Interrater reliability of pediatric point-of-care lung ultrasound findings

Lung Ultrasound Findings in Children With Asthma Exacerbations

OBJECTIVE

We sought to assess whether the presence and extent of lung ultrasound (LUS) findings were associated with asthma exacerbation severity in children.

METHODS

We enrolled a convenience sample of patients aged 5-18 years presenting with acute asthma exacerbation to a tertiary care pediatric emergency department. Severity of an asthma exacerbation (mild, moderate, severe) was assessed within 1 hour of the LUS using the Hospital Asthma Severity Score, a validated asthma assessment tool. LUS was performed by trained pediatric emergency providers. The presence of LUS findings (B-lines, consolidations, pleural effusion, and pleural line abnormalities) was assessed using a standardized criterion based on consensus guidelines.

RESULTS

A total of 111 patients with a median age of 8 years (interquartile range 6-12) were enrolled. LUS was positive in 57% of patients. Pleural line abnormalities were observed in 34%, B-lines in 29%, consolidations <1 cm in 24%, and consolidations ≥1 cm in 7%. Patients with moderate and severe asthma exacerbations were more likely to have any B-lines (31% and 43%, respectively) than patients with mild exacerbations (12%; P = .021); however, the presence of ≥3 B-lines or confluent B-lines did not differ across severity groups. The presence of other findings did not differ based on asthma severity.

CONCLUSIONS

LUS findings are observed in a substantial portion of children presenting with asthma exacerbations. B-lines were the only LUS finding significantly associated with asthma severity, while lung consolidations <1 cm and >1 cm were not correlated with severity. These findings provide valuable information for the diagnostic use of LUS in pediatric patients with asthma exacerbation.

Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Data Set Labeling: Prospective Analysis

BACKGROUND

Machine learning (ML) models can yield faster and more accurate medical diagnoses; however, developing ML models is limited by a lack of high-quality labeled training data. Crowdsourced labeling is a potential solution but can be constrained by concerns about label quality.

OBJECTIVE

This study aims to examine whether a gamified crowdsourcing platform with continuous performance assessment, user feedback, and performance-based incentives could produce expert-quality labels on medical imaging data.

METHODS

In this diagnostic comparison study, 2384 lung ultrasound clips were retrospectively collected from 203 emergency department patients. A total of 6 lung ultrasound experts classified 393 of these clips as having no B-lines, one or more discrete B-lines, or confluent B-lines to create 2 sets of reference standard data sets (195 training clips and 198 test clips). Sets were respectively used to (1) train users on a gamified crowdsourcing platform and (2) compare the concordance of the resulting crowd labels to the concordance of individual experts to reference standards. Crowd opinions were sourced from DiagnosUs (Centaur Labs) iOS app users over 8 days, filtered based on past performance, aggregated using majority rule, and analyzed for label concordance compared with a hold-out test set of expert-labeled clips. The primary outcome was comparing the labeling concordance of collated crowd opinions to trained experts in classifying B-lines on lung ultrasound clips.

RESULTS

Our clinical data set included patients with a mean age of 60.0 (SD 19.0) years; 105 (51.7%) patients were female and 114 (56.1%) patients were White. Over the 195 training clips, the expert-consensus label distribution was 114 (58%) no B-lines, 56 (29%) discrete B-lines, and 25 (13%) confluent B-lines. Over the 198 test clips, expert-consensus label distribution was 138 (70%) no B-lines, 36 (18%) discrete B-lines, and 24 (12%) confluent B-lines. In total, 99,238 opinions were collected from 426 unique users. On a test set of 198 clips, the mean labeling concordance of individual experts relative to the reference standard was 85.0% (SE 2.0), compared with 87.9% crowdsourced label concordance (P=.15). When individual experts' opinions were compared with reference standard labels created by majority vote excluding their own opinion, crowd concordance was higher than the mean concordance of individual experts to reference standards (87.4% vs 80.8%, SE 1.6 for expert concordance; P<.001). Clips with discrete B-lines had the most disagreement from both the crowd consensus and individual experts with the expert consensus. Using randomly sampled subsets of crowd opinions, 7 quality-filtered opinions were sufficient to achieve near the maximum crowd concordance.

