Exploring the EVolution in PrognOstic CapabiLity of MUltisequence Cardiac MagneTIc ResOnance in PatieNts Affected by Takotsubo Cardiomyopathy Based on Machine Learning Analysis: Design and Rationale of the EVOLUTION Study.

Riccardo CauGiuseppe MuscogiuriFrancesco PisuMarco GattiBirgitta VelthuisChristian LoeweFilippo CademartiriGianluca PontoneRoberta MontisciMarco GuglielmoSandro SironiAntonio EspositoMarco FranconeNicholas DacherCharles PeeblesGorka BastarrikaRodrigo SalgadoLuca Saba

Published in: Journal of thoracic imaging (2023)

The main goal of the study is to develop a comprehensive clinical and imaging score, that includes TTE and CMR data, in a large cohort of TTC patients for risk stratification and outcome prediction as a basis for possible changes in patient management.

Keyphrases

magnetic resonance
machine learning
end stage renal disease
newly diagnosed
ejection fraction
prognostic factors
peritoneal dialysis
heart failure
deep learning
photodynamic therapy
magnetic resonance imaging
patient reported outcomes