Lung ultrasound in the COVID-19 pandemic

The Current Status of Virtual Autopsy Using Combined Imaging Modalities: A Scoping Review

Background/Objectives: Virtual autopsy (virtopsy) is a new domain of research for interdisciplinary teams of radiologists and forensic specialists. This scoping review aims to underline the current state-of-the-art research using combined imaging modalities. Methods: We searched the PubMed database using the term virtopsy for articles that are available in free full text, indexed in the Medline Database, and published in English. The query returned 49 articles on this subject that have been published since 2002. Results: The main imaging modalities used for postmortem imaging were computed tomography (PMCT), angiography (PMCTA), magnetic resonance imaging (PMMRI), and ultrasonography (PMUS). PMCT is highly effective for detecting complex osseous injuries, tracing bullet trajectories, or identifying characteristic findings in drowning cases. PMCTA is valuable for evaluating vascular lesions, particularly in natural death cases. PMMRI is superior in analyzing soft tissues, including brain and spinal structures, cerebrospinal fluid, microbleeds, and laryngohyoid lesions, and identifying cardiomyopathies in young individuals. PMUS serves as an alternative, and its portability also allows for use in forensic settings. One specific situation observed was the increased number of studies published about virtopsy during the COVID-19 pandemic. Another aspect is the increased focus on this alternative to conventional autopsy in the regions where maneuvering of the deceased is limited according to cultural and social customs. Conclusions: We underline the advantages and limitations of each imaging modality used for virtopsy. Further studies need to be developed in order to gather supplementary data regarding the use of these imaging modalities in the new era of artificial intelligence in medicine.

Knowledge fused latent representation from lung ultrasound examination for COVID-19 pneumonia severity assessment

COVID-19 pneumonia severity assessment is of great clinical importance, and lung ultrasound (LUS) plays a crucial role in aiding the severity assessment of COVID-19 pneumonia due to its safety and portability. However, its reliance on qualitative and subjective observations by clinicians is a limitation. Moreover, LUS images often exhibit significant heterogeneity, emphasizing the need for more quantitative assessment methods. In this paper, we propose a knowledge fused latent representation framework tailored for COVID-19 pneumonia severity assessment using LUS examinations. The framework transforms the LUS examination into latent representation and extracts knowledge from regions labeled by clinicians to improve accuracy. To fuse the knowledge into the latent representation, we employ a knowledge fusion with latent representation (KFLR) model. This model significantly reduces errors compared to approaches that lack prior knowledge integration. Experimental results demonstrate the effectiveness of our method, achieving high accuracy of 96.4 % and 87.4 % for binary-level and four-level COVID-19 pneumonia severity assessments, respectively. It is worth noting that only a limited number of studies have reported accuracy for clinically valuable exam level assessments, and our method surpass existing methods in this context. These findings highlight the potential of the proposed framework for monitoring disease progression and patient stratification in COVID-19 pneumonia cases.

Current Diagnostic Techniques for Pneumonia: A Scoping Review

Community-acquired pneumonia is one of the most lethal infectious diseases, especially for infants and the elderly. Given the variety of causative agents, the accurate early detection of pneumonia is an active research area. To the best of our knowledge, scoping reviews on diagnostic techniques for pneumonia are lacking. In this scoping review, three major electronic databases were searched and the resulting research was screened. We categorized these diagnostic techniques into four classes (i.e., lab-based methods, imaging-based techniques, acoustic-based techniques, and physiological-measurement-based techniques) and summarized their recent applications. Major research has been skewed towards imaging-based techniques, especially after COVID-19. Currently, chest X-rays and blood tests are the most common tools in the clinical setting to establish a diagnosis; however, there is a need to look for safe, non-invasive, and more rapid techniques for diagnosis. Recently, some non-invasive techniques based on wearable sensors achieved reasonable diagnostic accuracy that could open a new chapter for future applications. Consequently, further research and technology development are still needed for pneumonia diagnosis using non-invasive physiological parameters to attain a better point of care for pneumonia patients.

The Role of POCUS to Face COVID-19: A Narrative Review

COVID-19 has been a challenging outbreak to face, with millions of deaths among the globe. Acute respiratory failure due to interstitial pneumonia was the leading cause of death other than prothrombotic activation and complications. Lung ultrasound (LUS) and point-of-care ultrasound (POCUS) are widely used not only to triage, to identify, and to monitor lungs involvement but also to assess hemodynamic status and thrombotic and hemorrhagic complications, mainly in critically ill patients. POCUS has gained growing consideration due to its bedside utilization, reliability, and reproducibility even in emergency settings especially in unstable patients. In this narrative review, we aim to describe LUS and POCUS utilization in COVID-19 infection based on the literature found on this topic. We reported the LUS patterns of COVID-19 pulmonary infection, the diagnostic accuracy with respect to CT lung scan, its prognostic value, the variety of scores and protocols proposed, and the utilization of POCUS to investigate the extra-lung complications.

