An observational study in Cardiovascular Diseases, Ischemic Heart Disease (IHD) and Cardiomyopathy, sponsored by Second Affiliated Hospital, School of Medicine, Zhejiang University. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-07-28.
Sponsored by Second Affiliated Hospital, School of Medicine, Zhejiang University · Observational
This single-center, prospective, observational cohort study aims to evaluate the clinical application value of multi-modal cardiovascular magnetic resonance (CMR) imaging in patients with cardiovascular diseases (CVD).
While traditional imaging methods have limitations in fully evaluating myocardial tissue characteristics, multi-modal CMR offers a comprehensive, non-invasive "one-stop" assessment. It can simultaneously evaluate heart structure, function, tissue features (such as fibrosis and edema), and hemodynamics.
The study plans to enroll patients with suspected or confirmed CVD. Participants will undergo a comprehensive multi-modal CMR scan (including Cine, T1/T2 mapping, Late Gadolinium Enhancement, and 4D flow sequences) as part of their evaluation. In addition to clinical evaluation, the study will explore sequence optimization (e.g., comparing pre-contrast vs. post-contrast Cine, and 3-slice vs. 9-slice T1 mapping) and evaluate deep learning-based virtual native enhancement (VNE) models trained under different sequence protocols.
By tracking clinical outcomes, the study seeks to establish a standardized imaging assessment system to improve the early detection, accurate diagnosis, risk stratification, and prognostic prediction for various types of cardiovascular diseases.
Cardiovascular disease (CVD) remains a leading cause of global mortality and disability. Accurate and early assessment of cardiac structure, function, and myocardial tissue characteristics is crucial for optimal clinical management. Cardiac Magnetic Resonance (CMR) has evolved from single morphological imaging into advanced multi-modal imaging. By integrating Cine, Late Gadolinium Enhancement (LGE), T1/T2 mapping, and 4D flow techniques, multi-modal CMR serves as a "gold standard" that provides a comprehensive macroscopic and cellular-level evaluation, including the identification of myocardial fibrosis, edema, and complex hemodynamic alterations.
Despite its clinical potential, systematic research comparing the diagnostic efficacy and prognostic value of multi-modal CMR features across a broad spectrum of cardiovascular diseases (such as ischemic heart disease, non-ischemic cardiomyopathy, and valvular diseases) is still lacking. Furthermore, optimization of scan efficiency, standardization of sequence acquisition protocols, and the development of contrast-free or AI-driven virtual imaging techniques (such as deep learning-based virtual native enhancement ) represent critical avenues to enhance clinical utility.
This prospective, observational registry study is designed to address this gap by establishing a large-scale, standardized CMR imaging database. Approximately 2,000 patients with clinically suspected or confirmed CVD will be consecutively enrolled. Following routine clinical care pathways, participants will undergo a "one-stop" multi-modal CMR examination using 3.0T MRI scanners.
To refine imaging protocols and validate novel synthetic imaging algorithms, a subset/sub-cohort analysis will specifically investigate the impacts of acquisition parameters-comparing performance between pre-contrast Cine vs. post-contrast Cine, as well as 3-slice vs. 9-slice T1 mapping protocols-on downstream machine learning/deep learning models for virtual native enhancement and tissue characterization.
The primary objectives are to: 1) systematically delineate the imaging feature spectrum across different CVD subtypes; 2) optimize multi-modal CMR acquisition protocols and validate deep learning models for virtual image generation (e.g., VNE); 3) assess the sensitivity of hemodynamic and tissue-characterization parameters (especially T1 mapping and extracellular volume [ECV]) in detecting early cardiac damage; and 4) explore the correlation between multi-modal CMR parameters and major adverse cardiovascular events (MACE) during the follow-up period. Ultimately, this study aims to provide robust, evidence-based support for precision diagnosis and risk stratification in cardiovascular medicine.
5,368 studies on the registry are indexed under Cardiovascular Diseases; 939 are open to participants now.
This study's planned enrollment of 2,000 is above the median of 506 across 1,572 observational studies indexed under Cardiovascular Diseases.
Browse Cardiovascular Diseases studies →Second Affiliated Hospital, School of Medicine, Zhejiang University is the lead sponsor of 1,047 studies on the registry; 502 are open to participants now.
