A unified approach for EIT imaging of regional overdistension and atelectasis in acute lung injury

IEEE Trans Med Imaging. 2012 Mar;31(3):834-42. doi: 10.1109/TMI.2012.2183641. Epub 2012 Jan 10.

Abstract

Patients with acute lung injury or acute respiratory distress syndrome (ALI/ARDS) are vulnerable to ventilator-induced lung injury. Although this syndrome affects the lung heterogeneously, mechanical ventilation is not guided by regional indicators of potential lung injury. We used electrical impedance tomography (EIT) to estimate the extent of regional lung overdistension and atelectasis during mechanical ventilation. Techniques for tidal breath detection, lung identification, and regional compliance estimation were combined with the Graz consensus on EIT lung imaging (GREIT) algorithm. Nine ALI/ARDS patients were monitored during stepwise increases and decreases in airway pressure. Our method detected individual breaths with 96.0% sensitivity and 97.6% specificity. The duration and volume of tidal breaths erred on average by 0.2 s and 5%, respectively. Respiratory system compliance from EIT and ventilator measurements had a correlation coefficient of 0.80. Stepwise increases in pressure could reverse atelectasis in 17% of the lung. At the highest pressures, 73% of the lung became overdistended. During stepwise decreases in pressure, previously-atelectatic regions remained open at sub-baseline pressures. We recommend that the proposed approach be used in collaborative research of EIT-guided ventilation strategies for ALI/ARDS.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Electric Impedance*
  • Humans
  • Lung / physiopathology*
  • Positive-Pressure Respiration
  • Pulmonary Atelectasis / diagnosis
  • Pulmonary Atelectasis / pathology*
  • Respiratory Distress Syndrome / pathology
  • Sensitivity and Specificity
  • Tomography / methods*
  • Ventilator-Induced Lung Injury / diagnosis
  • Ventilator-Induced Lung Injury / pathology*
  • Ventilator-Induced Lung Injury / prevention & control

Grants and funding

This work was supported by the Center for Integration of Medicine and Innovative Technology, and the Translational Research Program at Children’s Hospital Boston.