Enhancing tidal volume estimation from electrical impedance tomography (EIT) by applying human anthropometric information.

Authors

Amelie Zitzmann, Anna Strübing, Daniel A Reuter, Andreas Waldmann, Stephan H Böhm, Fabian Müller-Graf

Published in

Journal of clinical monitoring and computing. Oct 15, 2025. Epub Oct 15, 2025.

Abstract

Electrical impedance tomography (EIT) is a functional imaging technique to monitor regional ventilation. However, the quantification of clinically used ventilation parameters like tidal volume (VT) has not been possible yet since EIT measures relative and not absolute changes in impedance. Thus, the study aimed to evaluate the relationship between impedance changes (dZ) and VT in humans and to identify influencing factors.
27 patients undergoing elective surgery under general anaesthesia were equipped with a commercially available EIT belt. Measurements were performed at four VTs (6, 8, 10 and 12 mL/BW) on each of four PEEP levels (0, 5, 10 and 15 cmH₂O). Linear regression analysis was performed for normalized dZ and VT per ideal bodyweight (VT_IBW). Additionally, PEEP, gender, age, height and weight were analysed as potential influencing factors.
Regression analysis for individual patients showed good correlations between VT_IBW and normalized dZ (mean R² 0.890 ± 0.15). However, for the group of patients, correlations were rather weak (R² 0.485). Including additional factors improved the model (adjusted R² 0.767), with VT_IBW having the biggest impact, followed by weight, height and PEEP; age did not contribute to it significantly. Higher VT_IBW, PEEP and height increased, while female gender and higher weight decreased normalized dZ.
Normalized dZ correlated strongly with VT_IBW in the individual ventilated humans but more weakly when analyzing the cohort. PEEP, gender, weight and height were identified as additional influencing factors.
This study was prospectively registered at the German Register of Clinical Studies (Deutsches Register Klinischer Studien; DRKS00027226) on 3rd December 2021.

PMID:
41091340
Bibliographic data and abstract were imported from PubMed on 15 Oct 2025.

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