CONCLUSIONS

Crowdsourced labels for B-line classification on lung ultrasound clips via a gamified approach achieved expert-level accuracy. This suggests a strategic role for gamified crowdsourcing in efficiently generating labeled image data sets for training ML systems.

POCUS in the PICU: A Narrative Review of Evidence-Based Bedside Ultrasound Techniques Ready for Prime-Time in Pediatric Critical Care

Point-of-care ultrasound (POCUS) is an accessible technology that can identify and treat life-threatening pathology in real time without exposing children to ionizing radiation. We aim to review current evidence supporting the use of POCUS by pediatric intensivists with novice-level experience with bedside ultrasound. Current evidence supports the universal adoption of POCUS-guided internal jugular venous catheter placement and arterial line placement by pediatric critical care physicians. Focused cardiac ultrasound performed by PICU physicians who have completed appropriate training with quality assurance measures in place can identify life-threatening cardiac pathology in most children and important physiological changes in children with septic shock. POCUS of the lungs, pleural space, and diaphragm have great potential to provide valuable information at the bedside after validation of these techniques for use in the PICU with additional research. Based on currently available evidence, a generalizable and attainable POCUS educational platform for pediatric intensivists should include training in vascular access techniques and focused cardiac examination. A POCUS educational program should strive to establish credentialing and quality assurance programs that can be expanded when additional research validates the adoption of additional POCUS techniques by pediatric intensive care physicians.

Automatic deep learning-based pleural effusion segmentation in lung ultrasound images

BACKGROUND

Point-of-care lung ultrasound (LUS) allows real-time patient scanning to help diagnose pleural effusion (PE) and plan further investigation and treatment. LUS typically requires training and experience from the clinician to accurately interpret the images. To address this limitation, we previously demonstrated a deep-learning model capable of detecting the presence of PE on LUS at an accuracy greater than 90%, when compared to an experienced LUS operator.

METHODS

This follow-up study aimed to develop a deep-learning model to provide segmentations for PE in LUS. Three thousand and forty-one LUS images from twenty-four patients diagnosed with PE were selected for this study. Two LUS experts provided the ground truth for training by reviewing and segmenting the images. The algorithm was then trained using ten-fold cross-validation. Once training was completed, the algorithm segmented a separate subset of patients.

RESULTS

Comparing the segmentations, we demonstrated an average Dice Similarity Coefficient (DSC) of 0.70 between the algorithm and experts. In contrast, an average DSC of 0.61 was observed between the experts.

CONCLUSION

In summary, we showed that the trained algorithm achieved a comparable average DSC at PE segmentation. This represents a promising step toward developing a computational tool for accurately augmenting PE diagnosis and treatment.

Interrater reliability in assigning a lung ultrasound score

BACKGROUND AND PURPOSE

Lung ultrasound (LUS) for physiotherapists is an emerging bedside tool. The LUS score of aeration presents as a possible means of assessing and monitoring lung aeration associated with respiratory physiotherapy treatments. There are no studies to date that have assessed the interrater reliability (IRR) of physiotherapists assigning the LUS score of aeration. This study assessed the IRR of assigning the LUS score among adult, mechanically ventilated patients in an intensive care unit with a clinical suspicion of acute lobar atelectasis.

METHODS

A convenience sample of patients had an LUS performed by a physiotherapist, and images were independently reviewed by two physiotherapists. Each lung zone was assigned an LUS score between 0 and 3 (with 0 being normal aeration and 3 being complete consolidation, presence of effusion, or pneumothorax). IRR was assessed using the kappa statistic.

RESULTS

A total of 1032 LUS images were obtained. Assigning of the LUS across all lung zones demonstrated substantial agreement with kappa 0.685 (95% confidence interval: 0.650, 0.720). Right (0.702 [0.653, 0.751]) and left (0.670 [0.619, 0.721]) lung zones also demonstrated substantial agreement.

CONCLUSION

We found substantial IRR between physiotherapists in assigning the LUS score in a mechanically ventilated adult population in the intensive care unit.

