Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach

ConclusionThe current study demonstrated that using a ML model, multi chamber myocardial strain, and function on non-contrast CMR parameters enables the discrimination between ICM and NICM with competitive diagnostic accuracy.Clinical relevance statementA machine learning model based on non-contrast cardiovascular magnetic resonance parameters may discriminate between ischemic and non-ischemic cardiomyopathy enabling wider access to cardiovascular magnetic resonance examinations with lower costs and faster imaging acquisition.Key Points• The exponential growth in cardiovascular magnetic resonance examinations may require faster and more cost-effective protocols.• Artificial intelligence models can be utilized to distinguish between ischemic and non-ischemic etiologies.• Machine learning using non-contrast CMR parameters can effectively distinguish between ischemic and non-ischemic cardiomyopathies.Graphical Abstract
Source: European Radiology - Category: Radiology Source Type: research