title: Data-driven classification of ventilated lung tissues using electrical impedance tomography.
abstract: Current methods for identifying ventilated lung regions utilizing electrical impedance tomography images rely on dividing the image into arbitrary regions of interest (ROI), manually delineating ROI, or forming ROI with pixels whose signal properties surpass an arbitrary threshold. In this paper, we propose a novel application of a data-driven classification method to identify ventilated lung ROI based on forming k clusters from pixels with correlated signals. A standard first-order model for lung mechanics is then applied to determine which ROI correspond to ventilated lung tissue. We applied the method in an experimental study of 16 mechanically ventilated swine in the supine position, which underwent changes in positive end-expiratory pressure (PEEP) and fraction of inspired oxygen (F(I)O(2)). In each stage of the experimental protocol, the method performed best with k = 4 and consistently identified 3 lung tissue ROI and 1 boundary tissue ROI in 15 of the 16 subjects. When testing for changes from baseline in lung position, tidal volume, and respiratory system compliance, we found that PEEP displaced the ventilated lung region dorsally by 2 cm, decreased tidal volume by 1.3%, and increased the respiratory system compliance time constant by 0.3 s. F(I)O(2) decreased tidal volume by 0.7%. All effects were tested at p < 0.05 with n = 16. These findings suggest that the proposed ROI detection method is robust and sensitive to ventilation dynamics in the experimental setting.
authors.affiliation: Department of Anesthesiology, Perioperative and Pain Medicine, Children's Hospital Boston, Harvard Medical School, Boston, MA 02115, USA. Camille.Gomez@childrens.harvard.edu
authors.forename: Camille
authors.initials: C
authors.lastname: Gómez-Laberge
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Hogan
authors.forename: Gunnar
authors.initials: G
authors.lastname: Elke
authors.forename: Norbert
authors.initials: N
authors.lastname: Weiler
authors.forename: Inéz
authors.initials: I
authors.lastname: Frerichs
authors.forename: Andy
authors.initials: A
authors.lastname: Adler
mesh_terms: D000818:Animals; D004553:Electric Conductivity; D017097:Electric Impedance; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000166:cytology* / Q000502:physiology*; D008170:Lung Compliance; D012123:Pulmonary Ventilation; D012119:Respiration; D013552:Swine; D013990:Tidal Volume; D014054:Tomography / Q000379:methods*