Noninvasive detection of pulmonary pathological accumulation with CT-guided electrical impedance tomography: a...

Objective.The objective of this study was to assess the feasibility and accuracy of computed tomography (CT)-guided electrical impedance tomography (CT-guided EIT) in the quantitative detection of the spatial distribution and location of pneumothorax, hemothorax, and hemopneumothorax lesions and effective ventilation regions in pig models.Approach. Five Bama miniature pigs were used to establish models of pneumothorax, hemothorax, and hemopneumothorax by incrementally injecting air or Ringer's solution in 100 ml steps up to a total volume of 500 ml into the right pleural cavity. Synchronous EIT data and CT images were acquired at each experimental stage. EIT images were reconstructed using the GREIT algorithm with anatomical constraints derived from CT-based lung contours. Mean total boundary voltage (mTBV), pneumothorax pixel area (PPA), hemothorax pixel area (HPA), center of ventilation (CoV), Dice similarity coefficient (Dice), and centroid distance (d_c) were used for quantitative assessment. PPA, HPA, and CoV are statistically compared between EIT and CT using Spearman correlation and Bland-Altman agreement analysis.Main results.mTBV showed a strong linear correlation with injected air volume (R²= 0.968-0.994) and fluid volume (R²= 0.712-0.994). In pneumothorax models, Dice = 0.828-0.884 andd_c= 2.80-3.33. In hemothorax models, Dice = 0.850-0.874 andd_c= 2.64-3.34. PPA, HPA, and CoV derived from CT-guided EIT images correlated significantly with CT findings (Spearmanr= 0.63-0.92,p< 0.001). Ventilation distribution patterns in EIT were consistent with CT, with dorsal shifts during pneumothorax and ventral shifts during hemothorax. Bland-Altman plots showed good agreement between EIT and CT measurements.Significance.This study demonstrates the feasibility of CT-guided EIT for dynamic monitoring and quantitative evaluation of pneumothorax, hemothorax, and hemopneumothorax in pig models. Its noninvasive, radiation-free, and bedside monitoring nature makes it a promising tool for detecting pulmonary pathological accumulation during mechanical ventilation and postoperative care.