Author:
Vellvé Kilian,Garcia-Canadilla Patricia,Nogueira Mariana,Youssef Lina,Arranz Angela,Nakaki Ayako,Boada David,Blanco Isabel,Faner Rosa,Figueras Francesc,Agustí Àlvar,Gratacós Eduard,Crovetto Francesca,Bijnens Bart,Crispi Fàtima
Abstract
AbstractThe aim of this study was to investigate the pulmonary vasculature in baseline conditions and after maternal hyperoxygenation in growth restricted fetuses (FGR). A prospective cohort study of singleton pregnancies including 97 FGR and 111 normally grown fetuses was carried out. Ultrasound Doppler of the pulmonary vessels was obtained at 24–37 weeks of gestation and data were acquired before and after oxygen administration. After, Machine Learning (ML) and a computational model were used on the Doppler waveforms to classify individuals and estimate pulmonary vascular resistance (PVR). Our results showed lower mean velocity time integral (VTI) in the main pulmonary and intrapulmonary arteries in baseline conditions in FGR individuals. Delta changes of the main pulmonary artery VTI and intrapulmonary artery pulsatility index before and after hyperoxygenation were significantly greater in FGR when compared with controls. Also, ML identified two clusters: A (including 66% controls and 34% FGR) with similar Doppler traces over time and B (including 33% controls and 67% FGR) with changes after hyperoxygenation. The computational model estimated the ratio of PVR before and after maternal hyperoxygenation which was closer to 1 in cluster A (cluster A 0.98 ± 0.33 vs cluster B 0.78 ± 0.28, p = 0.0156). Doppler ultrasound allows the detection of significant changes in pulmonary vasculature in most FGR at baseline, and distinct responses to hyperoxygenation. Future studies are warranted to assess its potential applicability in the clinical management of FGR.
Funder
European Commission
'la Caixa' Foundation
Instituto de Salud Carlos III
Cerebra Foundation for the Brain Injured Children, Carmarthen, Wales, UK
Agència de Gestió d'Ajuts Universitaris i de Recerca
Ministerio de Educación y Ciencia, Spain
CIBER Enfermedades Raras, Spain
Publisher
Springer Science and Business Media LLC
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