AUSTRALIAN NEW ZEALAND CLINICAL TRIALS REGISTRATION NUMBER

ACTRN12619000783123.

Lung Ultrasound in the Evaluation of Lung Disease Severity in Children with Clinically Stable Cystic Fibrosis: A Prospective Cross-Sectional Study

With the increasing longevity of cystic fibrosis (CF), there is a growing need to minimise exposure to ionising radiation in patients who undergo regular imaging tests while monitoring the course of the lung disease. This study aimed to define the role of lung ultrasounds (LUS) in the evaluation of lung disease severity in children with clinically stable CF. LUS was performed on 131 patients aged 5 weeks to 18 years (study group) and in 32 healthy children of an equivalent age range (control group). Additionally, an interobserver study was performed on 38 patients from the study group. In CF patients, the following ultrasound signs were identified: I-lines; Z-lines; single, numerous and confluent B-lines; Am-lines; small and major consolidations; pleural line abnormalities and small amounts of pleural fluid. The obtained results were evaluated against an original ultrasound score. LUS results were correlated with the results of chest X-ray (CXR) [very high], pulmonary function tests (PFTs) [high] and microbiological status [significant]. The interobserver study showed very good agreement between investigators. We conclude that LUS is a useful test in the evaluation of CF lung disease severity compared to routinely used methods. With appropriate standardisation, LUS is highly reproducible.

Interrater Reliability of Point-of-Care Cardiopulmonary Ultrasound in Patients With Septic Shock: An Analysis of Agreement Between Treating Clinician and Expert Reviewers

BACKGROUND

Cardiopulmonary ultrasound (CPUS) is commonly used to assess cardiac function and preload status in patients with septic shock. However, the reliability of CPUS findings at the point of care is unknown.

OBJECTIVE

To assess interrater reliability (IRR) of CPUS in patients with suspected septic shock between treating emergency physicians (EPs) vs emergency ultrasound (EUS) experts.

METHODS

Single-center, prospective, observational cohort enrolling patients (n = 51) with hypotension and suspected infection. Treating EPs performed and interpreted CPUS for cardiac function parameters (left ventricular [LV] function and right ventricular [RV] function and size) and preload volume parameters (inferior vena cava [IVC] diameter and pulmonary B-lines). The primary outcome was IRR (assessed by Kappa values [κ] and intraclass correlation coefficient [ICC]) between EP and EUS-expert consensus. Secondary analyses examined the effects on IRR of operator experience, respiratory rate, and known difficult views on a Cardiology-performed echocardiogram.

RESULTS

IRR was fair for LV function, κ = 0.37, 95% confidence interval (CI) 0.1-0.64; poor for RV function, κ = -0.05, 95% CI -0.6-0.5; moderate for RV size, κ = 0.47, 95% CI 0.07-0.88; and substantial for B-lines, κ = 0.73, 95% CI 0.51-0.95 and IVC size, ICC = 0.87, 95% CI 0.2-0.99. Involvement of ultrasound-trained faculty was associated with improved IRR of RV size (p = 0.002), but not other CPUS domains.

CONCLUSIONS

Our study demonstrated high IRR for preload volume parameters (IVC size and presence of B-lines), but not for cardiac parameters (LV function and RV function and size) in patients presenting with concern for septic shock. Future research must focus on determining sonographer and patient-specific factors affecting CPUS interpretation in real-time.

Artificial Intelligence-Augmented Pediatric Lung POCUS: A Pilot Study of Novice Learners

OBJECTIVE

Respiratory symptoms are among the most common chief complaints of pediatric patients in the emergency department (ED). Point-of-care ultrasound (POCUS) outperforms conventional chest X-ray and is user-dependent, which can be challenging to novice ultrasound (US) users. We introduce a novel concept using artificial intelligence (AI)-enhanced pleural sweep to generate complete panoramic views of the lungs, and then assess its accuracy among novice learners (NLs) to identify pneumonia.

