Hypertrophic, dilated and arrhythmogenic cardiomyopathies are a major cause of heart failure and sudden death. Current management guidelines recommend the use of risk stratification algorithms, to help with important decisions regarding medication initiation/uptitration and devices use, including implantable cardioverter-defibrillators or cardiac resynchronization therapy. These algorithms and scores are mainly comprised of symptomatic status and a few imaging and/or ambulatory ECG markers.
A significant proportion of heart muscle disease is genetically caused and a pathogenic/likely pathogenic variant can be found in around 40-50% of index cases. Advances in genetics have allowed for an increasing diagnostic certainty and optimized family screening processes. An influence of genetics in prognosis and outcomes has also been reported in the last few years but it is yet to be integrated in decision-making recommendations.
Great advances in cardiac imaging have also been described in the context of heart muscle disease, including myocardial deformation techniques, scar imaging, perfusion imaging, and tissue characterization. These have provided new insights regarding previously unknown phenotypes, including early disease, and already help with differential diagnosis dilemmas in the daily clinical practice. However, differently from old markers such as ejection fraction and wall thickness, these new imaging parameters have not yet been fully integrated in risk prediction algorithms, despite a number of publications describing associations with events.
The aim of this Research Topic is to gather contributions from Researchers working in the fields of cardiomyopathy genetics and/or cardiomyopathy imaging, who have interest in establishing a role of new genetics and imaging markers for comprehensive risk prediction in cardiomyopathies.
Hypertrophic, dilated and arrhythmogenic cardiomyopathies are a major cause of heart failure and sudden death. Current management guidelines recommend the use of risk stratification algorithms, to help with important decisions regarding medication initiation/uptitration and devices use, including implantable cardioverter-defibrillators or cardiac resynchronization therapy. These algorithms and scores are mainly comprised of symptomatic status and a few imaging and/or ambulatory ECG markers.
A significant proportion of heart muscle disease is genetically caused and a pathogenic/likely pathogenic variant can be found in around 40-50% of index cases. Advances in genetics have allowed for an increasing diagnostic certainty and optimized family screening processes. An influence of genetics in prognosis and outcomes has also been reported in the last few years but it is yet to be integrated in decision-making recommendations.
Great advances in cardiac imaging have also been described in the context of heart muscle disease, including myocardial deformation techniques, scar imaging, perfusion imaging, and tissue characterization. These have provided new insights regarding previously unknown phenotypes, including early disease, and already help with differential diagnosis dilemmas in the daily clinical practice. However, differently from old markers such as ejection fraction and wall thickness, these new imaging parameters have not yet been fully integrated in risk prediction algorithms, despite a number of publications describing associations with events.
The aim of this Research Topic is to gather contributions from Researchers working in the fields of cardiomyopathy genetics and/or cardiomyopathy imaging, who have interest in establishing a role of new genetics and imaging markers for comprehensive risk prediction in cardiomyopathies.
