In this paper, a novel approach to cardiac interventional navigation on 3D motion-compensated static roadmaps is presented. Current coronary interventions, e.g. percutaneous transluminal coronary angioplasties, are performed using 2D X-ray fluoroscopy. This comes along with well-known drawbacks like radiation exposure, use of contrast agent, and limited visualization, e.g. overlap and foreshortening, due to projection imaging. In the presented approach, the interventional device, i.e. the catheter, is tracked using an electromagnetic tracking system (MTS). Therefore, the catheters position is mapped into a static 3D image of the volume of interest (VOI) by means of an affine registration. In order to compensate for respiratory motion of the catheter with respect to the static image, a parameterized affine motion model is used which is driven by a respiratory sensor signal. This signal is derived from ultrasonic diaphragm tracking. The motion compensation for the heartbeat is done using ECG-gating. The methods are validated using a heart- and diaphragm-phantom. The mean displacement of the catheter due to the simulated organ motion decreases from approximately 9 mm to 1.3 mm. This result indicates that the proposed method is able to reconstruct the catheter position within the VOI accurately and that it can help to overcome drawbacks of current interventional procedures.
In this contribution, we investigate the spatial and temporal resolution of retrospectively gated cardiac cone-beam CT. Data of a static and a dynamic resolution phantom are acquired for various heart rates, table speeds and scanner rotation times. The projection data are reconstructed in different motion states with the help of a
retrospectively gated helical cardiac cone-beam reconstruction method. This multi-cycle method automatically adapts the number of heart cycles used for the reconstruction, based on the scan parameters and the ECG data. The spatial resolution is derived from a resolution phantom by multi-planar reformation (MPR) along the scan