Chinese PLA General Hospital
Wang Kaifei
The purpose of this study is to predict the CT visual score of emphysema with EIT-based parameters, in order to provide a non-invasive and convenient method for the evaluation of lung structure and physiological and pathological progression of COPD.
Electric Impedance
Respiratory Function Tests
Pulmonary Disease, Chronic Obstructive
Methods: By collecting pulmonary function data, CT visual scores, and EIT data, and employing deep machine learning algorithms to compare the predictive capabilities of EIT and PFT for CT visual scores of pulmonary emphysema, this study aims to validate the ability of EIT to assess the progression of COPD.
| Study Type : | OBSERVATIONAL |
| Estimated Enrollment : | 150 participants |
| Official Title : | Prediction of COPD Chest CT Severity Using Electrical Impedance Tomography by Machine Learning Methods |
| Actual Study Start Date : | 2023-04-01 |
| Estimated Primary Completion Date : | 2024-06-01 |
| Estimated Study Completion Date : | 2024-08-01 |
Information not available for Arms and Intervention/treatment
| Ages Eligible for Study: | 20 Years |
| Sexes Eligible for Study: | ALL |
| Accepts Healthy Volunteers: | 1 |
Want to participate in this study, select a site at your convenience, send yourself email to get contact details and prescreening steps.
RECRUITING
PLA
Beijing, Beijing Municipality, China, 100853