Advanced non-invasive diagnostics in congenital heart disease

Abstract

Advances in medical and surgical care have improved survival rates for children with congenital heart disease (CHD), allowing most patients to reach adulthood. As a result, clinical priorities have shifted toward optimizing long-term outcomes and quality of life. This growing population requires reliable diagnostic and prognostic tools to detect early functional changes and guide long-term management.

This thesis evaluates the value of non-invasive diagnostic tools in paediatric CHD patients, focusing on those after Fontan procedures, arterial switch operations (ASO), and Tetralogy of Fallot repair. Three approaches were studied: advanced echocardiography, including tissue Doppler imaging and speckle tracking, cardiopulmonary exercise testing (CPET), and assessment of autonomic nervous system function.

Advanced echocardiography identified subtle ventricular dysfunction not detectable with conventional methods. CPET revealed reduced exercise capacity and demonstrated the prognostic value of both maximal and submaximal parameters, particularly the oxygen uptake efficiency slope (OUES). Autonomic assessments indicated altered sympathetic responses after ASO, suggesting lasting physiological effects of surgery. Additionally, machine learning was explored to identify myocardial function patterns. Overall, this work supports integrating advanced non-invasive diagnostic tools to improve early diagnosis, risk stratification, and individualized follow-up, ultimately enhancing long-term outcomes and quality of life.