Assessment of lung density in pediatric patients using three-dimensional ultrashort echo-time and four-dimensional zero echo-time sequences

Author:

Zeimpekis Konstantinos G.ORCID,Kellenberger Christian J.,Geiger Julia

Abstract

Abstract Purpose Lung magnetic resonance imaging (MRI) using conventional sequences is limited due to strong signal loss by susceptibility effects of aerated lung. Our aim is to assess lung signal intensity in children on ultrashort echo-time (UTE) and zero echo-time (ZTE) sequences. We hypothesize that lung signal intensity can be correlated to lung physical density. Materials and methods Lung MRI was performed in 17 children with morphologically normal lungs (median age: 4.7 years, range 15 days to 17 years). Both lungs were manually segmented in UTE and ZTE images and the average signal intensities were extracted. Lung-to-background signal ratios (LBR) were compared for both sequences and between both patient groups using non-parametric tests and correlation analysis. Anatomical region-of-interest (ROI) analysis was performed for the normal cohort for assessment of the anteroposterior lung gradient. Results There was no significant difference between LBR of normal lungs using UTE and ZTE (p < 0.05). Both sequences revealed a LBR age-dependency with a high negative correlation for UTE (Rs =  – 0.77; range 2.98–1.41) and ZTE (Rs =  – 0.82; range 2.66–1.38)). Signal-to-noise (SNR) and contrast-to-noise ratios (CNR) were age-dependent for both sequences. SNR was higher for children up to 2 years old with 3D UTE Cones while for the rest it was higher with 4D ZTE. CNR was similar for both sequences. Posterior lung areas exhibited higher signal intensity compared to anterior ones (UTE 9.4% and ZTE 12% higher), both with high correlation coefficients (R2UTE = 0.94, R2ZTE = 0.97). Conclusion The ZTE sequence can measure signal intensity similarly to UTE in pediatric patients. Both sequences reveal an age- and gravity-dependency of LBR.

Funder

University of Bern

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging

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