BioMedical Engineering OnLine (Jul 2019)

Integrated EIT system for functional lung ventilation imaging

  • Geuk Young Jang,
  • Ghazal Ayoub,
  • Young Eun Kim,
  • Tong In Oh,
  • Chi Ryang Chung,
  • Gee Young Suh,
  • Eung Je Woo

DOI
https://doi.org/10.1186/s12938-019-0701-y
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 18

Abstract

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Abstract Background Electrical impedance tomography (EIT) has been used for functional lung imaging of regional air distributions during mechanical ventilation in intensive care units (ICU). From numerous clinical and animal studies focusing on specific lung functions, a consensus about how to use the EIT technique has been formed lately. We present an integrated EIT system implementing the functions proposed in the consensus. The integrated EIT system could improve the usefulness when monitoring of mechanical ventilation for lung protection so that it could facilitate the clinical acceptance of this new technique. Methods Using a custom-designed 16-channel EIT system with 50 frames/s temporal resolution, the integrated EIT system software was developed to implement five functional images and six EIT measures that can be observed in real-time screen view and analysis screen view mode, respectively. We evaluated the performance of the integrated EIT system with ten mechanically ventilated porcine subjects in normal and disease models. Results Quantitative and simultaneous imaging of tidal volume (TV), end-expiratory lung volume change ($$\triangle$$ ▵ EELV), compliance, ventilation delay, and overdistension/collapse images were performed. Clinically useful parameters were successfully extracted including anterior/posterior ventilation ratio (A/P ratio), center of ventilation ($${\mathrm{CoV}}_{{x}}$$ CoVx , $${\mathrm{CoV}}_{{y}}$$ CoVy ), global inhomogeneity (GI), coefficient of variation (CV), ventilation delay and percentile of overdistension/collapse. The integrated EIT system was demonstrated to suggest an optimal positive end-expiratory pressure (PEEP) for lung protective ventilation in normal and in the disease model of an acute injury. Optimal PEEP for normal and disease model was 2.3 and $$7.9 \, {\mathrm{cmH}}_{2}\mathrm{O}$$ 7.9cmH2O , respectively. Conclusions The proposed integrated approach for functional lung ventilation imaging could facilitate clinical acceptance of the bedside EIT imaging method in ICU. Future clinical studies of applying the proposed methods to human subjects are needed to show the clinical significance of the method for lung protective mechanical ventilation and mechanical ventilator weaning in ICU.

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