METHODS

Previously healthy 0- to 17-year-old patients presenting to a pediatric ED with cardiopulmonary chief complaint were recruited. NLs received a 1-hour training on traditional lung POCUS and the AI-assisted software. Two POCUS-trained experts interpreted the images, which served as the criterion standard. Both expert and learner groups were blinded to each other's interpretation, patient data, and outcomes. Kappa was used to determine agreement between POCUS expert interpretations.

RESULTS

Seven NLs, with limited to no prior POCUS experience, completed examinations on 32 patients. The average patient age was 5.53 years (±1.07). The median scan time of 7 minutes (minimum-maximum 3-43; interquartile 8). Three (8.8%) patients were diagnosed with pneumonia by criterion standard. Sensitivity, specificity, and accuracy for NLs AI-augmented interpretation were 66.7% (confidence interval [CI] 9.4-99.1%), 96.5% (CI 82.2-99.9%), and 93.7% (CI 79.1-99.2%). The average image quality rating was 2.94 (±0.16) out of 5 across all lung fields. Interrater reliability between expert sonographers was high with a kappa coefficient of 0.8.

CONCLUSION

This study shows that AI-augmented lung US for diagnosing pneumonia has the potential to increase accuracy and efficiency.

Reliability and clinical correlations of semi-quantitative lung ultrasound on BLUE points in COVID-19 mechanically ventilated patients: The 'BLUE-LUSS'-A feasibility clinical study

INTRODUCTION

Bedside lung ultrasound has gained a key role in each segment of the treatment chain during the COVID-19 pandemic. During the diagnostic assessment of the critically ill patients in ICUs, it is highly important to maximize the amount and quality of gathered information while minimizing unnecessary interventions (e.g. moving/rotating the patient). Another major factor is to reduce the risk of infection and the workload of the staff.

OBJECTIVES

To serve these significant issues we constructed a feasibility study, in which we used a single-operator technique without moving the patient, only assessing the easily achievable lung regions at conventional BLUE points. We hypothesized that calculating this 'BLUE lung ultrasound score' (BLUE-LUSS) is a reasonable clinical tool. Furthermore, we used both longitudinal and transverse scans to measure their reliability and assessed the interobserver variability as well.

METHODS

University Intensive Care Unit based, single-center, prospective, observational study was performed on 24 consecutive SARS-CoV2 RT-PCR positive, mechanically ventilated critically ill patients. Altogether 400 loops were recorded, rated and assessed off-line by 4 independent intensive care specialists (each 7+ years of LUS experience).

RESULTS

Intraclass correlation values indicated good reliability for transversal and longitudinal qLUSS scores, while we detected excellent interrater agreement of both cLUSS calculation methods. All of our LUS scores correlated inversely and significantly to the P/F values. Best correlation was achieved in the case of longitudinal qLUSS (r = -0.55, p = 0.0119).

CONCLUSION

Summarized score of BLUE-LUSS can be an important, easy-to-perform adjunct tool for assessing and quantifying lung pathology in critically ill ventilated patients at bedside, especially for the P/F ratio. The best agreement for the P/F ratio can be achieved with the longitudinal scans. Regarding these findings, assessing BLUE-points can be extended with the BLUE-LUSS for daily routine using both transverse and longitudinal views.

The Inter-Rater Reliability of Pediatric Point-of-Care Lung Ultrasound Interpretation in Children With Acute Respiratory Failure

OBJECTIVES

Use of point-of-care lung ultrasound (POC-LUS) has increased significantly in pediatrics yet it remains under-studied in the pediatric intensive care unit (PICU). No studies explicitly evaluate the reliability of POC-LUS artifact interpretation among critically ill children with acute respiratory failure (ARF) in the PICU. We thus designed this study to determine the inter-rater reliability of POC-LUS interpretation in pediatric ARF among pediatric intensivists trained in POC-LUS and an expert intensivist.

METHODS

We compared the interpretation of lung sliding, pleural line characteristics, ultrasound artifacts, and POC-LUS diagnoses among pediatric intensivists and an expert intensivist in a cohort of children admitted to the PICU for ARF. Kappa statistics (k) adjusted for maximum attainable agreement (k/k_max ) were used to quantify chance-correct agreement between the pediatric intensivist and expert physician.

