Lobe based image reconstruction in Electrical Impedance Tomography

Improved resolution of D-bar images of ventilation using a Schur complement property and an anatomical atlas

BACKGROUND

Electrical impedance tomography (EIT) is a nonionizing imaging technique for real-time imaging of ventilation of patients with respiratory distress. Cross-sectional dynamic images are formed by reconstructing the conductivity distribution from measured voltage data arising from applied alternating currents on electrodes placed circumferentially around the chest. Since the conductivity of lung tissue depends on air content, blood flow, and the presence of pathology, the dynamic images provide regional information about ventilation, pulsatile perfusion, and abnormalities. However, due to the ill-posedness of the inverse conductivity problem, EIT images have a coarse spatial resolution. One method of improving the resolution is to include prior information in the reconstruction.

PURPOSE

In this work, we propose a technique in which a statistical prior built from an anatomical atlas is used to postprocess EIT reconstructions of human chest data. The effectiveness of the method is demonstrated on data from two patients with cystic fibrosis.

METHODS

A direct reconstruction algorithm known as the D-bar method was used to compute a two-dimensional reconstruction of the conductivity distribution in the plane of the electrodes. Reconstructions using one step in an iterative (regularized) Newton's method were also computed for comparison. An anatomical atlas consisting of 1589 synthetic EIT images computed from X-ray computed tomography (CT) scans of 74 adult male subjects was computed for use as a statistical prior. The resolution of the D-bar images was then improved by maximizing the conditional probability density function of an image that is consistent with the a priori information and the statistical model. A new method to evaluate the accuracy of the EIT images using CT scans of the imaged patient as ground truth is presented. The novel approach is tested on data from two patients with cystic fibrosis.

RESULTS AND CONCLUSIONS

The D-bar images resulted in better structural similarity index measures (SSIM) and multiscale (MS) SSIM measures for both subjects using the mask or amplitude evaluation approach than the one-step (regularized) Newton's method. Further improvement was achieved using the Schur complement (SC) approach, with MS-SSIM values of 0.718 and 0.682 using SC evaluated with the mask and amplitude approach, respectively, for Patient 1, and MS-SSIM values of 0.726 and 0.692 using SC evaluated with the mask and amplitude approach, respectively, for Patient 2. The results from applying an anatomical atlas and statistical prior to EIT data from two patients with cystic fibrosis suggest that the spatial resolution of the EIT image can be improved to reveal pathology that may be difficult to discern in the original EIT image. The novel metric of evaluation is consistent with the appearance of improved spatial resolution and provides a new way to evaluate the accuracy of EIT reconstructions when a CT scan is available.

A narrative review of electrical impedance tomography in lung diseases with flow limitation and hyperinflation: methodologies and applications

Electrical impedance tomography (EIT) is a functional radiation-free imaging technique that measures regional lung ventilation distribution by calculating the impedance changes in the corresponding regions. The aim of the present review was to summarize the current literature concerning the methodologies and applications of EIT in lung diseases with flow limitation and hyperinflation. PubMed was searched up to May 2020 to identify studies investigating the use of EIT in patients with asthma, bronchiectasis, bronchitis, bronchiolitis, chronic obstructive pulmonary disease, and cystic fibrosis. The extracted data included study design, EIT methodologies, interventions, validation and comparators, population characteristics, and key findings. Of the 44 included studies, seven were related to simulation, animal experimentation, or reconstruction algorithm development with evaluation on patients; 27 studies had the primary objective of validating EIT technique and measures including regional ventilation distribution, regional EIT-spirometry parameters, end-expiratory lung impedance, and regional time constants; and 10 studies had the primary objective of applying EIT to monitor the response to therapeutic interventions, including various ventilation supports, patient repositioning, and airway suctioning. In pediatric and adult patients, EIT has been successfully validated for assessing spatial and temporal ventilation distribution, measuring changes in lung volume and flow, and studying regional respiratory mechanics. EIT has also demonstrated potential as an alternative or supplement to well-established measurement modalities (e.g., conventional pulmonary function testing) to monitor the progression of obstructive lung diseases, although the existing literature lacks prediction values as references and lacks clinical outcome evidence.

Three-dimensional Pulmonary Monitoring Using Focused Electrical Impedance Measurements

Lung pathologies such as edema, atelectasis or pneumonia are potentially life threatening conditions. Especially in critically ill and mechanically ventilated patients, an early diagnosis and treatment is crucial to prevent an Acute Respiratory Distress Syndrome [1]. Thus, continuous monitoring tool for the lung condition available at the bedside would be highly appreciated. One concept for this is Electrical Impedance Tomography (EIT). In EIT, an electrode belt of typically 16 or 32 electrodes is attached at the body surface and multiple impedance measurements are performed. From this, the conductivity change inside the body is reconstructed in a two-dimensional image. In various studies, EIT proved to be a useful tool for quantifying recruitment maneuvers, the assessment of the ventilation homogeneity, the detection of lung edema or perfusion monitoring [2, 3, 4, 5]. Nevertheless, the main problem of EIT is the low spatial resolution (compared to CT) and the limitation to two dimensional images. In this paper, we try to address the latter issue: Instead of projecting conductivity changes onto a two-dimensional image, we adjust electrode positions to focus single tetrapolar measurements to specific, three-dimensional regions of interest. In earlier work, we defined guidelines to achieve this focusing [6, 7]. In this paper, we demonstrate in simulations and in a water tank experiment that applying these guidelines can help to detect pathologies in specific lung regions.