Key words: Arrhythmogenic Cardiomyopathy, Personalized computational modelling, Digital Twin, Personalized Medicine

"Making it Personal - Model-based Cardiac Tissue Characterization in Arrhythmogenic Cardiomyopathy"

Various risk factors for sudden cardiac death have been identified. For example, several pathogenic mutations in DNA have been identified that cause Arrhythmogenic Cardiomyopathy and thereby an increased risk of sudden cardiac death. However, it is still unknown why on an individual level the outcomes differ between patients with the same diagnosis. In this thesis, the 'Digital Twin' concept was applied, in which an existing biophysical model of the heart and blood vessels was personalized to clinical measurements of the patient and in this way formed a digital mirror of that patient. The Digital Twin can be used to reveal properties of the heart that are normally not available, for example regional disease substrates in the heart muscle. Extensive analyses were used to identify the substrate for patients with Arrhytnmogenic Cardiomyopathy and to follow its development over time. The study showed that this substrate can develop not only at a young age, but also later in life.

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