Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Automatic 3D Model Generation based on a Matching of Adaptive Control Points

Abstract The use of a 3D model helps to diagnosis and accurately locate a disease where it is neither available, nor can be exactly measured in a 2D image. Therefore, highly accurate software for a 3D model of vessel is required for an accurate diagnosis of patients. We have generated standard vessel because the shape of the arterial is different for each individual vessel, where the standard vessel can be adjusted to suit individual vessel. In this paper, we propose a new approach for an automatic 3D model generation based on a matching of adaptive control points. The proposed method is carried out in three steps. First, standard and individual vessels are acquired. The standard vessel is acquired by a 3D model projection, while the individual vessel of the first segmented vessel bifurcation is obtained. Second is matching the corresponding control points between the standard and individual vessels, where a set of control and corner points are automatically extracted using the Harris corner detector. If control points exist between corner points in an individual vessel, it is adaptively interpolated in the corresponding standard vessel which is proportional to the distance ratio. And then, the control points of corresponding individual vessel match with those control points of standard vessel. Finally, we apply warping on the standard vessel to suit the individual vessel using the TPS (Thin Plate Spline) interpolation function. For experiments, we used angiograms of various patients from a coronary angiography in Sanggye Paik Hospital

Reconstruction of coronary arteries from X-ray angiography: A review.

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research

Physiology and coronary artery disease: emerging insights from computed tomography imaging based computational modeling

Improvements in spatial and temporal resolution now permit robust high quality characterization of presence, morphology and composition of coronary atherosclerosis in computed tomography (CT). These characteristics include high risk features such as large plaque volume, low CT attenuation, napkin-ring sign, spotty calcification and positive remodeling. Because of the high image quality, principles of patient-specific computational fluid dynamics modeling of blood flow through the coronary arteries can now be applied to CT and allow the calculation of local lesion-specific hemodynamics such as endothelial shear stress, fractional flow reserve and axial plaque stress. This review examines recent advances in coronary CT image-based computational modeling and discusses the opportunity to identify lesions at risk for rupture much earlier than today through the combination of anatomic and hemodynamic information

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

International audienceWe 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

Temporal tracking of 3D coronary arteries in projection angiograms

International audienceA method for 3D temporal tracking of a 3D coronary tree model through a sequence of biplane cineangiography images has been developed. A registration framework is formulated in which the coronary tree centerline model deforms in an external potential ¯eld de¯ned by a multiscale analysis response map computed from the angiogram images. To constrain the procedure and to improve convergence, a set of three motion models is hierarchically used: a 3D rigid-body transformation, a 3D a±ne transformation, and a 3D B-spline deformation ¯eld. This 3D motion tracking approach has signi¯cant advantages over 2D methods: (1) coherent deformation of a single 3D coronary reconstruction preserves the topology of the arterial tree; (2) constraints on arterial length and regularity, which lack meaning in 2D projection space, are directly applicable in 3D; and (3) tracking arterial segments through occlusions and crossings in the projection images is simpli¯ed with knowledge of the 3D relationship of the arteries. The method has been applied to patient data and results are presented

The effect of intracranial stent implantation on the curvature of the cerebrovasculature

BACKGROUND AND PURPOSE: Recently, the use of stents to assist in the coiling and repair of wide-neck aneurysms has been shown to be highly effective; however, the effect of these stents on the RC of the parent vessel has not been quantified. The purpose of this study was to quantify the effect of intracranial stenting on the RC of the implanted artery using 3D datasets. MATERIALS AND METHODS: Twenty-four patients receiving FDA-approved neurovascular stents to support coil embolization of brain aneurysms were chosen for this study. The stents were located in the ICA, ACA, or MCA. We analyzed C-arm rotational angiography and contrast-enhanced cone beam CT datasets before and after stent implantation, respectively, to ascertain changes in vessel curvature. The images were reconstructed, and the vessel centerline was extracted. From the centerline, the RC was calculated. RESULTS: The average implanted stent length was 25.4 +/- 5.8 mm, with a pre-implantation RC of 7.1 +/- 2.1 mm and a postimplantation RC of 10.7 +/- 3.5 mm. This resulted in a 3.6 +/- 2.7 mm change in the RC due to implantation (P \u3c .0001), more than a 50% increase from the pre-implantation value. There was no difference in the change of RC for the different locations studied. The change in RC was not impacted by the extent of coil packing within the aneurysm. CONCLUSIONS: The implantation of neurovascular stents can be shown to have a large impact on the RC of the vessel. This will lead to a change in the local hemodynamics and flow pattern within the aneurysm