Evaluation of the Effectiveness of Predicting the Integrity of Interlobar Fissures Based on Chest Image AI Technology

Study Overview
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Brief Summary
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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.

Official Title
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Evaluation of the Effectiveness of Predicting the Integrity of Interlobar Fissures Based on Chest Image AI Technology

Conditions
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Chronic Obstructive Pulmonary Disease

Intervention / Treatment
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* Other: Emphysema quantitative analysis software based on chest image AI technology
* Other: artificial analysis of chest image
* Procedure: imported Chartis detection system


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients with chronic obstructive pulmonary disease who meet the GOLD diagnostic criteria FEV1 ≤ 45% pred and FEV1/FVC<70% TLC>100% pred and RV>175% pred CAT≥18 >50% of emphysema destruction Smoking prohibition>6 months Sign the informed consent form Exclusion Criteria: PaCO2>8.0 kPa, or PaO2<6.0 kPa 6-minute walking test<160m Obvious chronic bronchitis, bronchiectasis or other infectious lung diseases Three hospitalizations due to pulmonary infection in the past 12 months before the baseline assessment Previous lobectomy, LVRS or lung transplantation LVEF<45% and or RVSP>50mmHg Anticoagulant therapy that cannot be stopped before surgery The patient has obvious immune deficiency Participated in other lung drug studies within 30 days before this study Pulmonary nodules requiring intervention Any disease or condition that interferes with the completion of the initial or subsequent assessment

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 90 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Emphysema quantitative analysis softwarebased on chest image AI technology<br> | Other: Emphysema quantitative analysis software based on chest image AI technology<br>* The participants would undergo lung CT, and the integrity of interlobar fissure will be quantitatively analyses by software based on chest image AI technology.<br>|
| artificial analysis<br> | Other: artificial analysis of chest image<br>* The participants would undergo lung CT, and the integrity of interlobar fissure will be artificially analyses.<br>|
| imported Chartis detection system<br> | Procedure: imported Chartis detection system<br>* The participants would undergo imported Chartis detection system.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Therapeutic effect of lung volume reduction surgery | Lung CT | 1 month after bronchoscopic valve lung volume reduction | 
| Therapeutic effect of lung volume reduction surgery | Lung CT | 3 months after bronchoscopic valve lung volume reduction | 
| Therapeutic effect of lung volume reduction surgery | Lung CT | 6 months after bronchoscopic valve lung volume reduction | 
| the integrity of interlobar fissure | Emphysema quantitative analysis softwarebased on chest image AI technology, artificial analysis and imported Chartis detection system | Before bronchoscopic valve lung volume reduction |