COVID-19 Detection From Respiratory Sounds With Hierarchical Spectrogram Transformers

Monitoring of prevalent airborne diseases such as COVID-19 characteristically involves respiratory assessments. While auscultation is a mainstream method for preliminary screening of disease symptoms, its utility is hampered by the need for dedicated hospital visits. Remote monitoring based on recordings of respiratory sounds on portable devices is a promising alternative, which can assist in early assessment of COVID-19 that primarily affects the lower respiratory tract. In this study, we introduce a novel deep learning approach to distinguish patients with COVID-19 from healthy controls given audio recordings of cough or breathing sounds. The proposed approach leverages a novel hierarchical spectrogram transformer (HST) on spectrogram representations of respiratory sounds. HST embodies self-attention mechanisms over local windows in spectrograms, and window size is progressively grown over model stages to capture local to global context. HST is compared against state-of-the-art conventional and deep-learning baselines. Demonstrations on crowd-sourced multi-national datasets indicate that HST outperforms competing methods, achieving over 90% area under the receiver operating characteristic curve (AUC) in detecting COVID-19 cases.

Use of a Handheld Ultrasonographic Device to Identify Heart Failure and Pulmonary Disease in Rural Africa

Importance

Agreement in lung ultrasonography findings between clinicians using a handheld ultrasonographic device and expert sonographers using a high-end ultrasonographic machine has not been studied in sub-Saharan Africa.

Objective

To determine the agreement in ultrasonographic findings and diagnoses between primary care clinicians trained in lung ultrasonography, board-certified expert sonographers, and senior physicians.

Design, Setting, and Participants

This cross-sectional single-center study was conducted from February 1, 2022, to April 30, 2023 at a referral center in rural Tanzania. Individuals 5 years or older with respiratory symptoms and at least 2 distinct respiratory signs or symptoms were eligible. A total of 459 individuals were screened.

Exposures

Participants provided their medical history and underwent a clinical examination and lung ultrasonography performed by a clinician, followed by a lung ultrasonography performed by an expert sonographer, and finally chest radiography and a final evaluation performed by a senior physician. Other tests, such as echocardiography and Mycobacterium tuberculosis testing, were conducted on the decision of the physician. Clinicians received 2 hours of instruction and three 2-hour sessions of clinical training in the use of a handheld lung ultrasonographic device; expert sonographers were board-certified.

Main Outcomes and Measures

Percentage agreement and Cohen κ coefficient for sonographic findings and diagnoses compared between clinicians and expert sonographers, and between clinicians and senior physicians.

Results

The median (IQR) age of 438 included participants was 54 (38-66) years, and 225 (51%) were male. The median (range) percentage agreement of ultrasonographic findings between clinicians and expert sonographers was 93% (71%-99%), with κ ranging from -0.003 to 0.83. Median (range) agreement of diagnoses between clinicians and expert sonographers was 90% (50%-99%), with κ ranging from -0.002 to 0.76. Between clinicians and senior physicians, median (range) agreement of diagnoses was 89% (55%-90%), with κ ranging from -0.008 to 0.76. Between clinicians and senior physicians, diagnosis agreements were 85% (κ, 0.69) for heart failure, 78% (κ, 0.57) for definite or probable tuberculosis, 50% (κ, 0.002) for viral pneumonia, and 56% (κ, 0.06) for bacterial pneumonia.

Conclusions and Relevance

In this cross-sectional study, the agreement of ultrasonographic findings between clinicians and sonographers was mostly substantial. Between clinicians and senior physicians, agreement was substantial in the diagnosis of heart failure, moderate in the diagnosis of tuberculosis, but slight in the diagnosis of pneumonia. These findings suggest that handheld ultrasonographic devices used in addition to clinical examination may support clinicians in diagnosing cardiac and pulmonary diseases in rural sub-Saharan Africa.

Role of Imaging in Diagnosis and Management of COVID-19: Evidence-Based Approaches

Imaging has been demonstrated to play a crucial role in both the diagnosis and management of COVID-19. Depending on resources, pre-test probability, and risk factors for severe disease progression, real-time polymerase chain reaction (RT-PCR) testing may be followed by chest radiography (CXR) or chest computed tomography (CT) to further aid in diagnosis or excluding COVID-19 disease. SARS-CoV-2 has been shown not only to pathologically impact the pulmonary system, but also the cardiovascular, gastrointestinal, and neurological systems to name a few. Imaging has again proven useful in further investigating and managing extrapulmonary disease, with the use of echocardiogram, CT angiography of the cardiovascular and cerebrovascular structures, MRI of the brain, as well as ultrasound of the abdomen and CT of the abdomen and pelvis proving particularly useful. Research in artificial intelligence and its application in the diagnosis of COVID-19 and disease severity prediction is underway, and point-of-care ultrasound is an emerging bedside technique that may allow for more efficient and timely diagnosis of COVID-19.

Implementing an interprofessional point-of-care ultrasound protocol for dyspneic patients in an emergency department as a blended learning concept-Feasibility of Employing Thoracic Ultrasound in Shortness of Breath

Objective

Dyspnea is a common symptom in the Emergency Department, with a wide variety of differential diagnoses. Previous research has demonstrated the diagnostic accuracy of Point-of-Care Ultrasound (POCUS) in this field of interest. Our goal was to better establish sonography in our emergency department with a practicable and time effective method. Therefore, we implemented a sonography protocol in an interprofessional emergency team using blended learning as a modern didactic approach and evaluated the learning and teaching success. We named the study FETUS, which stands for "Feasibility of Employing Thoracic Ultrasound in Shortness of Breath."

