Optimization of CT angiography using physiologically-informed computational plaques, dynamic XCAT phantoms, and physics-based CT simulation
Cardiovascular disease is a leading cause of death worldwide. Among all cardiovascular diseases, coronary artery disease (CAD) is a major contributor to mortality, accounting for approximately 10% of deaths per annum. Imaging techniques such as computed tomography (CT) can provide information on the location, composition, and severity of disease within the coronary arteries. However, cardiac motion makes protocol optimization for coronary CT angiography (CCTA) image acquisition and reconstruction uniquely challenging. The clinical trials necessary to optimize these protocols require a cohort of diverse patients, clinical staff, and are time-consuming. Consequently, there is a need for safer, less expensive, and faster alternatives. A virtual imaging trial (VIT) enables studies on the optimization of CCTA protocol parameters in a controlled (simulated) environment. In this work, we developed a framework to integrate computational models of CAD with computational, anthropomorphic phantoms (XCAT) and a CT simulator (DukeSim) so that VITs can be performed with these tools to optimize CCTA protocols for clinical tasks. To demonstrate the framework, we included a calcification in the right coronary artery of a 50th percentile BMI male XCAT phantom. The calcification was subjected to cardiac motion (60, 90, 120 BPM) and underwent simulated imaging with and without contrast enhancement (simulating a 370 mgI/mL injection) and was reconstructed via filtered back-projection (FBP) with two kernels (B26f, B70f). Measurements of the right coronary artery under imaging indicated that the small calcification was readily detected below 90 BPM, with no iodinated contrast media, and reconstructed via FBP with the B70f kernel. As demonstrated, this new VIT framework can provide an efficient means or CCTA protocol optimization.