RESULTS

We enrolled 88 patients, evaluating 3 zones per hemithorax (anterior, lateral, and posterior) for lung sliding, pleural line characteristics, ultrasound artifacts, and diagnosis. There was moderate agreement between the PICU intensivist and expert-derived diagnoses with 56% observed agreement (k/k_max  = 0.46, 95% confidence interval [CI] 0.31-0.65). Agreement in identification of lung sliding (k = 0.19, 95% CI -0.17 to 0.56) and pleural line characteristics (k = 0.24, 95% CI 0.08-0.40) was slight and fair, respectively, while agreement in the interpretation of ultrasound artifacts ranged from moderate to substantial.

CONCLUSIONS

Evidence supporting the evaluation of neonatal and adult patients with POC-LUS should not be extrapolated to critically ill pediatric patients. This study adds to the evidence supporting use of POC-LUS in the PICU by demonstrating moderate agreement between PICU intensivist and expert-derived POC-LUS diagnoses.

Point-of-care lung ultrasound is more reliable than chest X-ray for ruling out acute chest syndrome in sickle cell pediatric patients: A prospective study

BACKGROUND

Acute chest syndrome (ACS) is a leading cause of morbidity and mortality in sickle cell patients, and it is often challenging to establish its diagnosis.

PROCEDURE

This was a prospective observational study conducted in a pediatric emergency (PEM) department. We aimed to investigate the performance characteristics of point-of-care lung ultrasound (LUS) for diagnosing ACS in sickle cell children. LUS by trained PEM physicians was performed and interpreted as either positive or negative for consolidation. LUS results were compared to chest X-ray (CXR) and discharge diagnosis as reference standards.

RESULTS

Four PEM physicians performed the LUS studies in 79 suspected ACS cases. The median age was 8 years (range 1-17 years). Fourteen cases (18%) received a diagnosis of ACS based on CXR and 21 (26.5%) had ACS discharge diagnosis. Comparing to CXR interpretation as the reference standard, LUS had a sensitivity of 100% (95% CI: 77%-100%), specificity of 68% (95% CI: 56%-79%), positive predictive value of 40% (95% CI: 24%-56%), and negative predictive value of 100% (95% CI: 92%-100%). Overall LUS accuracy was 73.42% (95% CI: 62%-83%). Using discharge diagnosis as the endpoint for both CXR and LUS, LUS had significantly higher sensitivity (100% vs. 62%, p = .0047) and lower specificity (76% vs.100%, p = .0002). LUS also had lower positive (60% vs.100%, p < .0001) and higher negative (100% vs.77%, p = .0025) predictive values. The overall accuracy was similar for both tests (82% vs. 88%, p = .2593).

CONCLUSION

The high negative predictive value, with narrow CIs, makes LUS an excellent ruling-out tool for ACS.

Interobserver Agreement of Lung Ultrasound Findings of COVID-19

BACKGROUND

Lung ultrasound (LUS) has received considerable interest in the clinical evaluation of patients with COVID-19. Previously described LUS manifestations for COVID-19 include B-lines, consolidations, and pleural thickening. The interrater reliability (IRR) of these findings for COVID-19 is unknown.

METHODS

This study was conducted between March and June 2020. Nine physicians (hospitalists: n = 4; emergency medicine: n = 5) from 3 medical centers independently evaluated n = 20 LUS scans (n = 180 independent observations) collected from patients with COVID-19, diagnosed via RT-PCR. These studies were randomly selected from an image database consisting of COVID-19 patients evaluated in the emergency department with portable ultrasound devices. Physicians were blinded to any patient information or previous LUS interpretation. Kappa values (κ) were used to calculate IRR.

RESULTS

There was substantial IRR on the following items: normal LUS scan (κ = 0.79 [95% CI: 0.72-0.87]), presence of B-lines (κ = 0.79 [95% CI: 0.72-0.87]), ≥3 B-lines observed (κ = 0.72 [95% CI: 0.64-0.79]). Moderate IRR was observed for the presence of any consolidation (κ = 0.57 [95% CI: 0.50-0.64]), subpleural consolidation (κ = 0.49 [95% CI: 0.42-0.56]), and presence of effusion (κ = 0.49 [95% CI: 0.41-0.56]). Fair IRR was observed for pleural thickening (κ = 0.23 [95% CI: 0.15-0.30]).