Methods

A demonstration of the POCUS protocol was given, followed by individual supervision during clinical routine. A written manual, a pocket card, and further materials for personal training supplemented the training. A post-training questionnaire measured several parameters regarding the training, e.g., subjective skill-acquisition or media use.

Results

32 medical and nursing staff participated in this study, 14 of whom completed the questionnaire. All training modalities offered were well received. A pre-post comparison of subjective sonographic competence shows a significant increase in both medical and nursing staff.The other items surveyed also indicate the success of the intervention undertaken.

Conclusion

The use of different media as a blended learning approach can support the implementation of new measures in the ongoing working routine within an interprofessional team.

Role of cardiac and lung ultrasound in the COVID-19 era

INTRODUCTION

The primary diagnostic method of Coronavirus disease 2019 is reverse transcription polymerase chain reaction of the nucleic acid of severe acute respiratory syndrome coronavirus 2 in nasopharyngeal swabs. There is growing evidence regarding the 2019 coronavirus disease imaging results on chest X-rays and computed tomography but the accessibility to standard diagnostic methods may be limited during the pandemic.

EVIDENCE ACQUISITION

Databases used for the search were MEDLINE (PubMed), Scopus Search, and Cochrane Library. The research took into consideration studies published in English until March 2022 and was conducted using the following research query: ((((sars cov [MeSH Terms])) OR (COVID-19)) OR (Sars-Cov2)) OR (Coronavirus)) AND (((((2d echocardiography [MeSH Terms]) OR (doppler ultrasound imaging [MeSH Terms]))) OR (echography [MeSH Terms])) OR (LUS)) OR ("LUNG ULTRASOUND")).

EVIDENCE SYNTHESIS

Pulmonary and cardiac ultrasound are cost-effective, widely available, and provide information that can influence management.

CONCLUSIONS

Point-of-care ultrasonography is a method that can provide relevant clinical and therapeutic information in patients with COVID-19 where other diagnostic methods may not be easily accessible.

Machine learning with multimodal data for COVID-19

In response to the unprecedented global healthcare crisis of the COVID-19 pandemic, the scientific community has joined forces to tackle the challenges and prepare for future pandemics. Multiple modalities of data have been investigated to understand the nature of COVID-19. In this paper, MIDRC investigators present an overview of the state-of-the-art development of multimodal machine learning for COVID-19 and model assessment considerations for future studies. We begin with a discussion of the lessons learned from radiogenomic studies for cancer diagnosis. We then summarize the multi-modality COVID-19 data investigated in the literature including symptoms and other clinical data, laboratory tests, imaging, pathology, physiology, and other omics data. Publicly available multimodal COVID-19 data provided by MIDRC and other sources are summarized. After an overview of machine learning developments using multimodal data for COVID-19, we present our perspectives on the future development of multimodal machine learning models for COVID-19.

Lung ultrasound score severity cut-off points in COVID-19 pneumonia. A systematic review and validating cohort

OBJECTIVES

Our purpose was to establish different cut-off points based on the lung ultrasound score (LUS) to classify COVID-19 pneumonia severity.

METHODS

Initially, we conducted a systematic review among previously proposed LUS cut-off points. Then, these results were validated by a single-centre prospective cohort study of adult patients with confirmed SARS-CoV-2 infection. Studied variables were poor outcome (ventilation support, intensive care unit admission or 28-days mortality) and 28-days mortality.

RESULTS

From 510 articles, 11 articles were included. Among the cut-off points proposed in the articles included, only the LUS>15 cut-off point could be validated for its original endpoint, demonstrating also the strongest relation with poor outcome (odds ratio [OR]=3.636, confidence interval [CI] 1.411-9.374). Regarding our cohort, 127 patients were admitted. In these patients, LUS was statistically associated with poor outcome (OR=1.303, CI 1.137-1.493), and with 28-days mortality (OR=1.024, CI 1.006-1.042). LUS>15 showed the best diagnostic performance when choosing a single cut-off point in our cohort (area under the curve 0.650). LUS≤7 showed high sensitivity to rule out poor outcome (0.89, CI 0.695-0.955), while LUS>20 revealed high specificity to predict poor outcome (0.86, CI 0.776-0.917).

CONCLUSIONS

LUS is a good predictor of poor outcome and 28-days mortality in COVID-19. LUS≤7 cut-off point is associated with mild pneumonia, LUS 8-20 with moderate pneumonia and ≥20 with severe pneumonia. If a single cut-off point were used, LUS>15 would be the point which better discriminates mild from severe disease.

Lung ultrasound score severity cut-off points in COVID-19 pneumonia. A systematic review and validating cohort

Objectives

Our purpose was to establish different cut-off points based on the lung ultrasound score (LUS) to classify COVID-19 pneumonia severity.

Methods

Initially, we conducted a systematic review among previously proposed LUS cut-off points. Then, these results were validated by a single-centre prospective cohort study of adult patients with confirmed SARS-CoV-2 infection. Studied variables were poor outcome (ventilation support, intensive care unit admission or 28-days mortality) and 28-days mortality.

