Functional Regions of Interest in Electrical Impedance Tomography: A Secondary Analysis of Two Clinical Studies

Abstract

IntroductionPatients with acute respiratory distress syndrome (ARDS) typically show a high degree of ventilation inhomogeneity, which is associated with morbidity and unfavorable outcomes. Electrical impedance tomography (EIT) is able to detect ventilation inhomogeneity, but it is unclear which method for defining the region of interest (ROI) should be used for this purpose. The aim of our study was to compare the functional region of interest (fROI) method to both the lung area estimation method (LAEM) and no ROI when analysing global parameters of ventilation inhomogeneity. We assumed that a good method for ROI determination would lead to a high discriminatory power for ventilation inhomogeneity, as defined by the area under the receiver operating characteristics curve (AUC), comparing patients suffering from ARDS and control patients without pulmonary pathologies.MethodsWe retrospectively analysed EIT data from 24 ARDS patients and 12 control patients without pulmonary pathology. In all patients, a standardized low-flow-pressure volume maneuver had been performed and was used for EIT image generation. We compared the AUC for global inhomogeneity (GI) index and coefficient of variation (CV) between ARDS and control patients using all EIT image pixels, the fROI method and the LAEM for ROI determination.ResultsWhen analysing all EIT image pixels, we found an acceptable AUC both for the GI index (AUC = 0.76; 95% confidence interval (CI) 0.58–0.94) and the CV (AUC = 0.74; 95% CI 0.55–0.92). With the fROI method, we found a deteriorating AUC with increasing threshold criteria. With the LAEM, we found the best AUC both for the GI index (AUC = 0.89; 95% CI 0.78–1.0) and the CV (AUC = 0.89; 95% CI 0.78–1.0) using a threshold criterion of 50% of the maximum tidal impedance change.ConclusionIn the assessment of ventilation inhomogeneity with EIT, functional regions of interest obscure the difference between patients with ARDS and control patients without pulmonary pathologies. The LAEM is preferable to the fROI method when assessing ventilation inhomogeneity.

Characterization of blunt chest trauma in a long-term porcine model of severe multiple trauma

“…Its application during the resuscitation phase respectively the initial operation period and during following intensive care treatment may improve outcome by real-time diagnosis and prompt adaptation of treatment, e.g. by avoiding abnormal distension of primarily unaffected lung sections6566. As a growing number of clinical studies implies establishment of EIT under diverse medical conditions67, we are certain that this method, once provided in the trauma setting, will help to detect time-displaced lung dysfunction also in trauma patients that suffer from consequences of indirect damage to the lung caused by remote injuries, and multiple organ failure or sepsis.…”

Chest electrical impedance tomography examination, data analysis, terminology, clinical use and recommendations: consensus statement of the TRanslational EIT developmeNt stuDy group

“…One subgroup describes the overall degree of spatial heterogeneity of ventilation. Examples are the global inhomogeneity index36 40 49 or the coefficient of variation,36 42 50 calculated from the maps of tidal impedance variation. Another subgroup describes the orientation of the spatial distribution of functional measures, usually in the anteroposterior direction.…”

Effects of individualized electrical impedance tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4-dimensional computed tomography in a porcine model

“…Determining the lung regions from static volume CT during inspiratory hold did not capture the movement in thoracic shape, lung and heart regions caused by tidal ventilation. Here, a combination of the presented method with other evaluation methods to assess moving lung borders or functional ROI methods [ 35 ] might be a valuable extension to our analysis. Other potential sources of errors are the choice of tissue property weighting (e.g., for lungs and heart) [ 36 ] and the exclusion of bones and other tissue properies in the FEMs, but a complete evaluation was beyond the scope of this work.…”