Warning Model of Myocardial Remodeling After Acute Myocardial Infarction Using Multimodal Feature Structure Technology

April 28, 2024 updated by: Xuanwu Hospital, Beijing

Early Warning Model of Myocardial Remodeling After Acute Myocardial Infarction Based on Multimodal Feature Structure Technology

Acute myocardial infarction (AMI) is one of the most important diseases threatening human life. The existing MI prognosis prediction scales mostly predict the incidence of death, recurrent MI and heart failure through 6-8 clinical text indicators, and the data are collected relatively simply. Myocardial remodeling, as an adverse pathological change that can start and continue to progress in the early stage after myocardial infarction, is the main pathological mechanism of heart failure and death. However, there is no quantitative early-warning model of myocardial remodeling, and the clinical guidance of early intervention is lacking.

Our previous study found that cardiac magnetic resonance imaging can accurately quantify the necrotic area and recoverable myocardium in the edematous myocardium after myocardial infarction. In this study, machine learning algorithm, variable convolution network (DCN) and capsule network (capsnet) are used to build a new neural network architecture. Structural feature extraction of multi-modal clinical image data such as MRI and ultrasound is realized. Combined with the established database of 3000 patients with myocardial infarction, the multimodal feature matrix will be constructed, and a variety of classifiers such as support vector machine (SVM) and random forest (RF) will be used for quantitative prediction of myocardial remodeling, and the effects of different classifiers were evaluated. It is expected that this project will establish a quantitative early warning model of myocardial remodeling after acute myocardial infarction in line with the characteristics of Chinese people. The same type of data outside the database will be used for verification to establish an efficient and stable early warning model.

Study Overview

Status

Active, not recruiting

Conditions

Study Type

Observational

Enrollment (Actual)

4000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Xicheng
      • Beijing, Xicheng, China, 100000
        • Xuanwu Hospital, Capital Medical University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Criteria for the diagnosis of acute myocardial infarction:

increased or decreased cardiac biomarkers (preferably cTn), at least once exceeding the 99th percentile of the upper reference value, cut-off variability ≤10%, and at least one evidence of myocardial ischemia (including symptoms, electrocardiographic ischemic changes, pathological Q-waves, or imaging evidence).

Description

Inclusion Criteria:

  • 1.Patients with acute myocardial infarction, aged 18-80 years; 2.The time from onset to treatment is less than 72h 3.Myocardial enzyme Tni/Tnt(+).

Exclusion Criteria:

  • 1.Patients with malignant tumors; 2.Patients who could not receive conventional treatment 3.Patients who did not receive coronary angiography, lacking anatomical and imaging data; 4.Patients who have undergone cardiac surgery (except coronary artery bypass surgery)

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Novel convolutional neural network algorithm and cardiac magnetic resonance imaging to evaluate the occurrence of myocardial remodeling.remodeling after myocardial infarction.
Time Frame: 1year
(Quantitative characterization of myocardial remodeling, cardiac magnetic resonance imaging quantifying necrotic areas and recoverable myocardium within the edematous myocardium after myocardial infarction).
1year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The multi-dimensional indexes of existing database were compared with the location and course of myocardial remodeling by artificial intelligence method Degree of correlation analysis.
Time Frame: 1year

Through the new Deformable Convolutional Capsule network that has been developed The Networks (DCCN) study focused on the existing clinical and imaging comprehensive database of patients with acute myocardial infarction Machine learning was performed on the data to complete the extraction of relevant features and logical relationship analysis of myocardial remodeling after myocardial infarction.

Strong correlation features were screened.
1year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Xuanwu Hospital, Beijing

Collaborators

Beijing Institute of Technology

Investigators

  • Principal Investigator: Zhi Liu, Xuanwu Hospital, Beijing

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 10, 2022

Primary Completion (Estimated)

June 1, 2024

Study Completion (Estimated)

June 1, 2024

Study Registration Dates

First Submitted

September 17, 2023

First Submitted That Met QC Criteria

September 27, 2023

First Posted (Actual)

October 2, 2023

Study Record Updates

Last Update Posted (Actual)

April 30, 2024

Last Update Submitted That Met QC Criteria

April 28, 2024

Last Verified

October 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • xuanwuliuzhi

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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