Evaluation and Treatment Strategy Development of Coronary Heart Disease Guided by OCT Based on Multimodal Deep Learning
Evaluation and Treatment Strategy Development of Coronary Heart Disease Guided by Optical Coherence Tomography Based on Multimodal Deep Learning
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Xiang Ma, Ph.D
- Phone Number: +86 13669939349
- Email: maxiangxj@yeah.net
Study Contact Backup
- Name: Pengfei Liu, M.D
- Phone Number: +86 18653773715
- Email: liupf918@126.com
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age ≥20 years old;
- Angiography was performed, and OCT imaging of criminal blood vessels was performed before intervention;
- Type of coronary heart disease: Unstable angina pectoris (UA), ST elevation myocardial infarction (STEMI) And non-ST elevation myocardial infarction (NSTEMI);
Exclusion Criteria:
- Lack of medical records;
- Failure to complete follow-up;
- Previous coronary artery bypass grafting;
- Severe liver or kidney insufficiency;
- Infectious diseases, malignancies and bleeding diseases;
- OCT image quality was caused by large thrombus volume or residual blood in lumen and percutaneous coronary angiography Poor and further excluded.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Coronary Stent Malapposition
Measurement results of deep learning-based OCT system: Coronary Stent Malapposition
|
Stenting will be performed with OCT guidance according to the algorithm described in the protocol.
A deep learning-based OCT system was used to measure the adherence of coronary stents.
|
|
Coronary Stent Well Apposed
Measurement results of a deep learning-based OCT system: Coronary Stent Well Apposed
|
Stenting will be performed with OCT guidance according to the algorithm described in the protocol.
A deep learning-based OCT system was used to measure the adherence of coronary stents.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
MACE
Time Frame: Post-procedure within 1 year
|
Patients were followed up within 1 year after OCT and PCI.
The follow-up included major adverse cardiac events: All causes were death, recurrent myocardial infarction, target vessel reconstruction, and stent thrombosis.
|
Post-procedure within 1 year
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Pengfei Liu, M.D, First Affiliated Hospital of Xinjiang Medical University
- Principal Investigator: Xinliang Peng, M.D, First Affiliated Hospital of Xinjiang Medical University
- Principal Investigator: Abudusalamu Tuerdimaimaiti, M.D, First Affiliated Hospital of Xinjiang Medical University
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 2022B03022-3
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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