Knowledge of patient-specific cardiac anatomy is required for catheter-based ablation in epicardial ablation
procedures such as ventricular tachycardia (VT) ablation interventions. In particular, knowledge of
critical structures such as the coronary arteries is essential to avoid collateral damage. In such ablation
procedures, ablation catheters are brought in via minimally-invasive subxiphoid access. The catheter is
then steered to ablation target sites on the left ventricle (LV). During the ablation and catheter navigation
it is of vital importance to avoid damage of coronary structures. Contrast-enhanced rotational X-ray
angiography of the coronary arteries delivers a 3D impression of the anatomy during the time of intervention.
Vessel modeling techniques have been shown to be able to deliver accurate 3D anatomical models
of the coronary arteries. To simplify epicardial navigation and ablation, we propose to overlay coronary
arterial models, derived from rotational X-ray angiography and vessel modeling, onto real-time X-ray
fluoroscopy. In a preclinical animal study, we show that overlay of intra-operatively acquired 3D arterial
models onto X-ray helps to place ablation lesions at a safe distance from coronary structures. Example
ablation lesions have been placed based on the model overlay at reasonable distances between key arterial
vessels and on top of marginal branches.
The complete expansion of the stent during a percutaneous transluminal coronary angioplasty (PTCA) procedure is
essential for treatment of a stenotic segment of a coronary artery. Inadequate expansion of the stent is a major
predisposing factor to in-stent restenosis and acute thrombosis. Stents are positioned and deployed by fluoroscopic
guidance. Although the current generation of stents are made of materials with some degree of radio-opacity to detect
their location after deployment, proper stent expansion is hard to asses. In this work, we introduce a new method for the
three-dimensional (3D) reconstruction of the coronary stents in-vivo utilizing two-dimensional projection images
acquired during rotational angiography (RA). The acquisition protocol consist of a propeller rotation of the X-ray C-arm
system of 180°, which ensures sufficient angular coverage for volume reconstruction. The angiographic projections were
acquired at 30 frames per second resulting in 180 projections during a 7 second rotational run. The motion of the stent is
estimated from the automatically tracked 2D coordinates of the markers on the balloon catheter. This information is used
within a motion-compensated reconstruction algorithm. Therefore, projections from different cardiac phases and motion
states can be used, resulting in improved signal-to-noise ratio of the stent. Results of 3D reconstructed coronary stents in
vivo, with high spatial resolution are presented. The proposed method allows for a comprehensive and unique
quantitative 3D assessment of stent expansion that rivals current X-ray and intravascular ultrasound techniques.
KEYWORDS: Arteries, Angiography, X-rays, 3D image processing, 3D image reconstruction, 3D acquisition, Data acquisition, X-ray imaging, Sensors, Imaging systems
A method is proposed that allows for a fully automated computation of a series of high-resolution volumetric reconstructions
of a patient's coronary arteries based on a single rotational acquisition. During the 7.2 second acquisition
the coronary arteries are injected with contrast material while the imaging system rotates around the patient to obtain a
series of X-ray projection images over an angular range of 180 degrees. Based on the simultaneously recorded ECG-signal
the projection images corresponding to the same cardiac cycle can be utilized to reconstruct three-dimensional
(3D) high-spatial-resolution angiograms of the coronary arteries in multiple (3D+t) cardiac phases within the cardiac
cycle. The proposed acquisition protocol has been applied to 22 patients and the tomograpic reconstructions depicted
the main arteries as well as the main bifurcations in multiple cardiac phases in all enrolled patients. For the first
time, this feasibility study shows that a three-dimensional description of the coronary arteries can be obtained intraprocedurally
in a conventional interventional suite by means of tomographic reconstruction from projection images without any user interaction.
