The Clinical Value of Deep Learning-Based Reconstruction Techniques in Cardiac MRI Scanning

NCT07274436 | Recruiting

• 1 other identifier: 2025-0804
• Study Type: observational
• Target: 50
• Locations: 1 country
• Sites: 1

Brief Summary

By enrolling patients who underwent cardiac MR(Magnetic Resonance) examinations at our center and using randomized allocation, the patients were divided into a study group and a control group. The study group underwent scanning using AI-based(Artificial Intelligence-based) cardiac MRI(Magnetic Resonance Imaging) sequences, while the control group was scanned using non-AI cardiac MRI sequences

Conditions

Cardiac Disease

Outcome Measures

Primary Outcomes (1)

• Patient satisfaction

  Patient satisfaction will be evaluated using a Likert scale with the following scoring criteria:5 - Very Satisfied;4 - Satisfied;3 - Neutral;2 - Dissatisfied;1 - Very Dissatisfied

  immediately after procedure

Secondary Outcomes (2)

• total scan time

  During procedure

• objective image measurements (signal-to-noise ratio)

  one week

Study Arms (2)

scanning using AI-based cardiac MRI sequences

scanning using non-AI cardiac MRI sequences

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients requiring cardiac MRI in clinical practice

You may qualify if:

• Patients requiring cardiac MRI in clinical practice;
• Patient age ≥ 18 years;
• The patient has signed an informed consent form.

You may not qualify if:

• Patients with contraindications to magnetic resonance imaging;
• Patients who failed to complete the MRI examination or whose image quality was inadequate for diagnostic requirements;
• Other circumstances deemed by clinical trial personnel as unsuitable for participation in this trial;
• Subjects or their legal guardians voluntarily requesting to withdraw.

Sponsors & Collaborators

• Lian Yang: lead

Study Sites (1)

Union Hospital，Tongji Medical College，Huazhong University of Science and Technology

Wuhan, Hubei, 430000, China

RECRUITING

MeSH Terms

Conditions

Heart Diseases

Condition Hierarchy (Ancestors)

Cardiovascular Diseases

Central Study Contacts

Lian Yang

CONTACT

18986273791; yanglian@hust.edu.cn

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Director

Study Record Dates

• First Submitted: November 19, 2025
• First Posted: December 10, 2025
• Study Start: August 1, 2025
• Primary Completion (Estimated): August 1, 2026
• Study Completion (Estimated): August 1, 2026
• Last Updated: December 10, 2025

Record last verified: 2025-11

Locations

CN (1)