Raoul Florent

The Effect of Automated Marker Detection on in Vivo Volumetric Stent Reconstruction

New drug eluting stents are less radiopaque than bare metal stents and therefore difficult to see with conventional X-ray coronary angiography. 2D StentBoost and intravascular ultrasound (IVUS) are routinely used to evaluate stent deployment and vessel apposition during a percutaneous coronary intervention. IVUS images give cross-sectional information about the stent lumen and surrounding tissue. 2D StentBoost is a boosted angiogram sequence and visualizes the geometry of the deployed stent from a fixed viewing direction. Three-dimensional motion compensated volumetric stent reconstruction has been developed to give insight into the 3D geometry of the stent. Markers on the balloon wire are used to motion compensate cardiac rotational angiography acquisitions. In this paper we present the effect of automated marker detection on in vivo volumetric cardiac stent reconstructions. Automated or semi-automated marker detection reduces user interaction, potentially reduces total processing time, and increases detection results which leads to higher quality of stent reconstructions.

Three-dimensional reconstruction of coronary stents in vivo based on motion compensated x-ray angiography

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.

3D coronary reconstruction from calibrated motion-compensated 2D projections

Abstract One of the application areas of three-dimensional rotational X-ray imaging (3D-RX) techniques is focused on the 3D visualization of coronary vessel structures (3D rotational coronary angiography, 3DRCA). Since the heart is a moving object, only projections can be used, which correspond to the same acquisition time (e.g. end diastole) in the cardiac cycle. This significantly limits the number of projections available for reconstruction causing streaking artefacts in the reconstructed image due to the angular undersampling. The involvement of additional projections in the reconstruction procedure from different viewing angles would increase the quality of the volume data. However, each successive acquired projection is slightly different compared with the previous one due to two reasons: First, a nonlinear movement owing to the heart beat and, second, a linear movement owing to a different viewing angle. In order to use additional projections, the movement due to the different heart phase has to be transformed in the desired prior heart phase and the transformation (motion compensation) must take into account the geometrical rotation of the gantry. Therefore, considering two successive acquired projections and calculating the transformation matrix that transforms one projection into another must include both components. The purpose of this work is to determine and to separate the two mentioned movements and to involve additional projections (acquired at different acquisition geometry and in different motion state) in the reconstruction procedure. Motion-compensated reconstructed volume data will be presented for coronary arteries in an animal (pig) model.

Projection-based motion compensation and reconstruction of coronary segments and cardiac implantable devices using rotational X-ray angiography

Cardiologists use two-dimensional projection images in conventional X-ray coronary angiography for the assessment of three-dimensional structures. During minimally invasive interventions there is a need to clearly visualize and analyze contrast filled coronary arteries, surrounding tissue, and implanted devices. Three-dimensional reconstruction of these structures is challenging due to the cardiac and respiratory motion. In this paper we describe a method to automatically generate motion compensated reconstructions of various structures using rotational X-ray angiography. The method uses markers on a device or guide wire to identify and estimate the motion of an object or region of interest in order to register and motion compensate the projection images to generate a motion compensated reconstruction. The method is evaluated on 20 rotational acquisitions and the average marker couple detection rate is 84% for cardiac stents, 90% for closure devices and 20% for contrast filled coronaries. The projection images are motion compensated based on the semi-automatically detected markers and subsequently used for reconstruction. We conclude that it is feasible to reconstruct cardiac stents, closure devices, contrast filled coronaries, and calcified plaques using rotational X-ray angiography.

Model-based segmentation of the left main coronary bifurcation from 2D angiograms

This paper deals with the identification of the left main coronary bifurcation (LMB) in 2D angiograms. We resort to a generic 3D model of the LMB that is projected in the proper angulation to retrieve the expected 2D skeleton of the LMB in the considered image. We derive from it an efficient discriminating filter that allows detecting the LMB, while being robust to anatomical variations. We demonstrate the potential of the method over a large database of 120 angiographic sequences from 15 patients. We also propose a method extension that exploits not only the present angiography, but also the previous ones, as acquired in the course of the exam.

Decomposing the bony thorax in X-ray images

The identification and segmentation of target objects from medical images is often confused by other more salient objects in the image. This is a specific problem for X-ray projection images where the shadows of semi-transparent objects are overlaid. A bone shadow may confuse the automated detection of other crossing bones and of important soft tissue findings in the lung like lung nodules. We present a method to identify and remove such bone shadows from a chest radiograph for the purpose of suppressing all bone shadows overlapping with the lung field in a standard posterior-anterior view. In this context an elegant novel approach to the problem of identifying and segmenting overlaid objects is followed: Disturbing objects are identified first and literally removed from the image, therefore no longer confusing the detection of other more subtle objects. This method allowed the identification, segmentation, and suppression of the clavicles, the posterior and the anterior parts of the ribs - one after another. In a clinical study the detection of lung nodules by experienced radiologists was improved after bone suppression.

Advanced Visibility Enhancement for Stents and Other Devices: Image Processing Aspects

In non-contrast-enhanced x-ray sequences, the image quality of stents can be enhanced by motion compensating and integrating images of exposure sequences. Three-dimensional stent reconstruction has been developed to allow enhanced stent visualization and assessment in three dimensions. This article gives an overview of the different methods used for enhanced stent visualization, describes studies that have evaluated these methods, and summarizes results of these methods on other cardiac and non-cardiac devices.

Geometry-constrained coronary arteries motion estimation from 2D angiograms - Application to injection side recognition

This paper deals with the 2D motion estimation of coronary arteries. It exploits the geometry of acquisition to strongly constrain the problem, thereby ensuring smooth and robust motion fields.

Device enhancement using rotational X-ray angiography

Implantable cardiac devices, such as stents and septal defect closure devices are sometimes difficult to see on angiographic X-ray projection images. We present a method to enhance the visibility of these devices in rotational X-ray angiography acquisitions using automated marker detection and motion compensation. Automatic marker detection allows registration of the devices in the images of the rotational run. Motion compensation is done by warping the images to a specific reference position. Averaging multiple of those motion compensated images together with the reference frame results in an enhanced image with improved visibility due to an increase in contrast of the device with the background structure. This allows the clinician to look at the device from multiple angles with an improved visibility of the device to better appreciate the 3D geometry of the device. In particular, enhancement of rotational acquisitions compared to standard enhanced fixed-angle acquisitions allows the clinician to better perceive any asymmetry in the deployed device.

Abdominal arteries recognition in x-ray using a structural model

The automatic recognition of vascular trees is a challenging task, required for roadmapping or advanced visualization. For instance, during an endovascular aneurysm repair (EVAR), the recognition of abdominal arteries in angiograms can be used to select the appropriate stent graft. This choice is based on a reduced set of arteries (aorta, renal arteries, iliac arteries) whose relative positions are quite stable. We propose in this article a recognition process based on a structural model. The centerlines of the target vessels are represented by a set of control points whose relative positions are constrained. To find their position in an angiogram, we enhance the target vessels and extract a set of possible positions for each control point. Then, a constraint propagation algorithm based on the model prunes those sets of candidates, removing inconsistent ones. We present preliminary results on 5 cases, illustrating the potential of this approach and especially its ability to handle the high variability of the target vessels.