The ACE1 thoracic Electrical Impedance Tomography system for ventilation and perfusion

Evaluation of Pulmonary Structure and Function in Patients with Cystic Fibrosis from Electrical Impedance Tomography Data

Electrical impedance tomography (EIT) is a medical imaging technique in which low frequency, low amplitude electromagnetic fields applied through electrodes on the skin are used to compute the conductivity and/or permittivity inside the body and form functional images from the reconstructed values. This work describes methods of computing EIT-derived surrogate measures of pulmonary function and identifying regions of air trapping and consolidation from functional EIT images. These methods were developed for pediatric patients with cystic fibrosis, for whom a real-time non-ionizing imaging modality can be of great benefit for monitoring disease progression or a pulmonary exacerbation.

Calderón's Method with a Spatial Prior for 2-D EIT Imaging of Ventilation and Perfusion

Bedside imaging of ventilation and perfusion is a leading application of 2-D medical electrical impedance tomography (EIT), in which dynamic cross-sectional images of the torso are created by numerically solving the inverse problem of computing the conductivity from voltage measurements arising on electrodes due to currents applied on electrodes on the surface. Methods of reconstruction may be direct or iterative. Calderón’s method is a direct reconstruction method based on complex geometrical optics solutions to Laplace’s equation capable of providing real-time reconstructions in a region of interest. In this paper, the importance of accurate modeling of the electrode location on the body is demonstrated on simulated and experimental data, and a method of including a priori spatial information in dynamic human subject data is presented. The results of accurate electrode modeling and a spatial prior are shown to improve detection of inhomogeneities not included in the prior and to improve the resolution of ventilation and perfusion images in a human subject.

Robust computation in 2D absolute EIT (a-EIT) using D-bar methods with the 'exp' approximation

OBJECTIVE

Absolute images have important applications in medical electrical impedance tomography (EIT) imaging, but the traditional minimization and statistical based computations are very sensitive to modeling errors and noise. In this paper, it is demonstrated that D-bar reconstruction methods for absolute EIT are robust to such errors.

APPROACH

The effects of errors in domain shape and electrode placement on absolute images computed with 2D D-bar reconstruction algorithms are studied on experimental data.

MAIN RESULTS

It is demonstrated with tank data from several EIT systems that these methods are quite robust to such modeling errors, and furthermore the artefacts arising from such modeling errors are similar to those occurring in classic time-difference EIT imaging.

SIGNIFICANCE

This study is promising for clinical applications where absolute EIT images are desirable but previously thought impossible.

Estimating regions of air trapping from electrical impedance tomography data

OBJECTIVE

Electrical impedance tomography (EIT) has been shown to be a viable non-invasive, bedside imaging modality to monitor lung function. This paper introduces a method for identifying regions of air trapping from EIT data collected during tidal breathing and breath-holding maneuvers.

APPROACH

Ventilation-perfusion index maps are computed from dynamic EIT images. These maps are then used to identify regions of air trapping in the area of the lung as regions that are poorly ventilated but well perfused throughout the breathing and cardiac cycles. These EIT-identified regions are then compared with independently identified regions of low attenuation, or air trapping, on chest CT. Results of this method are demonstrated in two children with cystic fibrosis and on a healthy control subject.

MAIN RESULTS

In both CF children, the EIT-identified regions of air trapping matched the regions indicated from the chest CT. The EIT-based method is only validated with CT scans within 4 cm of the chest cross-section defined by the electrode plane.

SIGNIFICANCE

The results indicate the potential use of EIT-derived ventilation-perfusion index maps as a non-invasive method for identifying regions of air trapping.

Evaluation of surrogate measures of pulmonary function derived from electrical impedance tomography data in children with cystic fibrosis

OBJECTIVE

Lung function monitoring by spirometry plays a critical role in the clinical care of pediatric cystic fibrosis (CF) patients, but many young children are unable to perform spirometry, and the outputs are often normal even in the presence of lung disease. Measures derived from electrical impedance tomography (EIT) images were studied for their utility as potential surrogates for spirometry in CF patients and to assess response to intravenous antibiotic treatment for acute pulmonary exacerbations (PEx) in a subset of patients.

APPROACH

EIT data were collected on 35 subjects (21 with CF, 14 healthy controls, 8 CF patients pre- and post-treatment for an acute PEx) ages 2 to 20 years during tidal breathing and also concurrently with spirometry on subjects over age 8. EIT-derived measures of FEV1, FVC, and FEV1/FVC were computed globally and regionally from dynamic EIT images.

MAIN RESULTS

Global EIT-derived FEV1/FVC showed good correlation with spirometry FEV1/FVC values (r  =  0.54, p  =  0.01), and were able to distinguish between the groups (p  =  0.01). Lung heterogeneity was assessed through the spatial coefficient of variation (CV) of EIT difference images between key time points, and the CVs for EIT-derived FEV1 and FVC showed significant correlation with the CV for tidal breathing (r  =  0.47, p  =  0.01 and r  =  0.50, p  =  0.01, respectively). Global EIT-derived FEV1/FVC was better able to distinguish between groups than spirometry FEV1 (F-values 776.5 and 146.3, respectively, p  <  0.01.) The same held true for the CVs for EIT-derived FEV1, FVC, and tidal breathing (F-values 215.93, 193.89, 204.57, respectively, p  <  0.01).

SIGNIFICANCE

The strong correlation between the CVs for tidal breathing, FEV1, and FVC, and the statistically significant ability of CV for tidal breathing to distinguish between healthy subjects and CF patients, and between the studied CF disease states suggests that the CV may be useful for measuring the extent and severity of structural lung disease.

Real-Time Implementation of Calderón's Method on Subject-Specific Domains

A real-time implementation of Calderón's method for the reconstruction of a 2-D conductivity from electrical impedance tomography data is presented, in which domain-specific modeling is taken into account. This is the first implementation of Calderón's method that accounts for correct modeling of non-symmetric domain boundaries in image reconstruction. The domain-specific Calderón's method is derived and reconstructions from experimental tank data are presented, quantifying the distortion when correct modeling is not included in the reconstruction algorithm. Reconstructions from human subject volunteers are presented, demonstrating the method's effectiveness for imaging changes due to ventilation and perfusion in the human thorax.