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Published in: Journal of Clinical Monitoring and Computing 1/2019

01-02-2019 | Original Research

Quantitative computed tomography in comparison with transpulmonary thermodilution for the estimation of pulmonary fluid status: a clinical study in critically ill patients

Authors: Bernd Saugel, Moritz Wildgruber, Albrecht Staudt, Michael Dieckmeyer, Konstantin Holzapfel, Georgios Kaissis, Mikhail Y. Kirov, Vsevolod V. Kuzkov, Roland M. Schmid, Wolfgang Huber

Published in: Journal of Clinical Monitoring and Computing | Issue 1/2019

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Abstract

Extravascular lung water (index) (EVLW(I)) can be estimated using transpulmonary thermodilution (TPTD). Computed tomography (CT) with quantitative analysis of lung tissue density has been proposed to quantify pulmonary edema. We compared variables of pulmonary fluid status assessed using quantitative CT and TPTD in critically ill patients. In 21 intensive care unit patients, we performed TPTD measurements directly before and after chest CT. Based on the density data of segmented CT images we calculated the tissue volume (TV), tissue volume index (TVI), and the mean weighted index of voxel aqueous density (VMWaq). CT-derived TV, TVI, and VMWaq did not predict TPTD-derived EVLWI values ≥ 14 mL/kg. There was a significant moderate positive correlation between VMWaq and mean EVLWI (EVLWI before and after CT) (r = 0.45, p = 0.042) and EVLWI after CT (r = 0.49, p = 0.025) but not EVLWI before CT (r = 0.38, p = 0.086). There was no significant correlation between TV and EVLW before CT, EVLW after CT, or mean EVLW. There was no significant correlation between TVI and EVLWI before CT, EVLWI after CT, or mean EVLWI. CT-derived variables did not predict elevated TPTD-derived EVLWI values. In unselected critically ill patients, variables of pulmonary fluid status assessed using quantitative CT cannot be used to predict EVLWI.
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Metadata
Title
Quantitative computed tomography in comparison with transpulmonary thermodilution for the estimation of pulmonary fluid status: a clinical study in critically ill patients
Authors
Bernd Saugel
Moritz Wildgruber
Albrecht Staudt
Michael Dieckmeyer
Konstantin Holzapfel
Georgios Kaissis
Mikhail Y. Kirov
Vsevolod V. Kuzkov
Roland M. Schmid
Wolfgang Huber
Publication date
01-02-2019
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 1/2019
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-018-0144-1

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