ZusammenfassungThe detection and prediction of cardiac remodeling, especially of subclinical stages therein, is highly relevant for the understanding of cardiovascular disease development and progression as well as its modification. Deep phenotyping applying cardiac magnetic resonance imaging in a large sample allows rigorous identification of subclinical cardiac changes as well as quantification of the intricate relationship between different parameters of cardiac remodeling. Furthermore, a systematic population-based analysis supports the corroboration of the most significant risk factors and their impact on cardiac functioning. We aim at comprehensively quantifying established and innovative CMR-parameters, namely, parameters of left and right ventricular and left atrial function, as well as of diffuse left ventricular myocardial fibrosis of the heart, and assessing their interrelation to provide a sound basis for future epidemiologic association analyses in the NaKo sample. Moreover, to explicitly invest in future technical developments regarding objective, reliable, and valid parameter extraction from large amounts of imaging data, we aim to establish machine learning approaches based on expert validated data. Here, the NaKo provides a unique data set to establish robust standard procedures for future analysis.

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EinrichtungenCharité Universitätsmedizin Berlin, Universitätsklinikum Freiburg, Universität Potsdam, Charite Berlin Buch, Helios Klinikum Berlin-Buch, University of Freiburg, Universitätsklinikum Heidelberg, Helios Klinikum Berlin-Buch, Max-Delbrück-Centrum für Molekulare Medizin (MDC)