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. 2023 May;93(6):1591-1598.
doi: 10.1038/s41390-022-02316-0. Epub 2022 Sep 27.

Quantitative lung ultrasound detects dynamic changes in lung recruitment in the preterm lamb

Arun Sett  1   2   3   4   5 , Gillian W C Foo  6 , Kelly R Kenna  7 , Rebecca J Sutton  7   8 , Elizabeth J Perkins  7 , Magdy Sourial  8 , Sheryle R Rogerson  6   9   10 , Brett J Manley  7   6   9 , Peter G Davis  7   6   9 , Prue M Pereira-Fantini  7   6   11 , David G Tingay  7   6   11   12
Affiliations

Quantitative lung ultrasound detects dynamic changes in lung recruitment in the preterm lamb

Arun Sett et al. Pediatr Res. 2023 May.

Abstract

Background: Lung ultrasound (LUS) may not detect small, dynamic changes in lung volume. Mean greyscale measurement using computer-assisted image analysis (Q-LUSMGV) may improve the precision of these measurements.

Methods: Preterm lambs (n = 40) underwent LUS of the dependent or non-dependent lung during static pressure-volume curve mapping. Total and regional lung volumes were determined using the super-syringe technique and electrical impedance tomography. Q-LUSMGV and gold standard measurements of lung volume were compared in 520 images.

Results: Dependent Q-LUSMGV moderately correlated with total lung volume (rho = 0.60, 95% CI 0.51-0.67) and fairly with right whole (rho = 0.39, 0.27-0.49), central (rho = 0.38, 0.27-0.48), ventral (rho = 0.41, 0.31-0.51) and dorsal regional lung volumes (rho = 0.32, 0.21-0.43). Non-dependent Q-LUSMGV moderately correlated with total lung volume (rho = 0.57, 0.48-0.65) and fairly with right whole (rho = 0.43, 0.32-0.52), central (rho = 0.46, 0.35-0.55), ventral (rho = 0.36, 0.25-0.47) and dorsal lung volumes (rho = 0.36, 0.25-0.47). All correlation coefficients were statistically significant. Distinct inflation and deflation limbs, and sonographic pulmonary hysteresis occurred in 95% of lambs. The greatest changes in Q-LUSMGV occurred at the opening and closing pressures.

Conclusion: Q-LUSMGV detected changes in total and regional lung volume and offers objective quantification of LUS images, and may improve bedside discrimination of real-time changes in lung volume.

Impact: Lung ultrasound (LUS) offers continuous, radiation-free imaging that may play a role in assessing lung recruitment but may not detect small changes in lung volume. Mean greyscale image analysis using computer-assisted quantitative LUS (Q-LUSMGV) moderately correlated with changes in total and regional lung volume. Q-LUSMGV identified opening and closing pressure and pulmonary hysteresis in 95% of lambs. Computer-assisted image analysis may enhance LUS estimation of lung recruitment at the bedside. Future research should focus on improving precision prior to clinical translation.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. ROI (red tracing) for measurement of Q-LUSMGV.
The ROI was delineated by (1) superior margin defined by the pleural surface; (2) lateral margin defined by the rib shadows; and (3) inferior margin defined by a depth of 50 pixels corresponding to one millimetre in depth. Q-LUSMGV; quantitative lung ultrasound mean grey value.
Fig. 2
Fig. 2. Dependent lung imaging.
A Static PV curve derived from the super-syringe method (squares, grey dashed line) and ∆Q-LUSMGV (circles, solid black line). All data are represented as median (IQR). ∆Q-LUSMGV is normalised to baseline. Open shapes represent the inflation limb and closed shapes the deflation limb. B Correlation between ∆Q-LUSMGV and total lung volume. AU arbitrary units, CI confidence interval, cm H2O centimetres of water, ml/kg, rho Spearman’s correlation coefficient, Q-LUSMGV quantitative lung ultrasound mean grey value. Left axis: lung volume (ml/kg). Right axis: ∆Q-LUSMGV.
Fig. 3
Fig. 3. Non-dependent lung imaging.
A Static PV curve derived from the super-syringe method (squares, grey dashed line) and ∆Q-LUSMGV (circles, solid black line). All data are represented as median (IQR). ∆Q-LUSMGV normalised to baseline. Open shapes represent the inflation limb and closed shapes the deflation limb.  B Correlation between ∆Q-LUSMGV and total lung volume. AU arbitrary units, CI confidence interval, cm H2O centimetres of water, ml/kg, rho Spearman’s correlation co-efficient, Q-LUSMGV quantitative lung ultrasound mean grey value. Left axis: lung volume (ml/kg). Right axis: ∆Q-LUSMGV.
Fig. 4
Fig. 4. Dependent lung.
A–D Static regional PV curves from EIT (squares, grey dashed line) of the whole right lung (A), ventral (B), central (C) and dorsal (D) regions and Q-LUSMGV from dependent lung imaging (circles, black solid line). All data median (IQR). ∆Q-LUSMGV normalised to baseline. Open shapes represent the inflation limb and closed shapes the deflation limb. E–H Correlation between ∆Q-LUSMGV and regional lung volume for the corresponding lung regions in panels A–D. AU arbitrary units, CI confidence interval, cm H2O centimetres of water, EELV end-expiratory lung volume, rho Spearman’s correlation co-efficient, Q-LUSMGV quantitative lung ultrasound mean grey value. Left axis: lung volume (ml/kg). Right axis: ∆Q-LUSMGV.
Fig. 5
Fig. 5. Non-dependent lung.
A–D Static regional PV curves from EIT (squares, grey dashed line) of the whole right lung (A), ventral (B), central (C) and dorsal (D) regions and ∆Q-LUSMGV from non-dependent lung imaging (circles, black solid line). All data median (IQR). ∆Q-LUSMGV normalised to baseline. Open shapes represent the inflation limb and closed shapes the deflation limb. E–H Correlation between ∆Q-LUSMGV and regional lung volume for the corresponding lung regions in panels A–D. AU arbitrary units, CI confidence interval, cm H2O centimetres of water, EELV end-expiratory lung volume, rho Spearman’s correlation co-efficient, Q-LUSMGV quantitative lung ultrasound mean grey value. Left axis: lung volume (ml/kg). Right axis: ∆Q-LUSMGV.
See this image and copyright information in PMC

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