Individuals with chronic lung disease often have conditions that are very difficult to diagnose without the aid of imaging technology. The gold standard, CT scanning, exposes the patient to ionizing radiation and may be harmful in children. Electrical impedance tomography (EIT) is a noninvasive, non-ionizing functional imaging technique in which electrodes are placed on the surface of the body, and low amplitude, low frequency current is applied on the electrodes. This results in a voltage distribution on the electrodes which can then be measured. From these voltages, an image is formed that re acts the conductivity and/or permittivity distribution within the region of interest. Since EIT is a saf and portable technology with no damaging side effects, it can be used as needed. This project is part of a long term goal to develop an EIT system for imaging patients with chronic lung disease. The goal of this research is to determine whether electrical impedance tomography can provide a means to obtain quantitative and regional information about the extent and nature of bronchial obstruction in patients with cystic fibrosis (CF). In particular, EIT will be used to identify regions of obstruction (air trapping) and consolidation comprised of atelectasis and airway occlusion in CF patients, and to correlate these measures with improvements seen after hospitalized treatment for a pulmonary exacerbation. The first specific aim is to develop algorithms for quantifying bronchial obstruction and consolidation and to determine their sensitivity and specificity. The algorithms will extract information from EIT images of conductivit and permittivity computed using the D-bar reconstruction algorithm developed by the P.I. Data will be collected during spirometry on CF patients clinically indicated for CT scans and on subjects with healthy lungs, and the sensitivity and specificity of the algorithms will be determined using both the data from the healthy subjects and data calculated from CT VIDA Software. The second specific aim is to determine whether these algorithms can demonstrate the beneficial effects of antibiotic treatment for CF patients with an acute PE by correlating changes in quantitative EIT measures with clinical measures known to improve following therapy, with patients serving as their own controls. Regional changes in air trapping and consolidation from pre to post treatment as indicated by the EIT images will be calculated, with subjects serving as their own control.

Public Health Relevance

With emerging concerns about the long term risks of repeated exposures to radiation, and with the increasing lifespans of individuals with chronic lung disease, including cystic fibrosis, there is a great need to develop imaging techniques that do not rely on radiation and can be done as needed from infancy to adulthood. Electrical impedance tomography may provide a means to obtain quantitative and regional information about the extent and nature of bronchial obstruction in cystic fibrosis patients as needed in a routine and non-invasive manner. Such knowledge may improve the care of patients with chronic lung disease by providing additional information for treatment of pulmonary exacerbation, as well as nearly immediate feedback on the effectiveness of airway clearance therapies.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZRG1)
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Sastre, Antonio
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Colorado State University-Fort Collins
Biostatistics & Other Math Sci
Schools of Arts and Sciences
Fort Collins
United States
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Muller, Peter A; Mueller, Jennifer L; Mellenthin, Michelle et al. (2018) Evaluation of surrogate measures of pulmonary function derived from electrical impedance tomography data in children with cystic fibrosis. Physiol Meas 39:045008
Mueller, Jennifer L; Muller, Peter; Mellenthin, Michelle et al. (2018) Estimating regions of air trapping from electrical impedance tomography data. Physiol Meas 39:05NT01
Hamilton, Sarah J; Mueller, J L; Alsaker, M (2017) Incorporating a Spatial Prior into Nonlinear D-Bar EIT Imaging for Complex Admittivities. IEEE Trans Med Imaging 36:457-466
Muller, Peter A; Mueller, Jennifer L; Mellenthin, Michelle M (2017) Real-Time Implementation of Calderón's Method on Subject-Specific Domains. IEEE Trans Med Imaging 36:1868-1875
Mellenthin, Michelle M; Mueller, Jennifer L; Bueno de Camargo, Erick Dario León et al. (2015) The ACE1 thoracic Electrical Impedance Tomography system for ventilation and perfusion. Conf Proc IEEE Eng Med Biol Soc 2015:4073-6
Dodd, Melody; Mueller, Jennifer L (2014) A Real-time D-bar Algorithm for 2-D Electrical Impedance Tomography Data. Inverse Probl Imaging (Springfield) 8:1013-1031