Results

From 510 articles, 11 articles were included. Among the cut-off points proposed in the articles included, only the LUS > 15 cut-off point could be validated for its original endpoint, demonstrating also the strongest relation with poor outcome (odds ratio [OR] = 3.636, confidence interval [CI] 1.411-9.374). Regarding our cohort, 127 patients were admitted. In these patients, LUS was statistically associated with poor outcome (OR = 1.303, CI 1.137-1.493), and with 28-days mortality (OR = 1.024, CI 1.006-1.042). LUS > 15 showed the best diagnostic performance when choosing a single cut-off point in our cohort (area under the curve 0.650). LUS ≤ 7 showed high sensitivity to rule out poor outcome (0.89, CI 0.695-0.955), while LUS > 20 revealed high specificity to predict poor outcome (0.86, CI 0.776-0.917).

Conclusions

LUS is a good predictor of poor outcome and 28-days mortality in COVID-19. LUS ≤ 7 cut-off point is associated with mild pneumonia, LUS 8-20 with moderate pneumonia and ≥20 with severe pneumonia. If a single cut-off point were used, LUS > 15 would be the point which better discriminates mild from severe disease.

The value of lung ultrasound in COVID-19 pneumonia, verified by high resolution computed tomography assessed by artificial intelligence

BACKGROUND

Lung ultrasound (LUS) is an increasingly popular imaging method in clinical practice. It became particularly important during the COVID-19 pandemic due to its mobility and ease of use compared to high-resolution computed tomography (HRCT). The objective of this study was to assess the value of LUS in quantifying the degree of lung involvement and in discrimination of lesion types in the course of COVID-19 pneumonia as compared to HRCT analyzed by the artificial intelligence (AI).

METHODS

This was a prospective observational study including adult patients hospitalized due to COVID-19 in whom initial HRCT and LUS were performed with an interval < 72 h. HRCT assessment was performed automatically by AI. We evaluated the correlations between the inflammation volume assessed both in LUS and HRCT, between LUS results and the HRCT structure of inflammation, and between LUS and the laboratory markers of inflammation. Additionally we compared the LUS results in subgroups depending on the respiratory failure throughout the hospitalization.

RESULTS

Study group comprised 65 patients, median 63 years old. For both lungs, the median LUS score was 19 (IQR-interquartile range 11-24) and the median CT score was 22 (IQR 16-26). Strong correlations were found between LUS and CT scores (for both lungs r = 0.75), and between LUS score and percentage inflammation volume (PIV) (r = 0.69). The correlations remained significant, if weakened, for individual lung lobes. The correlations between LUS score and the value of the percentage consolidation volume (PCV) divided by percentage ground glass volume (PGV), were weak or not significant. We found significant correlation between LUS score and C-reactive protein (r = 0.55), and between LUS score and interleukin 6 (r = 0.39). LUS score was significantly higher in subgroups with more severe respiratory failure.

CONCLUSIONS

LUS can be regarded as an accurate method to evaluate the extent of COVID-19 pneumonia and as a promising tool to estimate its clinical severity. Evaluation of LUS in the assessment of the structure of inflammation, requires further studies in the course of the disease.

TRIAL REGISTRATION

The study has been preregistered 13 Aug 2020 on clinicaltrials.gov with the number NCT04513210.

Emergency Department Point-Of-Care Echocardiography and Lung Ultrasound in Predicting COVID-19 Severity

OBJECTIVES

We sought to determine if point-of-care ultrasound (POCUS) performed on patients with COVID-19 in the emergency department (ED) can help predict disease course, severity, or identify complications.

METHODS

This was a retrospective cohort study of adult ED patients who tested positive for COVID-19 at hospital admission or within 2 weeks of presentation and received heart or lung POCUS. Clips were reviewed for presence of decreased left ventricular ejection fraction (LVEF), right ventricular dilation, presence of B-lines, and pleural line abnormalities. Patients with worsening hypoxemic respiratory failure or shock requiring higher level of care and patients who expired were considered to have developed severe COVID-19. Regression analysis was performed to determine if there was a correlation between ED POCUS findings and development of severe COVID-19.

RESULTS

A total of 155 patients met study criteria; 148 patients had documented cardiac views and 116 patients had documented lung views (113 with both). Mean age was 66.5 years old (±18.6) and 53% of subjects were female. Subjects with decreased LVEF that was not previously documented had increased odds of having severe COVID during their hospitalization compared to those with old or no dysfunction (OR 5.66, 95% CI: 1.55-19.95, P = .08). The presence of pleural line abnormalities was also predictive for development of severe COVID (OR 2.68, 95% CI: 1.04-6.92, P = .04).

CONCLUSION

POCUS findings of previously unidentified decreased LVEF and pleural line abnormalities in patients with COVID-19 evaluated in the ED were correlated to a more severe clinical course and worse prognosis.

New International Guidelines and Consensus on the Use of Lung Ultrasound

Following the innovations and new discoveries of the last 10 years in the field of lung ultrasound (LUS), a multidisciplinary panel of international LUS experts from six countries and from different fields (clinical and technical) reviewed and updated the original international consensus for point-of-care LUS, dated 2012. As a result, a total of 20 statements have been produced. Each statement is complemented by guidelines and future developments proposals. The statements are furthermore classified based on their nature as technical (5), clinical (11), educational (3), and safety (1) statements.

