18 | Chapter 1 THESIS OUTLINE Part I. Deformation imaging methods in ARVC In a clinical evaluation of the diagnostic 2010 TFC, conventional echocardiography lacked sensitivity for ARVC diagnosis.26 This could be partly caused by visual assessment of RV wall motion abnormalities, prerequisite to fulfill a criterion, which is difficult and highly dependent on the observer’s experience. In Chapter 2, we investigated whether inclusion of RV deformation could lead to better detection of ARVC patients by echocardiography compared to conventional echocardiographic methods. While previous studies in ARVC patients and family members from Utrecht identified characteristic regional RV deformation patterns, studies performed in Oslo focused on RV mechanical dispersion, a measure for regional heterogeneity in contraction. Both methods have been successfully applied in subsequent cohorts in the center where they were developed, but were never externally validated. Chapter 3 describes an external validation study for both methods, designed in a way that a single, newly trained observer applied both methods in both cohorts. Besides, we combined data from Utrecht and Oslo to evaluate incremental value of combining the two methods in association to the occurrence of life-threatening ventricular arrhythmia. Part II. Characterizing the disease substrate underlying deformation abnormalities Although the gold standard for characterization of the disease substrate in ARVC is based on histology on tissue acquired by autopsy or biopsy of the thin walled RV, this is not an option in most patients. Deformation abnormalities most likely reflect the local tissue substrate, as was previously supported by simulations with the CircAdapt computer model.12 In this study, a general disease substrate of reduced contractility and increased stiffness was demonstrated. In part II of this thesis, we describe the steps from a general disease simulation to a patient-specific approach with possible clinical applications. This patient-specific cardiac model was used as a so-called Digital Twin, a virtual representation of reality based on a comprehensive physical and functional description of the heart. The idea was to use this Digital Twin to gain more insight in the structural disease substrate in early-stage ARVC. So in a way to use it as a non-invasive myocardial biopsy. The ultimate goal was to try to distinguish arrhythmogenic substrates from the more benign tissue abnormalities leading to deformation abnormalities. In Chapter 4 we apply this patient-specific approach in the cohort of desmosomal pathogenic variant carriers in which the general disease model was first described.27 Deformation data were used as input and the model estimates the underlying disease substrate in a specific patient. Chapter 5 describes the introduction of uncertainty to model estimations. Since both measurements and model estimations introduce uncertainty, this was a necessary step towards longitudinal follow-up of the disease substrate. In Chapter 6, we combined deformation measurements and model estimations to investigate age-related penetrance of ARVC in a longitudinal cohort of patients and family-members without overt structural abnormalities. In a position statement from 2010, it was suggested that serial screening of relatives can be stopped at the age of 50-60 years, due to completed penetrance.28 By monitoring structural progression and occurrence of events in different age groups, we evaluated if penetrance was indeed completed in the older group. Part III. Towards clinical implementation of deformation imaging Part III of this thesis is focused on proceeding deformation imaging into routine clinical practice. Although echocardiographic deformation imaging has already been in use for
RkJQdWJsaXNoZXIy MTk4NDMw