KEYWORDS: 3D modeling, Calibration, 3D image processing, Arteries, Data acquisition, Angiography, Data modeling, Image segmentation, X-rays, Systems modeling
For the diagnosis of ischemic heart disease, accurate quantitative analysis of the coronary arteries is important. In coronary angiography, a number of projections is acquired from which 3D models of the coronaries can be reconstructed. A signifcant limitation of the current 3D modeling procedures is the required user interaction
for defining the centerlines of the vessel structures in the 2D projections. Currently, the 3D centerlines of the coronary tree structure are calculated based on the interactively determined centerlines in two projections. For every interactively selected centerline point in a first projection the corresponding point in a second projection has to be determined interactively by the user. The correspondence is obtained based on the epipolar-geometry. In this paper a method is proposed to retrieve all the information required for the modeling procedure, by the interactive determination of the 2D centerline-points in only one projection. For every determined 2D centerline-point the corresponding 3D centerline-point is calculated by the analysis of the 1D gray value functions of the corresponding epipolarlines in space for all available 2D projections. This information is then used to build a 3D representation of the coronary arteries using coronary modeling techniques. The approach is illustrated on the analysis of calibrated phantom and calibrated coronary projection data.
KEYWORDS: Heart, 3D image processing, 3D modeling, 3D image reconstruction, Calibration, Motion models, 3D acquisition, Angiography, Animal model studies, Data modeling
3D rotational coronary angiography (3DRCA) is one of the
application areas of 3D rotational X-Ray imaging. In this
application a sequence of projection images is acquired when the
C-arm is rotated around the patient. Since the heart is a moving
object, only projections can be used which correspond to the same
phase of the cardiac cycle. This significantly limits the number
of projections available for reconstruction causing streaking
artefacts in the reconstructed image due to angular undersampling.
The involvement of additional projections in the reconstruction
procedure from different viewing angles would increase the quality
of the volume data. Each successive acquired projection is
slightly different compared with the previous one due to two
reasons: First, there is a motion to the deformation of the heart,
second there is an induced deformation owing to the change in the
projection angle. The purpose of this work is to determine the
motion owing to the heart deformation, so as to compensate for
this motion in projection images in a different heart phase.
Hereto we propose to use concepts from coronary modeling in
combination of conventional reconstruction procedures. The
proposed method facilitates the use of additional projections in
the reconstruction. Motion-compensated reconstructed volume data
are presented for coronary arteries in an animal (pig) model.
KEYWORDS: 3D image processing, 3D image reconstruction, Heart, 3D modeling, Angiography, 3D acquisition, Image segmentation, Arteries, Electrocardiography, 3D metrology
Three-dimensional rotational coronary angiography (3DRCA) is a new
technique for imaging coronary vessels in the human body. Due to
the residual cardiac motion, projections being in the same cardiac
motion state are extracted from the acquired series using
electrocardiogram (ECG) information. A gating window is determined
at a pre-defined trigger delay relative to the R-peaks with a
constant width. In order to achieve the best possible image
quality, cardiac phases must be found during which the heart is
nearly stationary. However, the (ECG) signal represents the
electrical activity of the heart and corresponds to the heart
movement only approximately. Currently, the optimum gating window
positioning is based on values derived by experience. It is
difficult to determine where the heart is most stable in the cycle
due to a high patient variability. Furthermore, the optimal gating
window position is depending on the coronary vessel segment. The
purpose of this work is to introduce a simple and efficient image
based technique, which is able to determine the optimal gating
window position fully automatically. The measurements in this
paper are based on the analysis of two-dimensional X-ray
projection data of the coronary arteries in an animal (pig) model.
A new approach for 3D vessel centreline extraction using multiple, ECG-gated, calibrated X-ray angiographic projections of the coronary arteries is described. The proposed method performs direct extraction of 3D vessel centrelines, without the requirement to either first compute prior 2D centreline estimates, or perform a complete volume reconstruction. A front propagation-based algorithm, initialised with one or more 3D seed points, is used to explore a volume of interest centred on the projection geometry's isocentre. The expansion of a 3D region is controlled by forward projecting boundary points into all projection images to compute vessel response measurements, which are combined into a 3D propagation speed so that the front expands rapidly when all projection images yield high vessel responses. Vessel centrelines are obtained by reconstructing the paths of fastest propagation. Based on these axes, a volume model of the coronaries can be constructed by forward projecting axis points into the 2D images where the borders are detected. The accuracy of the method was demonstrated via a comparison of automatically extracted centrelines with 3D centrelines derived from manually segmented projection data.
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