DISCUSSION

Many LUS manifestations for COVID-19 appear to have moderate to substantial IRR across providers from multiple specialties utilizing differing portable devices. The most reliable LUS findings with COVID-19 may include the presence/count of B-lines or determining if a scan is normal. Clinical protocols for LUS with COVID-19 may require additional observers for the confirmation of less reliable findings such as consolidations.

Ultrasound and Influenza: The Spectrum of Lung and Cardiac Ultrasound Findings in Patients with Suspected Influenza A and B

In patients with influenza, cardiac and lung ultrasound may help determine the severity of illness and predict clinical outcomes. To determine the ultrasound characteristics of influenza and define the spectrum of lung and cardiac findings in patients with suspected influenza A or B, we conducted a prospective observational study in patients presenting to the emergency department at a tertiary care academic institution. An ultrasound protocol consisting of cardiac, lung and inferior vena cava scans was performed within 6 h of admission. We compared the ultrasound findings in cases with positive and negative influenza polymerase chain reaction, while controlling for comorbidities. We enrolled 117 patients, 41.9% of whom (49/117) tested positive for influenza. In those with influenza, ultrasound confirmed preserved left ventricular and right ventricular (RV) function in 81.3% of patients. The most common cardiac pathology was RV dilation (10.4%), followed by left ventricular systolic dysfunction (8.3%). Patients with negative influenza polymerase chain reaction with RV dysfunction demonstrated higher hospital admission than those those with normal RV function (45.1%, 23/51, vs. 17.9%, 5/28; p = 0.016). B-lines were prevalent in both influenza and non-influenza groups (40.8% and 69.1%, respectively; p = 0.013). Lung consolidation was identified in only 8.25% of patients with influenza. In conclusion, in patients with influenza we were unable to define distinct ultrasound features specific to influenza A or B, suggesting that ultrasound may not be beneficial in diagnosing influenza nor in evaluating its severity.

Usefulness of Lung Ultrasound in Paediatric Respiratory Diseases

Respiratory infection diseases are among the major causes of morbidity and mortality in children. Diagnosis is focused on clinical presentation, yet signs and symptoms are not specific and there is a need for new non-radiating diagnostic tools. Among these, lung ultrasound (LUS) has recently been included in point-of-care protocols showing interesting results. In comparison to other imaging techniques, such as chest X-ray and computed tomography, ultrasonography does not use ionizing radiations. Therefore, it is particularly suitable for clinical follow-up of paediatric patients. LUS requires only 5-10 min and allows physicians to make quick decisions about the patient's management. Nowadays, LUS has become an early diagnostic tool to detect pneumonia during the COVID-19 pandemic. In this narrative review, we show the most recent scientific literature about advantages and limits of LUS performance in children. Furthermore, we discuss the major paediatric indications separately, with a paragraph fully dedicated to COVID-19. Finally, we mention potential future perspectives about LUS application in paediatric respiratory diseases.

[Paediatric Life Support]

The European Resuscitation Council (ERC) Paediatric Life Support (PLS) guidelines are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations of the International Liaison Committee on Resuscitation (ILCOR). This section provides guidelines on the management of critically ill or injured infants, children and adolescents before, during and after respiratory/cardiac arrest.

European Resuscitation Council Guidelines 2021: Paediatric Life Support

These European Resuscitation Council Paediatric Life Support (PLS) guidelines, are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the management of critically ill infants and children, before, during and after cardiac arrest.

CPIS Lung Ultrasound and the Erratic March toward Diagnostic Certainty in VAP

How to cite this article: Rajagopalan RE. CPIS Lung Ultrasound and the Erratic March toward Diagnostic Certainty in VAP. Indian J Crit Care Med 2021;25(3):255-257.

Point-of-care ultrasound by the pediatrician in the diagnosis and follow-up of community-acquired pneumonia

OBJECTIVES

To review, analyze, and present the available evidence on the usefulness of point-of-care pulmonary ultrasound in the diagnosis and monitoring of community-acquired pneumonia (CAP), aiming to facilitate its potential inclusion into pediatric clinical reference guidelines.

