ReviewDiagnostics (Basel, Switzerland)2023
Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed.
- Clinical application of cardiac computed tomography in cardiomyopathy.The international journal of cardiovascular imaging · 2026Review
- Heart-Brain axis: is microvascular dysfunction the link between stroke and Takotsubo syndrome?The international journal of cardiovascular imaging · 2025Review
- Artificial Intelligence Performance in Cardiac Magnetic Resonance Strain Analysis for Aortic Stenosis: Validation with Echocardiography and Healthy Controls.Medicina (Kaunas, Lithuania) · 2025Article
- Review of the Current State of Artificial Intelligence in Pediatric Cardiovascular Magnetic Resonance Imaging.Children (Basel, Switzerland) · 2025Review
- Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability.Scientific reports · 2025Article
- Cardiovascular magnetic resonance in β-thalassemia major: beyond T2.La Radiologia medica · 2024Review
- Assessing Acute Pericarditis with T1 Mapping: A Supportive Contrast-Free CMR Marker.Tomography (Ann Arbor, Mich.) · 2024Article
- Atrial and ventricular strain using cardiovascular magnetic resonance in the prediction of outcomes of pericarditis patients: a pilot study.European radiology · 2024Article
- Left and right atrioventricular coupling index in patients with beta-thalassemia major.The international journal of cardiovascular imaging · 2024Article
- Atrial and Ventricular Strain Imaging Using CMR in the Prediction of Ventricular Arrhythmia in Patients with Myocarditis.Journal of clinical medicine · 2024Article
- Artificial Intelligence in the Differential Diagnosis of Cardiomyopathy Phenotypes.Diagnostics (Basel, Switzerland) · 2024Review
- AI-powered contrast-free cardiovascular magnetic resonance imaging for myocardial infarction.Frontiers in cardiovascular medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more precise characterization of different cardiovascular diseases. However, contrast media have contraindications and side effects that limit their clinical application in determinant patients. The application of artificial intelligence (AI)-based techniques to CMR imaging has led to the development of non-contrast models. These AI models utilize non-contrast imaging data, either independently or in combination with clinical and demographic data, as input to generate diagnostic or prognostic algorithms. In this review, we provide an overview of the main concepts pertaining to AI, review the existing literature on non-contrast AI models in CMR, and finally, discuss the strengths and limitations of these AI models and their possible future development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.