Lung ultrasound detects regional aeration inhomogeneity in ventilated preterm lambs.


Journal

Pediatric research
ISSN: 1530-0447
Titre abrégé: Pediatr Res
Pays: United States
ID NLM: 0100714

Informations de publication

Date de publication:
17 Aug 2023
Historique:
received: 11 04 2023
accepted: 29 07 2023
revised: 04 07 2023
medline: 18 8 2023
pubmed: 18 8 2023
entrez: 17 8 2023
Statut: aheadofprint

Résumé

Inhomogeneous lung aeration is a significant contributor to preterm lung injury. EIT detects inhomogeneous aeration in the research setting. Whether LUS detects inhomogeneous aeration is unknown. The aim was to determine whether LUS detects regional inhomogeneity identified by EIT in preterm lambs. LUS and EIT were simultaneously performed on mechanically ventilated preterm lambs. LUS images from non-dependent and dependent regions were acquired and reported using a validated scoring system and computer-assisted quantitative LUS greyscale analysis (Q-LUS LUS was performed in 32 lambs (~125d gestation, 128 images). LUS scores were greater in upper anterior (non-dependent) compared to lower lateral (dependent) regions of the left (3.4 vs 2.9, p = 0.1) and right (3.4 vs 2.7, p < 0.0087). The left and right upper regions also had greater LUS scores compared to right lower (3.4 vs 2.7, p < 0.0087) and left lower (3.7 vs 2.9, p = 0.1). Q-LUS LUS may have potential in measuring regional aeration, which should be further explored in human studies. Inhomogeneous lung aeration is an important contributor to preterm lung injury, however, tools detecting inhomogeneous aeration at the bedside are limited. Currently, the only tool clinically available to detect this is electrical impedance tomography (EIT), however, its use is largely limited to research. Lung ultrasound (LUS) may play a role in monitoring lung aeration in preterm infants, however, whether it detects inhomogeneous lung aeration is unknown. Visual LUS scores and mean greyscale image analysis using computer assisted quantitative LUS (Q-LUS

Sections du résumé

BACKGROUND BACKGROUND
Inhomogeneous lung aeration is a significant contributor to preterm lung injury. EIT detects inhomogeneous aeration in the research setting. Whether LUS detects inhomogeneous aeration is unknown. The aim was to determine whether LUS detects regional inhomogeneity identified by EIT in preterm lambs.
METHODS METHODS
LUS and EIT were simultaneously performed on mechanically ventilated preterm lambs. LUS images from non-dependent and dependent regions were acquired and reported using a validated scoring system and computer-assisted quantitative LUS greyscale analysis (Q-LUS
RESULTS RESULTS
LUS was performed in 32 lambs (~125d gestation, 128 images). LUS scores were greater in upper anterior (non-dependent) compared to lower lateral (dependent) regions of the left (3.4 vs 2.9, p = 0.1) and right (3.4 vs 2.7, p < 0.0087). The left and right upper regions also had greater LUS scores compared to right lower (3.4 vs 2.7, p < 0.0087) and left lower (3.7 vs 2.9, p = 0.1). Q-LUS
CONCLUSION CONCLUSIONS
LUS may have potential in measuring regional aeration, which should be further explored in human studies.
IMPACT CONCLUSIONS
Inhomogeneous lung aeration is an important contributor to preterm lung injury, however, tools detecting inhomogeneous aeration at the bedside are limited. Currently, the only tool clinically available to detect this is electrical impedance tomography (EIT), however, its use is largely limited to research. Lung ultrasound (LUS) may play a role in monitoring lung aeration in preterm infants, however, whether it detects inhomogeneous lung aeration is unknown. Visual LUS scores and mean greyscale image analysis using computer assisted quantitative LUS (Q-LUS

Identifiants

pubmed: 37591926
doi: 10.1038/s41390-023-02781-1
pii: 10.1038/s41390-023-02781-1
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023. The Author(s).

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Auteurs

Laura L H He (LLH)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia. laurah2@student.unimelb.edu.au.
Department of Paediatrics, University of Melbourne, Victoria, VIC, Australia. laurah2@student.unimelb.edu.au.

Gillian Foo (G)

Joan Kirner Women's and Children's Hospital, Western Health, Victoria, VIC, Australia.

Kelly R Kenna (KR)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.

Ellen Douglas (E)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.

Monique Fatmous (M)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.

Rebecca J Sutton (RJ)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.
Translational Research Unit, Murdoch Children's Research Institute, Victoria, VIC, Australia.

Elizabeth J Perkins (EJ)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.

Magdy Sourial (M)

Translational Research Unit, Murdoch Children's Research Institute, Victoria, VIC, Australia.

Prue M Pereira-Fantini (PM)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.
Department of Paediatrics, University of Melbourne, Victoria, VIC, Australia.

David G Tingay (DG)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.
Department of Paediatrics, University of Melbourne, Victoria, VIC, Australia.

Arun Sett (A)

Neonatal Research, Murdoch Children's Research Institute, Victoria, VIC, Australia.
Department of Paediatrics, University of Melbourne, Victoria, VIC, Australia.
Joan Kirner Women's and Children's Hospital, Western Health, Victoria, VIC, Australia.
Newborn Research Centre, The Royal Women's Hospital, Victoria, VIC, Australia.
Department of Obstetrics and Gynaecology, The University of Melbourne, Victoria, VIC, Australia.

Classifications MeSH