COVID-19: Recent Advances in Lung Ultrasound

Abstract:

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) has become a global threat that has led to tremendous societal instability. The SARS-CoV- 2 can exhibit a drastic variation in terms of the signs and symptoms in the patient’s body. This virus manifests its existence through cough, fever, sore throat, body aches, chest pain, headaches, and dyspnoea. These can lead to life-threatening respiratory insufficiency, thereby affecting several other organs such as the kidney, heart, lungs, liver, and nervous system. The lungs are the primary target site for SARS-CoV-2 and several diagnoses are being deployed in real time for treatment purposes. Although chest CT is the standard method for early diagnosis and management of coronavirus disease (COVID-19), lung ultrasound (US) has some merits over chest CT and may be used in addition to it in the workup of COVID-19. The goal of our review is to look at the observations of the reports on lung ultrasound in COVID-19 patients and the current advances.

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

AIMS

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

METHODS AND RESULTS

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

CONCLUSION

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

Use of POCUS in Chest Pain and Dyspnea in Emergency Department: What Role Could It Have?

Chest pain and dyspnea are common symptoms in patients presenting to the emergency room (ER); oftentimes it is not possible to clearly identify the underlying cause, which may cause the patient to have to return to the ER. In other cases, while it is possible to identify the underlying cause, it is necessary to perform a large number of tests before being able to make a diagnosis. Over the last twenty years, emergency medicine physicians have had the possibility of using ultrasound to help them make and rule out diagnoses. Specific ultrasound tests have been designed to evaluate patients presenting with specific symptoms to ensure a fast, yet complete, evaluation. In this paper, we examine the role of ultrasound in helping physicians understand the etiology behind chest pain and dyspnea. We analyze the different diseases and disorders which may cause chest pain and dyspnea as symptoms and discuss the corresponding ultrasound findings.

From the Triage to the Intermediate Area: A Simple and Fast Model for COVID-19 in the Emergency Department

Introduction: The early identification of patients with SARS-CoV-2 infection is still a real challenge for emergency departments (ED). First, we aimed to develop a score, based on the use of the lung ultrasonography (LUS), in addition to the pre-triage interview, to correctly address patients; second, we aimed to prove the usefulness of a three-path organization (COVID-19, not-COVID-19 and intermediate) compared to a two-path organization (COVID-19, non-COVID-19). Methods: We retrospectively analysed 292 patients admitted to our ED from 10 April to 15 April 2020, with a definite diagnosis of positivity (93 COVID-19 patients) or negativity (179 not-COVID-19 patients) for SARS-COV-2 infection. Using a logistic regression, we found a set of predictors for infection selected from the pre-triage interview items and the LUS findings, which contribute with a different weight to the final score. Then, we compared the organization of two different pathways. Results: The most informative factors for classifying the patient are known nasopharyngeal swab positivity, close contact with a COVID-19 patient, fever associated with respiratory symptoms, respiratory failure, anosmia or dysgeusia, and the ultrasound criteria of diffuse alveolar interstitial syndrome, absence of B-lines and presence of pleural effusion. Their sensitivity, specificity, accuracy, and AUC-ROC are, respectively, 0.83, 0.81, 0.82 and 0.81. The most significant difference between the two pathways is the percentage of not-COVID-19 patients assigned to the COVID-19 area, that is, 10.6% (19/179) in the three-path organization, and 18.9% (34/179) in the two-path organization (p = 0.037). Conclusions: Our study suggests the possibility to use a score based on the pre-triage interview and the LUS findings to correctly manage the patients admitted to the ED, and the importance of an intermediate area to limit the spread of SARS-CoV-2 in the ED and, as a consequence, in the hospital.

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.

Can Lung Imaging Scores and Clinical Variables Predict Severe Course and Fatal Outcome in COVID-19 Pneumonia Patients? A Single-Center Observational Study

COVID-19 prediction models mostly consist of combined clinical features, laboratory parameters, and, less often, chest X-ray (CXR) findings. Our main goal was to propose a prediction model involving imaging methods, specifically ultrasound. This was a single-center, retrospective cohort observational study of patients admitted to the University Hospital Split from November 2020 to May 2021. Imaging protocols were based on the assessment of 14 lung zones for both lung ultrasound (LUS) and computed tomography (CT), correlated to a CXR score assessing 6 lung zones. Prediction models for the necessity of mechanical ventilation (MV) or a lethal outcome were developed by combining imaging, biometric, and biochemical parameters. A total of 255 patients with COVID-19 pneumonia were included in the study. Four independent predictors were added to the regression model for the necessity of MV: LUS score, day of the illness, leukocyte count, and cardiovascular disease (χ2 = 29.16, p < 0.001). The model accurately classified 89.9% of cases. For the lethal outcome, only two independent predictors contributed to the regression model: LUS score and patient’s age (χ2 = 48.56, p < 0.001, 93.2% correctly classified). The predictive model identified four key parameters at patient admission which could predict an adverse outcome.

Radio-Histological Correlation of Lung Features in Severe COVID-19 Through CT-Scan and Lung Ultrasound Evaluation

Background

Patients with coronavirus disease 2019 (COVID-19) can develop severe bilateral pneumonia leading to respiratory failure. Lung histological samples were scarce due to the high risk of contamination during autopsies. We aimed to correlate histological COVID-19 features with radiological findings through lung ultrasound (LU)-guided postmortem core needle biopsies (CNBs) and computerized tomography (CT) scans.

