Peter Eshuis

Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

Limited angle c-arm tomography and segmentation for guidance of atrial fibrillation ablation procedures

Angiographic projections of the left atrium (LA) and the pulmonary veins (PV) acquired with a rotational C-arm system are used for 3D image reconstruction and subsequent automatic segmentation of the LA and PV to be used as roadmap in fluoroscopy guided LA ablation procedures. Acquisition of projections at high oblique angulations may be problematic due to increased collision danger of the detector with the right shoulder of the patient. We investigate the accuracy of image reconstruction and model based roadmap segmentation using limited angle C-arm tomography. The reduction of the angular range from 200 degrees to 150 degrees leads only to a moderate increase of the segmentation error from 1.5 mm to 2.0 mm if matched conditions are used in the segmentation, i.e., the model based segmentation is trained on images reconstructed with the same angular range as the test images. The minor decrease in accuracy may be outweighed by clinical workflow improvement, gained when large C-arm angulations can be avoided.

Automated volume of interest delineation and rendering of cone beam CT images in interventional cardiology

Interventional C-arm systems allow the efficient acquisition of 3D cone beam CT images. They can be used for intervention planning, navigation, and outcome assessment. We present a fast and completely automated volume of interest (VOI) delineation for cardiac interventions, covering the whole visceral cavity including mediastinum and lungs but leaving out rib-cage and spine. The problem is addressed in a model based approach. The procedure has been evaluated on 22 patient cases and achieves an average surface error below 2mm. The method is able to cope with varying image intensities, varying truncations due to the limited reconstruction volume, and partially with heavy metal and motion artifacts.

Image quality improvements in C-Arm CT (CACT) for liver oncology applications: Preliminary study in rabbits

Abstract Introduction: C-Arm CT (CACT) is a new imaging modality in liver oncology therapy that allows for the acquisition of 3D images intra-procedurally. CACT has been used to enhance intra-arterial therapies for the liver by improving lesion detection, avoiding non-target embolization, and allowing for more selective delivery of agents. However, one of the limitations of this technology is image artifacts created by respiratory motion. Purpose: To determine in this preliminary study improvements in image acquisition, motion compensation, and high resolution 3D reconstruction that can improve CACT image quality (IQ). Material and methods: Three adult male New Zealand white rabbits were used for this study. First, a control rabbit was used to select the best x-ray acquisition imaging protocol and then two rabbits were implanted with liver tumor to further develop 3D image reconstruction and motion compensation algorithms. Results: The best IQ was obtained using the low 80 kVp protocol with motion compensated reconstruction with high resolution and fast acquisition speed (60 fps, 5 s/scan, and 312 images). Conclusion: IQ improved by: (1) decreasing acquisition time, (2) applying motion-compensated reconstruction, and (3) high resolution 3D reconstruction. The findings of this study can be applied to future animal studies and eventually could be translated into the clinical environment.

Automatic cable artifact removal for cardiac C-arm CT imaging

Cardiac C-arm computed tomography (CT) imaging using interventional C-arm systems can be applied in various areas of interventional cardiology ranging from structural heart disease and electrophysiology interventions to valve procedures in hybrid operating rooms. In contrast to conventional CT systems, the reconstruction field of view (FOV) of C-arm systems is limited to a region of interest in cone-beam (along the patient axis) and fan-beam (in the transaxial plane) direction. Hence, highly X-ray opaque objects (e.g. cables from the interventional setup) outside the reconstruction field of view, yield streak artifacts in the reconstruction volume. To decrease the impact of these streaks a cable tracking approach on the 2D projection sequences with subsequent interpolation is applied. The proposed approach uses the fact that the projected position of objects outside the reconstruction volume depends strongly on the projection perspective. By tracking candidate points over multiple projections only objects outside the reconstruction volume are segmented in the projections. The method is quantitatively evaluated based on 30 simulated CT data sets. The 3D root mean square deviation to a reference image could be reduced for all cases by an average of 50 % (min 16 %, max 76 %). Image quality improvement is shown for clinical whole heart data sets acquired on an interventional C-arm system.

First pass cable artefact correction for cardiac C-arm CT imaging.

Cardiac C-arm CT imaging delivers a tomographic region-of-interest reconstruction of the patients heart during image guided catheter interventions. Due to the limited size of the flat detector a volume image is reconstructed, which is truncated in the cone-beam (along the patient axis) and the fan-beam (in the transaxial plane) direction. To practically address this local tomography problem correction methods, like projection extension, are available for first pass image reconstruction. For second pass correction methods, like metal artefact reduction, alternative correction schemes are required when the field of view is limited to a region-of-interest of the patient. In classical CT imaging metal artefacts are corrected by metal identification in a first volume reconstruction and generation of a corrected projection data set followed by a second reconstruction. This approach fails when the metal structures are located outside the reconstruction field of view. When a C-arm CT is performed during a cardiac intervention pacing leads and other cables are frequently positioned on the patients skin, which results in propagating streak artefacts in the reconstruction volume. A first pass approach to reduce this type of artefact is introduced and evaluated here. It makes use of the fact that the projected position of objects outside the reconstruction volume changes with the projection perspective. It is shown that projection based identification, tracking and removal of high contrast structures like cables, only detected in a subset of the projections, delivers a more consistent reconstruction volume with reduced artefact level. The method is quantitatively evaluated based on 50 simulations using cardiac CT data sets with variable cable positioning. These data sets are forward projected using a C-arm CT system geometry and generate artefacts comparable to those observed in clinical cardiac C-arm CT acquisitions. A C-arm CT simulation of every cardiac CT data set without cables served as a ground truth. The 3D root mean square deviation between the simulated data set with and without cables could be reduced for 96% of the simulated cases by an average of 37% (min -9%, max 73%) when using the first pass correction method. In addition, image quality improvement is demonstrated for clinical whole heart C-arm CT data sets when the cable removal algorithm was applied.