Detection of Fibrosis in Cine Magnetic Resonance Images Using Artificial Intelligence Techniques

CURIALE, ARIEL H.; CABRERA, FACUNDO; JIMENEZ, PABLO; MEDUS, JORGELINA; MATO, GERMÁN; CALANDRELLI, MATÍAS

Revista Argentina de Cardiologia

Sociedad Argentina de Cardiologia

Año: 2022 vol. 90 p. 130 - 133

Background: Artificial intelligence techniques have demonstrated great potential in cardiology, especially to detect imperceptiblepatterns for the human eye. In this sense, these techniques seem to be adequate to identify patterns in the myocardial texture whichcould lead to characterize and quantify fibrosis.Purpose: The aim of this study was to postulate a new artificial intelligence method to identify fibrosis in cine cardiac magneticresonance (CMR) imaging.Methods: A retrospective observational study was carried out in a population of 75 subjects from a clinical center of San Carlosde Bariloche. The proposed method analyzes the myocardial texture in cine CMR images using a convolutional neural network todetermine local myocardial tissue damage.Results: An accuracy of 89% for quantifying local tissue damage was observed for the validation data set and 70% for the test set. Inaddition, the qualitative analysis showed a high spatial correlation in lesion location.Conclusions: The postulated method enables to spatially identify fibrosis using only the information from cine nuclear magneticresonance studies, demonstrating the potential of this technique to quantify myocardial viability in the future or to study the lesionsetiology