Methodology

We performed an observational prospective study, including 30 consecutive patients with severe COVID-19. The thorax was divided into 12 explorations regions to correlate LU and CT-scan features. Histological findings were also related to radiological features through CNBs.

Results

Mean age was 62.56 ± 13.27 years old, with 96.7% male patients. Postmortem LU-guided CNBs were performed in 13 patients. Thirty patients were evaluated with both thoracic LU and chest CT scan, representing a total of 279 thoracic regions explored. The most frequent LU finding was B2-lines (49.1%). The most CT-scan finding was ground-glass opacity (GGO, 29%). Pathological CT-scan findings were commonly observed when B2-lines or C-lines were identified through LU (positive predictive value, PPV, 87.1%). Twenty-five postmortem echo-guided histological samples were obtained from 12 patients. Histological samples showed diffuse alveolar damage (DAD) (75%) and chronic interstitial inflammation (25%). The observed DAD was heterogeneous, showing multiple evolving patterns of damage, including exudative (33.3%), fibrotic (33.3%), and organizing (8.3%) phases. In those patients with acute or exudative pattern, two lesions were distinguished: classic hyaline membrane; fibrin "plug" in alveolar space (acute fibrinous organizing pneumonia, AFOP). C-profile was described in 33.3% and presented histological signs of DAD and lung fibrosis. The predominant findings were collagen deposition (50%) and AFOP (50%). B2-lines were identified in 66.7%; the presence of hyaline membrane was the predominant finding (37.5%), then organizing pneumonia (12.5%) and fibrosis (37.5%). No A-lines or B1-lines were observed in these patients.

Conclusion

LU B2-lines and C-profile are predominantly identified in patients with severe COVID-19 with respiratory worsening, which correspond to different CT patterns and histological findings of DAD and lung fibrosis.

Critically Ill Pediatric Patient and SARS-CoV-2 Infection

In December 2019 SARS-CoV-2 initiated a worldwide COVID-19 pandemic, which is still ongoing in 2022. Although adult elderly patients with chronic preexisting diseases had been identified as the most vulnerable group, COVID-19 has also had a significant impact on pediatric intensive care. Early in 2020, a new disease presentation, multisystemic inflammatory syndrome, was described in children. Despite the vaccination that is available for all age categories, due to its selection process, new viral mutations and highly variable vaccination rate, COVID-19 remains a significant clinical challenge in adult and pediatric intensive care in 2022.

Review of Machine Learning in Lung Ultrasound in COVID-19 Pandemic

Ultrasound imaging of the lung has played an important role in managing patients with COVID-19-associated pneumonia and acute respiratory distress syndrome (ARDS). During the COVID-19 pandemic, lung ultrasound (LUS) or point-of-care ultrasound (POCUS) has been a popular diagnostic tool due to its unique imaging capability and logistical advantages over chest X-ray and CT. Pneumonia/ARDS is associated with the sonographic appearances of pleural line irregularities and B-line artefacts, which are caused by interstitial thickening and inflammation, and increase in number with severity. Artificial intelligence (AI), particularly machine learning, is increasingly used as a critical tool that assists clinicians in LUS image reading and COVID-19 decision making. We conducted a systematic review from academic databases (PubMed and Google Scholar) and preprints on arXiv or TechRxiv of the state-of-the-art machine learning technologies for LUS images in COVID-19 diagnosis. Openly accessible LUS datasets are listed. Various machine learning architectures have been employed to evaluate LUS and showed high performance. This paper will summarize the current development of AI for COVID-19 management and the outlook for emerging trends of combining AI-based LUS with robotics, telehealth, and other techniques.

Incidental radiological findings suggestive of COVID-19 in asymptomatic patients

Despite routine screening of patients for coronavirus disease 2019 (COVID-19) symptoms and signs at hospital entrances, patients may slip between the cracks and be incidentally discovered to have lung findings that could indicate COVID-19 infection on imaging obtained for other reasons. Multiple case reports and case series have been published to identify the pattern of this highly infectious disease. This article addresses the radiographic findings in different imaging modalities that may be incidentally seen in asymptomatic patients who carry COVID-19. In general, findings of COVID-19 infection may appear in computed tomography (CT), magnetic resonance imaging, positron emission tomography-CT, ultrasound, or plain X-rays that show lung or only apical or basal cuts. The identification of these characteristics by radiologists and clinicians is crucial because this would help in the early recognition of cases so that a rapid treatment protocol can be established, the immediate isolation to reduce community transmission, and the organization of close monitoring. Thus, it is important to both the patient and the physician that these findings are highlighted and reported.

Acute management of COVID-19 in the emergency department: An evidence-based review

Coronavirus disease (COVID-19) has been relentlessly battering the world wave after wave in different countries at different rates and times. Emergency departments (EDs) around the globe have had to constantly adapt to this ever-changing influx of information and recommendations by various national and international health agencies. This review compiles the available evidence on the guidelines for triaging, evaluation, and management of critically ill patients with COVID-19 presenting to the ED and in need of emergency resuscitation. The quintessential components of resuscitation focus on airway, breathing, and circulation with good supportive care as the cornerstone of acute management of critically ill COVID-19 patients. Irrational investigations and therapeutics must be avoided during these times of medical uncertainty and antibiotic stewardship should be diligently followed.

