Quantitative cardiac dual source CT; from morphology to function

Abstract

Cardiovascular diseases are a large contributor to the global mortality rate. Non-invasive imaging techniques, such as computed tomography (CT) imaging, have been playing a growing role in the risk assessment, diagnosis, and prognosis of coronary artery disease (CAD). One of the main challenges in the evaluation of CAD is the establishment of the optimal workflow to evaluate the anatomical as well as the functional aspects of CAD in all phases of the ischemic cascade. The research described in this thesis investigates the possibilities of CT to perform both morphological and functional evaluation of CAD and it is debated whether CT can be used clinically for the visualization of the entire ischemic cascade. Results show that the diagnostic and prognostic value of CT procedures for coronary artery disease evaluation can be improved by adding additional functional information to the anatomical evaluation. This was concluded from research done on two new technologies analyzing the blood flow through the coronaries and through the heart muscle. Besides that, important questions regarding protocol optimization and standardization have been investigated. Although CT shows great potential for the evaluation of CAD, the clinical workflow and combination of techniques to be used is yet to be optimized. Automating processes, for example with the use of Artificial Intelligence (AI), can enhance the clinical implementation and can help the field of cardiac radiology deal with the increased demand for cardiac imaging.