Regis Vaillant

Model-Based Detection of Tubular Structures in 3D Images

Detection of tubular structures in 3D images is an important issue for vascular medical imaging. We present in this paper a new approach for centerline detection and reconstruction of 3D tubular structures. Several models of vessels are introduced for estimating the sensitivity of the image second-order derivatives according to elliptical cross section, to curvature of the axis, or to partial volume effects. Our approach uses a multiscale analysis for extracting vessels of different sizes according to the scale. For a given model of vessel, we derive an analytic expression of the relationship between the radius of the structure and the scale at which it is detected. The algorithm gives both centerline extraction and radius estimation of the vessels allowing their reconstruction. The method has been tested on synthetic images, an image of a phantom, and real images, with encouraging results.

Reconstruction of coronary arteries from a single rotational X-ray projection sequence

Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in two-dimensional projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a three-dimensional (3-D) model of coronary arteries, e.g., for absolute 3-D measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this paper, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of three main consecutive steps: 1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation; 2) coronary artery four-dimensional motion computation; 3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.

VOIDD: automatic vessel of intervention dynamic detection in PCI procedures

In this article, we present the work towards improving the overall workflow of the Percutaneous Coronary Interventions (PCI) procedures by capacitating the imaging instruments to precisely monitor the steps of the procedure. In the long term, such capabilities can be used to optimize the image acquisition to reduce the amount of dose or contrast media employed during the procedure. We present the automatic VOIDD algorithm to detect the vessel of intervention which is going to be treated during the procedure by combining information from the vessel image with contrast agent injection and images acquired during guidewire tip navigation. Due to the robust guidewire tip segmentation method, this algorithm is also able to automatically detect the sequence corresponding to guidewire navigation. We present an evaluation methodology which characterizes the correctness of the guide wire tip detection and correct identification of the vessel navigated during the procedure. On a dataset of 2213 images from 8 sequences of 4 patients, VOIDD identifies vessel-of-intervention with accuracy in the range of 88% or above and absence of tip with accuracy in range of 98% or above depending on the test case.

Registration of Three-Dimensional Left Atrial Computed Tomographic Images With Projection Images Obtained Using Fluoroscopy

Background— Anatomic structures such as the left atrium and the pulmonary veins (PVs) are not delineated by fluoroscopy because there is no contrast differentiation between them and the surrounding anatomy. Representation of an anatomic structure via a 3D model obtained from computed tomography (CT) imaging and subsequent projection of these images over the fluoroscopy system may help in navigation of the mapping and ablation catheter to the appropriate sites during electrophysiology procedures. Methods and Results— In this feasibility study, in vitro experiments were performed with a plastic heart model (phantom) with 2 catheters or radiopaque platinum beads placed in the phantom at the time of CT imaging and fluoroscopy. Subsequently, 20 consecutive patients underwent contrast-enhanced, ECG-gated CT scanning. Left atrial volumes were generated from the reconstructed data at ≈75% of the R-R interval during the cardiac cycle. Similarly, the superior vena cava and the coronary sinus were also reconstructed from these images. During the electrophysiology procedure, digital records (cine sequences) were obtained. Using predetermined algorithms, both the phantom model and the patients’ 3D left atrial models derived from the CT were registered with projection images of fluoroscopy. Registration was performed with a transformation that linked the superior vena cava and the coronary sinus from the CT model with a catheter placed inside the coronary sinus via the superior vena cava. Registration was successfully accomplished with the plastic phantom and in all 20 patients. Registration accuracy was assessed in the phantom by assessing the overlapping beads seen both in the CT and the fluoroscopy images. The mean registration error was 1.4 mm (range 0.9 to 2.3 mm). Accuracy of the registered images was assessed in patients with recordings from a basket catheter placed sequentially in the superior PVs and by injecting contrast into the PVs to assess overlapping of contrast-filled PVs with the corresponding vessels on the registered images. The images could be calibrated quite accurately. Any rotational error, which was usually minor, could be corrected by rotating the images as needed. Conclusions— Registration of 3D models of the left atrium and PVs with fluoroscopic images of the same is feasible and could enable appropriate navigation and localization of the mapping and ablation catheter during procedures such as atrial fibrillation ablation.

Fully Automatic 3D/2D Subtracted Angiography Registration

Today, 3-D angiography volumes are routinely generated from rotational angiography sequences. In previous work [7], we have studied the precision reached by registering such volumes with classical 2-D angiography images, inferring this matching only from the sensors of the angiography machine. The error led by such a registration can be described as a 3-D rigid motion composed of a large translation and a small rotation.

