Which ultrasound transducer type is best for diagnosing pneumothorax?

Airway and Thoracic Ultrasound

Airway and thoracic ultrasound applications can provide critical information to improve patient safety for procedures and management of pulmonary conditions. Emergency physicians should utilize airway ultrasound in the preparation for an anatomically and/or physiologically difficult airway, which may include site demarcation for surgical airway planning. Thoracic ultrasound is useful in the prompt evaluation of a dyspneic patient. This article underscores the crucial role of airway and thoracic ultrasound in emergency medicine, emphasizing its utility for assessing difficult airways, planning surgical airways, and promptly evaluating dyspneic patients.

Thoracic ultrasound in guiding management of respiratory disease

INTRODUCTION

The use of ultrasound in respiratory disease has evolved substantially over the past two decades. From a test done to confirm the safe site of pleural fluid drainage, thoracic ultrasound has become a point-of-care test that guides the management of patients on respiratory wards, in clinics and endoscopy.

AREAS COVERED

This review overviews the process of ultrasound examination in the chest. It then delves into specific disease areas (pleural disease, lung disease, diaphragm disease, and invasive procedures) to highlight how thoracic ultrasound is being used to refine management. The review concludes with discussion on the training curricula and assessment tools for competency in thoracic ultrasound. Being a scoping review, literature searches were conducted on PubMed using relevant search terms.

EXPERT OPINION

In addition to its current uses, there are many avenues where thoracic ultrasound will soon be beneficial. Recent studies show promising roles in areas such as patient-tailored guidance of pleurodesis and non-invasively predicting lung re-expansion after pleural fluid drainage. In addition, auxiliary tools such as contrast-enhanced ultrasound and elastography are proving useful in identifying the etiology and directing the successful sampling of pleural and lung lesions. Studies are also exploring the utility of sonographic biomarkers such as echogenicity and septations to predict outcomes in pleural disease.

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.

Lung ultrasound: A comparison of image interpretation accuracy between curvilinear and phased array transducers

Introduction

Both curvilinear and phased array transducers are commonly used to perform lung ultrasound (LUS). This study seeks to compare LUS interpretation accuracy of images obtained using a curvilinear transducer with those obtained using a phased array transducer.

Methods

We invited 166 internists and trainees to interpret 16 LUS images/cineloops of eight patients in an online survey: eight curvilinear and eight phased array, performed on the same lung location. Images depicted normal lung, pneumothorax, pleural irregularities, consolidation/hepatisation, pleural effusions and B-lines. Primary outcome for each participant is the difference in image interpretation accuracy scores between the two transducers.

Results

A total of 112 (67%) participants completed the survey. The mean paired accuracy score difference between the curvilinear and phased array images was 3.0% (95% CI: 0.6 to 5.4%, P = 0.015). For novices, scores were higher on curvilinear images (mean difference: 5.4%, 95% CI: 0.9 to 9.9%, P = 0.020). For non-novices, there were no differences between the two transducers (mean difference: 1.4%, 95% CI: -1.1 to 3.9%, P = 0.263). For pleural-based findings, the mean of the paired differences between transducers was higher in the novice group (estimated mean difference-in-differences: 9.5%, 95% CI: 0.6 to 18.4%; P = 0.036). No difference in mean accuracies was noted between novices and non-novices for non-pleural-based pathologies (estimated mean difference-in-differences: 0.6%, 95% CI to 5.4-6.6%; P = 0.837).

Conclusions

Lung ultrasound images obtained using the curvilinear transducer are associated with higher interpretation accuracy than the phased array transducer. This is especially true for novices interpreting pleural-based pathologies.

An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound

The COVID-19 pandemic has become one of the biggest threats to the global healthcare system, creating an unprecedented condition worldwide. The necessity of rapid diagnosis calls for alternative methods to predict the condition of the patient, for which disease severity estimation on the basis of Lung Ultrasound (LUS) can be a safe, radiation-free, flexible, and favorable option. In this paper, a frame-based 4-score disease severity prediction architecture is proposed with the integration of deep convolutional and recurrent neural networks to consider both spatial and temporal features of the LUS frames. The proposed convolutional neural network (CNN) architecture implements an autoencoder network and separable convolutional branches fused with a modified DenseNet-201 network to build a vigorous, noise-free classification model. A five-fold cross-validation scheme is performed to affirm the efficacy of the proposed network. In-depth result analysis shows a promising improvement in the classification performance by introducing the Long Short-Term Memory (LSTM) layers after the proposed CNN architecture by an average of 7-12%, which is approximately 17% more than the traditional DenseNet architecture alone. From an extensive analysis, it is found that the proposed end-to-end scheme is very effective in detecting COVID-19 severity scores from LUS images.

