C. Haase, D. Schäfer, O. Dössel, and M. Grass. Model based 3D CS-catheter tracking from 2D X-ray projections: binary versus attenuation models. In Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society, vol. 38(3) , pp. 224-231, 2014
Tracking the location of medical devices in interventional X-ray data solves different problems. For example the motion information of the devices is used to determine cardiac or respiratory motion during X-ray guided procedures or device features are used as landmarks to register images. In this publication an approach using a 3D deformable catheter model is presented and used to track a coronary sinus (CS) catheter in 3D plus time through a complete rotational angiography sequence. The benefits of using voxel based models with attenuation information for 2D/3D registration are investigated in comparison to binary catheter models. The 2D/3D registration of the model allows to extract a 3D catheter shape from every individual 2D projection. The tracking accuracy is evaluated on simulated and clinical rotational angiography data of the contrast enhanced left atrium. The quantitative evaluation of the experiments delivers an average registration accuracy for all catheter electrodes of 0.23 mm in 2D and 0.95 mm in 3D when using an attenuation model of the catheter. The overall tracking accuracy is lower when using binary catheter models.
Cardiac ablation procedures during electrophysiology interventions are performed under x-ray guidance with a C-arm imaging system. Some procedures require catheter navigation in complex anatomies like the left atrium. Navigation aids like 3D road maps and external tracking systems may be used to facilitate catheter navigation. As an alternative to external tracking a fully automatic method is presented here that enables the calculation of the 3D location of the ablation catheter from individual 2D x-ray projections. The method registers a high resolution, deformable 3D attenuation model of the catheter to a 2D x-ray projection. The 3D localization is based on the divergent beam projection of the catheter. On an individual projection, the catheter tip is detected in 2D by image filtering and a template matching method. The deformable 3D catheter model is adapted using the projection geometry provided by the C-arm system and 2D similarity measures for an accurate 2D/3D registration. Prior to the tracking and registration procedure, the deformable 3D attenuation model is automatically extracted from a separate 3D cone beam CT reconstruction of the device. The method can hence be applied to various cardiac ablation catheters. In a simulation study of a virtual ablation procedure with realistic background, noise, scatter and motion blur an average 3D registration accuracy of 3.8 mm is reached for the catheter tip. In this study four different types of ablation catheters were used. Experiments using measured C-arm fluoroscopy projections of a catheter in a RSD phantom deliver an average 3D accuracy of 4.5 mm.
Cardiac C-arm CT imaging delivers a tomographic region-of-interest reconstruction of the patient's 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.
Purpose: Three-dimensional (3-D) reconstruction of the coronary arteries during a cardiac catheter-based intervention can be performed from a C-arm based rotational x-ray angiography sequence. It can support the diagnosis of coronary artery disease, treatment planning, and intervention guidance. 3-D reconstruction also enables quantitative vessel analysis, including vessel dynamics from a time-series of reconstructions.Methods: The strong angular undersampling and motion effects present in gated cardiac reconstruction necessitate the development of special reconstruction methods. This contribution presents a fully automatic method for creating high-quality coronary artery reconstructions. It employs a sparseness-prior based iterative reconstruction technique in combination with projection-based motion compensation.Results: The method is tested on a dynamic software phantom, assessing reconstruction accuracy with respect to vessel radii and attenuation coefficients. Reconstructions from clinical cases are presented, displaying high contrast, sharpness, and level of detail.Conclusions: The presented method enables high-quality 3-D coronary artery imaging on an interventional C-arm system.
E. Hansis, D. Schäfer, O. Dössel, and M. Grass. Evaluation of iterative sparse object reconstruction from few projections for 3-D rotational coronary angiography. In IEEE Transactions on Medical Imaging, vol. 27(11) , pp. 1548-1555, 2008
A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the heart's motion, rotational coronary angiography typically provides only 5-10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the mbiL(1) norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved.