Lung Ultrasound: A Diagnostic Leading Tool for SARS-CoV-2 Pneumonia: A Narrative Review

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global pandemic. In this context, lung ultrasound (LUS) has played an important role due to its high diagnostic sensitivity, low costs, simplicity of execution and radiation safeness. Despite computed tomography (CT) being the imaging gold standard, lung ultrasound point of care exam is essential in every situation where CT is not readily available nor applicable. The aim of our review is to highlight the considerable versatility of LUS in diagnosis, framing the therapeutic route and follow-up for SARS-CoV-2 interstitial syndrome.

Diagnostic performance of lung ultrasound compared to CT scan in the diagnosis of pulmonary lesions of COVID-19 induced pneumonia: a preliminary study

Chest CT scan is currently used to assess the extent of lung involvement in patients with the coronavirus disease 2019 (COVID-19). The aim of this study was to evaluate the diagnostic performance of lung ultrasound in the diagnosis of COVID-19 pulmonary manifestations in comparison to CT scan. Thirty-three symptomatic patients with suspected COVID-19 pneumonia were evaluated by lung ultrasound and then, at a short interval, chest CT scan. In the anterior chest, each hemithorax was divided into four areas. In the posterior chest, eight zones similar to the anterior part were examined. The axillary areas were also divided into upper and lower zones (20 zones were determined per patient). Mean age of the patients was 58.66 years. The sensitivity (95% CI) and specificity (95% CI) of lung ultrasound for the diagnosis of parenchymal lesions were 90.5% (69.6-98.8%) and 50% (21.1-78.9%), respectively. In the evaluation of pleural lesions, the sensitivity (95% CI) and specificity (95% CI) of lung ultrasound were 100% (71.5-100%) and 22.7% (7.8-45.4%), respectively. Owing to the high sensitivity of ultrasound in identifying lung lesions in patients with COVID-19 pneumonia, it can be recommended to use lung ultrasound as a tool for initial screening of patients with high clinical suspicion for SARS-CoV-2 infection during the pandemic.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13337-021-00736-w.

Management of COVID-19 Patients in the Emergency Department

COVID-19 is an emerging disease of global public health concern. As the pandemic overwhelmed emergency departments (EDs), a restructuring of emergency care delivery became necessary in many hospitals. Furthermore, with more than 2000 papers being published each week, keeping up with ever-changing information has proven to be difficult for emergency physicians. The aim of the present review is to provide emergency physician with a summary of the current literature regarding the management of COVID-19 patients in the emergency department.

Chest pain mimicking pulmonary embolism may be a common presentation of COVID-19 in ambulant patients without other typical features of infection

BACKGROUND

Radiological and pathological studies in severe COVID-19 pneumonia (SARS-CoV-2) have demonstrated extensive pulmonary immunovascular thrombosis and infarction. This study investigated whether these focal changes may present with chest pain mimicking pulmonary emoblism (PE) in ambulant patients.

METHODS

CTPAs from outpatients presenting with chest pain to Leeds Teaching Hospital NHS Trust 1st March to 31 May 2020 (n = 146) and 2019 (n = 85) were compared. Regions of focal ground glass opacity (GGO), consolidation and/or atelectasis (parenchymal changes) were determined, and all scans were scored using British Society for Thoracic Imaging (BSTI) criteria for COVID-19, and the 2020 cohort was offered SARS-CoV-2 antibody testing.

RESULTS

Baseline demographic and clinical data were similar between groups with absence of fever, normal lymphocytes and marginally elevated CRP and D-Dimer values. Evidence of COVID-19 or parenchymal changes was observed in 32.9% (48/146) of cases in 2020 compared to 16.5% (14/85) in 2019 (P = 0.007). 11/146 (7.5%) patients met BSTI criteria for COVID-19 in 2020 compared with 0/14 in 2019 (P = 0.008). 3/39 patients tested had detectable COVID-19 antibodies (2 with parenchymal changes and 1 with normal parenchyma) however 0/6 patients whose CTPA met BSTI criteria "likely/suspicious for COVID-19" and attended antibody testing were SARS-CoV-2 antibody positive.

CONCLUSIONS

32.8% ambulatory patients with suspected PE in 2020 had parenchymal changes with 7.5% diagnosed as COVID-19 infection by imaging criteria, despite the absence of other COVID-19 symptoms. These findings suggest that localized COVID-19 pneumonitis with immunothrombosis occurs distal to the bronchiolar arteriolar circulation, causing pleural irritation and chest pain without viraemia, accounting for the lack of fever and systemic symptoms.

Role of Lung Ultrasound in Predicting Clinical Severity and Fatality in COVID-19 Pneumonia

Background: Lung ultrasound (LUS) is a useful imaging method for identifying COVID-19 pneumonia. The aim of this study was to explore the role of LUS in predicting the severity of the disease and fatality in patients with COVID-19. Methods: This was a single-center, follow-up study, conducted from 1 November 2020, to 22 March 2021. The LUS protocol was based on the assessment of 14 lung zones with a total score up to 42, which was compared to the disease severity and fatality. Results: A total of 133 patients with COVID-19 pneumonia confirmed by RT-PCR were enrolled, with a median time from hospital admission to lung ultrasound of one day. The LUS score was correlated with clinical severity at hospital admission (Spearman’s rho 0.40, 95% CI 0.24 to 0.53, p < 0.001). Patients with higher LUS scores were experiencing greater disease severity; a high flow nasal cannula had an odds ratio of 1.43 (5% CI 1.17–1.74) in patients with LUS score > 29; the same score also predicted the need for mechanical ventilation (1.25, [1.07–1.48]). An LUS score > 30 (1.41 [1.18–1.68]) and age over 68 (1.26 [1.11–1.43]) were significant predictors of fatality. Conclusions: LUS at hospital admission is shown to have a high predictive power of the severity and fatality of COVID-19 pneumonia.

