The use of lung ultrasound in COVID-19

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.

Standardization of interstitial lung disease assessment by ultrasound: results from a Delphi process and web-reliability exercise by the OMERACT ultrasound working group

OBJECTIVES

Over the last years ultrasound has shown to be an important tool for evaluating lung involvement, including interstitial lung disease (ILD) a potentially severe systemic involvement in many rheumatic and musculoskeletal diseases (RMD). Despite the potential sensitivity of the technique the actual use is hampered by the lack of consensual definitions of elementary lesions to be assessed and of the scanning protocol to apply. Within the Outcome Measures in Rheumatology (OMERACT) Ultrasound Working Group we aimed at developing consensus-based definitions for ultrasound detected ILD findings in RMDs and assessing their reliability in dynamic images.

METHODS

Based on the results from a systematic literature review, several findings were identified for defining the presence of ILD by ultrasound (i.e., Am-lines, B-lines, pleural cysts and pleural line irregularity). Therefore, a Delphi survey was conducted among 23 experts in sonography to agree on which findings should be included and on their definitions. Subsequently, a web-reliability exercise was performed to test the reliability of the agreed definitions on video-clips, by using kappa statistics.

RESULTS

After three rounds of Delphi an agreement >75 % was obtained to include and define B-lines and pleural line irregularity as elementary lesions to assess. The reliability in the web-based exercise, consisting of 80 video-clips (30 for pleural line irregularity, 50 for B-lines), showed moderate inter-reader reliability for both B-lines (kappa = 0.51) and pleural line irregularity (kappa = 0.58), while intra-reader reliability was good for both B-lines (kappa = 0.72) and pleural line irregularity (kappa = 0.75).

CONCLUSION

Consensus-based ultrasound definitions for B-lines and pleural line irregularity were obtained, with moderate to good reliability to detect these lesions using video-clips. The next step will be testing the reliability in patients with ILD linked to RMDs and to propose a consensual and standardized protocol to scan such patients.

COVID-Net L2C-ULTRA: An Explainable Linear-Convex Ultrasound Augmentation Learning Framework to Improve COVID-19 Assessment and Monitoring

While no longer a public health emergency of international concern, COVID-19 remains an established and ongoing global health threat. As the global population continues to face significant negative impacts of the pandemic, there has been an increased usage of point-of-care ultrasound (POCUS) imaging as a low-cost, portable, and effective modality of choice in the COVID-19 clinical workflow. A major barrier to the widespread adoption of POCUS in the COVID-19 clinical workflow is the scarcity of expert clinicians who can interpret POCUS examinations, leading to considerable interest in artificial intelligence-driven clinical decision support systems to tackle this challenge. A major challenge to building deep neural networks for COVID-19 screening using POCUS is the heterogeneity in the types of probes used to capture ultrasound images (e.g., convex vs. linear probes), which can lead to very different visual appearances. In this study, we propose an analytic framework for COVID-19 assessment able to consume ultrasound images captured by linear and convex probes. We analyze the impact of leveraging extended linear-convex ultrasound augmentation learning on producing enhanced deep neural networks for COVID-19 assessment, where we conduct data augmentation on convex probe data alongside linear probe data that have been transformed to better resemble convex probe data. The proposed explainable framework, called COVID-Net L2C-ULTRA, employs an efficient deep columnar anti-aliased convolutional neural network designed via a machine-driven design exploration strategy. Our experimental results confirm that the proposed extended linear-convex ultrasound augmentation learning significantly increases performance, with a gain of 3.9% in test accuracy and 3.2% in AUC, 10.9% in recall, and 4.4% in precision. The proposed method also demonstrates a much more effective utilization of linear probe images through a 5.1% performance improvement in recall when such images are added to the training dataset, while all other methods show a decrease in recall when trained on the combined linear-convex dataset. We further verify the validity of the model by assessing what the network considers to be the critical regions of an image with our contribution clinician.

Evaluating Acute Pulmonary Changes in Coronavirus Disease 2019: A Comparative Analysis of Computed Tomography, Chest Radiography, Lung Ultrasound, Magnetic Resonance Imaging, and Positron Emission Tomography with Fluorodeoxyglucose Modalities

This review explores imaging's crucial role in acute Coronavirus Disease 2019 (COVID-19) assessment. High Resolution Computer Tomography is especially effective in detection of lung abnormalities. Chest radiography has limited utility in the initial stages of COVID-19 infection. Lung Ultrasound has emerged as a valuable, radiation-free tool in critical care, and Magnetic Resonance Imaging shows promise as a Computed Tomography alternative. Typical and atypical findings of COVID-19 by each of these modalities are discussed with emphasis on their prognostic value. Considerations for pediatric and immunocompromised cases are outlined. A comprehensive diagnostic approach is recommended, as radiological diagnosis remains challenging in the acute phase.

