Lung Ultrasound in the Neonatal Intensive Care Unit: Does It Impact Clinical Care?

A neonatal point-of-care ultrasound has multiple applications, but its use has been limited in neonatal intensive care units in the Unites States. An increasing body of evidence suggests that lung ultrasound performed by the neonatologist, at the bedside, is reliable and accurate in differentiating neonatal respiratory conditions, predicting morbidity, and guiding invasive interventions. Recent research has shown that a lung ultrasound can assist the clinician in accurately identifying and managing conditions such as respiratory distress syndrome, transient tachypnea of the newborn, and bronchopulmonary dysplasia. In this review, we discuss basic lung ultrasound terminology, evidence for applications of neonatal lung ultrasound, and its use as a diagnostic and predictive tool for common neonatal respiratory pathologies.

Dynamic Regulation of GH–IGF1 Signaling in Injury and Recovery in Hyperoxia-Induced Neonatal Lung Injury

Prematurely born infants often require supplemental oxygen that impairs lung growth and results in arrest of alveolarization and bronchopulmonary dysplasia (BPD). The growth hormone (GH)- and insulin-like growth factor (IGF)1 systems regulate cell homeostasis and organ development. Since IGF1 is decreased in preterm infants, we investigated the GH- and IGF1 signaling (1) in newborn mice with acute and prolonged exposure to hyperoxia as well as after recovery in room air; and (2) in cultured murine lung epithelial cells (MLE-12) and primary neonatal lung fibroblasts (pLFs) after treatment with GH, IGF1, and IGF1-receptor (IGF1-R) inhibitor or silencing of GH-receptor (Ghr) and Igf1r using the siRNA technique. We found that (1) early postnatal hyperoxia caused an arrest of alveolarization that persisted until adulthood. Both short-term and prolonged hyperoxia reduced GH-receptor expression and STAT5 signaling, whereas Igf1 mRNA and pAKT signaling were increased. These findings were related to a loss of epithelial cell markers (SFTPC, AQP5) and proliferation of myofibroblasts (αSMA+ cells). After recovery, GH-R-expression and STAT5 signaling were activated, Igf1r mRNA reduced, and SFTPC protein significantly increased. Cell culture studies showed that IGF1 induced expression of mesenchymal (e.g., Col1a1, Col4a4) and alveolar epithelial cell type I (Hopx, Igfbp2) markers, whereas inhibition of IGF1 increased SFTPC and reduced AQP5 in MLE-12. GH increased Il6 mRNA and reduced proliferation of pLFs, whereas IGF1 exhibited the opposite effect. In summary, our data demonstrate an opposite regulation of GH- and IGF1- signaling during short-term/prolonged hyperoxia-induced lung injury and recovery, affecting alveolar epithelial cell differentiation, inflammatory activation of fibroblasts, and a possible uncoupling of the GH-IGF1 axis in lungs after hyperoxia.

Deep Learning-Based Magnetic Resonance Imaging Lung Segmentation and Volumetric Marker Extraction in Preterm Infants

Objective and Impact Statement: We apply a deep learning (DL) segmentation method and automate the extraction of imaging markers for neonatal lung structure using magnetic resonance imaging (MRI) in order to inform clinical care with robust and quantifiable information about the neonatal lung. Introduction: Quantification of lung structural information in a standardized fashion is crucial to inform diagnostic processes that enable personalized treatment and monitoring strategies. Increased efficiency and accuracy in image quantification is especially needed in prematurely born infants, for whom long-term survival is critically determined by acute and chronic pulmonary complications, currently diagnosed based on clinical criteria due to the lack of routinely applicable diagnostic tools. Methods: We prospectively enrolled 107 premature infants in two clinical centers with and without chronic lung disease, i.e., Bronchopulmonary Dysplasia (BPD) to perform quiet-breathing lung MRI. An ensemble of deep convolutional neural networks was developed to perform lung segmentation, with a subsequent reconstruction of the 3-dimensional lung and computation of MRI volumetric measurements and compared to the standard manual segmentation. Results: The DL model successfully annotates lung segments with a volumetric dice score of 0.908 (Site 1) and 0.880 (Site 2), thereby reaching expert-level performance while demonstrating high transferability between study sites and robustness towards technical (low spatial resolution, movement artifacts) and disease conditions. Estimated lung volumes correlated with infant lung function testing measures and enabled the separation of neonates with and without BPD. Conclusion: Our work demonstrates the potential of AI-supported MRI measures to perform monitoring of neonatal lung development and characterization of respiratory diseases in this high-risk patient cohort.

Safety Aspects of Perinatal Ultrasound

Ultrasound safety is of particular importance in fetal and neonatal scanning. Fetal tissues are vulnerable and often still developing, the scanning depth may be low, and potential biological effects have been insufficiently investigated. On the other hand, the clinical benefit may be considerable. The perinatal period is probably less vulnerable than the first and second trimesters of pregnancy, and ultrasound is often a safer alternative to other diagnostic imaging modalities. Here we present step-by-step procedures for obtaining clinically relevant images while maintaining ultrasound safety. We briefly discuss the current status of the field of ultrasound safety, with special attention to the safety of novel modalities, safety considerations when ultrasound is employed for research and education, and ultrasound of particularly vulnerable tissues, such as the neonatal lung. This CME is prepared by ECMUS, the safety committee of EFSUMB, with contributions from OB/GYN clinicians with a special interest in ultrasound safety.

Lung ultrasound features and relationships with respiratory mechanics of evolving BPD in preterm rabbits and human neonates

Evolving broncho-pulmonary dysplasia (BPD) is a regionally heterogeneous disorder characterized by impaired alveolarization leading to lung aeration inhomogeneities. Hyperoxia-exposed preterm rabbits have been proposed to mimic evolving BPD and we aim to verify if this model has the same lung ultrasound and mechanical features of evolving BPD in human neonates. Twenty-five preterm rabbits and twenty-five neonates with evolving BPD were enrolled and subjected to semi-quantitative lung ultrasound and lung mechanics measurement. A modified rabbit lung ultrasound score (rLUS), the previously validated neonatal lung ultrasound score (LUS) and classical mechanics measurements were obtained. Lung ultrasound images were also recorded and evaluated by two independent observers with different expertise blinded to each other's evaluation. Lung ultrasound findings were equally heterogeneous both in rabbits as in human neonates: images were very similar and encompassed all the classical lung ultrasound semiology. The inter-rater absolute agreement for the evaluation of lung ultrasound images in rabbits was very high (ICC: 0.989 (95%CI: 0.975-0.995); p<0.0001) and there was no difference between the two observers. Lung mechanics parameters were similarly altered both in rabbits and human neonates. There were significant correlations between airway resistances and lung ultrasound scores both in rabbits (r=0.519; p=0.008) and in neonates (r=0.409; p=0.042). No significant correlation between rLUS, LUS and any other mechanics parameter. Lung ultrasound was easy to be performed and accurate even in these small animals and with a short training. In conclusion, the preterm rabbit model fairly reproduces the lung ultrasound and mechanical characteristics of preterm neonates with evolving BPD.