SOURCE OF DATA

A non-systematic research was carried out in the MEDLINE (PubMed), LILACS, and SciELO databases, from January 1985 to September 2019. The articles that were considered the most relevant were selected.

SYNTHESIS OF DATA

CAP is a relevant cause of morbidity and mortality in pediatrics and its clinical management remains a major challenge. The systematic use of chest X-ray for its diagnosis is controversial because it exposes the child to ionizing radiation and there are interobserver differences in its interpretation. Recently, the use of point-of-care pulmonary ultrasound by the pediatrician has been presented as an alternative for the diagnosis and monitoring of CAP. A great deal of evidence has disclosed its high sensitivity and diagnostic specificity, with the advantages of no ionizing radiation, relatively low cost, immediate results, portability, and the possibility of repetition according to the requirements of disease evolution. Moreover, its use can help rule out possible bacterial etiology and thus prevent inappropriate antibiotic treatments that favor bacterial resistance.

CONCLUSIONS

Point-of-care ultrasonography represents an opportunity to improve the diagnosis and monitoring of CAP. However, as an operator-dependent technique, training is required for adequate image acquisition, correct interpretation, and integration with clinical data for correct decision-making.

Consensus on the Application of Lung Ultrasound in Pneumonia and Bronchiolitis in Children

This evidence-based consensus aims to establish the role of point-of-care lung ultrasound in the management of pneumonia and bronchiolitis in paediatric patients. A panel of thirteen experts form five Polish tertiary pediatric centres was involved in the development of this document. The literature search was done in PubMed database. Statements were established based on a review of full-text articles published in English up to December 2019. The development of this consensus was conducted according to the GRADE (Grading of Recommendations, Assessment, Development and Evaluations)-adopted and Delphi method. Initially, 22 proposed statements were debated over 3 rounds of on-line discussion and anonymous voting sessions. A total of 17 statements were agreed upon, including four statements referring to general issues, nine referring to pneumonia and four to bronchiolitis. For five statements experts did not achieve an agreement. The evidence supporting each statement was evaluated to assess the strength of each statement. Overall, eight statements were rated strong, five statements moderate, and four statements weak. For each statement, experts provided their comments based on the literature review and their own experience. This consensus is the first to establish the role of lung ultrasound in the diagnosis and management of pneumonia and bronchiolitis in children as an evidence-based method of imaging.

Could It Be Pneumonia? Lung Ultrasound in Children With Low Clinical Suspicion for Pneumonia

Supplemental Digital Content is available in the text.

Background:

Community-acquired pneumonia (CAP) is a significant cause of pediatric morbidity and mortality worldwide. Emergency department point of care ultrasound (POCUS) is a first-line modality for diagnosis of CAP. The current coronavirus disease 2019 pandemic creates a unique opportunity to incorporate lung POCUS into the evaluation of a broader range of children. It has increased the utility of lung POCUS in both evaluation and follow-up of pediatric coronavirus cases. An increased use of lung POCUS creates an opportunity for earlier diagnosis while allowing the opportunity for overdiagnosis of small infiltrates and atelectasis. We collated a case series to demonstrate the benefit of lung POCUS in a very broad range of children.

Methods:

We collected a case series of 5 patients between December 2018 and December 2019 who presented nonclassically and were diagnosed with CAP on POCUS by a pediatric emergency physician.

Conclusion:

Routine lung POCUS in ill children will allow treating physicians to identify and follow a pulmonary infiltrate consistent with CAP quickly. We anticipate that early and more frequent use of POCUS and earlier diagnosis of CAP may improve outcomes by decreasing healthcare encounters within the same illness and by reducing the incidence of late sequelae of pneumonia such as empyema and effusions. However, we acknowledge that this may come at the expense of the overtreatment of viral infiltrates and atelectasis. Further study is required to improve the specificity of lung POCUS in the evaluation of CAP.