Correlation between Serum Biomarkers and Lung Ultrasound in COVID-19: An Observational Study

Serum biomarkers and lung ultrasound are important measures for prognostication and treatment allocation in patients with COVID-19. Currently, there is a paucity of studies investigating relationships between serum biomarkers and ultrasonographic biomarkers derived from lung ultrasound. This study aims to assess correlations between serum biomarkers and lung ultrasound findings. This study is a secondary analysis of four prospective observational studies in adult patients with COVID-19. Serum biomarkers included markers of epithelial injury, endothelial dysfunction and immune activation. The primary outcome was the correlation between biomarker concentrations and lung ultrasound score assessed with Pearson's (r) or Spearman's (rs) correlations. Forty-four patients (67 [41-88] years old, 25% female, 52% ICU patients) were included. GAS6 (rs = 0.39), CRP (rs = 0.42) and SP-D (rs = 0.36) were correlated with lung ultrasound scores. ANG-1 (rs = -0.39) was inversely correlated with lung ultrasound scores. No correlations were found between lung ultrasound score and several other serum biomarkers. In patients with COVID-19, several serum biomarkers of epithelial injury, endothelial dysfunction and immune activation correlated with lung ultrasound findings. The lack of correlations with certain biomarkers could offer opportunities for precise prognostication and targeted therapeutic interventions by integrating these unlinked biomarkers.

Lung ultrasound and supine chest X-ray use in modern adult intensive care: mapping 30 years of advancement (1993-2023)

In critically ill patients with acute respiratory failure, thoracic images are essential for evaluating the nature, extent and progression of the disease, and for clinical management decisions. For this purpose, computed tomography (CT) is the gold standard. However, transporting patients to the radiology suite and exposure to ionized radiation limit its use. Furthermore, a CT scan is a static diagnostic exam for the thorax, not allowing, for example, appreciation of "lung sliding". Its use is also unsuitable when it is necessary to adapt or decide to modify mechanical ventilation parameters at the bedside in real-time. Therefore, chest X-ray and lung ultrasound are today's contenders for shared second place on the podium to acquire a thoracic image, with their specific strengths and limitations. Finally, electrical impedance tomography (EIT) could soon have a role, however, its assessment is outside the scope of this review. Thus, we aim to carry out the following points: (1) analyze the advancement in knowledge of lung ultrasound use and the related main protocols adopted in intensive care units (ICUs) over the latest 30 years, reporting the principal publications along the way, (2) discuss how and when lung ultrasound should be used in a modern ICU and (3) illustrate the possible future development of LUS.

A Modified Corona Score Using Lung Ultrasound to Identify COVID-19 Patients

BACKGROUND

COVID-19 continues to circulate around the world with multiple different strains being active at once. While diagnosis with antigen and molecular testing is more readily available, there is still room for alternative methods of diagnosis, particularly in out-of-hospital settings, e.g., home or nursing homes, and in low-medium income countries, where testing may not be readily available.

STUDY OBJECTIVES

To evaluate the performance of two modified corona score methods compared with a traditional corona score approach to identify patients with COVID-19.

METHODS

This was a retrospective multicenter study performed to compare the ability to predict SARS-CoV-2 test results on a nasopharyngeal swab between the corona scores and two novel corona scores (modified 1 corona score (M1CS) and modified 2 corona score (M2CS)). The M1CS included lung ultrasound (LUS) and chest X-ray (CXR) results, while the M2SC only utilized LUS findings without CXRs. Emergency physicians performed point-of-care LUS and a physical examination upon admission to the emergency department.

RESULTS

Subjects positive for SARS-CoV-2 were older and had higher ferritin levels and temperature and lower diastolic blood pressure and oxygen saturation. The two groups differed on corona score and modified corona scores (p < 0.001 for all). SARS-CoV-2-positive patients had fewer pleural line irregularities (p = 0.025) but presented more frequently with an interstitial pattern on CXRs (p < 0.001).

CONCLUSIONS

In our study, LUS alone provided a valuable contribution to the corona score and improved its performance more than when CXR results were included. These results suggest that resource-limited areas where CXRs may be unavailable or prohibitively expensive can utilize an ultrasound as the sole imaging modality without a loss of diagnostic performance for SARS-CoV-2 pneumonia diagnosis.

Can Artificial Intelligence Aid Diagnosis by Teleguided Point-of-Care Ultrasound? A Pilot Study for Evaluating a Novel Computer Algorithm for COVID-19 Diagnosis Using Lung Ultrasound

With the 2019 coronavirus disease (COVID-19) pandemic, there is an increasing demand for remote monitoring technologies to reduce patient and provider exposure. One field that has an increasing potential is teleguided ultrasound, where telemedicine and point-of-care ultrasound (POCUS) merge to create this new scope. Teleguided POCUS can minimize staff exposure while preserving patient safety and oversight during bedside procedures. In this paper, we propose the use of teleguided POCUS supported by AI technologies for the remote monitoring of COVID-19 patients by non-experienced personnel including self-monitoring by the patients themselves. Our hypothesis is that AI technologies can facilitate the remote monitoring of COVID-19 patients through the utilization of POCUS devices, even when operated by individuals without formal medical training. In pursuit of this goal, we performed a pilot analysis to evaluate the performance of users with different clinical backgrounds using a computer-based system for COVID-19 detection using lung ultrasound. The purpose of the analysis was to emphasize the potential of the proposed AI technology for improving diagnostic performance, especially for users with less experience.

