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Updated: May 3, 2026
Quantitative Mapping of Specific Ventilation in the Human Lung using Proton Magnetic Resonance Imaging and Oxygen as a Contrast Agent
Published on: June 5, 2019
Enhancing tidal volume estimation from electrical impedance tomography (EIT) by applying human anthropometric
Amelie Zitzmann1, Anna Strübing2,3, Daniel A Reuter2
1Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medical Centre Rostock, Schillingallee 35, 18057, Rostock, Germany. amelie.zitzmann@med.uni-rostock.de.
Electrical impedance tomography (EIT) can monitor ventilation, but tidal volume (VT) quantification is challenging. This study found that while individual correlations between impedance changes and VT are strong, group analysis requires considering factors like PEEP, gender, weight, and height for accurate ventilation monitoring.
Area of Science:
- Medical imaging
- Physiology
- Anesthesiology
Background:
- Electrical impedance tomography (EIT) is a functional imaging technique for monitoring regional ventilation.
- Quantifying clinical ventilation parameters like tidal volume (VT) using EIT has been limited due to its measurement of relative impedance changes.
Purpose of the Study:
- To evaluate the relationship between impedance changes (dZ) and VT in humans.
- To identify factors influencing this relationship for improved EIT-based ventilation quantification.
Main Methods:
- 27 patients undergoing general anesthesia were monitored using a commercial EIT belt.
- Measurements were taken at varying tidal volumes (6-12 mL/BW) and positive end-expiratory pressure (PEEP) levels (0-15 cmH2O).
- Linear regression analyzed normalized dZ against VT per ideal bodyweight (VT_IBW), with PEEP, gender, age, height, and weight as potential covariates.
Main Results:
- Individual patient analysis showed strong correlations between VT_IBW and normalized dZ (mean R²=0.890).
- Group analysis revealed weaker correlations (R²=0.485), improved by including covariates (adjusted R²=0.767).
- VT_IBW, weight, height, and PEEP significantly influenced normalized dZ; age did not.
Conclusions:
- Normalized dZ strongly correlates with VT_IBW in individual ventilated humans.
- PEEP, gender, weight, and height are significant influencing factors for group analysis.
- These findings enhance the potential for accurate VT quantification using EIT in clinical settings.
