Detecting the Absence of Lung Sliding in Lung Ultrasounds Using Deep Learning

Certain post-thoracic surgery complications are monitored in a standard manner using methods that employ ionising radiation. A need to automatise the diagnostic procedure has now arisen following the clinical trial of a novel lung ultrasound examination procedure that can replace X-rays. Deep learning was used as a powerful tool for lung ultrasound analysis. We present a novel deep-learning method, automated M-mode classification, to detect the absence of lung sliding motion in lung ultrasound. Automated M-mode classification leverages semantic segmentation to select 2D slices across the temporal dimension of the video recording. These 2D slices are the input for a convolutional neural network, and the output of the neural network indicates the presence or absence of lung sliding in the given time slot. We aggregate the partial predictions over the entire video recording to determine whether the subject has developed post-surgery complications. With a 64-frame version of this architecture, we detected lung sliding on average with a balanced accuracy of 89%, sensitivity of 82%, and specificity of 92%. Automated M-mode classification is suitable for lung sliding detection from clinical lung ultrasound videos. Furthermore, in lung ultrasound videos, we recommend using time windows between 0.53 and 2.13 s for the classification of lung sliding motion followed by aggregation.

Advantages of lung ultrasound in triage, diagnosis and monitoring COVID-19 patients: review

Over the last decades, especially during the COVID-19 pandemic period, lung ultrasound (LUS) gained interest due to multiple advantages: radiation-free, repeatable, cost-effective, portable devices with a bedside approach. These advantages can help clinicians in triage, in positive diagnostic, stratification of disease forms according to severity and prognosis, evaluation of mechanically ventilated patients from Intensive Care Units, as well as monitoring the progress of COVID-19 lesions, thus reducing the health care contamination. LUS should be performed by standard protocol examination. The characteristic lesions from COVID-19 pneumonia are the abolished lung sliding, presence of multiple and coalescent B-lines, disruption and thickening of pleural line with subpleural consolidations. LUS is a useful method for post-COVID-19 lesions evaluation, highlight the remaining fibrotic lesions in some patients with moderate or severe forms of pneumonia.

Efficiency of Lung Ultrasonography in the Diagnosis and Follow-up of Viral Pneumonia in Newborn

Objective Lung ultrasonography (LUS) is a useful method for diagnosis of lung diseases such as respiratory distress syndrome, transient tachypnea of the newborn, pneumonia, and pneumothorax in the neonatal period. LUS has become an important tool in the diagnosis and follow-up of lung diseases. LUS is easy to apply at the bedside and is a practical and low-cost method for diagnosing pneumonia. Study Design This study was conducted in neonatal intensive care unit of Dr. Sami Ulus Obstetrics, Children's Health and Diseases Training and Research Hospital. From September 2019 to April 2020, 50 patients who were diagnosed with viral pneumonia were included in the study. Also, 24 patients with sepsis-related respiratory failure were included in the study as a control group. LUS was performed at the bedside three times, by a single expert, once each before treatment for diagnosis, on discharge, and after discharge in outpatient clinic control. Results Before treatment, LUS findings were lung consolidation with air bronchograms (50/50), pleural line abnormalities (35/50), B-pattern (25/50), disappearance of lung sliding (21/50), lung pulse (5/50), and pleural effusion (9/50). During discharge, we found significant changes: lung consolidation with air bronchograms (6/50), pleural line abnormalities (7/50), B-pattern (12/50), and pleural effusion (1/50) (p < 0.05). Outpatient clinic control LUS findings were lung consolidation with air bronchograms (0/50), pleural line abnormalities (0/50), B-pattern (0/50), disappearance of lung sliding (0/50), and pleural effusion (0/50) (p < 0.05). Also, B-pattern image, disappearance of lung sliding, and pleural line abnormalities were higher in control group (p < 0.05). Conclusion Ultrasound gives no hazard, and the application of bedside ultrasonography is comfortable for the patients. Pneumonia is a serious infection in the neonatal period. Repeated chest radiography may be required depending on the clinical condition of the patient with pneumonia. This study focuses on adequacy of LUS in neonatal pneumonia. Key Points

Lung Ultrasound to Detect Pneumothorax in Children Evaluated for Acute Chest Pain in the Emergency Department: An Observational Pilot Study

Objectives- We prospectively analyzed children with acute chest pain and clinical suspicion of pneumothorax (PNX) evaluated at the pediatric Emergency Department. Methods- After clinical examination and before Chest X-Ray, children underwent LUS to evaluate the presence of PNX. We enrolled 70 children, 13 (18,57%) received a final diagnosis of PNX. Results- In all 13 (100%) patients LUS showed the &ldquo;bar-code sign&rdquo;, the absence of lung sliding and the absence of B lines while in 12 (92,3%) there was the lung point, giving a diagnosis of PNX. All cases had PNX features on CXR. The &ldquo;bar-code sign&rdquo;, the absence of lung sliding and the absence of B lines had a sensitivity of 100% and a specificity of 100%. The &ldquo;bar-code sign&rdquo; had a positive predictive value of 100% and a negative predictive value of 100% for the detection of PNX. Conclusions- LUS is highly accurate in detecting or excluding pneumothorax in children with acute chest pain evaluated in the pediatric emergency department.

Lung ultrasound findings in patients with novel SARS-CoV2

Background: Over 2 million people worldwide have been infected with Severe Acute Respiratory Distress Syndrome Corona Virus 2 (SARS CoV2). Lung ultrasound has been proposed to diagnose and it. However, little is known about ultrasound findings in these patients. Our aim is to present an overview of lung ultrasound characteristics in critically ill patients with SARS CoV2 pneumonia overall and in relation to the duration of symptoms and clinical parameters. Methods: On the Intensive Care Unit of two academic hospitals, adult patients who tested positive for SARS-CoV2 were included. Images were analyzed for pleural line characteristics, number and appearance of B-lines, BLUE-profiles (Bedside Lung Ultrasound in Emergency), pathology in the PLAPS (Postero Lateral Alveolar and Pleural Syndrome) point and a LUS-score (lung ultrasound). The primary outcomes were frequencies, percentages and differences in lung ultrasound findings overall and between short (≤14 days) and long (>14 days) duration of symptoms and their correlation with clinical parameters. Results: In this pilot observational study, 61 patients were included with 75 examinations for analysis. The most prevalent ultrasound findings were decreased lung sliding (36%), thickening of the pleural line (42%) and a C-profile per view (37%). Patients with ″long″ duration of symptoms presented more frequently with a thickened and irregular pleural line (21% (32) vs 9% (11), p=.01), C-profile per patient (47% (18) vs. 25% (8),p=.01) and pleural effusion (19% (14) vs 5% (3),p=.02) compared to patients with short duration of symptoms. Lung ultrasound findings did not correlate with P/F ratio, fluid balance or dynamic compliance, with the exception of the LUS-score and dynamic compliance (R2=0.27, p=.02). Conclusion: SARS CoV2 results in significant ultrasound changes, with decreased lung sliding, thickening of the pleural line and a C-profile being the most observed. With time, a thickened and irregular pleural line, C-profile and pleural effusion become more common findings.

Republication of “Ultrasonographic Appearance of Lung Sliding in a Patient With a Bronchopleural Fistula on a High-Frequency Oscillator Ventilator”

The patient with a bronchopleural fistula and acute respiratory distress syndrome can present a therapeutic challenge for the treating clinician. In this case, the authors describe the use of bedside thoracic sonography to show real-time improvement in a pneumothorax after initiation of high-frequency oscillatory ventilation. Sonography may have a role in the evaluation of ventilator strategies in the future, although validation of this application is still needed.