Serial lung ultrasound in monitoring viral pneumonia: the lesson learned from COVID-19

Background

Lung ultrasound (LUS) has proven to be useful in the evaluation of lung involvement in COVID-19. However, its effectiveness for predicting the risk of severe disease is still up for debate. The aim of the study was to establish the prognostic accuracy of serial LUS examinations in the prediction of clinical deterioration in hospitalised patients with COVID-19.

Methods

Prospective single-centre cohort study of patients hospitalised for COVID-19. The study protocol consisted of a LUS examination within 24 h from admission and a follow-up examination on day 3 of hospitalisation. Lung involvement was evaluated by a 14-area LUS score. The primary end-point was the ability of LUS to predict clinical deterioration defined as need for intensive respiratory support with high-flow oxygen or invasive mechanical ventilation.

Results

200 patients were included and 35 (17.5%) of them reached the primary end-point and were transferred to the intensive care unit (ICU). The LUS score at admission had been significantly higher in the ICU group than in the non-ICU group (22 (interquartile range (IQR) 20-26) versus 12 (IQR 8-15)). A LUS score at admission ≥17 was shown to be the best cut-off point to discriminate patients at risk of deterioration (area under the curve (AUC) 0.95). The absence of progression in LUS score on day 3 significantly increased the prediction accuracy by ruling out deterioration with a negative predictive value of 99.29%.

Conclusion

Serial LUS is a reliable tool in predicting the risk of respiratory deterioration in patients hospitalised due to COVID-19 pneumonia. LUS could be further implemented in the future for risk stratification of viral pneumonia.

Lung Ultrasound in Critical Care and Emergency Medicine: Clinical Review

Lung ultrasound has become a part of the daily examination of physicians working in intensive, sub-intensive, and general medical wards. The easy access to hand-held ultrasound machines in wards where they were not available in the past facilitated the widespread use of ultrasound, both for clinical examination and as a guide to procedures; among point-of-care ultrasound techniques, the lung ultrasound saw the greatest spread in the last decade. The COVID-19 pandemic has given a boost to the use of ultrasound since it allows to obtain a wide range of clinical information with a bedside, not harmful, repeatable examination that is reliable. This led to the remarkable growth of publications on lung ultrasounds. The first part of this narrative review aims to discuss basic aspects of lung ultrasounds, from the machine setting, probe choice, and standard examination to signs and semiotics for qualitative and quantitative lung ultrasound interpretation. The second part focuses on how to use lung ultrasound to answer specific clinical questions in critical care units and in emergency departments.

Role of Lung Ultrasound in the Follow-Up of Children with Previous SARS-CoV-2 Infection: A Case-Control Assessment of Children with Long COVID or Fully Recovered

Lung ultrasound (LUS) can detect lower respiratory tract involvement in children with acute SARS-CoV-2 infection. However, its role in follow-up assessments is still unclear. To describe LUS findings in children after SARS-CoV-2 infection, we conducted a prospective study in a population of pediatric patients referred to the post-COVID unit in a tertiary center during the study period from February 2021 to May 2022. Children were classified as recovered from acute infection or with persisting symptoms. LUS was performed in all children and a LUS score (ranging from 0 to 36 points) was calculated according to the Italian Academy of Thoracic Ultrasound. Six hundred forty-seven children (304 females, 47%) were enrolled. The median follow-up evaluation was two months. The median age was 7.9 (IQR: 6) years. At the follow-up evaluation, 251 patients (38.8%) had persistent symptoms, of whom 104 (16.1%) had at least one respiratory symptom. The median LUS level was 2 (IQR: 4). LUS findings and LUS scores did not differ in children with Long COVID compared to the group of children fully recovered from the initial infection. In conclusion, after SARS-CoV-2 infection, LUS was mostly normal or showed minimal artifacts in all groups of children.

A Global Review of the Impacts of the Coronavirus (COVID-19) Pandemic on Radiology Practice, Finances, and Operations

The Coronavirus Disease 2019 (COVID-19) pandemic ushered in rapid changes in healthcare, including radiology, globally. This review discusses the impact of the pandemic on various radiology departments globally. We analyze the implications of the COVID-19 pandemic on the imaging volumes, finances, and clinical operations of radiology departments in 2020. Studies from health systems and outpatient imaging centers were analyzed, and the activity throughout 2020 was compared to the pre-pandemic activity, including activity during similar timeframes in 2019. Imaging volumes across modalities, including MRI and CT scans, were compared, as were the Relative Value Units (RVUs) for imaging finances. Furthermore, we compared clinical operations, including staffing and sanitation procedures. We found that imaging volumes in private practices and academic centers decreased globally. The decreases in volume could be attributed to delayed patient screenings, as well as the implementation of protocols, such as the deep cleaning of equipment between patients. Revenues from imaging also decreased globally, with many institutions noting a substantial decline in RVUs and revenue compared with pre-COVID-19 levels. Our analysis thus found significant changes in the volumes, finances, and operations of radiology departments due to the COVID-19 pandemic.