Motion Correction for Coronary Stent Reconstruction From Rotational X-ray Projection Sequences

This paper presents a new method for 3-D tomographic reconstruction of stent in X-ray cardiac rotational angiography. The method relies on 2-D motion correction from two radiopaque markerballs located on each side of the stent. The two markerballs are on a guidewire and linked to the balloon, which is introduced into the artery. Once the balloon has been inflated, deflated, and the stent deployed, a rotational sequence around the patient is acquired. Under the assumption that the guidewire and the stent have the same 3-D motion during rotational acquisition, we developed an algorithm to correct cardiac stent motion on the 2-D X-ray projection images. The 3-D image of the deployed stent is then reconstructed with the Feldkamp algorithm using all the available projections. Although the correction is an approximation, we show that the intrinsic geometrical error of our method has no visual impact on the reconstruction when the 2-D markerball centers are exactly detected and the markerballs have the same 3-D motion as the stent. Qualitative and quantitative results on simulated sequences under different realistic conditions demonstrate the robustness of the method. Finally, results from animal data acquired on a rotational angiography device are presented.

Automatic trinocular 3D reconstruction of coronary artery centerlines from rotational X-ray angiography

We present a method for fully automatic 3D reconstruction of coronary artery centerlines using three X-ray angiogram projections from a single rotating monoplane acquisition. The reconstruction method consists of three steps: (1) filtering and segmenting the images using a multiscale analysis, (2) matching points in two of the segmented images using the information from the third image, and (3) reconstructing in 3D the matched points. This method needs good calibration of the system geometry and requires breatheld acquisitions. The final algorithm is formulated as an energy minimization problem that we solve using dynamic programming optimization. This method provides a fast and automatic way to compute 3D models of vessels centerlines. It has been applied to both phantoms, for validation purposes, and patient data sets.

Accuracy and usefulness of fusion imaging between three-dimensional coronary sinus and coronary veins computed tomographic images with projection images obtained using fluoroscopy

AIMS Coronary sinus (CS) and coronary veins are not delineated by fluoroscopy. The study evaluates the feasibility and accuracy of cardiac tomography (CT) image registration of CS anatomy on fluoroscopic image. METHODS AND RESULTS Eighteen consecutive patients underwent contrast-enhanced, ECG-gated CT scanning. Coronary sinus, coronary veins, superior vena cava, the distal portion of the trachea, and of the two main bronchi were reconstructed. These images were then fused over the CS fluoroscopic angiogram. Registration accuracy was verified by assessing the overlap of CS borders both in the CT- and in the fluoroscopy-derived images. The mean distance between the centrelines of the CS was 0.73 mm, with a maximum distance of 2.22 mm. For the first-order branches, mean distance was 0.80 mm with a maximum distance of 2.64 mm. High Lin concordance correlation coefficients were computed (>0.95) for the CS and first-order branch diameters, although the Bland and Altman limits were large. The agreement between the number of vessels identified was moderate with kappa = 0.43. CONCLUSION Fusion imaging processing of two different imaging modalities (CT and fluoroscopy) may be feasible and accurate for guiding CRT implantation as it allows constant comprehensive display of CS body and branches. Prospective studies are needed for assessing clinical implications.

Machine precision assessment in 3D/2D digital subtracted angiography image registration

During an interventional neuroradiology exam, knowing the exact location of the catheter tip with respect to the patient can dramatically help the physician. An image registration between digital subtracted angiography (DSA) images and a volumic pre-operative image (magnetic resonance or computed tomography volumes) is a way to infer this important information. This mono-patient multimodality matching can be reduced to finding the projection matrix that transforms any voxel of the volume onto the DSA image plane. This modelization is unfortunately not valid in the case of distorted images, which is the case for DSA images. A classical angiography room can now generate 3D X-ray angiography volumes (3DXA). Since the DSA images are obtained with the same machine, it should be possible to deduce the projection matrix from the sensor data indicating the current machine position. We propose an interpolation scheme, associated to a pre-operative calibration of the machine that allows us to correct the distortions in the image at any position used during the exam with a precision of one pixel. Thereafter, we describe some calibration procedures and an associated model of the machine that can provide us with a projection matrix at any position of the machine. Thus, we obtain a machine-based 2D DSA/3DXA registration. The misregistration error can be limited to 2.5 mm if the patient is well centered within the system. This error is confirmed by a validation on a phantom of the vascular tree. This validation also yields that the residual error is a translation in the 3D space. As a consequence, the registration method presented in this paper can be used as an initial guess to an iterative refining algorithm.

Curvilinear structure enhancement with the polygonal path image - application to guide-wire segmentation in x-ray fluoroscopy

Curvilinear structures are common in medical imaging, which typically require dedicated processing techniques. We present a new structure to process these, that we call the polygonal path image, denoted (see text for symbol). We derive from (see text for symbol) some curvilinear structure enhancement and analysis algorithms. We show that (see text for symbol) has some interesting properties: it generalizes several concepts found in other methods; it makes it possible to control the smoothness and length of the structures under study; and it can be computed efficiently. We estimate quantitatively its performance in the context of interventional cardiology for the detection of guide-wires in Xray images. We show that (see text for symbol) is particularly well suited for this task where it appears to outperform previous state of the art techniques.