Lung ultrasound detects regional aeration inhomogeneity in ventilated preterm lambs

Abstract

Abstract 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 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-LUSMGV). Regional inhomogeneity was calculated by observed over predicted aeration ratio from the EIT reconstructive model. LUS scores and Q-LUSMGV were compared with EIT aeration ratios using one-way ANOVA. 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-LUSMGV yielded similar results. All LUS findings corresponded with EIT regional differences. Conclusion LUS may have potential in measuring regional aeration, which should be further explored in human studies. Impact 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-LUSMGV) detects regional lung aeration differences when compared to EIT. This suggests LUS reliably detects aeration inhomogeneity warranting further investigation in human trials.