E. Hansis, D. Schäfer, O. Dössel, and M. Grass. Automatic optimum phase point selection based on centerline consistency for 3D rotational coronary angiography. In International Journal of Computer Assisted Radiology and Surgery, vol. 3(3-4) , pp. 355-361, 2008
The quality of three-dimensional (3D) reconstructions of the coronary arteries from rotational coronary angiography depends on the selected phase point. Inconsistencies in the projection data, due to heart motion, degrade the image quality. Here, a method for the automatic selection of the optimum phase points for reconstruction is presented.The method aims at determining heart phases with minimum inconsistency of the motion state in the selected projection data. This is achieved by calculating an error measure which describes the inconsistency of the vessel centerline geometry in three dimensions for all cardiac phases. The phases with minimum inconsistency are then selected as optimum reconstruction phases. The method's feasibility was tested on 22 clinical cases. One late-diastolic and one end-systolic optimum phase were determined automatically for each case. For comparison, three observers visually determined the optimum phases.Overall, 82% of the 44 automatically determined phases delivered optimum image quality, only 5% showed considerably lower quality than the visually determined optimum phase. For all 22 cases at least one of the two automatically determined phases yielded optimum quality.In a first test the method proved to robustly determine optimum reconstruction phase points.
E. Hansis, D. Schäfer, O. Dössel, and M. Grass. Projection-based motion compensation for gated coronary artery reconstruction from rotational x-ray angiograms. In Physics in Medicine and Biology, vol. 53(14) , pp. 3807-3820, 2008
Three-dimensional reconstruction of coronary arteries can be performed during x-ray-guided interventions by gated reconstruction from a rotational coronary angiography sequence. Due to imperfect gating and cardiac or breathing motion, the heart's motion state might not be the same in all projections used for the reconstruction of one cardiac phase. The motion state inconsistency causes motion artefacts and degrades the reconstruction quality. These effects can be reduced by a projection-based 2D motion compensation method. Using maximum-intensity forward projections of an initial uncompensated reconstruction as reference, the projection data are transformed elastically to improve the consistency with respect to the heart's motion state. A fast iterative closest-point algorithm working on vessel centrelines is employed for estimating the optimum transformation. Motion compensation is carried out prior to and independently from a final reconstruction. The motion compensation improves the accuracy of reconstructed vessel radii and the image contrast in a software phantom study. Reconstructions of human clinical cases are presented, in which the motion compensation substantially reduces motion blur and improves contrast and visibility of the coronary arteries.
Conference Contributions (1)
E. Hansis, D. Schäfer, M. Grass, and O. Dössel. An iterative method for the reconstruction of the coronary arteries from rotational x-ray angiography. In Proc. SPIE, Medical Imaging 2007: Physics of Medical Imaging, vol. 6510, pp. 651026, 2007
Three-dimensional (3D) reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular diseases, compared to two-dimensional X-ray angiograms. Besides improved roadmapping, quantitative analysis of vessel lesions is possible. To perform 3D reconstruction, rotational projection data of the selectively contrast agent enhanced coronary arteries are acquired with simultaneous ECG recording. For the reconstruction of one cardiac phase, the corresponding projections are selected from the rotational sequence by nearest-neighbor ECG gating. This typically provides only 5-10 projections per cardiac phase. The severe angular undersampling leads to an ill-posed reconstruction problem. In this contribution, an iterative reconstruction method is presented which employs regularizations especially suited for the given reconstruction problem. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, we formulate the reconstruction problem as a minimization of the L1-norm of the reconstructed image, which results in a spatially sparse object. Two additional regularization terms are introduced: a 3D vesselness prior, which is reconstructed from vesselness-filtered projection data, and a Gibbs smoothing prior. The regularizations favor the reconstruction of the desired object, while taking care not to over-constrain the reconstruction by too detailed a-priori assumptions. Simulated projection data of a coronary artery software phantom are used to evaluate the performance of the method. Human data of clinical cases are presented to show the method's potential for clinical application.