Cardiovascular diseases, including coronary artery disease (CAD), are one of the leading causes of death globally. Computed tomography (CT) allows for non-invasive evaluation of the heart and coronary arteries. By evaluation of the coronary anatomy and morphology of plaques, narrowing of the lumen can be defined as degree of coronary stenosis. However, a significant degree of coronary stenosis does not necessarily imply myocardial ischemia.
Recent developments in CT hardware and software technique might allow for functional analysis of CAD. The aim of this thesis was to evaluate the diagnostic performance of both anatomical and functional analysis on CT for the evaluation of CAD. As the interest in CT as a tool for the evaluation of cardiovascular disease is increasing, the secondary aim of this thesis was to reduce the drawbacks of CT.
Major drawback of CT are the use of ionizing radiation dose and the need for injection of iodinated contrast media. Typically, a cardiac CT investigation for CAD evaluation comprises a non-contrast cardiac CT scan followed by a contrast enhanced coronary CT scan (CCTA). Quantification of atherosclerotic calcifications is performed on the non-contrast CT to identify patients at risk for adverse cardiovascular events. In this thesis we showed that these calcifications can be quantified on CT scans acquired at reduced radiation dose. We found that iterative reconstruction, an alternative method to reconstruct acquired images, allowed for even further dose reduction. The contrast enhanced coronary CT scan is performed to evaluate CAD in the coronary lumen. Results of our phantom studies showed that with the use of dual-energy CT (DECT), iodinated contrast media concentrations can be reduced without loss of objective image quality. And that gadolinium can be used as an alternative contrast agent for DECT acquisitions.
In this thesis we showed that DECT allows for accurate iodine quantification. Because iodine quantification in the myocardium is a surrogate for myocardial perfusion, this opens up the possibilities for functional analysis of CAD. In additional patients studies we showed that CT software techniques (namely CCTA-derived fractional flow reserve and deep learning) allowed for functional analysis of CAD and increased the diagnostic performance of CT. A clinical study in which these CT hardware and software techniques are combined to improve the specificity of CT was proposed, and is currently ongoing.
A combined evaluation of both anatomical and functional analysis improves the diagnostic performance of CT for the diagnosis of functionally significant CAD. The ongoing clinical study will clarify to what extent the diagnostic performance of CT can be improved. Additionally, iterative reconstruction and DECT can be used to reduce major drawbacks of CT. With an improved diagnostic performance and reduction of drawbacks, CT might become an even more important tool for the detection, visualization and evaluation of cardiovascular disease.