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Triple EIT (Electrical Impedance Tomography)

Characterizing the Evolution of Neonatal Lung Disease Throughout Infancy and Childhood Using Electrical Impedance Tomography: A Pilot Study

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07247474
Enrollment
140
Registered
2025-11-25
Start date
2026-01-30
Completion date
2028-12-01
Last updated
2026-02-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cardiopulmonary, Neonates and Preterm Infants

Brief summary

This study plans to learn more about ways to look at participant's lungs using new machines called Electrical Impedance Tomography (EIT). The EIT does not use harmful radiation like CT or x-ray. It is read through electrodes like using EKG reading heartbeats. The investigators want to compare the results of patients who have chronic respiratory disease to patients without chronic respiratory disease to learn more about lung structure and composition.

Interventions

DEVICEElectrical impedance tomography (EIT)

Electrical impedance tomography (EIT) is a noninvasive and non-ionizing imaging technique that describes lung ventilation and perfusion

Sponsors

University of Colorado, Denver
Lead SponsorOTHER
Colorado State University
CollaboratorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
2 Weeks to 25 Years
Healthy volunteers
Yes

Inclusion criteria

* 2 weeks to 25 years of age * evidence of cardiopulmonary disease including, but not limited to: 1. Post-prematurity respiratory disease 2. Congenital diaphragmatic hernia 3. Pulmonary Hypertension 4. Congenital heart disease 5. Respiratory failure 6. Neuromuscular Disease 7. Developmental or congenital lung disease OR matched healthy controls (born at term gestation (\>36 weeks gestational age) with no cardiopulmonary disease)

Exclusion criteria

* \<2 weeks of age * Anything that interferes with lead placement on the chest wall (such as, dermatologic conditions, multiple chest tubes, anatomic abnormality, or large dressings that cannot be moved) * No informed consent * Pregnant or lactating * Pacemaker or other metal intrathoracic surgical implant (causes noise in the data)

Design outcomes

Primary

MeasureTime frameDescription
EIT Imaging Maps that provide information about regional ventilation and perfusion of the lung4 hoursThese images will be analyzed both visually for qualitative abnormalities and through quantitative pixel analysis that can provide information regarding lung volume, blood volume, and changes in either based on respiratory cycle, cardiac cycle, or intervention. Areas of low ventilation (atelectasis and consolidation) will be identified.

Secondary

MeasureTime frameDescription
Comparison of Ventilation and Perfusion Ratio4 hoursIn participants with both ventilation and perfusion metrics from the ACT5 EIT system, a regional comparison of ventilation and perfusion will be generated. These values will indicate whether a segment of the lung has relatively more or less ventilation or perfusion.
Regional Conductivity Due to Ventilation4 hoursThis is a qualitative aim and will summarize EIT images pictorially. Pixel densities will be evaluated for normality and summarized as mean (SD) or median (interquartile range). EIT images will be qualitatively compared between cases and controls. Outcome metrics may be generated to measure things such as ventilation heterogeneity
Regional Conductivity Due to Perfusion4 hoursThis is a qualitative and quantitative aim that will only be performed using the ACT5 EIT system. Results will qualitatively compare EIT images with CXR and CT scan images when available. Images will be displayed side by side and interpreted by both the clinician and the EIT study staff. Various summary measures of EIT outcomes will be calculated including pixel heterogeneity, summary changes over tidal breath and variation between tidal peaks. Pearson and Spearman correlation will be calculated between summary EIT outcomes and continuous primary clinical values. Linear and logistic regression will be used to estimate associations (with 95% CI) between EIT measures and clinical outcomes. Summary data will be presented in tables and figures using basic descriptive statistics stratified by study group.

Countries

United States

Contacts

CONTACTKatelyn Enzer, MD
allison.keck@childrenscolorado.org7207779137
CONTACTAllison Keck, BS
allison.keck@childrenscolorado.org720-777-0734
PRINCIPAL_INVESTIGATORKatelyn Enzer, MD

University of Colorado, Denver

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 24, 2026