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Final ID: Poster #: EDU-060

Point-of-Care Ultrasound for the Diagnosis of Pediatric Lung Disease

Purpose or Case Report: Pneumonia is a leading cause of pediatric morbidity and mortality worldwide. In 2017, 15% of under-5 mortalities were due to pneumonia. Children in sub-Saharan Africa are disproportionately affected. Chest radiography (CXR) is currently the reference standard for imaging diagnosis of pediatric lung diseases. However, radiographic equipment is not available in many clinical settings, particularly in low and middle-income countries. In these scenarios, point-of-care lung ultrasound (LUS) is much more readily accessible. Thus, it is important to understand the US appearance of both interstitial and bacterial pneumonias and how they correlate with CXR findings.

In this pictorial essay, we will discuss the US appearance of common lower respiratory tract infections such as RSV, COVID-19, and bacterial pneumonia using images obtained from patients ages 1 month to 5 years with symptomatic respiratory illness in Lusaka, Zambia. All images were obtained by a technologist with a Butterfly portable ultrasound probe connected to an iPad. Images were obtained in the anterior, lateral, and posterior lung fields bilaterally. US images will be correlated with CXR findings.

The following examples of LUS findings will be discussed: 1) Normal LUS: The pleural line is thin and smooth with normal lung sliding. A-lines are present, and B-lines are limited to less than three in each field of view. 2) Abnormal B-lines: When three or more B-lines are seen in a single field of view, there is an abnormal increase in interstitial fluid. A focal B line is an abnormally thickened B-line and likely represents a confluence of multiple B-lines. 3) White lung: Confluent echogenicity involving two or more rib interspaces. 4) Pleural irregularity: The pleural line is jagged or fragmented and may also appear thickened with small sub-centimeter subpleural consolidations. 5) Pleural effusion: Well-defined fluid above the diaphragm. In a simple transudative effusion, the fluid appears anechoic. In a complex exudative effusion, the fluid may have loculations, septations, and/or internal echogenic floating debris. 6) Consolidation: Poorly defined, tissue-like region within the lung, usually seen adjacent to the pleural line. 7) Lung necrosis or abscess: Well-defined, hypoechoic region within an area of consolidation. By understanding the US appearance of lung pathologies, LUS can be used to diagnose pediatric lung diseases in areas where CXRs are currently unavailable.
Methods & Materials:
Results:
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  • Chang, Hailey  ( Boston Medical Center , Boston , Massachusetts , United States )
  • Gill, Christopher  ( Boston University School of Public Health , Boston , Massachusetts , United States )
  • Setty, Bindu  ( Boston Medical Center , Boston , Massachusetts , United States )
  • Castro-aragon, Ilse  ( Boston Medical Center , Boston , Massachusetts , United States )
  • Camelo, Ingrid  ( University of Massachusetts Medical School , Worcester , Massachusetts , United States )
  • Etter, Lauren  ( Boston University School of Public Health , Boston , Massachusetts , United States )
  • Pieciak, Rachel  ( Boston University School of Public Health , Boston , Massachusetts , United States )
  • Thompson, Russell  ( Worcester Polytechnic Institute , Worcester , Massachusetts , United States )
  • Wang, Kaihong  ( Boston University Graduate School of Arts and Sciences , Boston , Massachusetts , United States )
  • Li, Jason  ( Boston University College of Arts and Sciences , Boston , Massachusetts , United States )
Session Info:

Posters - Educational

Thoracic Imaging

SPR Posters - Educational

More abstracts from these authors:
Using Artificial Intelligence to Interpret Pneumonia CXR (chest X ray) Findings in Children with a Phone Application Platform

Thompson Russell, Pieciak Rachel, Gill Christopher, Li Jason, Wang Kaihong, Etter Lauren, Camelo Ingrid, Castro-aragon Ilse, Setty Bindu, Chang Hailey, Betke Margaret

Artificial intelligence-based Brightness Profiles Pattern Recognition to Detect Pediatric Pneumonia from Lung Ultrasound Images

Li Jason, Betke Margaret, Gill Christopher, Thompson Russell, Wang Kaihong, Etter Lauren, Camelo Ingrid, Chang Hailey, Setty Bindu, Castro Ilse, Pieciak Rachel

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