The purpose of this study is to determine the ability of electrical impedance tomography (EIT) to identify structural and functional physiological changes that occur with disease progression in cystic fibrosis patients. The investigators also aim to determine whether EIT can serve as an alternative for CT to identify regions of air trapping and consolidation, whether EIT can provide clinically useful information about response to treatment for an acute PE, and whether EIT can provide longitudinal information about structural changes in the lung.
Study Type
OBSERVATIONAL
Enrollment
48
Children's Hospital Colorado
Aurora, Colorado, United States
Identification of air trapping and consolidation by EIT
The detection task for identifying air trapping and consolidation is to determine by inspection regions of EIT VQ index significantly lower than the surrounding lung region, with actual numbers or relative differences to be determined as part of this study in the correlation analysis to CT scans.
Time frame: 36 months
Determining utility of EIT information in response to treatment for a pulmonary exacerbation
Individual outcome measures (CFCS, LCI , PFT, and EIT measures) will be evaluated using paired t-tests, and the corresponding t-statistics from each of the tests will be used as measures of effect size for comparison. In addition, all of the clinical outcomes can be compared statistically using a joint model approach (this is the same model that is referenced in Q3 below).
Time frame: 36 months
Determination of structural changes in the lung by EIT
The EIT-derived global VQ indices, FEV1, FEV1/FVC, FVC, and extent of air trapping and consolidation will be studied longitudinally and compared to LCIs, PFTs, and CT scans when available to assess the ability of EIT to identify structural and reversible physiological changes that occur with disease progression. To estimate the change in the EIT measures of global VQ, air trapping and consolidation, and EIT-derived PFT outputs over time, a random coefficient model with an intercept and slope fit for each subject with at least two measurements over the 3 years will be used. A bivariate version of the random coefficients model will be fit to address whether the EIT outcome variable is associated with the spirometer PFT outputs, LCI, and CFCS while accounting for repeated measures.
Time frame: 36 months
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