Abstract
Cardiac diseases are the leading cause of death. Many diseases can be specifically treated once avalid diagnosis is established. Cardiac magnetic resonance imaging (MRI) plays acentral role in the workup of many cardiac pathologies. However, image acquisition as well as interpretation and related secondary image evaluation are time-consuming and complex. Cardiac MRI is becoming increasingly established in international guidelines for the evaluation of cardiac function and differential diagnosis of awide variety of cardiac diseases. Cardiac MRI has limited reproducibility due to the acquisition technique and interpretation of findings with complex secondary measurements. Artificial intelligence techniques and radiomics offer the potential to improve the acquisition, interpretation, and reproducibility of cardiac MRI. Research suggests that artificial intelligence and radiomic analysis can improve cardiac MRI in terms of image acquisition and also diagnostic and prognostic value. Furthermore, the implementation of artificial intelligence and radiomics may result in the identification of new biomarkers. The implementation of artificial intelligence in cardiac MRI has great potential. However, the current level of evidence is still limited in some aspects; in particular there are too few prospective and large multicenter studies available. As aresult, the algorithms developed are often not sufficiently validated scientifically and are not yet applied in clinical routine.
Published Version
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