Using electrical impedance tomography to predict COPD severity
Prediction of COPD Chest CT Severity Using Electrical Impedance Tomography by Machine Learning Methods
Chinese PLA General Hospital · NCT06359145
This study is testing if a new non-invasive method using electrical signals can help predict how severe COPD is in patients compared to standard lung tests.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 150 (estimated) |
| Ages | 20 Years and up |
| Sex | All |
| Sponsor | Chinese PLA General Hospital (other) |
| Locations | 1 site (Beijing, Beijing) |
| Trial ID | NCT06359145 on ClinicalTrials.gov |
What this trial studies
This study aims to predict the severity of chronic obstructive pulmonary disease (COPD) by utilizing electrical impedance tomography (EIT) to assess lung structure. It involves collecting pulmonary function data, CT visual scores, and EIT data, and applying deep machine learning algorithms to evaluate the predictive capabilities of EIT compared to traditional pulmonary function tests. The goal is to establish a non-invasive method for monitoring the progression of COPD.
Who should consider this trial
Good fit: Ideal candidates include individuals over 20 years old who exhibit symptoms of COPD but have not yet received a definitive diagnosis through pulmonary function tests.
Not a fit: Patients who refuse the EIT examination or have incomplete CT scan information may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could provide a more accessible and non-invasive method for evaluating and monitoring COPD severity.
How similar studies have performed: While the use of EIT in assessing lung conditions is emerging, this specific application for predicting COPD severity is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Clinical physicians suspect a patient may have COPD based on symptoms and physical examination, but a definitive diagnosis has not been confirmed through PFTs. * Age \> 20 years, and be able to communicate with doctors. * Willing to sign informed consent for the course of the study. Exclusion Criteria: * Patient refusal of EIT examination. * The CT scan information is incomplete, and the interval between the pulmonary function test and the CT scan is more than 180 days.
Where this trial is running
Beijing, Beijing
- PLA — Beijing, Beijing, China (RECRUITING)
Study contacts
- Study coordinator: Zhimei Duan, doctor
- Email: 549117002@qq.com
- Phone: 13716376758
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Electric Impedance, Respiratory Function Tests, Pulmonary Disease, Chronic Obstructive