Trials / Unknown
UnknownNCT05774730
Evaluation of the Effectiveness of Predicting the Integrity of Interlobar Fissures Based on Chest Image AI Technology
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 40 (estimated)
- Sponsor
- China-Japan Friendship Hospital · Academic / Other
- Sex
- All
- Age
- 18 Years – 90 Years
- Healthy volunteers
- Not accepted
Summary
The goal of observational study is to evaluate effectiveness of predicting the integrity of interlobar fissures based on chest image AI technology in patients with Chronic Obstructive Pulmonary Disease who will undergo lung volume reduction surgery with endobronchial valve implantation. The main question it aims to answer is: evaluation of the effectiveness of predicting the integrity of interlobar fissures based on chest image AI technology. Participants will be evaluated by lung CT (quantitative analysis based on chest image AI technology and artificial analysis) and imported Chartis detection system.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| OTHER | Emphysema quantitative analysis software based on chest image AI technology | The participants would undergo lung CT, and the integrity of interlobar fissure will be quantitatively analyses by software based on chest image AI technology. |
| OTHER | artificial analysis of chest image | The participants would undergo lung CT, and the integrity of interlobar fissure will be artificially analyses. |
| PROCEDURE | imported Chartis detection system | The participants would undergo imported Chartis detection system. |
Timeline
- Start date
- 2023-03-26
- Primary completion
- 2024-12-31
- Completion
- 2024-12-31
- First posted
- 2023-03-20
- Last updated
- 2023-03-21
Source: ClinicalTrials.gov record NCT05774730. Inclusion in this directory is not an endorsement.