Lung ultrasound in pediatric radiology - cons

In the 1990s, intensivists suggested a new type of sonography: lung ultrasound, based on artefacts that receive information even from physical acoustic phenomena not directly convertible into images of the human body. They compared the artefacts from the lung zones with no acoustic window with various computed tomography (CT) patterns. They used and still use US as a tool to evaluate patients bedside, i.e. monitoring of lung recruitment. They included Lung ultrasound in what was termed POCUS (Point-of-Care Ultrasound). Lung ultrasound has been progressively extended to paediatrics in general. The most appealing novelty has been the diagnosis of pneumothorax. Lung ultrasound was developed as a support tool for critical patients. Extrapolation with mass diffusion, in the absence of appropriate training, has led to misunderstandings and dangerous therapeutic diagnostic drifts.

Training and standardization of general practitioners in the use of lung ultrasound for the diagnosis of pediatric pneumonia

BACKGROUND

Pneumonia is a leading cause of death in children of low-resource settings. Barriers to care include an early and accurate diagnosis. Lung ultrasound is a novel tool for the identification of pediatric pneumonia; however, there is currently no standardized approach to train in image acquisition and interpretation of findings in epidemiological studies. We developed a training program for physicians with limited ultrasound experience on how to use ultrasound for the diagnosis of pediatric pneumonia and how to standardize image interpretation using a panel of readers.

METHODS

Twenty-five physicians participating in the training program conducted lung ultrasounds in all children with suspected pneumonia, aged 3 to 35 months, presenting to three subdistrict hospitals in Sylhet, Bangladesh, between June 2015 and September 2017.

RESULTS

A total of 9051 pediatric lung ultrasound assessments were conducted through 27 months of data collection. Study physicians underwent training and all were successfully standardized, achieving 91% agreement and maintained a sensitivity and specificity of 88% and 92%, respectively, when their diagnosis was compared with experts. Overall kappa between two readers was high (0.86, 95% confidence interval [CI], 0.84-0.87), and remained high when a third expert reader was included (0.80, 95% CI, 0.79-0.81). Agreement and kappa statistics were similarly high when stratified by age, sex, presence of danger signs, or hypoxemia.

CONCLUSIONS

Lung ultrasound is a novel tool for the diagnosis of pediatric pneumonia with evidence supporting its validity and feasibility of implementation. Here we introduced a training program that resulted in a high level of inter-sonographer agreement.

Lung ultrasound in children with pneumonia: interoperator agreement on specific thoracic regions

The objective of this study was to evaluate the interoperator agreement of lung ultrasonography (LUS) on specific thoracic regions in children diagnosed with pneumonia and to compare the findings of the LUS with the chest X-ray. Participants admitted to the ward or PICU underwent LUS examinations performed by an expert and a novice operator. A total of 261 thoracic regions in 23 patients were evaluated. Median age and weight of participants were 30 months and 11.6 kg, respectively. A substantial overall agreement between operators was found for normal lung tissue (κ = 0.615, 95% confidence interval (95% CI) = 0.516-0.715) and for consolidations (κ = 0.635, 95% CI = 0.532-0.738). For B-lines, a moderate agreement was observed (κ = 0.573, 95% CI = 0.475-0.671). An almost perfect agreement was found for pleural effusion (κ = 0.868, 95% CI = 0.754-0.982). The diagnosis of consolidations by LUS showed a high sensitivity (93% for both operators) but a low specificity (14% for expert and 25% for novice operator). While intubated patients presented significantly more consolidations, nonintubated patients presented more normal ultrasound patterns.Conclusion: Even when performed by operators with very distinct degrees of experience, LUS had a good interoperator reliability for detecting sonographic patterns on specific thoracic regions. What is Known: • Lung ultrasound is feasible, safe, and highly accurate for the diagnosis of pneumonia in children; however, it does not allow global visualization of the thorax in a single moment as in chest X-rays, and, similar to the stethoscope, partial thorax assessments must be performed sequentially. What is New: • This is the first study evaluating the agreement of LUS on specific thoracic regions between operators with distinct degrees of experience performing the sonograms. • There is a good agreement between an expert operator and a novice operator who underwent a brief theoretical-practical training program on LUS.