Comparison between lung ultrasonography and chest X-ray in the evaluation of neonatal respiratory distress syndrome

Setting the Standards: Neonatal Lung Ultrasound in Clinical Practice

The use of lung ultrasonography in neonates is increasing at a very fast rate. Evidence-based guidelines on the use of lung ultrasound (LU) in neonates and children have been published and well received across the world. However, there remains a lack of standardized curriculum for lung ultrasound training and standards for its application at the bedside. This article focuses on providing a standardized approach to the application of lung ultrasonography in neonates for the common neonatal conditions and how it can be integrated into bedside clinical decision-making.

Diagnostic Potentials of Lung Ultrasound In Neonatal Care: An Updated Overview

Recent technological strides, including high-frequency probes and lung ultrasound, have become a crucial non-invasive diagnostic tool in neonatal care, revolutionizing how respiratory conditions are assessed in the neonatal intensive care unit (NICU). High-frequency probes and portable devices significantly enhance the effectiveness of lung ultrasound in identifying respiratory distress syndrome (RDS), pneumonia, and pneumothorax, and underscore its growing significance. This comprehensive review explores the historical journey of lung ultrasonography, technological advancements, contemporary applications in neonatal care, emerging trends, and collaborative initiatives, and foresees a future where personalized healthcare optimizes outcomes for neonates.

Neonatal point-of-care lung ultrasound: what should be known and done out of the NICU?

Lung ultrasound is rapidly becoming a useful tool in the care of neonates: its ease of use, reproducibility, low cost, and negligible side effects make it a very suitable tool for the respiratory care of all neonates. This technique has been extensively studied by different approaches in neonatal intensive care unit (NICU), both for diagnostic and prognostic aims and to guide respiratory treatments. However, many neonates are being born in level I/II hospitals without NICU facilities so all pediatricians, not just neonatal intensivists, should be aware of its potential. This is made possible by the increasing access to ultrasound machines in a modern hospital setting. In this review, we describe the ultrasonographic characteristics of the normal neonatal lung. We also discuss the ultrasound features of main neonatal respiratory diseases: transient tachypnea of the neonate (TTN), respiratory distress syndrome (RDS), meconium aspiration syndrome (MAS), pneumothorax (PNX), pleural effusion (PE), or pneumonia. Finally, we mention two functional approaches to lung ultrasound: 1. The use of lung ultrasound in level I delivery centers as a mean to assess the severity of neonatal respiratory distress and request a transport to a higher degree structure in a timely fashion. 2. The prognostic accuracy of lung ultrasound for early and targeted surfactant replacement.

CONCLUSION

 LU is still a useful tool in level I/II neonatal units, both for diagnostic and functional issues.

WHAT IS KNOWN

• Neonatal lung ultrasound has been recently introduced in the usual care in many Neonatal Intensive Care Units.

WHAT IS NEW

• It also has many advantages in level I/II neonatal units, both for neonatologist or even pediatricians that treat neonates in those sites.

Classification of lung pathologies in neonates using dual-tree complex wavelet transform

INTRODUCTION

Undiagnosed and untreated lung pathologies are among the leading causes of neonatal deaths in developing countries. Lung Ultrasound (LUS) has been widely accepted as a diagnostic tool for neonatal lung pathologies due to its affordability, portability, and safety. However, healthcare institutions in developing countries lack well-trained clinicians to interpret LUS images, which limits the use of LUS, especially in remote areas. An automated point-of-care tool that could screen and capture LUS morphologies associated with neonatal lung pathologies could aid in rapid and accurate diagnosis.

METHODS

We propose a framework for classifying the six most common neonatal lung pathologies using spatially localized line and texture patterns extracted via 2D dual-tree complex wavelet transform (DTCWT). We acquired 1550 LUS images from 42 neonates with varying numbers of lung pathologies. Furthermore, we balanced our data set to avoid bias towards a pathology class.

RESULTS

Using DTCWT and clinical features as inputs to a linear discriminant analysis (LDA), our approach achieved a per-image cross-validated classification accuracy of 74.39% for the imbalanced data set. Our classification accuracy improved to 92.78% after balancing our data set. Moreover, our proposed framework achieved a maximum per-subject cross-validated classification accuracy of 64.97% with an imbalanced data set while using a balanced data set improves its classification accuracy up to 81.53%.

CONCLUSION

Our work could aid in automating the diagnosis of lung pathologies among neonates using LUS. Rapid and accurate diagnosis of lung pathologies could help to decrease neonatal deaths in healthcare institutions that lack well-trained clinicians, especially in developing countries.