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The study population consists of consecutive adult patients (aged 18 years and older) who are clinically suspected or confirmed to have cardiovascular diseases (CVD), including but not limited to ischemic heart disease, non-ischemic cardiomyopathy, myocarditis, and valvular heart disease. These participants are enrolled from the Second Affiliated Hospital Zhejiang University School of Medicine. They are patients who are scheduled to undergo a multi-modal cardiac magnetic resonance (CMR) examination as part of their clinical evaluation to determine disease etiology or assess myocardial tissue characteristics.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Clinically suspected or confirmed cardiovascular disease (including but not limited to ischemic heart disease, non-ischemic cardiomyopathy, myocarditis, valvular disease, etc.), requiring a cardiac magnetic resonance (CMR) examination to determine the etiology or evaluate myocardial tissue characteristics.
No to magnetic resonance examination, and able to cooperate with breath-holding instructions.
Voluntarily participate in this study and sign a written form.
Exclusion Criteria:
Relative contraindications: Severe claustrophobia, unable to complete the examination despite communication.
Severe renal insufficiency.
Special populations: Pregnant or lactating women.
Presence of severe arrhythmias (e.g., persistent atrial fibrillation) leading to severely impaired magnetic resonance signal acquisition, rendering the image quality inadequate for diagnosis.
Poor expected compliance: Unable to complete follow-up, or deemed unsuitable for enrollment by the investigator for other reasons.
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
A reason a treatment, test or procedure should not be given to a particular person, such as an allergy, another illness or a medicine they take.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Contraindication
A reason a treatment, test or procedure should not be given to a particular person, such as an allergy, another illness or a medicine they take.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
A comprehensive "one-stop" scanning protocol using 3.0T MRI scanners. The protocol includes Cine imaging, T1/T2 mapping, Late Gadolinium Enhancement (LGE), first-pass perfusion, and 4D flow sequences to evaluate cardiac structure, function, myocardial tissue characteristics, and hemodynamics.
Diagnostic Efficacy of Multi-modal CMR Parameters (AUC)
The Area Under the Receiver Operating Characteristic Curve (AUC) will be calculated to assess the diagnostic performance of multi-modal CMR parameters (specifically T1 mapping and extracellular volume \[ECV\]) in differentiating various types of cardiovascular diseases (e.g., ischemic vs. non-ischemic). The final clinical diagnosis based on ESC/ACC guidelines will serve as the gold standard.
Time frame: Baseline (at the time of CMR scan)
Correlation Between Imaging Parameters and Clinical Indicators
To evaluate the Pearson or Spearman correlation coefficients between multi-modal CMR parameters (such as LGE, T1/T2 mapping, 4D flow metrics) and clinical functional/laboratory indicators.
Time frame: Baseline
Incidence of Major Adverse Cardiovascular Events (MACE)
To evaluate the occurrence rate of MACE during the follow-up period. MACE is defined as a composite of cardiac death, readmission for heart failure, malignant arrhythmia (sustained ventricular tachycardia/ventricular fibrillation), and non-fatal myocardial infarction.
Time frame: Up to 3 years
Model performance for virtual native enhancement across different sequence acquisition protocols
Model performance for virtual LGE generation across sequence protocols: Structural Similarity Index Measure (SSIM)
Time frame: At baseline
Model performance for virtual LGE generation across sequence protocols: Peak Signal-to-Noise Ratio (PSNR)
Peak Signal-to-Noise Ratio (PSNR) will be evaluated to compare virtual LGE algorithms trained on pre- vs. post-contrast Cine and 3-slice vs. 9-slice T1 mapping protocols.
Time frame: At baseline
Model performance for virtual LGE generation across sequence protocols: DICE coefficient
DICE coefficient will be evaluated to compare virtual LGE algorithms trained on pre- vs. post-contrast Cine and 3-slice vs. 9-slice T1 mapping protocols.
Time frame: At baseline
Plan to share: No — The individual participant data (IPD) will not be shared because of current institutional policies and national data security regulations regarding the protection of patient privacy and human genetic resources. The data contains sensitive medical imaging information that is restricted from being transferred or shared outside the participating institution without specific governmental and ethical approvals.
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