Multimodal mAgnetic Resonance imaGIng in Cardiovascular Disease (MAGIC)
Multimodal-MRI in Cardiovascular Diseases
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.
Přehled studie
Postavení
Postavení
Podmínky
Podmínky
Intervence / Léčba
Intervence / Léčba
Detailní popis
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.
Typ studie
Typ studie
Zápis (Odhadovaný)
Zápis
Kontakty a umístění
Studijní kontakt
Studijní kontakt
- Jméno: jiaqi Fan
- Telefonní číslo: +86 15267029492
- E-mail: jqfan@zju.edu.cn
Studijní záloha kontaktů
- Jméno: linyun Xie
- Telefonní číslo: +86 15990004158
- E-mail: 12518519@zju.edu.cn
Studijní místa
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Zhejiang
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Hangzhou, Zhejiang, Čína, 310009
- Nábor
- The Second Affiliated Hospital Zhejiang University School of Medicine
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Kontakt:
- jiaqi Fan
- Telefonní číslo: +86 15267024942
- E-mail: jqfan@zju.edu.cn
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-
Kritéria účasti
Kritéria způsobilosti
Kritéria způsobilosti
Věk způsobilý ke studiu
- Dospělý
- Starší dospělý
Přijímá zdravé dobrovolníky
Metoda odběru vzorků
Studijní populace
Popis
Inclusion Criteria:
- Aged 18 years and older, with no gender restrictions.
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 contraindications to magnetic resonance examination, and able to cooperate with breath-holding instructions.
Voluntarily participate in this study and sign a written informed consent form.
Exclusion Criteria:
- Absolute contraindications: Implantation of non-MRI compatible metallic foreign bodies (e.g., old pacemakers, implantable cardioverter-defibrillators [ICD], aneurysm clips, etc.).
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.
Studijní plán
Jak je studie koncipována?
Detaily designu
Co je měření studie?
Primární výstupní opatření
Primární výstupní opatření
Měření výsledku |
Popis opatření |
Časové okno |
|---|---|---|
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Diagnostic Efficacy of Multi-modal CMR Parameters (AUC)
Časové okno: Baseline (at the time of CMR scan)
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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.
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Baseline (at the time of CMR scan)
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Sekundární výstupní opatření
Sekundární výstupní opatření
Měření výsledku |
Popis opatření |
Časové okno |
|---|---|---|
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Correlation Between Imaging Parameters and Clinical Indicators
Časové okno: Baseline
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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.
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Baseline
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Incidence of Major Adverse Cardiovascular Events (MACE)
Časové okno: Up to 3 years
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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.
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Up to 3 years
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Model performance for virtual native enhancement across different sequence acquisition protocols
Časové okno: At baseline
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Model performance for virtual LGE generation across sequence protocols: Structural Similarity Index Measure (SSIM)
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At baseline
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Model performance for virtual LGE generation across sequence protocols: Peak Signal-to-Noise Ratio (PSNR)
Časové okno: At baseline
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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.
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At baseline
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Model performance for virtual LGE generation across sequence protocols: DICE coefficient
Časové okno: At baseline
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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.
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At baseline
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Spolupracovníci a vyšetřovatelé
Sponzor
Sponzor
Publikace a užitečné odkazy
Obecné publikace
- Paiva L, Ferreira MJ, Afonso S, Donato P, Goncalves L. Cardiac T1 mapping in non-ST-segment elevation myocardial infarction: temporal changes in myocardial fibrosis. Front Cardiovasc Med. 2025 May 23;12:1563368. doi: 10.3389/fcvm.2025.1563368. eCollection 2025.
- Eichhorn C, Greulich S, Bucciarelli-Ducci C, Sznitman R, Kwong RY, Grani C. Multiparametric Cardiovascular Magnetic Resonance Approach in Diagnosing, Monitoring, and Prognostication of Myocarditis. JACC Cardiovasc Imaging. 2022 Jul;15(7):1325-1338. doi: 10.1016/j.jcmg.2021.11.017. Epub 2022 Jan 12.
- Leong DP, Joseph PG, McKee M, Anand SS, Teo KK, Schwalm JD, Yusuf S. Reducing the Global Burden of Cardiovascular Disease, Part 2: Prevention and Treatment of Cardiovascular Disease. Circ Res. 2017 Sep 1;121(6):695-710. doi: 10.1161/CIRCRESAHA.117.311849.
Termíny studijních záznamů
Hlavní termíny studia
Začátek studia (Aktuální)
Začátek studia
Primární dokončení (Odhadovaný)
Primární dokončení
Dokončení studie (Odhadovaný)
Dokončení studie
Termíny zápisu do studia
První předloženo
První předloženo
První předloženo, které splnilo kritéria kontroly kvality
První předloženo, které splnilo kritéria kontroly kvality
První zveřejněno (Aktuální)
První zveřejněno
Aktualizace studijních záznamů
Poslední zveřejněná aktualizace (Aktuální)
Poslední zveřejněná aktualizace
Odeslaná poslední aktualizace, která splnila kritéria kontroly kvality
Odeslaná poslední aktualizace, která splnila kritéria kontroly kvality
Naposledy ověřeno
Naposledy ověřeno
Více informací
Termíny související s touto studií
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