxemia or moderate-to-severe dyspnea. CT scans were analyzed for quantitative and qualitative features obtained visually and by software. Cox proportional hazards regression analysis examined the association between variables and overall survival (OS). Three models were built for stratification of mortality risk: clinical, clinical/visual CT evaluation, and clinical/software-based CT assessment. AUC for each model was used to assess performance in predicting death.

RESULTS

The study included 248 patients (70% males, median age 68 years). Death occurred in 78/248 (32%) patients. Visual pneumonia extent > 40% (HR 2.15, 95% CI 1.2-3.85, P = 0.01), %high attenuation area - 700 HU > 35% (HR 2.17, 95% CI 1.2-3.94, P = 0.01), exudative consolidations (HR 2.85-2.93, 95% CI 1.61-5.05/1.66-5.16, P < 0.001), visual CAC score > 1 (HR 2.76-3.32, 95% CI 1.4-5.45/1.71-6.46, P < 0.01/P < 0.001), and CT classified as COVID-19 and other disease (HR 1.92-2.03, 95% CI 1.01-3.67/1.06-3.9, P = 0.04/P = 0.03) were significantly associated with shorter OS. Models including CT parameters (AUC 0.911-0.913, 95% CI 0.873-0.95/0.875-0.952) were better predictors of death as compared to clinical model (AUC 0.869, 95% CI 0.816-0.922; P = 0.04 for both models).

CONCLUSIONS

In COVID-19 patients, qualitative and quantitative chest CT parameters obtained visually or by software are predictors of mortality. Predictive models including CT metrics were better predictors of death in comparison to clinical model.