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

COVID-19 imaging: Diagnostic approaches, challenges, and evolving advances

The role of radiology and the radiologist have evolved throughout the coronavirus disease-2019 (COVID-19) pandemic. Early on, chest computed tomography was used for screening and diagnosis of COVID-19; however, it is now indicated for high-risk patients, those with severe disease, or in areas where polymerase chain reaction testing is sparsely available. Chest radiography is now utilized mainly for monitoring disease progression in hospitalized patients showing signs of worsening clinical status. Additionally, many challenges at the operational level have been overcome within the field of radiology throughout the COVID-19 pandemic. The use of teleradiology and virtual care clinics greatly enhanced our ability to socially distance and both are likely to remain important mediums for diagnostic imaging delivery and patient care. Opportunities to better utilize of imaging for detection of extrapulmonary manifestations and complications of COVID-19 disease will continue to arise as a more detailed understanding of the pathophysiology of the virus continues to be uncovered and identification of predisposing risk factors for complication development continue to be better understood. Furthermore, unidentified advancements in areas such as standardized imaging reporting, point-of-care ultrasound, and artificial intelligence offer exciting discovery pathways that will inevitably lead to improved care for patients with COVID-19.

Radiological and clinical spectrum of COVID-19: A major concern for public health

The pandemic of novel coronavirus disease 2019 (COVID-19) is an infectious disease caused by +ve strand RNA virus (SARS-CoV-2, severe acute respiratory syndrome coronavirus 2) that belongs to the corona viridae family. In March, the World Health Organization declared the outbreak of novel coronavirus for the public health emergency. Although SARS-CoV-2 infection presents with respiratory symptoms, it affects other organs such as the kidneys, liver, heart and brain. Early-stage laboratory disease testing shows many false positive or negative outcomes such as less white blood cell count and a low number of lymphocyte count. However, radiological examination and diagnosis are among the main components of the diagnosis and treatment of COVID-19. In particular, for COVID-19, chest computed tomography developed vigorous initial diagnosis and disease progression assessment. However, the accuracy is limited. Although real-time reverse transcription-polymerase chain reaction is the gold standard method for the diagnosis of COVID-19, sometimes it may give false-negative results. Due to the consequences of the missing diagnosis. This resulted in a discrepancy between the two means of examination. Conversely, based on currently available evidence, we summarized the possible understanding of the various patho-physiology, radio diagnostic methods in severe COVID-19 patients. As the information on COVID-19 evolves rapidly, this review will provide vital information for scientists and clinicians to consider novel perceptions for the comprehensive knowledge of the diagnostic approaches based on current experience.

Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis

Care during the COVID-19 pandemic hinges upon the existence of fast, safe, and highly sensitive diagnostic tools. Considering significant practical advantages of lung ultrasound (LUS) over other imaging techniques, but difficulties for doctors in pattern recognition, we aim to leverage machine learning toward guiding diagnosis from LUS. We release the largest publicly available LUS dataset for COVID-19 consisting of 202 videos from four classes (COVID-19, bacterial pneumonia, non-COVID-19 viral pneumonia and healthy controls). On this dataset, we perform an in-depth study of the value of deep learning methods for the differential diagnosis of lung pathologies. We propose a frame-based model that correctly distinguishes COVID-19 LUS videos from healthy and bacterial pneumonia data with a sensitivity of 0.90±0.08 and a specificity of 0.96±0.04. To investigate the utility of the proposed method, we employ interpretability methods for the spatio-temporal localization of pulmonary biomarkers, which are deemed useful for human-in-the-loop scenarios in a blinded study with medical experts. Aiming for robustness, we perform uncertainty estimation and demonstrate the model to recognize low-confidence situations which also improves performance. Lastly, we validated our model on an independent test dataset and report promising performance (sensitivity 0.806, specificity 0.962). The provided dataset facilitates the validation of related methodology in the community and the proposed framework might aid the development of a fast, accessible screening method for pulmonary diseases. Dataset and all code are publicly available at: https://github.com/BorgwardtLab/covid19_ultrasound.

Post-mortem ultrasonography: a safer alternative to autopsies in COVID-19 deaths

Ultrasonography is known to have many applications in the diagnoses of diseases, as well as in guiding medical practitioners through precise medical procedures. However, its use as a post-mortem radiographic modality has been limited. Post-mortem ultrasonographic techniques are considered to be a safer alternative to high-risk post-mortem procedures, especially in infectious diseases. The present communication discusses the possibilities of using ultrasonography in post-mortem examinations in times of the ongoing COVID-19 pandemic to minimize the associated risk of SARS-CoV-2 infection of those working in mortuaries during full-body dissection in traditional autopsies. Post-mortem ultrasonography can be useful in reducing the extent of autopsies, thus decreasing the risk of exposure of forensic personnel.