European Respiratory Society statement on thoracic ultrasound

Thoracic ultrasound is increasingly considered to be an essential tool for the pulmonologist. It is used in diverse clinical scenarios, including as an adjunct to clinical decision making for diagnosis, a real-time guide to procedures and a predictor or measurement of treatment response. The aim of this European Respiratory Society task force was to produce a statement on thoracic ultrasound for pulmonologists using thoracic ultrasound within the field of respiratory medicine. The multidisciplinary panel performed a review of the literature, addressing major areas of thoracic ultrasound practice and application. The selected major areas include equipment and technique, assessment of the chest wall, parietal pleura, pleural effusion, pneumothorax, interstitial syndrome, lung consolidation, diaphragm assessment, intervention guidance, training and the patient perspective. Despite the growing evidence supporting the use of thoracic ultrasound, the published literature still contains a paucity of data in some important fields. Key research questions for each of the major areas were identified, which serve to facilitate future multicentre collaborations and research to further consolidate an evidence-based use of thoracic ultrasound, for the benefit of the many patients being exposed to clinicians using thoracic ultrasound.

Bedside ultrasound in the management of critically ill patients; Echocardiographic signs of acute respiratory distress syndrome and pulmonary embolism can be very similar, and lung ultrasound can act as a key: A case report

Right-sided heart failure (RHF) diagnosed at point-of-care-ultrasonography examination of critical patients may reveal an acute disease, such as pulmonary embolism (PE), requiring emergency thrombolytic treatment. However, acute respiratory distress syndrome (ARDS) and PE leading to acute RHF may exhibit very similar echocardiographic features. We report the case of a 27-year-old pregnant woman diagnosed with ARDS due to septic abortion, and in whom ARDS mimicked PE both clinically and on echocardiography. Such similarity may lead to inappropriate administration of thrombolytic therapy and/or delay the correct treatment. Lung ultrasonography may help avoiding this pitfall.

Current Ultrasound Technologies and Instrumentation in the Assessment and Monitoring of COVID-19 Positive Patients

Since the emergence of the COVID-19 pandemic in December of 2019, clinicians and scientists all over the world have faced overwhelming new challenges that not only threaten their own communities and countries but also the world at large. These challenges have been enormous and debilitating, as the infrastructure of many countries, including developing ones, had little or no resources to deal with the crisis. Even in developed countries, such as Italy, health systems have been so inundated by cases that health care facilities became oversaturated and could not accommodate the unexpected influx of patients to be tested. Initially, resources were focused on testing to identify those who were infected. When it became clear that the virus mainly attacks the lungs by causing parenchymal changes in the form of multifocal pneumonia of different levels of severity, imaging became paramount in the assessment of disease severity, progression, and even response to treatment. As a result, there was a need to establish protocols for imaging of the lungs in these patients. In North America, the focus was on chest X-ray and computed tomography (CT) as these are widely available and accessible at most health facilities. However, in Europe and China, this was not the case, and a cost-effective and relatively fast imaging modality was needed to scan a large number of sick patients promptly. Hence, ultrasound (US) found its way into the hands of Chinese and European physicians and has since become an important imaging modality in those locations. US is a highly versatile, portable, and inexpensive imaging modality that has application across a broad spectrum of conditions and, in this way, is ideally suited to assess the lungs of COVID-19 patients in the intensive care unit (ICU). This bedside test can be done with little to no movement of the patients from the unit that keeps them in their isolated rooms, thereby limiting further exposure to other health personnel. This article presents a basic introduction to COVID-19 and the use of the US for lung imaging. It further provides a high-level overview of the existing US technologies that are driving development in current and potential future US imaging systems for lung, with a specific emphasis on portable and 3-D systems.

Thoracic Ultrasound for Immediate Exclusion of Pneumothorax after Interventional Bronchoscopy

Background. Pneumothorax is a common side effect in interventional pulmonology. The ideal moment for detection with chest X-ray or ultrasound has not yet been defined. Earlier studies demonstrated the utility of performing these tests with a certain delay, which always results in a potentially dangerous gap. Methods. We prospectively enrolled patients with pulmonary interventions at increased risk of pneumothorax. Thoracic ultrasound was performed immediately after the intervention and at the moment of chest X-ray with a delay up to two hours. Results: Overall, we detected four pneumothoraxes in 115 procedures. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 75%, 100%, 100%, 99%, 99% for ultrasound and 75%, 90%, 21%, 99% und 89% for chest X-ray respectively. All pneumothoraces requiring chest tube were sufficiently detected by both methods. Conclusion. Thoracic ultrasound when performed immediately can more accurately exclude pneumothorax after interventional bronchoscopy when compared to chest X-ray. Further ultrasound examinations are unnecessary.