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

NCT05774730 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 40

Last updated 2023-03-21

No results posted yet for this study

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

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.

Sponsors & Collaborators

  • China-Japan Friendship Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-03-26
Primary Completion
2024-12-31
Completion
2024-12-31

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05774730 on ClinicalTrials.gov