C-arm CT angiography is an established modality for cerebral imaging as it provides very high spatial resolution. Acquisition of two scans, one with injected contrast agent and a mask scan without contrast agent, 3D digital subtraction angiography images (3D DSA) can be computed. While this allows for excellent visualization of the vasculature, the images are not temporally resolved.

In contrast, traditional 2D DSA projection images provide temporally resolved images. However, due to vessel overlap, often multiple acquisitions are necessary, leading to increased dose and contrast agent.

4D DSA is a first approach to combine high spatial resolution and temporal information, using a special image acquisition protocol. It allows us to create 3D volumetric reconstructions of the vasculature with additional temporal information of the blood flow, as the contrast bolus is imaged with 30fps. However, vessel overlap and foreshortening in the projection images can lead to unreliable temporal information and therefore image artifacts, thus appropriate interpolation techniques are required.

Computational Fluid Dynamics (CFD) allows us to simulate blood flow, given a model of the vasculature. The aim of this project is the improvement of 4D DSA image quality using CFD simulations and ultimately blood flow quantification using 4D DSA.This entails an optimization of CFD boundary conditions such that they fit to the 4D DSA data. Based on the CFD results, 4D DSA image quality should be improved. In turn, these results can be iteratively be used to further refine the CFD simulation. Finally, we aim to extract quantitative flow measurements from 4D DSA images.

This project is in cooperation with the Innovation Group of the Angiography & Interventional X-Ray Systems department, Siemens AG, Healthcare Sector, Forchheim.