Abstract:

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.

Abstract:

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.

Abstract:

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.

Abstract:

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.

Abstract:

The tomographic reconstruction of the beating heart requires dedicated methods. One possibility is gated reconstruction, where only data corresponding to a certain motion state are incorporated. Another one is motioncompensated reconstruction with a pre-computed motion vector field, which requires a preceding estimation of the motion. Here, results of a new approach are presented: simultaneous reconstruction of a three-dimensional object and its motion over time, yielding a fully four-dimensional representation. The object motion is modeled by a time-dependent elastic transformation. The reconstruction is carried out with an iterative gradient-descent algorithm which simultaneously optimizes the three-dimensional image and the motion parameters. The method was tested on a simulated rotational X-ray acquisition of a dynamic coronary artery phantom, acquired on a C-arm system with a slowly rotating C-arm. Accurate reconstruction of both absorption coefficient and motion could be achieved. First results from experiments on clinical rotational X-ray coronary angiography data are shown. The resulting reconstructions enable the analysis of both static properties, such as vessel geometry and cross-sectional areas, and dynamic properties, like magnitude, speed, and synchrony of motion during the cardiac cycle.

Abstract:

Three-dimensional (3-D) reconstruction of the coronary arteries from a rotational X-ray angiography sequence can support diagnosis of coronary artery disease, treatment planning, and intervention guidance during catheter interventions. 3-D reconstruction enables quantitative vessel analysis, including vessel dynamics from a time-series of reconstructions. This contribution presents a method for reconstructing coronary arteries with high contrast and high level of detail. It employs an iterative reconstruction algorithm in combination with projection-based motion compensation. An efficient implementation using a graphics processing unit delivers reconstruction times close to clinically acceptable values. Reconstructions from clinical human cases, acquired on an interventional C-arm system, are presented. Excellent image quality is achieved.

Abstract:

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.